159/2002

Vaisala expands into lightning data services

Global Atmospherics Inc. joins Vaisala

The Scope and Future of Nowcasting

Meteorological studies in the marine Arctic

The Arctic Ocean 2001 Experiment

President’s Column 3

Remote Sensing

Global Atmospherics Inc. Joins Vaisala 4

Upper Air

Arctic Ocean 2001 Expedition 6

Measurement Accuracy

and Repeatability of RS90 11

RS80 Humidity Data Set Corrections 14

Vaisala Launches the RK91 Rocketsonde 16

Development of Light Meteorological

Sounding System M200 17

Surface Weather

USAF TMOS at 2002 Winter Olympics 18

MAWS Enhanced with New Features 21

MAWS AWSs to Synoptic Stations in Poland 24

FS11 Visibility Sensor Launched 25

Aviation Weather

LD40 Ceilometer Launched 26

Romanian Air Force Choose AW11 26

Vaisala AWOS System to Helsinki-Vantaa Airport 27

Road Traffic Weather

Field Trial of Vehicle Grip Compared

to RWS Data 28

Dynamic Warning Signs Act as Signs of Rain 30

Additional Features

Role and Scope of Nowcasting 33

Two German Scientists win

Professor Vilho Vaisala Award 38

Vaisala at AMS 2002 38

Vaisala Centralizes USA Manufacturing

Operations 39

2 159/2002

Contents

Editor-in-Chief:Marit Finne(absent on study leave June 1, 2001 - July 15,2002)

Acting Editor-in-Chief:Ritva Siikamäki

Publisher:Vaisala Oyj , P.O. Box 26FIN-00421 HelsinkiFINLAND

Phone (int.):+358 9 894 91

Telefax:+358 9 8949 2227

Internet:http://www.vaisala.com

Design and Artwork:Edita Oyj

Editors:Bellcrest LanguageServices Oy

Printed in Finland byEdita Oyj, Finland

ISSN 1238-2388

Cover photo:Summer scenery at Nagu guest harbor on theFinnish archipelago. Photo by Mauri Rautkari,Lehtikuva.

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Vaisala in Brief– We develop, manufacture andmarket products and services forenvironmental and industrialmeasurements.

– The purpose of these measure-ments is to provide a basis for abetter quality of life, cost sa-vings, protection of the environ-

ment, improved safety and bet-ter performance.

– We focus on market segmentswhere we can be the world leader,the preferred supplier. We put ahigh priority on customer satis-faction and product leadership.We secure our competitive advan-tage through economies of scaleand scope.

The US Air Forces used TMOS (VaisalaTACMET Systems) at the 2002 WinterOlympics for real-time meteorological datafrom the sports venues. The support for medicaland security aviation operations came fromthe extensive weather support system at theOlympics in which meteorologists fromgovernment agencies, private companies andthe University of Utah cooperated to provideaccurate and timely weather information.

Driving safety is a key concern for roadauthorities. Other than the weather, one of themost interesting factors which affects safety is avehicle’s grip, i.e. the friction between avehicle’s tires and the road surface. Togetherwith the Finnish Road AdministrationVaisala conducted a field trial in SouthernFinland during the winters of 1999-2000 and2000-2001, to study which measurementresults best indicated a vehicle’s grip.

Nowadays, a number of systems providedynamic advice to motorists on the real-timestatus of the road network. Most commonlyreal-time information on congestion allowsdrivers to take alternative routes to reducetravel time. Road weather systems andvariable message signs are also used toimprove road safety, for example by the Roadsand Traffic Authority of New South Wales inAustralia. With the help of dynamic warningsigns driving speed can be adjusted as weatherconditions change.

I n the past decades, efforts todevelop weather forecastshave focused on long-term

forecasts, the range of which ex-tends from five or six days to upto seven days. Less attention hasbeen paid to short-term high-precision local forecasts, now-casting and mesoscale services.

In many applications, how-ever, a high-precision local fore-cast, pertaining to short term lo-cal conditions, is the most use-ful. Application-specific weatherobservation systems for theneeds of aviation and road traf-fic have already been availablefor a long time and defenseforces too now have their ownnowcasting applications. Nowa-days, ever-increasing invest-ments are also being made inweather systems for the needs ofagriculture. Many other profes-sions benefit from high-preci-sion weather forecasts. So evendoes Everyman, for examplewhen planning leisure activities.

In my opinion, the time isstarting to be ripe for the broadand large-scale provision of now-casting and mesoscale forecasts.We have forecast models, andthe required observation meth-ods already exist. I believe thatthe market for such services is al-

so there. A radical change couldbe about to happen, similar tothe one that took place in thetelecommunications sectorwhen it moved from line teleph-ony to mobile communications.

The question is, however,whose business would the provi-sion of such a service be? Wouldit fall in the domain of nationalweather services or would it bethe business of the private sec-tor? How would the products betraded? Would the consumerpay for them, would the field beopen for sponsoring or advertis-ing, or should the money comefrom public funds? This seemsto be where the dilemma lies.What will be the business ideaand earnings principle? It will beestablished. It is time for pio-neers to step up.

Vaisala has been active as asupplier of application-specificweather observation systems for

a long time, and we have appre-ciated their benefits. Conse-quently we believe that high-pre-cision weather forecasts have alarger market to conquer, includ-ing the general public. We havemade a focused investment inthe observation technologiesthat high-precision weather fore-casting require, with lightningdetection and wind profilers be-ing the most recent examples.

Long-term forecasts and thesynoptic observations for themwill naturally always be needed.They form the very basis of allweather services. But high-preci-sion forecasts could comple-ment them in an excellent man-ner, and to a much greater extentthan is the case today. �

Pekka KetonenPresident and CEO

159/2002 3

President’s Column

Towards a new generation of high-precision forecasts

4 159/2002

Vaisala expands into lightning data services

Global AtmosphericsInc. joins VaisalaIn March 2002, Vaisala acquired Global AtmosphericsIncorporated of Tucson, Arizona, USA, from the Sankosha Group.Global Atmospherics is the world’s largest lightning detectionequipment manufacturer and lightning data services operator.Renamed as Vaisala-GAI Inc., the company is now part of Vaisala’sRemote Sensing Division. This acquisition strengthens Vaisala’slightning and thunderstorm detection expertise and expands theproduct selection offered to clients whose operations areaffected by severe weather.

NLDN communicationswork as follows: 1) Sensorsdetect lightning and transmitthe data to a satellite, 2) Thesatellite relays theinformation to earthstations, 3) Data aretransmitted to the NetworkControl Center vialandlines, 4) The NetworkControl Center processes thedata, 5) The processed dataare relayed back to thesatellite, 6) Lightning dataappear on user’s displayacross the country withinseconds of occurrence.

Ritva Siikamaki, MAActing Editor-in-Chief, Vaisala NewsVaisala HelsinkiFinland

V aisala-GAI is the lead-ing manufacturer ofstandalone lightning

detection instruments and LF(Low Frequency) lightning de-tection networks and has also re-cently developed VHF (VeryHigh Frequency) lightning de-tection technology. The compa-ny owns and operates a nationallightning sensor network in theU.S. and sells various lightningdata products to the U.S. Na-tional Weather Service, airports,power utilities, recreational facil-ities, insurance companies andweather service providers. Thecompany also participates inlightning data services in Cana-da, France, Central Europe andthe Benelux countries.

Comprehensive remotesensing and lightningdetection expertiseIn early 2000, Vaisala acquiredanother lightning detection net-work manufacturer, DimensionsSA of France, which also part ofthe Remote Sensing Division ofVaisala. It is currently the lead-ing manufacturer of VHF tech-nology Total Lightning Detec-tion Networks. Mr. Martti Husu,

Director of the Remote SensingDivision, stresses that there areremarkable synergies in combin-ing the two lightning detectionnetwork product lines into onebusiness unit. The combinationwill provide optimized systemsfor the varied needs of lightningdetection network clients.

The Remote Sensing Divi-sion focuses on two new and ex-panding fields of atmosphericmeasurement: nowcasting andmeso-scale forecasting. These arefields where severe weather phe-nomena which rise within a rela-tively short time, like thunder-storms, windshear, local rainfalland hailstorms, can be predicted.Following the acquisition ofGlobal Atmospherics Inc. andthe previous acquisition of Di-mensions SA, Vaisala will elevateto a global market leadership po-sition in the field of lightning de-tection and localization.

Vaisala-GAI’s historyVaisala-GAI was founded in1976 by three University of Ari-zona scientists, Dr. E. PhilipKrider, Dr. Burt Pifer, and Dr.Martin Uman, who began re-searching lightning propertiesand behavior in the mid-1970’s.Over the next decade their re-search, combined with the con-tributions of others, resulted inthe development of the UnitedStates’ only national lightningdetection system, the U.S. Na-tional Lightning Detection Net-work® (NLDN®). At the time ofacquisition by Vaisala, the com-

pany was a subsidiary of theSankosha Group of Japan.

Real-time lightning datanationwide in the U.S.Since 1989, the NLDN® hasmonitored the 20 to 25 millioncloud-to-ground lightningstrikes that occur every yearacross the contiguous 48 states.NLDN® consists of over 100 re-mote, ground-based sensing sta-tions located across the UnitedStates which detect the electro-magnetic signals given off whenlightning strikes the earth’s sur-face. These remote sensors sendthe raw data via a satellite-basedcommunications network to theNetwork Control Center operat-ed by Vaisala-GAI Inc. in Tuc-son, Arizona. Within seconds ofa lightning strike, the NCC’scentral analyzers process infor-mation on the location, time,polarity, and amplitude of eachstrike. The lightning informa-tion is then communicated tousers across the country. Light-ning data users in the US in-clude the National Weather Ser-vice (NWS), the Federal Avia-tion Administration (FAA), theNational Aeronautics and SpaceAdministration (NASA), theWeather Channel® and PGATOUR®, as well as major powercompanies, airports, and thou-sands of businesses nationwide.NLDN data is accessible to sub-scribers through various DOS,Windows®, or Unix® based dis-play and analytical software.

European cooperationin lightning detectionOperators of Vaisal-GAI light-ning information system tech-nology in Europe establishedthe European Cooperation forLightning Detection (EUCLID)

in August 2001. This lightningdetection network covers thegreater part of the Europeancontinent. EUCLID is capableof tracking lightning by mappingup-to-the-second lightning activ-ity throughout Austria, Belgium,Czech Republic, France, Ger-many, Hungary, Italy, Luxem-bourg, Netherlands, Norway,Poland, Slovakia, Slovenia, andSwitzerland. The network uses85 ground-based sensors that de-tect and then report detailed in-formation on each lightningevent to a single, central proces-sor. The network then providesaccurate and reliable informa-tion about the cloud and cloud-to-ground lightning strikes toeach member.

Preparing for stormhazardsLightning information is criticalfor weather forecasters andweather-sensitive businesses,such as airport operators and airtraffic controllers, electric powerutilities, mission critical facili-ties, golf courses and outdoorsports facilities. They closelywatch storm development sothat they can be prepared forstorm hazards. When a stormstarts generating lightning thelightning alerts forecasters towatch the thunderstorm for oth-er dangerous weather elementsthat often occur with electrifiedstorms, for example heavy rain,hail, flash flooding, high winds,downbursts, and tornadoes. �

159/2002 5

The National LightningDetection Network® locatesstrikes across the U.S. inseconds. The network operates24 hours day, 365 days a year.Pictured is the control center atthe Vaisala GAI Inc. office inTucson.

The management of Vaisala-GAI Inc at a meeting inTucson. From the left: MarttiHusu, Philippe Richard, JackNelson, Michael Austin,Ellen Carolan, Rich Pyle andKen Cummins.

their history, is essential to pre-dict future developments.Swedish researchers have beenactive in marine Arctic research,with several expeditions carriedout in the 1990s under the aus-pices of the Swedish Polar Re-search Secretariat. During theArctic Ocean 2001 expedition,four extensive international andinterdisciplinary research

6 159/2002

T he marine Arctic is inti-mately connected withthe global climate and

large-scale biogeochemical cy-cles. Disturbances and variationsin the function of these systemscan drastically change condi-tions of life in countries in theNorthern Hemisphere. Under-standing the natural processes inthe Arctic today, and studying

Michael TjernströmProfessor Department of MeteorologyStockholm University Sweden

Eric ErixonTechnician Swedish Polar Research Secretariat

The Meteorological Department of Stockholm University sailed north for the

Arctic Ocean 2001 ExpeditionThe Swedish Polar Research Secretariat carriedout a two-month expedition to the high Arc-tic in summer 2001. The Secretariat cooperat-ed with the Swedish Maritime Administrationand the icebreaker Oden, which functioned asthe research platform. The expedition wasparticipated in by some 50 researchers andhad several research programs, which dealtwith biogeochemistry, physical oceanography,geophysics, and atmospheric processes. The atmospheric research included a largeprogram of meteorological measurementswhere several Vaisala products, includingsounding systems, radiosondes, heated cupanemometers and other measurement instruments, were used.

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Figure 1. Container housing the Vaisala equipment andthe ship’s weather station on the 7th deck of Oden

159/2002 7

26 June departure from Stockholm, transit and test of equipment29 June embarking and departure from Gothenburg, transit

4 July leg 1, priority biogeochemical program 14-15 July rotation, change of scientists

16 July leg 2, priority oceanographic program and remote sensing 25 July leg 3, seismology at the Lomonosov Ridge 30 July leg 4, taking of specimens in the Makarov Basin

1 August leg 5, atmospheric research carried out during the ice drift (Oden anchored to drifting sea ice)

29 August embarking Longyearbyen, Svalbard

Figure 2. The expedition on theicebreaker Oden set out fromStockholm on June 26, 2001 viaGothenburg to the Arctic Ocean,ending at Longyearbyen, Svalbard,on 29 August 2001.

Figure 3. A view ofthe ice camp takenfrom Oden’s 7th andhighest deck. In theforeground one can seethe red huts housingthe tethered soundingand Sodar equipment-– the Sodar antennasare the three whitecubes. Further awayare the 18-m mastand the blue hutwhich houses theelectronics for the mastinstrumentation.

programs were carried out tostudy various aspects of the Arc-tic environment. The sub-pro-grams were atmospheric process-es (including marine biology, gasand aerosol chemistry, aerosolphysics, and meteorology), bio-geochemistry, geophysics andoceanography, each of whichhad a dedicated leg of the expe-dition.

Versatile atmosphericdata collected The Arctic is an especially inter-esting research area for atmos-pheric studies as it is especiallysensitive to climatic changes.Moreover, the Arctic is the onlyregion on the Northern Hemi-sphere where the air in summeris relatively free of man-madepollutants, which might other-wise disturb the measurementand observation of naturalprocesses.

The atmosphere program ofthe expedition aimed to increaseknowledge of the impact ofaerosols on the climate and tostudy how natural aerosol parti-cles are produced and transport-ed in the Arctic atmosphere. Themajor part of the atmosphere

program was carried out with theship anchored to drifting sea ice.During the 20-day ice drift inAugust data was collected usingvarious methods both aboardthe ship and on the ice. Meteor-ological instruments included asuite of remote sensing equip-ment with a wind profiler, acloud radar, a scanning radiome-ter and a Sodar. In addition, an18-m tower with profile, turbu-lence and radiation instruments,two remote stations with a com-plete energy balance instrumen-tation, and a system for tetheredsoundings were mounted on theice. Atmospheric variables werealso measured with some 120 ra-diosoundings. Every six hours,TEMPSHIP messages were sentto the Swedish Meteorologicaland Hydrological Institute(SMHI) which forwarded themto the international network.Additionally, the European Cen-tre for Medium Range WeatherForecasts (ECMWF) was inter-ested in the data, since measure-ments are not frequently per-formed at these latitudes. Weath-er forecasts for the expeditionwere supplied by the SwedishMeteorological and Hydrologi-

cal Institute (SMHI), sendingdaily HIRLAM-products oversatellite telephone email.

Meteorological measurements as a part of the atmospheric programThe purpose of the meteorolog-ical measurements was both tocomplement the atmosphericchemistry and aerosol measure-ments by providing a detaileddescription of processes relevantto the mixing of chemical con-stituents and aerosols, and to in-crease the understanding of theArctic boundary layer. The strat-egy was to obtain a continuousrecord of the lower troposphereconditions by continuouslymonitoring wind and cloudsthrough the lowest kilometer us-ing the remote sensing instru-ments. Another aim was to makedetailed observations of specificatmospheric events at the 3-weekice camp.

Challenging research environmentTo obtain detailed meteorolog-ical measurements in the harshArctic environment is a chal-

lenge. Some of the instrumentscould be disturbed by move-ments, local pollutants or noisefrom the Oden. Consequently,they were located about 300 me-ters away from the ship on an icefloe, where micrometeorologicalmeasurements were performedwith an 18-m telescopic mast,the tethered sounding site andthe Sodar. The stability of the icefloe aroused some concern,since August is in the middle ofthe melt season. Fortunately, thelarge ice floe with dimensions of1.5 by 3 km proved both suffi-ciently thick and stable. Two ad-ditional turbulence-flux stationswere also set up remotely, at adistance of 5 and 8 km respec-tively. Additionally, the expedi-tion was equipped with a smallhelicopter that had aerosol andmeteorology sensors for makingsoundings when the weatherpermitted. Our very study sub-ject, the weather, also affectedour operations - a snowstormcaused a delay of almost twodays in setting up the ice camp.

