Application of Over-the-Horizon Radar Observations to

44 VOLUME 12W E A T H E R A N D F O R E C A S T I N G

q 1997 American Meteorological Society

Application of Over-the-Horizon Radar Observations to Synoptic and Mesoanalysisover the Atlantic

G. S. YOUNG

Meteorology Department, The Pennsylvania State University, University Park, Pennsylvania

J. A. HARLAN

Cooperative Institute for Research in Environmental Sciences, University of Colorado/NOAA, Boulder, Colorado

T. M. GEORGES

NOAA/Environmental Technology Laboratory, Boulder, Colorado

(Manuscript received 2 January 1996, in final form 7 October 1996)

ABSTRACT

Over-the-horizon (OTH) radar observations of surface wind direction offer a high-resolution (15 km) resourcefor synoptic and mesoscale wind field analysis. With horizontal resolution at the lower end of the mesoscaleand areal coverage in the synoptic scale, OTH radar has the potential to contribute significantly to the ameliorationof the data sparseness that has long plagued over-ocean surface analysis. Because of a twofold ambiguity in theOTH radar algorithm for determining surface wind direction, however, mapping surface wind directions un-ambiguously would normally require two radars with overlapping coverage. Alternatively, the single-radarambiguity can be resolved by combining NWP model analyses and incidental surface wind observations withmeteorological insight. An approach to the latter, less expensive solution is presented that relies on the classicprinciples of streamline analysis and an easy-to-use graphical wind field editor developed specifically for thistask. A case study demonstrates the utility of the resulting OTH radar analyses of surface wind direction overthe tropical Atlantic Ocean. Existing military OTH radars in several countries could be used for such monitoringwith little impact on their primary mission.

1. Introduction

Data sparseness over the oceans has long been viewedas the most important limiting factor in the preparationof synoptic and mesoscale surface analyses of marineregions (Pierson 1983; Walker 1991) and in errors in-volved with numerical model initialization (e.g., Veldenet al. 1992). The primary in situ data source currentlyavailable is the constantly shifting and unevenly dis-tributed ship-of-opportunity network. At its densest inthe major shipping lanes, this network barely providesadequate resolution for synoptic, much less mesoscale,analysis. In less traveled regions, ship reports can bevirtually nonexistent (Walker 1991).

Supplementary information, mainly wind speed anddirection, is obtained by several satellite remote sensingtechniques. Cloud tracking, using a sequence of visibleimages from geostationary satellites, provides useful

Corresponding author address: George S. Young, Department ofMeteorology, College of Earth and Mineral Sciences, The Pennsyl-vania State University, 503 Walker Building, University Park, PA16802-5013.

surface wind vectors in those cases where scatteredboundary layer clouds are unobscured by higher cloudsand are sufficiently long lived, and where lower-atmo-spheric shear is weak (Rao et al. 1990). These conditionsseverely limit applicability of the cloud-tracking meth-odology in regions of strong synoptic-scale baroclin-icity, just where the interest in detailed synoptic andmesoscale surface analyses is greatest. Microwave ra-diometry (Special Sensor for Microwave/Imaging,SSM/I) (Goodberlet et al. 1989) and scatterometry (Of-filer 1994), using polar-orbiting satellites, are also usedto estimate surface wind speed and direction (Atlas etal. 1993), but scatterometer coverage in space and timeis limited by orbital dynamics to suborbital strips a fewhundred kilometers wide. One satellite typically inter-rogates a given spot on the ocean every 2–3 days. Inaddition, radiometric methods are not possible throughrain. Thus, there remains a strong need in marine me-teorology for a denser set of reliable observations ofsurface winds to aid in synoptic and mesoscale surfaceanalysis.

This problem of data sparseness is very pronouncedin the Tropics and subtropics, due both to the virtual

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MARCH 1997 45Y O U N G E T A L .

confinement of in situ observations to great circle ship-ping routes between major ports, and the inherent prom-inence of mesoscale phenomena in the low latitudes(