Soundings amidst iceAbout 120 soundings were car-ried out during the expedition of

8 159/2002

Figure 5. Eric Erixon, a long-timemeteorologist with experience of some10000 radiosoundings, performednumerous soundings during theexpedition, here preparing a Vaisalaradiosonde for release on Oden’shelicopter deck.

Figure 4. The icebreaker Odenfunctioned as the research platform.

which 80 were launched duringthe 3-week ice camp in August.The remainder were carried outduring shorter research sessions,either in open water or in themarginal ice zone, before enter-

ing the main pack ice. Duringsessions at research stationssoundings were performed every6 hours. Additional soundingswere also made in connectionwith research helicopter flights.

The Vaisala sounding stationwas located on the 7th deck ofOden, the top-deck of the ship(Figure 1), while all radiosondeswere launched from Oden’s heli-copter deck (Figure 5). South of80˚ N, Loran-C was successfullyused for wind measurements,while for the helicopter-coordi-nated soundings we used sondeswithout wind sensors (PTU-onlyradiosondes). For soundings inthe high Arctic, GPS sondeswere used. Only two of all theradiosondes released failed,these were due to balloon mal-functions. All the Loran-Cwindsondes gave satisfactory re-sults, even those released northof Svalbard, where an older re-ceiver type (MARWIN) wasused. North of 88˚ N, using GPSfor windfinding, we had a suc-cess rate of approximately 80%.Also the other GPS receivers hadperiods of poor reception.

Some findings of thestudyA composite of temperature andhumidity for all soundings fromthe ice camp is shown in figures7 & 9. The temperature was nev-er very low at the surface, staying

typically just below zero, i.e. atthe melting point of the ice. Thetemperature dropped lower thanthe freezing point of salty water(around –1.5 ˚C) only a fewtimes, which can be seen, for ex-ample, around day 226, andeven then only to ~ –6 ̊ C. Mostnotable in the temperaturerecords is the fact that the tem-perature increased from the topof boundary layer and upwardfor practically the whole period.The warmest temperatures by faroccurred at an altitude ofaround 1 km. In fact, a cappinginversion prevailed most of thetime. The solid blue line is the 0-degree isotherm; for quite a sub-stantial part of the time the tem-perature above the capping in-version was well above freezing.

The boundary layer was nev-er very stable and the capping in-version seldom touched the sur-face. The inversion was mostpronounced on the very fewclear days, see around days 220 –223 and 226 – 227. The lowesttroposphere was very humidthrough most of the experiment,but during these periods some-what lower humidity prevailedabove the inversion. With-

159/2002 9

Figure 6. The researchers spotted manypolar bears around the North Pole,which followed curiously the researchefforts of Oden.

➤

A erosols are small particles in the air, such as dust, sul-phur, pollutants or sea salt, which affect the radiation

balance of the atmosphere both directly and indirectly. Theparticle size and chemical composition of aerosols deter-mine how the aerosols affect the atmospheric radiation andthus the temperature.

Aerosols scatter and absorb solar and infrared radiationin the atmosphere, which is referred to as direct radiativeforcing. The aerosols also function as cloud condensationnuclei, vital to the formation of clouds, which also reflectsolar radiation. Aerosols modify the optical properties andlifetime of clouds (known as indirect radiative forcing).Consequently, aerosols are considered to have had a cool-ing effect on the global climate – an opposite effect to thatof greenhouse gases, which are known to cause globalwarming. However, aerosols typically have a short atmos-pheric lifetime. For this reason, aerosols cannot be regardedas an offset to the warming effect of greenhouse gases. �

Aerosols and their effecton climate

10 159/2002

in the boundary layer, however,relative humidity seldomdropped below 85% and oftenremained > 90%. The boundarylayer depth (dashed line in Fig-ure 6 and 7) was typicallyaround 300 – 500 m, tentativelyanalyzed from the potential tem-perature profile.

Figure 8 shows a compositeof the wind speed during the icecamp period. The white and grayareas in this plot indicate periodswhen we were unable to measurewinds with the GPS sonde. Thewinds in the boundary layerwere usually low, below 10 ms1.Winds aloft were also usuallylow with the exception of a fewstorms with winds reaching 25ms1. The first major storm,which caused difficulties in set-ting up the ice camp, penetrateddeeper. Only slight signs of thisstorm can be seen here as we didnot start using GPS sondes untilmost of the ice camp instrumen-tation was available.

SummaryThe main feature of the ArcticOcean 2001 expedition’s atmos-pheric program, the 3-week ice-

camp, provided a wealth of dataon the boundary layer in thehigh Arctic that will take us yearsto explore fully. A more or lesscontinuous record of the state ofthe lower atmosphere was col-lected with remote sensingequipment, and detailed bound-ary layer measurements weresampled on an 18-m mast, bytwo remote flux-stations andwith a tethered sounding systemusing balloons or kites. Vaisalaradiosondes provided a verygood record of the time-heightvariability of the whole tropo-sphere. These data are uniquesince such a record from a loca-tion this far north is very un-common.

The summer of 2001 seemedto be different from previoussummers when the Swedish Po-lar Research Secretariat has con-ducted icebreaker borne atmos-pheric research in the Arctic.There were no signs at all of themuch-discussed decrease in ei-ther ice-cover or ice-thickness.On the contrary, we had quitesevere ice conditions. There wasalso much more synoptic activi-ty, with several storms carrying

both snow and rain. The bound-ary layer remained relatively wellmixed and cloud-capped almostall the time. As a consequence,the temperatures were surpris-ingly mild and the boundary-layer stability was rather small.The often-quoted low-level jetsin the wind speed profile were al-so for most part absent. �

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Figure 7. Composite of temperature from all soundings during the ice-campoperations.

Figure 9. Composite of relative humidity from all soundings during the ice-camp operations.

Figure 8. Composite of scalar wind speed during the ice-camp operations. Thewhite and gray areas in this plot indicate periods of unavailable wind data.

159/2002 11

T his article summarizesthe paper (Paukkunen etal 2001) presented at the

AMS 2001 conference, focusingon accuracy and repeatability.Please note that some details onthe measurement and calibra-tion accuracy and repeatabilityof RS90 Radiosonde have beenupdated. The Vaisala RS90 Ra-diosonde participated in theWMO International RadiosondeIntercomparison in Brazil in2001, the results of which will bereported later.

Performance characteristics of theRS90

Factory calibration of RS90

Calibration and sensor qualityplay a key role in the perform-ance of radiosondes. For opti-mum accuracy, all Vaisala ra-diosonde sensors are individual-

ly calibrated with sensor elec-tronics. The calibration equip-ment measures the output dataof the radiosonde sensors in de-fined environmental conditionsand then computes individualcalibration coefficients for eachsensor. Ground equipment usesthese coefficients during sound-ing to calculate accurate meas-urement values from the sensoroutput data transmitted by theradiosonde.

Vaisala’s CAL4 CalibrationMachine was specially designedfor calibrating the advancedRS90 radiosonde sensors. Thenew calibration technique alsofurther improved the accuracyand reliability of Vaisala’s cali-bration procedures.

Temperature

In the construction of the ra-diosonde temperature sensor themost important design criteria

was to minimize thetime lag and the ef-fects of solar and in-frared radiation. Tomeet these require-ments the sensorhad to be as small aspossible. The size ofthe RS90 tempera-ture sensor com-plies with this re-quirement, with a

diameter of only 0.1 mm. More-over, the response time of theRS90 temperature sensor hasbeen reduced to less than onetenth of the RS80 response time(0.2 s vs. 2.5 s at 1000 hPa, 6m/s,see Fig.1). The solar radiationcorrection has also been reducedremarkably: the correction ofRS90 is about 1/5 of that ofRS80 (Fig. 2).

Humidity

Wide-range factory calibrationagainst well-defined referenceshas lowered production variabili-ty with the RS90 Radiosonde(Table 1). This has also further im-proved sounding accuracy.

In radiosonde humiditymeasurements, the followingfactors require special considera-tion:• response time • solar radiation• correction of sensor tempera-

ture dependence• elimination of possible

condensation of water vapor when emerging from a cloud

• elimination of possible contaminating gases from the radiosonde materials.

The minimized sensor allowsimproved humidity measure-ment performance. The re-sponse time of the RS90 humid-

ity sensor in comparison to thatof RS80 is presented in Fig. 3.

Possible condensation of wa-ter vapor when emerging from acloud is eliminated through theuse of two heated humidity sen-sors. As a result, in most caseswhere condensation could hap-pen, the RS90 humidity sensorperforms correctly.

Possible contaminating gas-es reaching the sensor from or-ganic materials in the ra-diosonde can be eliminated byperforming a sensor regenera-tion (heating) procedure beforethe factory calibration and dur-ing the ground check procedurejust before a sounding. With thisprocedure, the original highlyaccurate calibration of the sen-sor is recovered for optimumperformance.

Algorithms for solar radia-tion correction of the RS90 hu-midity measurement are current-ly under development. The algo-rithms for eliminating the tem-perature dependence error incold temperatures have been im-proved in comparison with theRS80 (Balagurov et al. 1998,Miloshevich et al. 2000, Wang etal, to be published). Details willbe available later in the reportfrom the WMO InternationalRadiosonde Intercomparison2001.

Veijo Antikainen, M.Sc. (Physics)Product Manager

Ari Paukkunen, Ph.L. (Physics). Research Manager, SensorsVaisala HelsinkiFinland

Hannu Jauhiainen, M.Sc. (EE)R&D Manager

The accuracy of the Vaisala RS90 Radiosonde is based on the improvedsensor technology and individual calibration of the radiosondes. High-performance in-house calibration technology was developed to enhancethis accuracy. In this article, the accuracy of pressure, temperature, relativehumidity measurements and total uncertainties are discussed.

Figure 1. Response time (63.2%) of the RS90temperature measurement. Averaged over T-range.

Measurement Accuracy and Repeatability of Vaisala RS90 Radiosonde

12 159/2002

Pressure

The RS90 incorporates a siliconmicro-mechanical pressure sen-sor which solves the problems oftemperature dependence duringfast temperature changes and im-proves mechanical strength dur-ing transportation and againstother mechanical shocks.

The excellent performance ofthe RS90 pressure sensor duringrapid temperature changes is illus-trated in Fig 4. The test was per-formed in extreme conditionswith rapid temperature changesfrom 25ºC to -55ºC and back. Inactual soundings, the maximumchange is few hectopascals inRS80 and negligible in the RS90compared to the RS80.

The new calibration facilitywith accurate temperature de-pendence correction has im-proved measurement accuracy.

RS90 uncertainty estimation in soundings

Definition of accuracy

When discussing accuracy, it isimportant to agree on its defini-tion. Based on the definitions ofthe International Organizationof Standardization (I.O.S. 1993),the following definitions areused in this article:

Accuracy is the closeness ofthe agreement between the re-sult of a measurement and a truevalue of the measurand (I.O.S.1993; EARL 1997). Accuracy is aqualitative concept.

Uncertainty of measure-ments is a parameter, associated

with the result of a measure-ment, that characterizes the dis-persion of the values that couldreasonably be attributed to themeasurand. The parameter maybe, for example, a standard devi-ation. Uncertainty gives a cer-tain confidence in the result of ameasurement.

Repeatability is the close-ness of the agreement betweenthe result of successive measure-ments of the same measurandcarried out under the same con-ditions of measurement. Re-peatability can be expressedquantitatively in terms of thedispersion characteristic of theresults (standard deviation).

Reproducibility is closenessof the agreement between the re-sult of successive measurementsof the same measurand carriedout under changed conditions ofmeasurement. It can be ex-pressed quantitatively in termsof the dispersion characteristicof the results (standard devia-tion).

Calibration is a set of opera-tions that establish, under speci-fied conditions, the relationshipbetween values of quantities in-dicated by a measuring instru-ment or system, and the corre-sponding values realized by stan-dards.

The concrete basis for ra-diosonde accuracy is the calibra-tion procedure, the calibrationequipment and the internationaltraceability of the referencesused in calibration (Paukkunen1998).

The startingpoint for the estima-tion of uncertaintiesin operational ra-diosoundings arethe short-term (�r)and long-term (�l)uncertainties of thecalibration equip-ment CAL4. Theseuncertainties arisefrom such factors as:reference uncertain-ty, conditions in thecalibration cham-ber.

Estimated short andlong-term uncertaintyvalues of CAL4 calibra-tion at various calibra-tion points at a 2 sigmaconfidence level are pre-sented in Table 1.

In the calibration pro-cedure there are also ra-diosonde-based uncertain-ties (�s) from such factorsas curve fitting, electronicnoise, and resolution.

Uncertainty estimat-ed as the standard devia-tion of differences in re-peated calibration (�rc)includes uncertainties (�r) and(�s). This means that:

The measured values for (�rc) aregiven in Table 2.

Long-term uncertainty is re-lated to systematic errors. Theuncertainty is calculated accord-ing to (I.O.S. 1993; EARL 1997).

Calibration uncertainty

The calibration uncertainty ofthe CAL4 Calibration Machineis the main factor in RS90 uncer-tainty estimation in soundings.

If �l is added to �rc, an ini-tial (low) estimate (�t1) of totaluncertainty (�t) for an individualRS90 radiosonde is reachedIf a specific general-purpose (lab-

oratory) measurement system,independently from the CAL4Calibration Machine, is used tomonitor and specify the uncer-tainty of the RS90 Radiosonde,a standard deviation of meas-ured differences against meas-

urement reference (�m ) and av-erage value (xm) are calculatedfrom a sample inspection ofRS90 production. This measure-ment system has its own uncer-tainty (�ar). The measured differ-ences are related to �t, �ar, �s,and they can be summed up assquares of the deviations:(3)

(�t) can be estimated as (�t2) ifthe maximum value of (xm ±3�m) is used(4)

and the high estimate is now

When a radiosonde is as-cending carried by a weather bal-loon, a new set of uncertaintiesmust be considered. They aremainly attributable to dynamicmeasurement or new phenome-na (compared to CAL4), such assolar radiation. All these factors

Figure 3. Response time of the RS90 humiditymeasurement. Sample size 20 pcs.

Figure 2. Solar radiation correction of the RS90 andRS80.

Uncertainty Pressure Temperature Humidity

hPa °C %RH

0 ... 1070 +60 ... - 90 0 ... 90Short term 2 ... 1080 0.1 ... 93(�r, k=2) < 0.22 < 0.01 ... 0.03 0.1 ... 0.5Long term (�l , k=2) < 0.10 0.05 ... 0.06 0.1 ... 0.6Total < 0.24 0.05 ... 0.07 0.2 ... 0.8

Table 1. Estimated short-term (�r) and long-term (�l) uncertainty ofCAL4 calibration at various calibration points at a 2 sigma confidence level (95.5%).

(1) �rc � √(�r)2+(�s)2

(2) �t1 � √(�rc)2+(�1)2

xm+3�m�3�√(�t)2+(�ar)2+(�s)2

�xm—3�m

�t2�√(xm/3+�m)2+(�ar)2—(�s)2

(5) �t2�√(xm/3+�m)2—(�ar)2

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can be estimated as uncertaintycomponents (I.O.S. 1993; EARL1997) and further combined asthe sum of squares of deviations(�f). The value of (�t) changes asa function of several variablesand therefore the expression iscomplicated to formulate. If(�so) is the RS90’s uncertainty ofcalibration, the total uncertaintyof the RS90 Radiosonde (�rs) insoundings can be estimated as

Uncertainty (�so) can be esti-mated with �t1, �t2,for example.Further, (�rs) can be comparedto the reproducibility of sound-ings (giving the general variabili-ty of sounding measurements).

Specifications based on uncertainty evaluations

On the basis of these uncertain-ty evaluations, the followingspecifications can be presented:

Repeatability (Standard de-viation of differences betweentwo successive repeated calibra-tions, k = 2 confidence level).

Uncertainty in sounding (2-sigma (95.5%) confidence level(k=2), cumulative uncertaintyincluding repeatability, long-term stability, effects due tomeasuring conditions, dynamiceffects (such as response time)and effects due to measurementelectronics).

Reproducibility in sound-ing (standard deviation of differ-ences, in dual soundings dividedby √2).

Uncertainty infactory calibration issampled and tested asan integral part ofproduction control.Additionally, an in-dependent laboratoryfacility is used as partof the quality controlsystem. Measure-ment results are usedin uncertainty evalu-ations mentionedearlier in this chapter.

Comparison flighttests

Some of the comparison flighttests were performed as twin ortriple soundings from 1999-01-26 to 1999-02-15 at VaisalaHelsinki sounding station. A to-tal of 27 soundings were per-formed. The compared ra-diosonde types were 1 - 2 pcsRS90-AL Radiosondes withRS80-15L Radiosonde. The aver-age of maximum direct differ-ences and maximum averagestandard deviations are shown inTable 3.

The standard deviation ofthe RS90/RS90 difference givesan estimate for reproducibilityof the pressure, temperature, hu-midity and geopotential heightreadings (PTUH) of the RS90 insoundings. This can be com-pared to standard deviation ofdifferences in RS90 calibrationand specified total uncertaintyin soundings (Table 2).

The RS80/RS90 temperaturedifferences are greatly affected bydifferent types of atmospherictemperature profiles due to thefast response time and small radi-ation correction of the RS90.

Large differences in heightdata between the RS90/RS90and RS90/RS80 values are main-ly due to differences in pressuresensors and the different re-sponse times of the temperaturesensors. In the troposphere, thefaster RS90 temperature sensorindicates slightly colder temper-atures. The reproducibility intest soundings meet the speci-fied values (in Table 2 the stan-dard deviation of differences isdivided by √2).

Conclusion and discussion

The main goals of the RS90 ra-diosonde design were to respondto the increasing demand forwell-defined uncertainties ofmeasurement and the need forimproved repeatability of cali-bration and reproducibility insoundings. Many of the knownweaknesses in earlier radiosondedesigns have been corrected.The uncertainty analysis seemsto agree with the uncertaintiesobserved in operational use.

Extensive testing and analy-sis of the radiosonde during op-erational use makes it possible tofurther improve the product inthe future. The test facilities for awide range of atmospheric con-ditions using high-accuracymethods are being constantlyimproved to reach the best pos-sible product know-how for ourusers. �

ReferencesA. Balagurov, A. Kats, N. Krestyanniko-

va, WMO Instruments and Observ-ing Methods Report No. 70,WMO/TD No. 877, 1998.

European Co-operation for Accreditationof Laboratories (EARL): EARL-R2,1997.

International Organization for Standard-ization (I.O.S.), ISBN 92-67-10188-9, 1993.

Miloshevich, L. M., H. Voemel, A.Paukkunen, A. J. Heymsfield, S. J.Oltmans, J. Atmos. Oc. Tech., Feb.2001, Vol. 18, pp. 135-156.

A. Paukkunen, Veijo Antikainen, HannuJauhiainen, 11th Symposium onMeteorological Observations and In-strumentation, 14-19 Jan. 2001,New Mexico, AMS, 2001

A. Paukkunen, Vaisala News No.147/1998.

Wang J., Cole H. L., Carlson D. J., MillerE. R., Beierle K, Paukkunen A.,Laine T. K., Corrections of HumidityMeasurement Errors from the VaisalaRS80 Radiosonde - Application toTOGA-COARE Data, accepted tobe published in Journal of Atmospher-ic and Oceanic Technology.

Figure 4. RS90 and RS80 pressure sensorresponses to fast temperature changes in extremeconditions. The temperature was changed rapidlyfrom 25°C to - 55°C and back to 25°C.

(6) �rs = √(�so)2+(�f)2

P (hPa) T (ºC) U (%RH) H (gpm)RS90/RS90Max. average 0.25 0.13 0.50 25RS90/RS90Max. std. dev. 0.40 0.51 0.17 28RS80/RS90Max. average 1.39 0.52 3.6 455RS80/RS90Max. std. dev. 1.1 0.90 6.0 125

Table 3. Maximum direct differences and maximum standard deviationsof test flights (27 soundings).

Specification P (hPa) T (°C) U (%RH)Uncertainty in soundings 1.5 ... 0.7 0.5 5

Reproducibility in 2soundings 1080-100 hPa 0.5100-3 hPa 0.3

1080-50 hPa 0.250-20 hPa 0.320-3 hPa 0.4

Repeatability 0.4 0.1 2

Table 2. Accuracy specifications for RS90.

T he NCAR and Vaisalacollaboration projectstarted in 1998 and built

on a mutual effort to identifyand correct a dry humidity biasin Vaisala radiosondes. JunhongWang, Harold Cole, David Carl-son, Erik Miller and KathrynBeierle of NCAR’s AtmosphericTechnology Division (ATD), andAri Paukkunen and Tapani Laineof Vaisala have recently pro-duced a set of correction algo-rithms that allow researchers toreprocess historical sounding da-ta sets to obtain improved hu-midity measurements.

How do the correctionalgorithms work?The ATD-Vaisala research on ra-diosonde humidity errors identi-fied several sensor, calibration,and handling factors that can af-fect humidity measurement ac-curacy. The ATD-Vaisala correc-tion algorithm focuses on six

primary and tractable factors:chemical contamination of thehumidity sensors, temperaturedependence of sensor response,basic calibration models, groundcheck processes, sensor aging,and solar-induced sensor armheating. Of these factors, chemi-cal contamination, primarilyfrom packaging materials, in-duces the largest uncertainties atwarm temperatures and high hu-midities while the temperature-dependence properties of thehumidity sensors induce signifi-cant uncertainties at very coldtemperatures. The ATD-Vaisalacorrection procedures compilethese sometimes offsetting fac-tors into specific physically-based algorithms for Vaisala A-type humidity sensors (e.g.RS80-A) and H-type sensors (e.g.RS80-H). In most cases, the cor-rection algorithms for chemicalcontamination require know-ledge of the radiosonde’s age

(e.g. time sincemanufacture),obtainable fromthe radiosondeserial numberrecorded as partof standard datafiles. ATD and afew other userstypically recordadditional data,especially sensordata before ra-diosond launch,that, in combi-nation with separate surfacedata, can pro-vide an alternatecorrection pathfor sonde hu-midity bias thatdoes not requireknowledge ofsonde age.

The ATD-Vaisala correc-tion algorithmincorporatesthese variousfactors into anorderly correc-tion sequence with simple inputfactors and decision points relat-ed to availability of sonde age in-formation or prelaunch compar-ison data. Inputs include meas-ured humidity, measured tem-perature, sonde serial number ifrecorded and independent sur-face humidity data if measured,and the algorithms will then pro-duce corrected humidity data.Decision points accommodatedata sets with prelaunch data orwhich lack sonde age informa-tion. The algorithm applies insequence ground check errorcorrections, contamination and

aging corrections, calibration er-ror corrections, temperature de-pendence corrections, and sen-sor arm heating corrections us-ing documented assumptionsand equations at each step.

Who might use the correction algorithms?Contamination-induced humid-ity errors generally increase withradiosonde age and with the rel-ative humidity of the measuredatmosphere. These errors aver-age about 2% and about 10% atrelative humidities near 100%for one-year-old RS80-A and

14 159/2002

The Atmospheric Technology Division (ATD) ofthe National Center for Atmospheric Research(NCAR) uses Vaisala radiosondes and drop-sondes to support short-term research projectsaround the world. Researchers often use theATD data sets long after the initial data collec-tion period, and often for purposes beyondthe intent of the original project. Likewise,sounding data gathered by various nationalweather services as part of their daily opera-tional observations often become an impor-tant component of longer-term data sets usedfor reanalysis and climate monitoring. A set ofcorrection algorithms has been developed in ajoint project of NCAR and Vaisala that willsupport researchers in their work.

David Carlson, Ph.D.DirectorNational Center for Atmospheric ResearchAtmospheric Technology DivisionBoulder, ColoradoUSA

Junhong Wang, Ph.D.ScientistNational Center for Atmospheric ResearchAtmospheric Technology DivisionBoulder, ColoradoUSA

NCAR and Vaisala collaboration project for

RS80 Humidity Data Set Corrections - Steps to

Figure 1. The cumulative impact of applying theATD-Vaisala correction algorithm to the TOGACOARE data set.

RS80-H radiosondes, respective-ly. Temperature dependence er-rors occur mainly at tempera-tures below -20°C, increase sub-stantially with decreasing tem-peratures below -30°C, and oc-cur to a larger extent for theRS80-A than the RS80-H. TheATD-Vaisala correction algo-rithm produces substantial hu-midity improvements in datasets that include measurementsmade in warm moist conditions,such as tropical lower tropo-sphere data sets, or measure-ments made at cold tempera-tures such as in the upper tropo-sphere and lower stratosphere.

However, because the cor-rection methods introduce theirown uncertainties and may notcorrect all errors in Vaisala RS80Radiosonde humidity data,prospective users should careful-ly evaluate the humidity accura-cy needed, the probable sourcesof error, and the impact of thecorrection changes. An erroranalysis summary table includedin the published description ofthe ATD-Vaisala correction algo-rithm allows researchers to esti-

mate the impact and utility ofapplying these algorithms.

Impact of the corrected dataThe efforts of the ATD-Vaisalateam have made the TOGACOARE radiosonde data set oneof the most examined and high-est quality radiosonde data setsever collected. Figure 1 showsthe cumulative impact of apply-ing the ATD-Vaisala correctionalgorithm to the TOGACOARE data set. After correc-tion, over an important air-seainteraction region as large as thecontinental US, surface, mid-layer, and upper level moistureprofiles have all changed. Highnear-surface humidity valuesnow extend from 5ºN to 5ºS.Mid-level moisture values havealso increased while the dry in-trusions at 700 mb show insharper detail. Above 300 mb,moisture levels have increasedby more than 5% (due primarilyto temperature dependence cor-rections) and the presence of dri-er subtropical air in both north-ern and southern hemispheres

shows more clearly.For many research ques-

tions, humidity corrections ofthis magnitude can have sub-stantial impact. Guichard et al.(2000) showed that correctedTOGA COARE soundings re-sult in the net surface radiativeflux increasing by 4 W/m2 undera clear sky (equivalent to dou-bling CO2). Wang et al. (2001)showed that the use of correcteddata enabled some of the first re-liable estimates of long-termchanges in upper troposphericwater vapor concentrations.Johnson and Ciesielski (2000)show substantial changes in col-umn and volume moisturebudgets induced by the correc-tions applied to the TOGACOARE data. Interested readersshould consider the publisheddescription of the correction al-gorithms (Wang et al. 2002) andthe various papers reporting ini-tial results of using the algo-rithms.

What comes next?Based on the Vaisala-ATD re-search reported here and in earli-

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er issues of Vaisala News, Vaisalahas developed a sensor protec-tion cap on RS80 radiosondes toeliminate chemical contamina-tion. As those protected ra-diosondes come into wider useand as users evaluate these cor-rection algorithms for more datasets, some of the correction algo-rithm components might be-come real-time components ofdata processing systems or stan-dard parts of global reanalyses.Much of the research that pro-duced these correction algo-rithms will apply directly to theproblem of establishing reliabledata continuity as the Vaisalauser community changes fromRS80 to RS90 and newer ra-diosondes over the next fewyears. �

Improved Humidity Measurement

ReferencesGuichard, F., D. Parsons, and E. Miller,

2000: Thermodynamical and radia-tive impact of the correction of sound-ing humidity bias in the tropics. J. Cli-mate, 13, 3611-3624.

Johnson, R. H., and P. E. Ciesielski, 2000:Rainfall and radiative heating fromTOGA COARE atmospheric budg-ets. J. Atmos. Sci., 57, 1497-1514.

Wang, J., H. L. Cole, and D. J. Carlson,2001: Water vapor variability in thetropical western Pacific from 20- yearradiosonde data. Adv. in Atmos. Sci.,18, 752-766.

Wang, J., H. L. Cole, D. J. Carlson, E. R.Miller, K. Beierle, A. Paukkunen,and T. K. Laine, 2002: Corrections ofhumidity measurement errors from theVaisala RS80 radiosonde - Applica-tion to TOGA COARE data. J. At-mos. Oceanic Technol., in press.

T he Tropical Ocean GlobalAtmosphere Coupled

Ocean-Atmosphere ResearchExperiment, TOGA COARE,was conducted in 1992 and1993. It represented one of thelargest international researchprograms of the past twenty-five years. More than twentynations provided resourcesand staff to study the interac-tion between ocean and at-mosphere in the western Pacif-ic Ocean. �

Figure 2. TheTOGA COAREstudy requiredupgraded orenhancedradiosondeoperations at morethan forty sites inthe tropicalwestern Pacificregion.

T he Rocketsonde, essen-tially a rocket-deployeddropsonde, was original-

ly designed in co-operation withJohns Hopkins University – Ap-plied Physics Laboratory, tomeet naval shipboard require-ments for data used in modifiedrefractive index calculations.Radar performance may be de-graded in certain atmosphericconditions that produce ductingeffects near the ocean’s surface.Good, vertical resolution of pres-sure, temperature and humiditydata is essential to determine the

refractivity conditions affectingthe performance of radar andmicrowave communication.

The Rocketsonde has a keyadvantage over radiosondes,when acquiring refractivity pro-files. Data from a ship-launchedradiosonde is contaminated bythe microenvironment sur-rounding the ship, and typicallyis not transmitting “clean” dataat less than 200 or 300 meters ofaltitude. The Rocketsonde ejectsits sensor payload outside of theship’s microenvironment andthus provides an uncontaminat-

ed profile down to the surface ofthe sea. Data acquired very nearthe water’s surface is essential fordetermining ducting conditions.

With a Rocketsonde, verticalresolution is dependent on therate of parachute aided descent(typically 3 m/s with the RK91),rate of data transmission (ap-proximately 1 Hz) and humiditysensor response time. The re-sponse time is dependent on theambient temperature. When it isabove freezing, vertical resolu-tion will typically be 3 meters.

The Rocketsonde can also be

used overland in applicationswhere only thermodynamic datais required, or is an essentialcomponent. Test range meteorol-ogy is one example. When Rock-etsonde data is integrated withwind data generated by anothersource such as a wind profiler, itbecomes possible to model pro-jectile trajectories over a widerange of atmospheric conditions.

The RK91 can be preparedfor launch in less than 10 min-utes; it reaches apogee in lessthan 20 seconds; and provides adetailed thermodynamic profilewith 1-sec resolution. After ejec-tion of the sonde payload, thesonde floats to the surface froman average altitude of 1 km inless than six minutes. The pres-sure, temperature and relativehumidity sensors used in theRK91 are the same as those usedin Vaisala’s RS90 radiosonde.The sensor outputs and sonde-specific calibration coefficientsare transmitted over the 400.15 -406 MHz meteorological bandto a Vaisala receiving ground sta-tion. The ground station usesthe sonde-specific calibrationcoefficients to convert the sen-sor outputs into raw PTU dataand outputs it in ASCII text onan RS-232 port. The raw PTUdata is the final product, unaf-fected by filtering, averaging orother post-processing.

Wherever detailed boundarylayer profiles of atmosphericpressure, temperature and rela-tive humidity are needed, theVaisala RK91 Low AltitudeRocketsonde is a practical solu-tion that is available today. �

Rocketsonde sounding component requirements:

• RK91 Low Altitude Rocketsonde

• Rocket motor• Rocket motor igniter• Ignition Control Unit (ICU)• Launcher• 400 MHz Antenna• Antenna pre-amplifier• Vaisala Sounding Processor

16 159/2002

Vaisala Launches the RK91 RocketsondeHistorically, in-situ measurements of pressure, temperature and hu-midity in the boundary layer have required the use of free-flight ra-diosonde or tethered balloon type atmospheric sounding systems. Insome cases, the use of these conventional sounding techniques is notpractical. Where availability of helium or hydrogen is a problem, orwhen ease and speed of deployment is desirable, Vaisala’s new RK91Rocketsonde is an ideal alternative for the acquisition of boundarylayer profiles.

The Vaisala RK91 Low-Altitude Rocketsonde offers detailed boundary layer profiles of atmospheric pressure,temperature and relative humidity.

The Finnish Defense Forcesdecided to acquire 10 systems ofthis kind and these were deli-vered between December 1998and November 1999. As is oftenthe case in this kind of extensivesystem delivery, some mechani-cal solutions naturally neededreview by Vaisala after the deliv-ery had taken place. However,Vaisala resolved these issuespromptly.

In August 2001 the ArtilleryBrigade trained system users inthe Field Artillery from othersites. After the training period,some of the systems were thenhanded over to the ReadinessBrigades. Various visiting foreigndefense forces have shown greatinterest in this concept, which isin our opinion the fastest andmost compact mobile soundingsystem in the world. �

T he Radiotheodolitemeasurement principleand its accuracy were

tested through the carrying outof dozens of soundings. Radio-theodolite was compared withthe Mobile Automatic SoundingStation (MAMS) and with thefixed Omega-based system.MAMS Sounding System com-prises a parabolic tracking anten-na on quite a heavy shelter witha dedicated Sounding Processor.The test results and experienceindicated this new concept to bea good choice for a light sound-ing system.

The production prototype ofthe Vaisala Radiotheodolite wastested at the Field Artilleryshooting range at Rovajärvi, Lap-land in 1993. The designdemonstrated at the camp intro-duced the functionality and fea-tures which are included in theproduction models. We appreci-ated for instance the system’slight weight and 24 VDC operat-ing voltage. Since then Vaisalahas participated in a number oftraining camps in Lapland in or-der to evaluate the performanceof the Radiotheodolite in

Finnish field conditions aroundthe year. I’m sure that all ofVaisala’s personnel who were in-volved will remember the condi-tions of the darkest and coldestLapland winter at Rovajärvi.Useful ideas on design detailsand accessories came up, manyof which have been implement-ed in the product.

New concepts for improved performanceWe tested the Radiotheodoliteantenna’s various lifting mecha-nisms (lifting heights rangedfrom a few meters up to 7 me-ters). Additionally, the basicconcept was to have all neededcomponents installed on a light

trailer, a problem we solved bymounting removable storageand transportation boxes on thetrailer. To operate the system theoperator simply needed to openthe protective tarpaulin, lowerthe hydraulic support legs, ele-vate the antenna to the uprightposition and prepare the sound-ing computer MARWIN.

The removable boxes andthe Radiotheodolite antennamake the system flexible to usein both mobile and fixed mode.It is possible to remove thewhole Radiotheodolite antenna,MARWIN Sounding Processorand power supply boxes fromthe trailer for operation in a tentor building.

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Mobility and ease of use

Development of the LightMeteorological SoundingSystem M200The Finnish Defense Forces at the Luonetjärvi Sounding Station incentral Finland pilot tested a Vaisala Radiotheodolite prototype inthe summer of 1992. Since then a number of development effortshave been made to develop a truly mobile and compact soundingstation which has all of its components integrated on a trailer whichis easy to transport and deploy.

Main features

T he light upper air sound-ing system M200 is an au-

tomated meteorological dataacquisition system to help makeballistic calculations for field ar-tillery and other tactical appli-cations. The system is highly au-tomated, including data qualitycontrol, message formattingand distribution to modernforms of communication.

The Radiotheodolite anten-na automatically tracks themovements of the radiosonde.The sounding system receivesupper air pressure, tempera-ture and humidity data fromthe radiosonde. Wind velocityand direction are calculatedfrom the antenna’s elevationand azimuth data and the hy-drostatic altitude. The systemweighs a maximum of 1300 kg(including all accessories) and istowed with a 4-wheel drive ve-hicle. The trailer houses a hy-drogen cylinder, hydrogen gen-erator, engineering tools, fieldcomputer, and manual weathermeasurement devices. �

Reijo Miettinen, Senior Lieutenant Leader of the Niinisalo Meteorological Observation StationReconnaissance Artillery BattalionArtillery BrigadeThe Finnish Defense ForcesNiinisaloFinland

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A team of three operatorscan set up and make thepreliminary preparationsfor sounding quite quickly(in less than 7-8 minutes).

The Salt Lake City Olympic Scene

The recent 2002 Winter Olym-pics Games and the subsequentParalympic Games in Salt LakeCity, Utah, during February andMarch are now a pleasant memo-ry. The Salt Lake Olympic Orga-nizing Committee (SLOC)earned high praise in doing agreat job in orchestrating all ofthe support activities for a recordnumber of events during theGames.

The sprawl of Olympic activ-ities was large. In addition to SaltLake City (SLC) being the sitefor the Opening and Closing cer-emonies, as well as Medal Awardceremonies, there were sevensports venues scattered northand south along the nearbyWasach Mountain Range: • Ogden/Snowbasin Area –Curling and Alpine Downhill(51 miles north of downtownSLC)

• Utah Olympic Park – Bob-sleigh, Luge, Ski Jumping,Nordic Combined (32 miles eastfrom downtown SLC)• Park City/Deer Valley –Alpine Giant Slalom, Snow-board, Freestyle (8 miles furtherfrom Olympic Park)• Heber City/Soldier Hollow –Biathlon, Cross-Country Skiing,Nordic Combined (15 miles fur-ther from Park City)• Provo – Ice Hockey (46 miles south of downtown SLC)• West Valley/Kearns – IceHockey, Speed Skating• Salt Lake City – Figure Skat-ing, Short-Track Speedskating

The Weather Monitoring ChallengeWeather information was essen-tial for the planning and main-taining of activities at the Olym-pic Games in SLC and sur-rounding areas. The venues ofthe Games spanned a large areain northern Utah, where the ter-

18 159/2002

Selwyn AlpertNorth American Sales ManagerSurface MeteorologyVaisala IncWoburn, MassachusettsUSA

The 2002 Salt Lake City Winter Olympic andParalympic Games are now a fond memoryof athletic achievement and enjoyablespectator experience. A key aspect of theoverall success was the extensive planningand effective implementation of a varietyof support activities, including aviation se-curity operations. The USAF Tactical Mete-orological Observing System (TMOS), sup-plied by Vaisala, provided sports venue re-al-time meteorological data and played animportant role for the USAF to effectivelycarry out their aviation support activities.

Support for medical and security aviation operations

US Air Force TMOS (TACMET) at 2002Winter Olympics in Salt Lake City

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rain is complex. Not only out-door sport events but also manyother activities were affected bythe weather, such as outdoor cer-emonies, transportation, park-ing, snow making, emergencyand security operations. In addi-tion to being prepared for ad-verse, even hazardous weather,the organizers and athletes par-ticipating in outdoor events con-tinuously required accurate andtimely weather information. Toprovide this information, an ex-tensive weather support systemwas developed, which was man-aged by the Salt Lake CityOlympic Organizing Commit-tee (SLOC). It involved meteo-rologists from government agen-cies, private companies and theUniversity of Utah. 1

Because of the complex ter-rain of Northern Utah and theinteraction with weather patternflows from the Northwest, a se-ries of unique microclimates de-velop in the area. Weather at onevenue can be quite differentfrom other venues, with differ-ences for such parameters astemperature, wind, precipitationand visibility. It is for this reasonthat performance of aviation op-erations in key corridors be-tween venues, as well as at spe-

cific venues, would call for avia-tion weather data providing real-time information at specific sitesof interest.

USAF Aviation Supportand TMOSLocal aviation operations for theOlympics were performed bythe US Air Force (USAF), withcoordination provided by theirAviation Security OperationsCenter (ASOC) at nearby HillAir Force Base. The ASOC fore-casters provided forecasts andbriefings to the pilots. Heli-copters from Hill Air Force Basewere utilized for security patrolsas well as for potential visits toand from the various venues. Insupport of these operations, US-AF weather forecasters fromASOC received forecast infor-mation from the US NationalWeather Service (NWS) WesternRegion Headquarters. Addition-ally, they used real-time aviationweather data from deployed US-AF portable aviation weather sta-tions at the sports venues andother key locations.

A compact and portable systemThese USAF aviation weatherstations have the military

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TMOS being installed at Mountain Airport. Note mobile ATC Tower onHumvee in the background. TMOS hard-wired to PC in ATC Tower forairport operations. Temperature at the time is -4 °F (-20 °C).

TMOS at Utah Winter Olympic Park site. TMOS team members providingcheckout during a routine site visit.

➤ Entrance to Snowbasin Ski Area. Site of Alpine Downhill and Super-G.

designation of AN/TMQ-53Tactical Meteorological Observ-ing System (TMOS), and arepart of the AF inventory in sup-port of tactical aviation opera-tions worldwide. This system issupplied by Vaisala, and is a con-figured version of Vaisala’sMAWS201M TACMET Sys-tem. These portable aviationweather stations are compactand quick to deploy. They pro-vide continuous automated datafor the following parameters:wind speed and direction (in-cluding gusts), air temperature,relative humidity, barometricpressure, liquid precipitation,liquid precipitation equivalentfor snow, visibility, cloud height,precipitation type (presentweather) and lightning detec-tion, giving range/direction.

The aviation data is viewedon a PC (radio or hardwire link)with MIDAS IV software, pro-viding real-time data as well asMETAR/SPECI reporting. Ahandheld display also providesdata/diagnostic information fora direct readout at the weatherstation. 2

Real-time aviation dataThe value of TMOS to ASOC

was that they provided reliablereal-time aviation data from thevenues and other sites, whichwas an important supplement tothe general model forecast dataavailable. The TMOS were de-ployed at 6 sites: Snowbasin SkiArea (Alpine events), WinterSports Olympic Park (Bobsleigh,Luge, Ski Jumping), Park CityMountain Resort (Alpine andSnowboard), Soldier Hollow(Biathlon and Cross-Country),the Mountain Pass location be-tween Salt Lake City and ParkCity, and the Mountain Airportlocation. With the TMOS, heli-copter pilots and others wouldknow exactly what weather con-ditions were at the specificTMOS sites. Based on a verypositive past experience with theTMOS, ASOC felt confidentTMOS would be a reliable anduseful tool. And it was!

The use of the TMOS at theOlympics was coordinated byMr. Ed Robinson, a contractorto the Air Force Weather Agency(AFWA) and a former Air Forceman. He and members of hisTMOS Support Team per-formed the installations and in-sured information flow made itback to ASOC. The USAF con-

siders TMOS data of high quali-ty. In addition to its local use atASOC, the data was forwardedto the USAF Weather ProcessingDistribution System (WPDS) forworldwide distribution.

USAF’s Overall Experience with TMOSMr. Ed Robinson has been fol-lowing the implementation ofTMOS from its initial stages ofqualification to its current de-ployment worldwide. He hasUSAF weather forecasting expe-rience, and has been the point-of-contact from AFWA to theend-users (field people who usethe equipment during tacticaloperations). Mr. Robinson andhis colleagues at AFWA arepleased with the very positive re-ception the TMOS has receivedfrom the end-users, includingASOC. Reports back from thefield by combat weather person-nel involved with the deploy-ment and use of TMOS includestatements such as: “The hand-held display was easy to programand worked flawlessly, as did theMIDAS IV software. The sensorintegration is outstanding.” Edhas indicated that, based on hisexperience as a USAF weather

forecaster and the equipmentavailable in the past, the“AN/TMQ-53 is the best tacticalweather equipment that AFWAhas fielded in the past 20 years.”Vaisala is proud to have its prod-ucts appreciated by key militaryorganizations, as well as to havebeen a part of the global stage ofOlympic competition. �

Footnotes1) An excellent article in the February2002 Bulletin of the American Mete-orological Society Journal describesWeather Support Operations for the2002 Salt Lake City Winter Games.

2) A more detailed description of thesystem is provided in the 2001 VaisalaNews article: “Versatile AutomatedWeather Observation for DemandingMilitary Needs,” by Hannu Kokko.

References1. Weather Support for the 2002 Winter

Olympic and Paralympic Games. ByJ. Horel et al. – Bulletin of the Ameri-can Meteorological Society: Vol. 83,pp. 227 – 240.

2. Versatile Automated Weather Observa-tions for Demanding Tactical Mili-tary Needs. By Hannu Kokko. –Vaisala News: Vol 155/2001, pp. 14 – 17.

20 159/2002

Mr. Ed Robinson, AFWA contractor and SLC TMOS Team coordinator,checks out TMOS at the Snowbasin site using a handheld display.

Weather office at Snowbasin, overlooking finish line and scoreboard (outsideoffice window). Weather forecaster uses display of weather networkinformation as well as local display from nearby USAF TMOS.

A vailable for both fixedinstallations andportable use, MAWS

weather stations provide contin-uous and reliable data on a mul-titude of meteorological and hy-drological parameters. TheMAWS product family is used ina wide variety of applications,such as climatological measure-ments, hydrometeorological net-works and a variety of researchand synoptic applications.

Extended sensor libraryThe sensor library has been ex-tended with new sensors such as

sunshine, rain duration and fuelmoisture sensors. Generic sensorinterfaces are also now available,allowing the connection of oth-er, third-party sensors to theMAWS.

The QFM101 Fuel Moistureand Temperature Sensor meas-ures the moisture content of ma-terial on the floor of a forest orother natural area to help forestmanagers assess the danger offire. The QFM101 sensor appliesthe carefully selected pine dowelto take moisture from the forestfloor and then measures themoisture content of the

159/2002 21

Hannu Kokko, B.Sc. (Eng.)Product ManagerSurface Weather DivisionVaisala Helsinki Finland

MAWS Automatic Weather Stations

Enhanced with New FeaturesThe Vaisala MAWS301 Automatic Weather Station, which waslaunched last year, has gained a significant market share in the au-tomation of synoptic and climatological networks in Europe andSouth America. We are now introducing a number of new and en-hanced features to the popular Vaisala MAWS product family of au-tomatic weather stations. In line with Vaisala’s commitment to con-tinuous product development, the new features further enhance theuse of the MAWS product family.

➤

The Vaisala MAWS family of versatile Automatic Weather Stations

T he Vaisala MAWS101 Automatic Weather Station (AWS)is a compact, economical solution for applications that

require accurate and reliable weather data from a limitednumber of parameters. It is easy to set up and operate.

The Vaisala MAWS201 Automatic Weather Station is atruly portable AWS specially designed for temporary instal-lations. Its light weight, low power consumption and largememory capacity make it ideal for research applications.

The Vaisala MAWS201M Tactical Meteorological Obser-vation System (TACMET) is a compact weather station offer-ing a broad range of sensors. It is easily deployed in the fieldand offers complete aviation support and lightning detec-tion. Its modularity makes it easy to up-grade in the field in support of differ-ent tactical missions. The MAWS201MTACMET is the meteorological systemused by the US Air Force in theirAN/TMQ-53 (TMOS) system.

The MAWS301 Automatic WeatherStation is designed for applicationswhere commercial power and commu-nications networks are not available.An extensive library of sensor andtelemetry options makes the MAWS301the ideal choice when a wide range ofaccurate meteorological and hydrome-teorological measurements are re-quired with a low ownership cost. �

The MAWS product family isused in a wide variety ofapplications, such as climatologicalmeasurements, research,precipitation networks, energyproduction and management, andbuilding automation.

wood according to its electricalcapacitance. In addition, a ther-mistor located in the dowelmeasures the temperature of theforest floor.

The QMT107 Multi-levelSoil Temperature Probe is aunique sensor measuring air/sur-face-soil temperatures at 7 differ-ent levels. The sensor probe isburied into the soil using a spe-cial auger. The sensor levels havebeen selected so that they corre-spond to the WMO instructions(WMO book No. 8), with addi-tional sensors at ground leveland 5 cm above it. The sensor el-ements are accurate Pt-100 resis-tors (IEC 751 1/3 Class B). Aswell as being a very compact sen-sor, the QMT107 takes only onedifferential sensor input in thelogger. The command set in-cludes a single-point calibrationcommand for calibrating all sev-en sensors at the same time in awaterbed at the same tempera-ture.

For water-level measurementthere are now several alternativemethods which can be selecteddepending on the characteristicsof the installation site and exist-ing structures. As an addition tothe current methods of pressuresensor and ultrasonic sensor, anIncremental Shaft Encoder,

QSE101, can also be selectedfrom the sensor library.

Serial communicationMany of the new sensors havetheir own microprocessor andfieldbus for data transmission.To make sure that these new sen-sors can be interfaced with theMAWS, the DSI486 Dual Isolat-ed RS-485 CommunicationModule has been added as anoption. This module offers twoisolated RS-485 I/O lines for in-terfacing sensors and/or displaysto the MAWS System. Alterna-tively, the same module can beconfigured by the user to haveone RS-485 and one RS-232port. Moreover, there is a SDI-12 port for interfacing hydrolog-ical sensors, for example.

TelemetryWhen monitoring remote sites,telemetry plays a most signifi-cant role. Telemetry often makesup the most significant part ofthe annual operating cost of amonitoring network. Therefore,in the MAWS Systems we havepaid special attention to teleme-try options. The wide range oftelemetry options has been fur-ther enhanced with the possibil-ity to use the OmniSAT satellitesystem for real-time data trans-

power in a system powered by asolar panel.

Statistical calculationsThe MAWS System automatical-ly calculates statistical parame-ters such as average, minimum,maximum, standard deviationand sums, over periods and atintervals that the user can speci-fy. This feature has been expand-ed to allow the reporting of theintermediate values of these cal-culations. For instance if wehave a standard calculation ofhourly averages for air tempera-ture, reports of 10-minute valueswill also be available (average,minimum and maximum) for 0 -10, 10 - 20, 20 - 30, etc. minutes.

Data loggingData logging can be done bylogging user-defined data groupsat freely configurable intervals.Logging can also be triggered bya measured or calculated para-meter exceeding the user-setthreshold value, in other wordsan alarm. The internal flashmemory of 1.7 Mbytes is suffi-cient for most applications.However, for extended memoryrequirements, there is a Com-pact flash memory card option,which enables the logging ofhundreds of megabytes intostandard CF cards.

22 159/2002

The generic sensor interface allows the user to set up powering, conversion anddata validation parameters.

The QMT107 Multi-level Soil TemperatureProbe measures air and surface soiltemperatures at 7 different levels.

New serial communicationmodules allow flexible sensorinterfacing.

mission. The first systems usingthis geostationary satellite sys-tem are now operational inBrazil. The Brazilian AUTO-TRAC system delivers the data100 % reliably and in real-time.The data are received with a de-lay of only 2-9 seconds in theground receiving station’s server.The data is available for the userat any time, for instance if thereare no preset time windows de-fined by the satellite operator.

The MAWS has the meansto switch on and off the trans-mitter automatically to save

for example, only every 3 or 6hours.

The user also has the optionof compressing the report(s).This function is particularly use-ful when the data is transferredusing methods which are costlyor otherwise limit the amount ofdata to be transferred. Suchmethods include, for example,satellite systems and SMS (ShortMessage Service) messages incellular data transfer.

There are two methods forautomatic report formatting:BASE32 and BCD. TheBASE32 formatting methodproduces ASCII data and thusprintable characters. In thismethod, every data item on thereport is scaled and convertedusing a radix of 32 instead of thenormal 10. The BCD (BinaryCoded Decimal) method is a Po-sitional Number System, with aradix of 10 and coefficients ex-pressed in a 4-bit binary word.The BCD formatting methodproduces non-printable binaryreports.

Flexible mechanical designThe MAWS301 System includesa large number of telemetry andpowering options. In addition,some of the new sensors requirenew powering arrangements,such as, for example, the heatedultrasonic anemometer. There-fore the layout of the systemcomponents in the equipmentenclosure BOX501 has been re-arranged to allow easier access tothem. There is also now morespace for optional surge protec-

159/2002 23

Report formatting

When the user configures theoutput reports, a very user-friendly interface provides accessto all the MAWS’s measuredand calculated parameters. Thisfeature has been further en-hanced with new options.

The logged data can alsonow be automatically formattedas reports. The user can selectthe number of records from thelogged file to be included in thereport. There are two automati-cally made report formats.When using the SCAN format,

the logged data items are organ-ized in columns, in such a waythat one column consists of themeasurements of one item overa user-set period of records. Inthe CHANNEL ordered reportformat, the logged data are or-ganized in rows, with one rowconsisting of the measurementsof one item over a period ofrecords. The data items are, bydefault, separated by a space, butthe user can also change thisparameter.

This option is the most con-venient when data is not neededin near-real-time but will be sent,

The new tiltable mast facilitates easyinstallation and maintenance.

The memory capacity ofthe QML102 AWSLogger can be extendedwith a Compact flashmemory card.

tion devices and wiring terminalsfor whenever larger systems mustbe engineered.

The new design also includesa white painted back plate asstandard, and new brackets formounting the enclosure to polemasts of various diameters.

New tiltable mastTo install a 10-meter mast ormaintain wind sensors at thatheight has previously required 2- 3 people. The new tiltable mastDKP210 can be installed or low-ered by just one person, whichsignificantly reduces the annualmaintenance cost. Installationhas also been made easier withthe careful design of equipmentmounting hardware and a lighterweight. Special attention hasbeen paid to proper lightningprotection and grounding of themast. The mast includes one setof guy wires, a lightning rod anda complete foundation set fornew or old concrete blocks. Anextra set of guy wires and awinch, which can easily be in-stalled and carried, are also avail-able as options.

Versatility for variousapplicationsConfiguration of the MAWSSystem is flexible and the systemcan incorporate a large numberof sensors and telemetry options,all of which are easy to install.These features make the MAWSSystem a cost-effective and reli-able choice for a vast number ofmeteorological and hydrometeo-rological monitoring applica-tions. �

A ccording to the con-tract signed in late2001, Vaisala will sup-

ply fifty Automatic Weather Sta-tions to the Polish Institute ofMeteorology and Water Manage-ment (IMGW). Delivery and in-stallation will take place in 2002.The Factory Acceptance Test wassuccessfully passed in April 2002.The project is financed with aWorld Bank loan.

The delivery includes 50Vaisala MAWS301 AutomaticWeather Stations, with sensorsfor measuring wind, pressure, airand soil temperature, relativehumidity, solar radiation, pres-ent weather, visibility and cloudheight. The delivery also in-cludes an Observation Console(MetMan) for collecting andmanaging the measurement da-ta. The MetMan Console con-

tains full SYNOP and otherweather message support.

Vaisala has delivered some120 MAWS stations to Poland intotal, about 50 of which are usedas climatological stations byIMGW, whereas the current de-livery is meant for the synopti-cal stations of IMGW. The re-mainder are used in applied me-teorology. �

24 159/2002

Fifty MAWS Automatic Weather Stations to Synoptic Stations in Poland

IMGW representativesparticipated in theFactory Acceptance Testand product training atVaisala. From the left:Mr. Andrzej Maciazek,Chief Engineer, Mr. JanOrlowski, Chief of theTeleinformatic Center,Beata Surdyk,Practicant, PiotrPitrzykowski, Engineer,Krzysztof Szymanski,Engineer, SebastianModliszewski,Engineer.

Chief Engineer, Mr. AndrzejMaciazek and Chief ofTeleinformatic Center Mr. JanOrlowski testing the MetManObservation Console.

159/2002 25

Automatically compensates for window contamination

Unlike most forward scatter sen-sors, the FS11 incorporates anew technique that measuresand compensates for the attenu-ation effect of window contami-nation. It ensures that measure-ment accuracy is maintainedthroughout the recommendedinterval between window clean-ings – and it lengthens this inter-val. The system works by moni-toring the total reflectance of thewindow surface. It automaticallycompensates for visibility meas-urement errors caused by win-dow contamination.

A scientifically validchain of calibrationWhen evaluating forward scattersensors, special attention mustbe paid to calibration. EveryVaisala FS11 is calibratedthrough a scientifically validchain of reference. The scatteringresponse of the calibration de-vice can be clearly traced to a ref-erence FS11 Visibility Sensor,which is in continuous operation

at Vaisala’s outdoor test field,along with reference transmis-someters and other instrumenta-tion. The FS11 offers a measure-ment range of up to 75 km andmeets WMO, ICAO and FAAspecifications for visibility meas-urement in civil aviation.

Operates reliably in theworst weatherFour main design features arecombined in the FS11 to ensurethat it operates reliably in theharshest weather. The first is thewindow contamination com-pensation technique. The sec-ond is the “head-down” designof the optical heads, which pro-tects them against virtually allwind-blown particles (even thoseflying horizontally). High-powerheaters are the third feature,each with its own temperaturemonitoring and control mecha-nism to prevent snow accumula-tion during the heaviest snow-storm. As a final measure, thereis optical path clearance moni-toring circuitry to verify thatmeasurement is not affected byobstructions.

A snap to serviceThe FS11’s sophisticated self-di-agnostics and modular design al-low for very short service times.The measurement fork and op-tional background luminancemeter (LM21) are independentinstruments that can be replacedquickly as pre-calibrated spareparts.

New level of reliabilityin background lumi-nance measurementA new LM21 Background Lumi-nance Sensor has been launchedalong with the FS11. The LM21provides similar monitoring andcontamination compensationfeatures as the FS11, and raisesbackground luminance measure-ment to a new level of reliability.Traditionally, background lumi-nance sensors have either incor-porated rudimentary self-moni-toring features or had none atall. �

New technology for runway visual range application

FS11 Visibility SensorLaunched

Traditionally, transmissometers have been theestablished type of visibility sensor for runwayvisual range (RVR) measurement, a key safetyparameter in commercial aviation. In recentyears, another type, the forward scatter sen-sor, has begun to gain acceptance around theworld for this demanding application. Thenew Vaisala FS11 Visibility Sensor offers anumber of new features that ensure reliablevisibility measurement in any weather.

The Vaisala FS11 ForwardScatter incorporates a newtechnique that measures andcompensates for the attenuationeffect of window contamination.

T he Vaisala LD40 is a long-range ceilometer for cloud

detection and atmospheric pro-filing that operates up to 43,000feet (13 km) and offers a verticalresolution of 25 feet (7.5 m). Themeasurement principle is basedon the LIDAR technique (LightDetection and Ranging). Shortpulses of light are emitted by alaser diode, focused to a parallelbeam, then transmitted verticallyinto the atmosphere. Part of thelight is scattered back to theceilometer from the aerosols inthe atmosphere (clouds, precipi-tation, fog etc.). From the re-ceived backscatter signal the

ceilometer calculates cloudheight and evaluates maximumdetection range, vertical visibilityand precipitation intensity sta-tus.

High performance under all kinds of precipitation The standard report that theLD40 produces includes heightvalues for up to 3 cloud layers.The long measurement range al-lows cirrus clouds to be detectedat a high altitude. Sophisticatedalgorithms are employed to en-sure reliable cloud detection un-der all kinds of precipitation.

When the cloud base is obscured,by, for example, heavy precipita-tion, and it cannot be distin-guished, vertical visibility is stillreported. In addition to the stan-dard data message the LD40 canalso report raw measurement da-ta, which can be utilised for dif-ferent research purposes.

Reliable instrument forversatile use The LD40 operates unattendedunder all climatic conditions. In-ternal monitoring ensures reli-able operation: messages are au-tomatically transmitted contain-ing information on internal di-agnostics. The LD40 can be op-erated as a stand-alone instru-ment or as part of a large mete-orological system. Connectionto different systems is, in fact,very flexible as the data line canbe configured to use different se-rial interface protocols. Its de-sign is modular: subassemblies

such as the laser transmitter caneasily be replaced in the fieldwithout optical realignment.

Due to its measurementrange, the LD-40 is especiallysuitable for synoptical measure-ment stations where the detec-tion of high clouds is also desir-able. At the moment, the largestinstalled bases are operated bythe German Weather Service(DWD) and the Royal Nether-lands Meteorological Institute(KNMI) at their weather obser-vation networks. �

26 159/2002

Vaisala LD40 Ceilometer launched

Cloud Height Measurement up to High Cirrus

I n Romania a program to devel-op a National Integrated Mete-

orological System (SIMIN) is un-der way. The program has beencarried out by Lockheed MartinOverseas in cooperation with theRomanian National Meteorolog-ical and Hydrological Institute. Inthis framework, two Vaisala Avia-tion Weather Reporter AW11Systems were installed at Roman-ian Air Force bases in November2001 and an additional two sys-tems in spring 2002.

For the next two years,SIMIN will provide meteorolog-ical infrastructure upgrades inRomania, including the integra-tion of ground, altitude, radarand satellite meteorological data,as well as disseminating the datato users in realtime.

The Romanian Air Forcechose to acquire Aviation Weath-

Complete aviation support

Romanian Air Force choose Vaisala AviationWeather Reporter AW11

The VaisalaLD40Ceilometeroffers a highmeasure-ment rangeenabling thedetection ofhigh cirrusclouds.

The Vaisala LD40 Ceilometer is a compact andeye-safe ceilometer for cloud detection andatmospheric profiling up to a height of 43,000feet (or 13 km). The high measurement rangeenables the detection of high cirrus clouds notreached by any other standard ceilometer.

The Vaisala Aviation Weather Reporter AW11 installed at BorceaAir Base . From the left product engineer Kusti Kairikko ofVaisala, captain-commander Dan Florea, Chief of the Air ForcesMeteorological Service and captain-commander Simion Pop of theRomanian Air Force.

Vaisala TACMET Stations weredeployed on the roof of the Free PressHouse in Bucharest to support theNational Day parade.

159/2002 27

T he Vaisala MIDAS IVAirport Weather Observ-ing System (AWOS) will

gather meteorological data fromsensors installed along Helsinki-Vantaa Airport’s existing tworunways, as well as from theVaisala meteorological sensorsthat are included in the deal tobe delivered for the new thirdrunway.

Meteorological sensorsfor the new third runwayVaisala sensors for measuringmeteorological parameters, Run-way Visual Range and cloudheight will be installed along thenew runway. For ice warningsand predictions, Vaisala will alsodeliver three ROSA RunwayWeather Stations, maintenanceinformation from which will beshown on displays incorporatedin the MIDAS IV AWOS. Anintegrated management systemis included in the deal that will

handle weather data from run-ways 1 and 2. Vaisala is theprime contractor supplying theaviation weather system toHelsinki-Vantaa Airport’s Run-way 3 project.

Leading the way This deal marks a significant firstfor Vaisala. The Vaisala MIDASIV AWOS, which will totally re-place Helsinki-Vantaa’s current,self-designed AWOS, will be in-stalled in summer 2002 in prepa-ration for the new runway’s in-auguration, and will gather andintegrate meteorological datafrom all 3 runways. Further-more, Vaisala will act as themain weather observation con-tractor, incorporating anATIS/VOLMET system provid-ed by Terma A/S, a leading Dan-ish contractor, and control towerdisplays provided by FRE-QUENTIS NachrichtentechnikGmbH of Austria, headquar-tered in Vienna.

New runway increasescapacity at Helsinki-Vantaa AirportConstruction of the new runway(runway 3) at Helsinki-VantaaAirport is one of the major re-cent airport developments inEurope. Scheduled for inaugura-tion in November 2002, runway3 will be used as the main run-way for takeoffs, allowing some40% increase in operations ca-pacity over the current two-run-way system. �

New runway for larger capacity

Vaisala Equips Helsinki-VantaaAirport with Automated Weather Observing SystemVaisala has signed a contract with the CivilAviation Administration of Finland to delivera MIDAS IV Automated Weather Observing System (AWOS) to Helsinki-Vantaa Airport.Under the terms of the contract, Vaisala willdeliver an Automated Weather ObservingSystem and associated meteorological sensors to the new runway of the airport.The system will be installed in summer 2002,and the new runway is scheduled to open inNovember 2002.

At present, Helsinki-VantaaAirport serves over 10 millionpassengers every year, and hasbeen rated as one of the bestairports in the word in the pastfour years.

T he Romanian Air Forceunits participated in

the annual parade organ-ized in Bucharest in cele-bration of Romanian Na-tional Day on December 1,2001. Among other demon-strations, a formation of six“IAR Socat” - type helicop-ters executed a formationflight.

The Romanian AirForce chose Vaisala’s Tacti-cal Meteorological (TAC-MET) Observation Systemto support this popularevent because of the easeof deployment, reliableperformance and versatilemeasurements. The en-hanced configuration of-fered accurate measure-ments of weather parame-ters, such as cloud base, vi-sibility and wind, whichwere crucial to support thehelicopters participating inthe parade. �

TACMET Systemsat National DayParade

er Reporter AW11 Systems man-ufactured by Vaisala on the basisof the special qualities, perform-ance and functionalities provid-ed for meteorological supportnecessary for the training and op-erations of the Air Force. The AirForce also appreciated the systemconcept and technology, beingalso compliant with the NATOrequirements. The fully automat-ic Vaisala Aviation ReporterAW11 is a stand-alone weatherobservation and reporting systemwhich measures all standard avia-tion weather parameters and gen-erates accurate real-time weatherreports. Standard measurementsinclude sky condition (cloud lay-er height and coverage), visibility,air pressure, temperature, dew-point, and wind speed and direc-tion. Precipitation occurrenceand intensity measurements arealso available.�

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28 159/2002

T he use of automatic roadweather stations has be-come increasingly com-

mon to help make road main-tenance decisions in countrieswhich experience adverse surfaceweather conditions in winter.Modern road weather stationsprovide the user with a widerange of measurement results,for example road surface temper-ature, detailed classification ofroad conditions, thickness of wa-ter and ice on the road, freezingpoint temperature, and amountand concentration of de-icingcompound. The grip depends

on a number of conditions andthe study focused on researchingexactly which measurement re-sults best indicate a vehicle’sgrip. To this end, a field trial wasconducted using an installedroad weather station (RWS) tofind out which of its measure-ment results best indicated a ve-hicle’s grip on the roadway. Atotal of 530 human observationsof grip were collected byFinnRA during two winters. Themeasurement results and obser-vations were analysed at Vaisalaboth manually and using a neu-ral network.

The trial setupFor the trial, a test system was setup with both the latest availablesensor technology and inde-pendent human observation.The test was conducted in such away that there was no feedbackin either direction. The field testwas conducted at the Utti roadweather station in SoutheasternFinland during the winters of1999-2000 and 2000-2001. TheRoad Weather Station was locat-ed beside a two-lane main roadwith average daily traffic of 8700vehicles. The test site was a verytypical Finnish road weather sta-

tion site set in demandingweather conditions and it was toyield a wide range of observa-tions on vehicle grip. The roadwas also monitored with a roadweather camera.

The measurements were car-ried out using the VaisalaDRS511 Road Sensor 1 and wereanalysed by the ROSA RoadWeather Station. From the widerange of output data, the thick-ness of ice and water were cho-sen to be used. To get the mostrepresentative data, the DRS511was located in the wheel track ofthe lane.

A Field Trial of Vehicle GripCompared to RWS DataDriving safety is a key concern for road author-ities. Other than the weather, one of the mostinteresting factors which affects safety is a ve-hicle’s grip, i.e. the friction between a vehicle’stires and the road surface. Together with theFinnish Road Administration Vaisala conduct-ed a field trial in Southern Finland during thewinters of 1999-2000 and 2000-2001 to studywhich measurement results best indicated avehicle’s grip. In the trial, the measurementsfrom the Vaisala ROSA Road Weather Station(RWS) were compared with independent hu-man observations of vehicle grip.

Figure 1. A picture of the field trial site taken by the roadweather camera. An arrow marks the DRS511 road sensor.The ROSA Road Weather Station is located outside the view.

Figure 2. The average thickness of the ice layer compared to the gripobservations. It has been determined in laboratory tests 2 that an ice layer of0.05 mm is the threshold value for dangerously slippery roads.

Taisto Haavasoja R&D Manager

Ville Haavisto, M.Sc. (Eng.)Electronics Engineer

Markus J. Turunen, M.Sc (Eng.)Scientist

Pauli Nylander, M. Sc (Eng.)Software Engineer

Vaisala HelsinkiFinland

Yrjö Pilli-SihvolaHead of the Traffic Information CentreFinnish Road AdministrationSoutheastern Traffic Management CentreKouvola Finland

The human observations

The observers for the trial weredrawn from the staff of theFinnish Road Administration.Altogether they collected 530 in-dependent human observationsof vehicle grip. The observationswere made over two winterweather periods from 16 Novem-ber 1999 - 28 March 2000 and 9November 2000 - 28 March2001. The observations were col-lected at different times of theday on almost a daily basis.

The observations were col-lected by driving past the roadweather station amongst othertraffic, and therefore representeda typical road user’s impressionof vehicle grip. The observerswere all professionals with exten-sive experience in classifyingwinter road conditions.

Grip was divided into threeclasses: good grip, reduced grip,and poor grip. These classes gavesufficient information on roadconditions and were also suit-able for the observation method.The following criteria were ap-plied:

The observations can beconsidered as representative dataas the number of reduced andpoor grip observations was fairlyhigh, altogether 21 %.

ResultsFirst we examined the thicknessof the ice layer compared to theobserved grip. The results areshown in fig. 2. The three datapoints in fig. 2 were calculatedby taking the average value ofthe thicknesses of the measuredice layers in each grip class.

It can clearly be seen that onaverage the grip correlates wellwith the thickness of ice layer.The thicker the ice layer, theworse the grip. It is also interest-ing to note that very thin ice lay-ers do not necessarily make theroad slippery: the average thick-ness of ice in the good grip classis 0.02 mm. This is in line withlaboratory tests 2, in which theeffect of ice thickness on gripwas examined in laboratory con-ditions. There results showedthat an ice layer of 0.02 mm onasphalt does not reduce grip sig-nificantly, whereas a layer of0.05 mm was found to be thethreshold value for dangerouslyslippery asphalt.

The other grip classes alsocorrespond with this thresholdline. The threshold line could beexpected to be located some-where between the reduced andpoor grip classes. However, thethreshold line that actually re-sulted is likely due to the factthat the laboratory tests weremade with a normal piece of tirewhereas the observers used stud-ded tires.

In summary, the results showthat on average the thickness ofthe ice layer indicates a vehicle’sgrip very well. However, to an-swer the question whether gripcan be determined only on thebasis of ice thickness in all cases,we studied the distribution ofthickness in each grip class.

In the good grip class, 97 %of cases stay below the thresholdline. The remaining 3 % repre-sent conditions with light snowor a thin layer of slush on theroad. It is thus obvious that if

ROSA shows a thickness of icegreater than 0.05 mm, grip willbe reduced or poor with a sub-stantial accuracy of 97.4 % of allobservations.

In the reduced and poor gripclasses we find thicknesses ashigh as 2 mm, which is commonwhen it is snowing. However, 40-45 % represent cases where thethickness is below the thresholdline but the road is still slippery.This differs from the assumptionthat grip is always dependent onthe thickness of ice. Indeed, inmost cases snow was packed as athin slippery layer on the roadsurface. Thus, even a thin layer ofice can actually be slippery. Theremay also be a little salt presentthat is not enough to reduce slip-periness. We may conclude thatif the thickness of ice is below0.05 mm, grip can be determinedto be good with an accuracy of90.6 % of all observations.

To find out whether therewere other indicators of vehiclegrip beside the thickness of theice layer, we next examined thedata with an artificial neural net-work.

Neural network resultsAn artificial neural networkmodel (multilayer perceptron)was fitted into the data in orderto find out which measurementsare of importance in determin-

ing grip. The data used as inputcontained the following quanti-ties obtained from the measure-ments of the road weather sta-tion:

• The road surface temperature (T).

• The measured amount of de-icing chemical (G), in this case sodium chloride expressed as total amount per surface area.

• The combined thickness of ice and liquid water on the roadway (H). This also includes snow and possible hoar frost reduced to their water equivalents.

• The difference between the surface temperature and the freezing temperature of the solution on the road (D), and

• The rate of precipitation (P), as measured by the road weather station.The input data was then

used to train the perceptron withthe observed grip figures as de-sired output. The usual back-propagation algorithm was ap-plied in the training. The rootmean square deviation betweenthe trained perceptron outputand the observed data is shownin figure 3, when the input dataincluded in the model was var-ied in different combinations. Asmaller deviation means

159/2002 29

Figure 3. The root mean square deviation of the trained artificial neuralnetwork with different inputs. The letters (TGHDP) indicate thecombinations of input data used.

Table 1. Grip Classes Used in Observations

Grip Class Criterion Number of Observations

Good grip The road is dry, moist, or wet, but not snowy or icy 420

Reduced grip The road is somewhat icy or snowy, but the vehicle is only slightly sliding when braking. 86

Poor grip The road is entirely icy or snowy, and the vehicle is clearly sliding when braking. 24

Total 530

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that the inputs will better ex-plain the observations.

Figure 3 shows that whenthe thickness (H) is not includedin the inputs, the deviation isclearly greater. The smallest devi-ations are obtained in the caseswhen both the thickness (H) andsome temperature data (T or D)is included.

ConclusionsIn this study the manual analysisof the data showed that thethickness of the ice layer on theroad is the main indicator of ve-hicle grip. The neural networkanalysis also supported this re-sult. When the thickness of theice layer was greater than 0.05mm, we could determine withan accuracy of 97.4 % that thegrip would be reduced or poor.On the other hand, when thethickness of the ice layer was be-low 0.05 mm, it was still possibleto assess the grip but in somecases the thickness alone did notyield enough information. Fur-thermore, the neural networkanalysis revealed that the secondimportant factor indicating gripwas the difference between roadtemperature and freezing tem-perature.

Based on this data we canconclude that it is essential forthe road weather station to accu-rately measure the thickness ofthe ice and water layer in orderto detect the likely grip and warnabout slippery conditions. How-

T he Road Traffic Authori-ty is the State Govern-ment agency responsible

for main roads, motor vehiclesand motor users in New SouthWales, Australia. Focusing onsafety concerns, the RTA has de-veloped systems to continuallymonitor road conditions, usinghazard detection devices. The re-al-time information can be dis-played on variable message signs(VMS). For instance, in 1995, a12-kilometre network of fibre-optic variable message signs wasconnected to 10 fog detectionunits and 24 speed detection de-vices to target individual mo-torists on the appropriate speedbehaviour for the visibility.Changeable message signs havealso been provided at several lo-cations which are connected topresence detectors to advisedrivers when queues build up atsites with restricted sight dis-tances. These displays revert to adifferent message when queuesare not present. The RTA’sSouthern Region have now ex-panded the use of these signs toprovide a changeable sign at asub-standard curve locationwhere wet weather conditionssignificantly increases the hazardto motorists. In wet weather andwhen the pavement is wet, theadvisory warning provided tomotorists changes to reflect theincreased risk at the site. This ar-ticle provides information onthe development of this systemand the behavioural response ofmotorists to the changed advicefor different conditions as theytravel through the curve.

Site selectionThe Princes Highway is the ma-jor highway running south, fol-lowing the coast. On the PrincesHighway immediately south ofKiama is a 2.3 km section of 4-lane road, which is built on awinding alignment developed inthe first half of the last century.The speed limit is 80 km/h. Anaccident study shows that in the3-year period from 1996 to 1998,65 accidents occurred within thesection of which 58 (89 %) werein wet weather conditions. Thiscompares to 65 % of accidents

30 159/2002

Winter Road Congress dealt withNew Challenges forWinter Road Maintenance

V aisala participated in theXIth Winter Road Con-

gress 28 - 31 January in Sap-poro, Japan. Arranged by theWorld Road Association PIARCunder the theme New Chal-lenges for Winter Road Main-tenance, the congress attract-ed a record number of atten-dees: 2200 people from 62countries.

In conjunction with theWinter Road Congress, theStanding International RoadWeather Commission (SIRWEC)Conference was also held inSapporo. Organized every 2years, SIRWEC discusses the lat-est research and technologyconcerning roads under a vari-ety of weather conditions.Moreover, this conference alsopresents meteorological instru-ments and related technology.

Founded in 1909, theWorld Road Association (PI-ARC) deals with road infra-structure planning, design,construction, maintenance andoperation. Its membership in-cludes 97 national or federalgovernment members, 2,000collective or individual mem-bers and over 750 experts in 20standing Technical Commit-tees.

The Standing Inter-national Road WeatherCommission (SIRWEC)was originally set up in1985 as SERWEC (Stand-ing European RoadWeather Commission),but to reflect changes inthe organization’s scope,the name was changed in1992. SIRWEC operates asa forum for the exchangeof information relevantto the field of highwaymeteorology, including,for example, manage-ment, maintenance, roadsafety, meteorology, andenvironmental protec-tion. �

ever, to detect only the thicknessis not sufficient in all situations.The road weather station shouldalso be capable of measuringroad surface temperature andfreezing temperature which werefound to be among the best indi-cators of vehicle grip in this setof data and observations. �

AcknowledgementThe authors wish to thank Mr. OssiPilli-Sihvola, Head of the Traffic Infor-mation Centre, and also the personnelof the Road District of SoutheasternFinland for their help in conductingthis trial and arranging the observa-tions.

References1. Haavisto, Haavasoja, Turunen, Nylan-

der: Performance of a Road SurfaceCondition Sensor. Proceedings of the10th International Road WeatherConference, 2000. Pages 145-152.

2. Nicolas, Jean-Peter: Glättebildung durchÜberfrieren. Schwellwerte der Ober-flächenfeuchte auf Fahrbahnen. BastHeft V 36, 1996. 26 pages.

Figure 5. Ville Haavisto of Vaisalapresented the vehicle grip survey atthe SIRWEC conference.

Figure 4. Vaisala showcased road weather products at the PIARC exhibitionin Sapporo.

occurring in wet weather in thenext homogeneous section ofthe Princes Highway immediate-ly to the south.

The 55 accidents are all lossof control accidents suggestingexcessive speed on the bends de-spite the provision of advisoryspeed warning signs throughoutthe section and the selective pro-

vision of skid-resistant pave-ments at the most frequent acci-dent locations. In 2000, New Jer-sey kerb treatment, together withcentral median drainage, wasprovided where practical in anattempt to reduce both accidentfrequency and severity.

Within the Kiama bends sec-tion, 17 of the accidents oc-

curred at the location selected,with 10 of those occurring in thenorthbound direction.

Site detailsThe selected site contains a righthand curve on a 4-lane sectionof the Princes Highway separat-ed by a New Jersey kerb. Annualrainfall is in the order of 120 cm,and there is an Annual AverageDaily Traffic (AADT) in excessof 13000 vehicles per day. Acurve warning sign is currentlylocated in the approach to thecurve with an advisory speed of65 km/hr.

In establishing the trial site,the sign has been converted to athree way sign with displaysshown as shown in fig. 2.

The different displays are ac-tivated by a moisture detectiondevice, which is able to detectweather conditions and theamount of precipitation when

raining as well as the pavementconditions in terms ofdry/moist/wet. The equipmentis also capable of detecting otherconditions such as frost andsnow which, however, are notrelevant at this site. Details ofthe display triggers are shown intable 2. Flashing Lights are at-tached to the sign for use in thethird mode, which is assessed asthe most dangerous situation.

In order to assess the effec-tiveness of the system, speed de-tection loops were placed inboth lanes as shown in fig. 3.This allowed speeds to be meas-ured during different condi-tions. For each vehicle, speedswere measured together withrecords of lane (fast or slow),time of day (to assess day andnight effects), rainfall and pave-ment conditions. Vehiclelengths were also recorded in or-der to provide data for heavy ve-hicles and motor cycles. Nochanges are proposed to sign-posting for southbound traffic.

Effects of signpostingassessed The site was commissioned on30th May and speed measure-ments were taken for a periodbefore the sign was activated toassess the effects of traditionalsignposting. These measure-ments are to be continued untila behaviour pattern had been es-tablished in wet as well as dryconditions. At the time of writ-ing the site remains in this con-dition as insufficient rain peri-ods have occurred to allow anadequate comparison of variableconditions to be made. Whensuch data has been obtained, thesign is to be commissioned andfurther data recorded using thedisplays triggered by the logicshown in Table 2.

159/2002 31

Figure 1. Selected site.

Figure 2. Variable sign arrangement

Normal (Condition1) Raining (Condition2) Wet Road - No Rain (Condition3)

Table 2. Display logic

Condition1 Condition2 Condition3

Weather Surface Weather Surface Weather Surface

Clear Dry Rain Dry Clear Moist

Cloudy Moist Cloudy Wet

Wet

Dynamic warning signs act as

Signs of RainA number of systems have been introduced in recent years thatprovide dynamic advice to motorists on the real-time status ofthe road network. Most commonly, motorists obtain real-timeinformation on congestion, allowing them to take alternateroutes for reduced travel time. However, the Roads and TrafficAuthority of New South Wales uses road weather systems andvariable message signs to improve road safety. These systems al-low drivers to modify their speed behaviour on the basis ofchanges in weather conditions. For instance, information on wetconditions is provided for locations where wet weather increasesthe hazard to motorists.

Dr Graham BrisbaneB.Eng. M.I.E. (Aust), Fellow of the AustralianInstitute of Traffic Planning and Management

Andrew Vasiliou B.Eng., B.Comp.Sc., M.I.E. (Aust)

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Results

Detailed results have been ob-tained for all conditions. For“Condition1” (clear and dry), afull week’s data has been ob-tained providing over 50,000 da-ta sets. This data has been ob-tained on days when no rainfallhas occurred. For “Condition2”and “Condition3”, only 3573and 8289 samples respectivelyhave been obtained which isconsidered insufficient to enablea full statistical comparison of abefore-situation. In the case of“Condition2”, a range of sam-ples is also required for differingprecipitation rates to allow astudy of the sign’s effectivenessin varying rainfall conditions.This would allow further studiesto be undertaken at a later dateto determine if additional fea-tures would be effective in heavyrain conditions when aquaplan-ing is more likely to occur (e.g.use of flashing lights when therain exceeds a certain intensity.)

The data has also been sepa-rated into four different time ofday periods (dawn, daytime,dusk and night) when differingambient light conditions mightbe expected to result in differingdriving behaviour. Table 3 showsthe average speeds that occur atthe two speed-detection sites be-fore and after the sign.

Speed profiles were also ob-

tained for each of these condi-tions. Figures 4 and 5 are an ex-ample showing the speed pro-files for all three conditions dur-ing the day and night times.

Not unexpectedly the earlyresults show that in more ad-verse conditions vehicles slowdown to a greater extent in theapproach to the curve (Loops1/2). This speed reduction variesby time of day with reductionsduring wet conditions of around4* km/hr during the day and 6**km/h at night.

Further reductions of around8 - 9 km/h occur as the vehiclesenter into the curve. However,the early indications (Fig. 4a &4b) are that during the day whenthe pavement is wet but rain isnot falling (“Condition3”) thespeed profile of vehicles is simi-lar to that for dry conditions.

This result is also very appar-ent at dawn and dusk periods(these results are not shown dueto the low sample numbers foradverse conditions).

At night vehicles appearmuch more likely to maintain

the speed reduction which occurswhen rain is falling (Fig. 5a & 5b).

A visual examination of thedata also shows that the pave-ment sometimes remains wet ormoist in some cases for severalhours after the rain has ceased.There is also evidence that dewis responsible for considerableperiods of a moist pavement. Itis noticeable that the samplenumbers obtained to date for“Condition3” are around doub-le those of “Condition2”.

CommentsThe results achieved to dateclearly raise concerns as to thebehaviour of motorists in condi-tions of wet pavements whenrain is not falling. The structureof the site arrangements will pro-vide important information toallow further analysis to occur.

The provision of the en-hanced signposting is intendedto further reduce the speed ofvehicles travelling through thecurve with particular emphasison maintaining speed reduc-tions when the pavement is wet

32 159/2002

Figure 4a. Speed variation during daytime before sign Figure 4b. Speed variation during daytime after sign

Figure 5a. Speed variations at night before sign Figure 5b. Speed variations at night after sign

or moist but no rain is actuallyfalling. Success in this area willprovide a further option forthose sites where significant wetweather problems exist and oth-er treatments have not been ful-ly successful in reducing the wetweather accident problem. �

ReferencesBrisbane, G.J.B., (1996): Driving In Fog

- Putting Research Into Practice. Pro-ceedings 18th ARRB Conference.Part 5. (Australian Road ResearchBoard. Christchurch, New Zealand.)

Brisbane, G.J.B., (1999): ITS - Not JustFor Cities Proceedings ITSA ’99 (Intelligent Transport Systems Australia, Adelaide)

This article was printed with the kindpermission of ITS Australia. For fur-ther information please refer to theITS Australia web site at www.ITS-Aus-tralia.com.au.

AcknowledgementWhilst the views and conclusions inthe paper are those of the authors, theassistance and support of the Roadsand Traffic Authority in using work ex-amples is greatly acknowledged.

Table 3. Average speeds by time of day

Dawn Day Dusk NightLoops1/2 Loops3/4 Loops1/2 Loops3/4 Loops1/2 Loops3/4 Loops1/2 Loops3/4

Condition1 75 68 75 67 75 67 75 67Condition2 74 65 71* 62 72 62 69** 60Condition3 73 64 74 65 71 62 71 63

159/2002 33

Climate modeling

Forecasting the state of the at-mosphere is done in many ways,by many groups and organiza-tions, and over many time scales.The very long time scales of in-

terest to climate modeling spandecades and even centuries. Theirfocus is on predictions of futureclimate and how the climate willvary according to solar variabili-ty, the Earth’s Copernican mo-tions, volcanic activity, and

The Scope and Future ofNowcasting What is nowcasting and how does it relate to

other weather and climate forecasting meth-ods and practices? Who uses or needs now-casts? And how far do they depend on at-mospheric observations? What is the futurefor operational nowcasting? To answer thesequestions, let us first consider the broad spec-trum of atmospheric forecasts, beginningwith long-range climate predictions, workingbackwards to conventional short- and medi-um-range weather forecasts and ending withthe ’nowcast’.

Walter Dabberdt, Ph.D.Director, Strategic ResearchVaisala BoulderColorado, USA

➤

of greatest public and political in-terest, controllable changes in an-thropogenic emissions of green-house gases and aerosols. Cli-mate models are general circula-tions models or GCMs that arenot unlike those used in day-to-day weather forecasting [seebox]. However, they must dealwith the additional challengesthat arise from their need to cov-er the full globe and very long pe-riods of time. They must also in-clude the interactions and feed-backs between the atmosphere,oceans, sea ice, land masses, andriver flows. And they must dothis in a way that will allow slow-ly varying, small-scale climate sig-natures of temperature and pre-cipitation to be separated fromthe very large signatures and vari-abilities of short-term weather.

Paleoclimate modeling is aspecial type of climate modeling

whose objective is to ’hindcast’ –predict in reverse – the historicalchanges in climate that havebeen detected with ice cores andtree rings. Yet another special as-pect of climate modeling is calleddownscaling. It is the process offorecasting regional climate fea-tures with greater spatial resolu-tion than is available from thecoarse low-resolution global cli-mate forecasts. The highest reso-lution of the best global climatemodels is about 100-200 km,while today’s downscaling activi-ties attempt to resolve regionalclimate features on scales ofabout 40 km. Downscaling seeksto quantify climate change onthese higher spatial scales in or-der to better reveal the impacts ofclimate change on agriculture,water supplies, fish habitats, sus-tainability and so forth.

Monthly and seasonaloutlooks

Between forecasts of climate andweather are monthly and season-al outlooks. Until recently, theirtypical focus has been on atmos-pheric temperature and precipi-tation, and how each will varyfrom average conditions for amonth or a season. A big changeoccurred in 1997, when at leastone national modeling centermade an accurate forecastmonths in advance of the onsetof the major El Niño event of1997-98. An El Niño is a warmtropical episode that is high-lighted by warm surface watersreplacing the upwelling of coldwater along the west coast ofSouth America. Significantchanges in global weather pat-terns accompany strong El Niñoevents as they also accompanyits cold-event counterpart, LaNiña. During major El Niñoevents, heavy precipitation andflooding can occur along thewest coast of tropical SouthAmerica, and at subtropical lati-tudes of North America (Gulf ofMexico) and South America(southern Brazil to central Ar-gentina). At the same time, ab-normally dry conditions occurover northern Australia, Indone-sia and the Philippines in winterand summer. Drier than normalconditions are also observedover southeastern Africa andnorthern Brazil, during thenorthern winter season. Duringthe northern summer season, In-dian monsoon rainfall tends tobe less than normal. If El Niñoand La Niña forecasts can bemade in the future with regulari-ty and adequate skill, the bene-fits to the global community willbe immense -- countries suscep-tible to drought and floodingcould do much to mitigate theseprolonged and devastating natu-ral hazards.

“Everyday” weatherforecastsTraditional synoptic weatherforecasts are the forecasts thatare most familiar to us. They are

prepared twice daily and are is-sued four-to-six hours after theweather observations that theyuse. These forecasts extend outas far as seven or more days intothe future (the forecast durationvaries according to the particularweather service issuing the fore-cast – e.g. eight days in Australiaand seven days in the U.S.).One-to-two day forecasts areconsidered to be short-rangeforecasts, medium-range fore-casts are three days and longer.Special high-resolution forecastscalled mesoscale forecasts arenow just beginning to come intooperational use in some sectorsalthough they are still primarilya research and special-purposeforecasting tool. Mesoscale fore-casts typically are valid for a pe-riod that extends from aboutthree hours after the time of theweather observations that theyuse out to one-to-two days later.They also cover a smaller area(model domain) than synopticforecasts. But their greatest at-tribute is their ability to providevery high spatial and temporalresolution – down to a few kilo-meters or less, and only tens ofminutes.

NowcastingThe important gap between cur-rent weather and the onset of va-lidity for a mesoscale forecast isthe domain of the nowcast. Inapproximate terms, the total pe-riod of interest to nowcastersranges from a few tens of min-utes up to three-to-six hours. Butin practical terms, current now-casting products for severeweather rapidly lose their validi-ty after one hour (figure 2). Theprinciple objective of nowcast-ing is to provide highly precisepredictions of the intensity, lo-cation, onset and cessation ofsignificant weather-relatedevents. Rather than making a se-vere-weather forecast of, say,“scattered afternoon severethunderstorms in the greater St.Louis area,” a nowcast seeks topredict the occurrence of a “se-vere thunderstorm with winds in

34 159/2002

Figure 1. Weather computing accuracy (in terms of predicting changes inatmospheric pressure fields) has increased over the decades as improvedscientific understanding has created higher-resolution models which demandthe most powerful computers available (source: Australian Bureau ofMeteorology).

Figure 2. Qualitative depiction of the accuracy of time and place-specificforecasts of convective storms (source: Jim Wilson, NCAR as adapted fromBrowning (1980), Doswell (1986) and Austin et al. (1987).

PH

OT

O C

OU

RT

ES

Y B

Y N

EC

AU

ST

RA

LIA

AN

D B

OM

excess of 30 meters per secondaccompanied by golf-ball-sizehail and intense lightning in theimmediate vicinity of the St.Louis Arch between 3:30 pmand 4:15 pm today….”

We may not always be awareof it, but every one of us regular-ly makes our own personal now-casts. We instinctively observethe types, amounts and changesin the clouds, the direction andspeed of the wind, the humidityand temperature of the air. Andthen we make our very ownnowcast – we project what theweather will be and how it willaffect us over the next tens ofminutes or over the course ofthe morning or afternoon. Sci-ence-based nowcasting has thesame objectives, but seeks to usestate-of-the-art-observing tech-nologies together with expertsystems, theoretical models andfrequently also human interven-tion to make precise very-short-term forecasts.

Numerical forecasts ofmesoscale and synoptic weatherdepend on numerical solutionof a coupled set of equations forenergy, momentum and massconservation – see weather pre-diction box. They use observa-tions to specify the initial atmos-pheric state and to aid in defin-ing conditions at the boundaryof the model domain. Observa-tions are also assimilated intothe numerical modeling processas a way to “tune” or adjust themodel to the most recentchanges in the state of the at-mosphere. In contrast, nowcast-ing methods depend heavily ondense local observations ofweather, winds, and state vari-ables, coupled with a variety ofempirical and rule-based formu-lations, and on a few theoreticalequations and some numericalmodeling as well. Nowcastingmethods vary widely and are tai-lored to fit the application thatthey are addressing. But the coreof the nowcast is a set of highlyresolved local measurementsand observations. These typical-ly are provided by weather radar,

surface mesonets, lightning de-tectors, wind profilers, radioson-des and satellites, among others.

NowcastingthunderstormsForecasting the developmentand movement of severe thun-derstorms is a major focus of thenowcasting research community.These storms are both dangerousand difficult to predict withgreat specificity in regard to lo-cation, timing and severity. Indi-vidual single-cell storms areshort-lived, lasting usually lessthan 30 minutes. On the otherhand, about half of multi-cellstorms typically last more thanone hour with their cells split-ting and merging throughoutthe lifecycle of the storm com-plex. And the very large stormcomplexes can last many hoursand their movement can be ex-trapolated with skill. The chal-lenge is to develop a suite ofnowcasting methods that can beapplied to the full spectrum ofdiverse storms. Different now-casting methods have been cre-ated over the past 40 years withthe goal of effectively predictingthe initiation, evolution and dis-sipation of convective storm sys-tems. These methods have yield-ed varying degrees of success

and can be grouped into threebroad categories: 1) extrapola-tion; 2) convection initiationand dissipation; and 3) explicitnumerical prediction. Extrapola-tion methods are actually of twotypes; the steady-state approachassumes no change in cell move-ment, size and intensity, while asecond type allows for change inintensity and size. The secondnowcasting category involvesthe use of expert systems thatseek to predict the initiation anddissipation of convection bymonitoring convergence bound-aries using radar, dense mesonets

and visual observations of clouddevelopment. It has been knownfor some time that human fore-casters were frequently able touse these methods with greaterskill than extrapolation. Recent-ly, new methods are emergingthat automate the convergence-detection and storm predictionprocess. They are likely to fur-ther increase predictive skill asscientific understanding ofstorm initiation becomes morecomplete, as detailed observa-tions become more available,and as computational advancescontinue. The third catego-

159/2002 35

Figure 3. Thunderstorm nowcastingmap provided by a SAFIR TotalLightning Detection Systemshowing a multicellular frontalstorm system over the north ofFrance (data courtesy of MeteoFrance). The thunderstorm cells arecharacterized by their total lightningdensity (total lightningdischarges/min/km2). For each cellthe system displays the overallcontour of the electrically active area(blue), and the core with a colorcoding (green, orange, red) reflectingthe cell’s intensity on the basis of thelightning density. Extrapolatedpositions and intensities aredisplayed for the next 30 minutes inincrements of 10 minutes.

➤

ry of nowcasting convectivestorms involves explicit numeri-cal simulation and prediction ofthunderstorms. Some approach-es are being developed that uti-lize radar observations of con-vergence lines to initialize themodel, while others do not relyon these special observations. Inboth cases, explicit numericalmodeling currently is an emerg-ing nowcasting research tool thatoffers future promise.

After about one hour theskill level of the various nowcast-ing methods decreases rapidlyfor all convective storms. Skilllevels are higher over longer pe-riods for organized bands ofconvective storm cells and largemesoscale storm systems, but al-so for nowcasting of non-con-vective events such as freezewarnings. Let’s explore a few ex-amples of other nowcastingmethods and their applications.

Vaisala’s IceBreak Nowcasting for roadways Vaisala is playing a significantrole in nowcasting applications.One such application is ice pre-diction for roadways, which en-ables road masters to use proac-tive anti-icing operations ratherthan less effective reactive roadmaintenance practices. IceBreak

is Vaisala’s fully physical heat-balance model that predicts site-specific road surface state andtemperature. This allows users toclosely monitor potential weath-er hazards and mobilize re-sources in sufficient time to takepreventive treatment. The mod-el may be run in eithermesoscale forecasting mode(from 24 to 72 hours ahead) or 3-hour nowcasting mode. Inmesoscale mode, IceBreak usesas its input data the standardshort-range forecasts of atmos-pheric variables, typically fromthe nearest mesoscale modelgrid point. IceBreak is currentlyused in mesoscale mode bymore than 10 national meteorol-ogical services, making it themost extensively used ice predic-tion method worldwide.

In nowcast mode, the inputdata are real-time local observa-tions from Vaisala’s ROSA roadweather stations. One extensivestudy of operational 3-hournowcast performance revealedvery encouraging results. Usingtemperature data from 74 sta-tions over a five-month periodfrom October 2000 throughFebruary 2001, the evaluationconsidered more than 37,000 in-dividual nowcasts comprising al-most 370,000 data pairs with thefollowing results:

Bias -0.19ºCStandard deviation 0.92ºCAccuracy1 91.30%Reliability2 1.00Miss rate3 10.20%False alarm rate4 7.90%

Because the IceBreak modelcontains accurate physical repre-sentations of all major heat flux-es, its performance does not de-generate as quickly as rule-basednowcasting roadway applica-tions. Indeed the model resultsdemonstrate significant skill outto the end of the typical 3-hournowcast period with a gradualincrease of bias and standard de-viation as far ahead as 6 hours.

Vaisala’s SAFIR Lightning SystemAnother Vaisala nowcasting ca-pability focuses on early light-ning and thunderstorm detec-tion and forecasting. The VaisalaSAFIR Lightning System con-sists of a network of detectionstations that is uniquely capableof locating at long range alllightning types – both Intra-Cloud (IC) and Cloud-to-Ground (CG). A central process-ing system computes the loca-tion of lightning discharges bytriangulation, and also performslightning activity analyses and

storm nowcasts. Total lightningactivity (IC + CG), with itsdominant IC lightning compo-nent, is an early indicator ofstorm development. It also cor-relates closely with storm severi-ty. This enables efficient earlydetection of storm cells, accuratetracking information and ad-vance warning of imminentthunderstorm hazards. IC detec-tion typically provides about tenminutes advance warning beforethe onset of CG lightning activi-ty as well as an order of magni-tude more information for mon-itoring and tracking of thunder-storm cells.

Early detection, monitoringand mapping of storm total elec-trical activity, either alone or to-gether with weather radar andother measurements, is a valu-able nowcasting tool for manyapplications. Users include met-eorological services (SAFIR isused by 12 national weatherservices around the world), aswell as electric power and trans-mission companies, sensitivemanufacturing industries, fireand safety personnel, flood man-agement districts, and aviation.

Early lightning detectionand warning is also critical to therecreation and outdoor enter-tainment sectors where largenumbers of individuals can beexposed. In the U.S. alone, light-ning caused an annual averageof 163 deaths and three times asmany injuries over the period1940-1991. Lightning deaths inthe U.S. exceed by 50% thosefrom either tornadoes or floods,and are 400% greater than hurri-cane deaths.

Flood forecastingTwo other examples of opera-tional nowcasting systems areflash flood prediction and emer-gency response. Flash floodanalysis and prediction modelsare now coming into widespreaduse in some countries. Flashflood models represent the to-pography, surface conditions,soil moisture and stream net-works of flood plains and basins,

36 159/2002

T he NCAR AutoNowcaster is an ongoing development at the NationalCenter for Atmospheric Research in the U.S. It is a nowcast environ-

ment for collecting weather data and executing algorithms to produceand display very short-term thunderstorm forecasts. At present, data in-corporated into the nowcast environment include Doppler radar data,GOES satellite images, soundings, and surface mesonet data. The soft-ware applications include algorithms for identifying and tracking thun-derstorm movement, identifying atmospheric boundaries, retrievingwinds from radar, and a fuzzy-logic engine that allows the user to pro-duce a single, unified nowcast.

The forecast image on the left shows a then-current radar reflectivityfield together with a 60-minute nowcast for the initiation of a line of se-vere thunderstorms over Washington DC on 2 June 2000. The white poly-gons indicate the predicted boundary of echoes with reflectivities >35dBZ. The image on the right shows the actual radar reflectivity field atverification time together with the forecast contour.

Source: Roberts, R.D., D. Burgess and M. Meister, 2001: Next steps in automated thunderstormnowcasting: improving performance and forecasting storm severity. Preprints, 30th Conf. onRadar Meteor., Munich, Germany, Amer. Meteor. Soc., 234-236

and they rely on observations ormodel predictions of precipita-tion rates and duration to makeshort-term forecasts of flooding.Nowcasting methods use radarto track and extrapolate stormcell trajectories and estimate theamount and type of precipita-tion. Radar observations are notused in isolation but are fre-quently combined with surfaceand upper-air lightning detectorsdata from atmospheric sound-ings, surface weather stations,rain gauges, cloud radars, windprofilers, satellites and virtuallyany measurement system avail-able in the area. The challenge isthe availability of adequate andrepresentative observations. Wewill return later to this importantpoint.

Emergency response forchemical releases Emergency response to the acci-dental or deliberate atmosphericreleases of toxic chemicals or bi-ological agents is an emergingnowcasting focus. Observationsand mesoscale model predic-tions are used in conjunctionwith atmospheric dispersionmodels to predict ground-levelexposures downwind of the re-lease point. Public safety person-nel rely on these predictions toquickly develop mitigation andprotection strategies. For exam-ple, they must decide with veryshort notice what areas to cor-don off, and whether it is betterto evacuate people in the affect-ed areas or to “shelter in place”in by having them remain in-doors. Nowcasting emergencyresponce systems are being de-signed but very few operationalsystems exist at present. One no-table exception is the NationalAtmospheric Release AdvisoryCenter (NARAC) at theLawrence Livermore NationalLaboratory in California. It hasbeen in existence since 1979 andhas assisted in supporting emer-gency response to more than 70incidents, including radiation re-leases from the Three Mile Is-land nuclear power plant in 1979

and Chernobyl in 1986, as wellas numerous chemical releases inthe U.S. and throughout theworld. The important challengefor the future is to provide simi-lar capabilities at multiple loca-tions, and to make available thecritical atmospheric measure-ments required to characterizeatmospheric transport and dis-persion. This will be especiallyimportant because existing at-mospheric measurement net-works have been designed tosupport the prediction of severeweather. On the other hand, themost adverse dispersion condi-tions are associated with benignweather regimes.

The future The development of advancednowcasting systems for severeweather events is ongoing in sev-eral countries. Researchers areexploring several approaches tothe problem of very short-rangeforecasts that are highly specificin time and space. These ap-proaches vary widely, rangingfrom extrapolation to expert sys-tems to explicit numerical mod-eling of storm cells. They allshare three common needs: da-ta, data and even more data! Theobservational data must be suffi-cient to characterize the stormand its environment in great de-tail. Herein lies the dilemma:how to ensure that the measure-ment systems will be availablewhere and when they will beneeded. Part of the answer lies indetermining in advance what lo-cations will be served by a now-casting capability. But an equallyimportant question is “Who willbe responsible for supportingthese nowcasting systems?” Willthey be a public or a private en-terprise? Or will there be public-private partnerships that emergeto meet these needs? One thingseems certain: nowcasting willbe an ever more important andvaluable component of theweather forecasting paradigm. �

159/2002 37

Weather prediction B efore weather models can predict the future state of

the atmosphere they must know its present state veryaccurately. This is the primary purpose of a disparate arrayof weather measurement instruments and platforms thatinclude surface weather stations, upper-air radiosonde ob-servations, aircraft and ship observations, satellites and var-ious other special-purpose devices. Twice daily at 00 and12UTC, weather observations are fed into a global telecom-munications network, and are then ingested by the nation-al meteorological services around the world where they arechecked for accuracy, and then projected onto a three-di-mensional modeling grid. Computer-based forecast modelsthen predict the weather using these observations to firstinitialize and then solve a set of mathematical equationsthat describe the laws governing atmospheric behavior.These laws include three equations of atmospheric motion,the thermodynamic equation (representing conservation ofenergy), the so-called gas law or equation of state, and thecontinuity equation (which express the conservation ofmass). Today’s sophisticated forecast models and vastlymore capable computers have significantly improved thetimeliness and accuracy of weather forecasts and warnings.However the accuracy of weather predictions is still inher-ently limited in four areas:

1. the quality, density and representativeness of atmospheric measurements;

2. the finite power of today’s computers; 3. our imperfect understanding of and ability to

model atmospheric processes, and4. the inherent unpredictability of atmospheric

processes on different scales due to their chaotic nature.

Progress in the accuracy and extent of atmosphericprediction will continue though. A recent report by theU.S. National Academy of Sciences stresses that improvedatmospheric measurements are imperative for improvedweather forecasting in the 21st century. �

ReferencesWilson, J.W., N. A. Crook, C. K. Mueller,

J. Sun and M. Dixon, 1998: Now-casting Thunderstorms: A Status Re-port. Bull. Amer. Meteor. Soc., 79,2079-2099.

Austin G. L., A. Bellon, P. Dionne andM. Roch, 1987: On the interactionbetween radar and satellite imagenowcasting systems and mesoscale nu-merical models. Proceedings,Mesoscale Analysis & Forecasting,European Space Agency SP-282,Vancover, Canada, 225-228.

Browning, K. A., 1980: Local weatherforecasting, Proc. R. Soc. London Ser.,A371, 179-211.

Doswell, C.A., 1986: Short-range forecast-ing. Mesoscale Meteorology and Fore-casting, P. Ray, Ed., Amer. Meteor.Soc., Boston, 793 pp.

Footnotes1) Accuracy is the percentage of thetime that a given atmospheric state(e.g. occurrence of frost vs. no frost) iscorrectly predicted.

2) Reliability is the ratio of the numberof times that an atmospheric state ispredicted relative to the number of ac-tual occurrences.

3) Miss rate is the proportion of atmospheric events or states that werenot predicted.

4) False alarm rate is defined as theproportion of atmospheric events orstates that were predicted but did notoccur.

The altitude-dependent devia-tions have in practice meant thatRASS technology has not metthe requirements set for opera-tional observation networks.Through their experiments andcomparisons Görsdorf andLehmann were able to identifyan insufficient height assign-ment in RASS measurements asthe main cause of measurementerror. They suggested a correc-tion method to compensate forthe error, including a variablerange correction, vertical veloci-ty correction and improved tem-perature retrieval. This allowedthe systematic deviation fromthe radiosonde measurement re-sults to be clearly reduced. Görs-dorf and Lehmann’s research in-troduces an important step to-wards the increased use ofRASS measurements in theworldwide operational aerologi-cal network. RASS instrumentsare normally used as a comple-mentary instrument with windprofilers so that both verticalwind and temperature profilescan be presented within thesame display software.

Designed to encourageresearch programsThe Professor Vilho VaisalaAward was established in 1985and is administrated by theWorld Meteorological Organiza-tion (WMO). It is awarded toencourage and stimulate interestin important research supportiveof WMO’s programs, in thefield of meteorological and cli-matic observation methods andinstruments. �

T he award was presentedin November 2001 bythe WMO General Sec-

retary G. O. P. Obasi at the Ger-man Research Centre for EarthSciences in Potsdam. Doctor Ul-rich Görsdorf and Mr. VolkerLehmann of the German Mete-orological Service, LindenbergObservatory were recognized fortheir scientific work on the meas-urement of atmospheric temper-ature with the Radio AcousticSounding System (RASS). Thewinning research paper “En-hanced Accuracy of RASS-Mea-sured Temperatures Due to anImproved Range Correction”was published in the Journal ofAtmospheric and Oceanic Tech-nology, vol. 17, no 4, 2000.

High resolution data forthe enhanced accuracyof forecastsTo improve the accuracy of

short-term forecasts the spatialand temporal resolution of nu-merical models should be con-stantly developed. This requiresdata which has a high temporaland spatial resolution and is ac-cessible with remote sensingmethods, such as the RadioAcoustic Sounding System fortemperature measurements.

Identifying the measurement error and developing a correction method In their winning paper Dr. Görs-dorf and Mr. Lehmann de-scribed the extensive compara-tive study they carried out at theMeteorological Observatory Lin-denberg. The study investigatedthe systematic errors in tempera-ture measurement that occurwith RASS at lower altitudes incomparison with radiosondeand tethersonde measurements.

A popular city for con-ventions, Orlando wasthe location of the 82

nd AMS Annual Meeting fromthe 13—17 January 2002. Themeeting incorporated 14 sym-posia and conferences coveringvarious topics from environ-mental applications, meteorolo-gy, hydrology and oceanogra-phy, to topics on education,global change and advancedweather interactive processingsystems, to name but a few.Vaisala attended or participatedin many of the symposia/confer-ences, three of which were:

– “Observations, Data Assimilation, and Probabilistic Prediction”

– “Interactive Information and Processing Systems”

–“Integrated Observing Systems”.

Short courses and specialconferences and sessions were al-so scheduled for participation.

For the first time the meet-ing also featured a special eventfor the local community, theAMS WeatherFest: a communi-cations workshop and studentconference. Additionally, a Pres-idential Policy Forum was held,devoted to societal aspects ofmeteorology, especially the roleof AMS in meeting society’sneeds. In the forum expertsshared their views on society’sweather and climate informationneeds. More than 130 compa-nies took part in the exhibitionthat was arranged in conjunctionwith the meeting.

Vaisala attendees at the AMSMeeting each had their role toplay whether it was meeting withbusiness partners and customers,presenting oral papers, attendingpresentations and courses,

38 159/2002

Two German Scientists Win the 16th Professor Vilho Vaisala Award

The winners of the 16th Professor Vilho VaisalaAward are two German scientists fromDeutscher Wetterdienst (DWD). Doctor UlrichGörsdorf and Mr. Volker Lehmann receivedthe award for their paper entitled “EnhancedAccuracy of RASS-Measured TemperaturesDue to an Improved Range Correction”.

The award was presented in November 2001 by the WMO GeneralSecretary G. O. P. Obasi at the German Research Centre for Earth Sciencesin Potsdam.

“manning the booth”, or pro-moting new products andVaisala - as well as everyone con-tinually establishing contacts.The activity level was high andthe image portrayed by Vaisalaexpansive. Vaisala introducedAMS attendees to a businessunit that was new from last year– the Wind Profiler group - and anew division, the Remote Sens-ing Division. In its spaciousbooth, Vaisala showcased anumber of products:

–new optical sensors - Vaisala FS11 Visibility Sensor and Vaisala LD40 Ceilometer

– a full IceCast Road Weather Station and TACMET station were erected

–Vaisala Rocketsonde and other upper air products

–new 16-channel GOES Direct Readout Ground station

– scale models of the SAFIR and LAP®-3000 Wind-profiler. Philippe Richard presented a

paper on SAFIR Total LightningDetection Technology. Otherpapers presented by Vaisala in-cluded two by Pekka Utela: oneon the new Vaisala FS11 Visibili-ty Sensor which has a uniquewindow contamination com-pensation method, and the sec-ond on a multiple instrumentsky condition algorithm forceilometers. �

D uring the last few yearsthe North Americanshare of Vaisala Group’s

sales has been increasing andthis increase is expected to con-tinue. “The US market has be-come increasingly important forus, and its share of the Group’snet sales has been increasing. Bycentralizing our operations wewant to show our commitmentto the North American marketand to our customers,” saysPekka Ketonen, President andCEO of Vaisala Group. By cen-tralizing operations Vaisala aimsat enhancing productivity andefficiency. Several importantmeteorological research insti-tutes and laboratories thatVaisala works in close coopera-tion with are also located inBoulder.

New facilities to bebuilt in BoulderVaisala will build a new produc-tion plant in the Colorado TechCenter area. Construction was

started in March 2002 and thefirst phase, which will be com-pleted by the end of the year,will include 40,000 sq. feet of of-fice and manufacturing space.The investment is valued atUSD 4.7 million.

The dropsonde productionfrom Boston, the aviation weath-er system production and aftersales services from Columbus,and the weather station and sys-tems production from Sunny-vale will be relocated to Boulderby the end of 2002. The windsensor production will be relo-cated from Sunnyvale to theVaisala office in Helsinki, Fin-land. At the same time, out-sourcing will be increased. ForVaisala customers in the U.S. therelocation does not implicateany major changes, since Vaisalaoffices in Boston, Columbus andSunnyvale will continue as sales,customer service and product de-velopment locations after theproduction unit relocation. �

159/2002 39

Vaisala CentralizesUSA ManufacturingOperations in Boulder

The AMS 82nd Annual Meeting was held 13–17January 2002 in Orlando, Florida. The event at-tracted more than 3000 attendees, includingregistrants, students, exhibitors and guests. Thetheme of the meeting was “Generating Envi-ronmental Information and Services” andVaisala participated to the full at the accompa-nying exhibition where more than 130 compa-nies were showcasing their products.

Vaisala Success at the82nd American Meteorological SocietyAnnual Meeting, January 2002

Vaisala showcased a numberof products and technologies atAMS in Orlando, Florida.

The Vaisala Group will centralize its US man-ufacturing operations into one location,Boulder, Colorado, from the present five pro-duction sites in the USA. This reflects Vaisala‘scommitment to the North American marketand to its customers. Vaisala offices inBoston, Columbus and Sunnyvale will contin-ue to function as sales, customer service andproduct development locations.

Europe

Vaisala Oyj P.O. Box 26, FIN-00421 HelsinkiFINLAND Telephone: +358 9 894 91Telefax: +358 9 8949 2227

Vaisala MalmöDrottninggatan 1 DS - 212 11 MalmöSWEDENTelephone: +46 40 298 991, in Sweden: 0200 848 848Telefax.: +46 40 298 992, in Sweden: 0200 849 849

Vaisala GmbHAchter de Weiden 10D-22869 SchenefeldAs of July 1, 2002, new address:Schnackenburgallee 41D-22525 HamburgGERMANYTelephone: +49 40 839 03 207Telefax: +49 40 839 03 211

Vaisala Impulsphysik GmbHAchter de Weiden 10D-22869 SchenefeldGERMANYAs of July 1, 2002, new address:Schnackenburgallee 41, D-22525 HamburgGERMANYTelephone: +49 40 839 030Telefax: +49 40 839 03 110

Vaisala GmbHBonn OfficeAdenauerallee 46 aD-53110 BonnGERMANYTelephone: +49 228 912 5110Telefax: +49 228 912 5111

Vaisala GmbHBremerhaven OfficeBuchtstrasse 4527570 BremerhavenGERMANYTelephone: +49 471 170 1655 Telefax: +49 471 170 1755

Vaisala GmbHHamburg OfficeAxel-Springer-Platz 2D - 20355 Hamburg GERMANYTelephone: +49 40 3410 7879Telefax: +49 40 3410 7887As of July 1, 2002, new contact information:Schnackenburgallee 41D-22525 Hamburg, GERMANYTelephone: +49 40 839 03 111Telefax: +49 40 839 03 122

Vaisala GmbHStuttgart OfficePestalozzi Str. 8D-70563 Stuttgart GERMANYTelephone: +49 711 734 057Telefax: +49 711 735 6340

Vaisala LtdBirmingham OperationsVaisala House349 Bristol RoadBirmingham B5 7SWUNITED KINGDOMTelephone: +44 121 683 1200Telefax: +44 121 683 1299

Vaisala LtdNewmarket OfficeSuffolk House Fordham RoadNewmarket Suffolk CB8 7AAUNITED KINGDOMTelephone: +44 1638 674 400Telefax: +44 1638 674 411

Vaisala SA2, rue Stéphenson (escalier 2bis)F-78181 Saint-Quentin-en-Yvelines CedexFRANCETelephone: +33 1 3057 2728Telefax: +33 1 3096 0858

Vaisala SA7, Europarc Ste-VictoireF-13590 Meyreuil FRANCETelephone: +33 4 4212 6464Telefax: +33 4 4212 6474

North America

Vaisala Inc. 100 Commerce WayWoburn, MA 01801-1068USATelephone: +1 781 933 4500Telefax: +1 781 933 8029

Vaisala Inc. Columbus Operations7450 Industrial ParkwayPlain City, Ohio 43064-9005USA Telephone: +1 614 873 6880Telefax: +1 614 873 6890

Vaisala Inc. Boulder Operations8401 Base Line RoadBoulder, CO 80303-4715USA Telephone: +1 303 499 1701Telefax: +1 303 499 1767

Vaisala Inc.5600 Airport Boulevard Boulder, CO 80301-2340USATelephone: +1 303 443 2378 Fax: +1 303 443 1628

Vaisala Inc. Sunnyvale Operations1288 Reamwood Ave. Sunnyvale, CA 94089-2233USATelephone: +1 408 734 9640Telefax: +1 408 734 0655

Vaisala-GAI Inc.2705 East Medina RoadTucson, Arizona 85706, USATelephone: +1 520 806 7300Telefax: +1 520 741 2848U.S. Toll Free 1 800 283 4557

Vaisala Inc. Regional Office CanadaP.O. Box 2241, Station “B”LondonOntario N6A 4E3CANADATelephone: +1 519 679-9563Telefax: +1 519 679-9992

Asia and PacificVaisala KK42 Kagurazaka 6-ChomeShinjuku-Ku Tokyo 162-0825JAPANTelephone: +81 3 3266 9611Telefax: +81 3 3266 9610

Vaisala KKOsaka Branch1-12-15, HigashimikuniYodogawa-Ku, Osaka 532-0002JAPANTelephone: +81 6 6391 2441Telefax: +81 6 6391 2442

Vaisala Pty Ltd3 Guest StreetHawthorn, VIC 3122AUSTRALIATelephone: +61 3 9818 4200Telefax: +61 3 9818 4522ABN 58 006 500 616

Vaisala Beijing Representative OfficeWangfujing Grand HotelRoom 518 - 52057, Wangfujing StreetBeijing 100006PEOPLE’S REPUBLIC OF CHINATelephone: +86 10 6522 4041+86 10 6522 4050+86 10 6522 4151Telefax: +86 10 6522 4051

Vaisala Regional Office MalaysiaLevel 36, Menara Citibank165 Jalan Ampang50450 Kuala LumpurMALAYSIATelephone: +60 3 2169 7776Telefax: +60 3 2169 7775

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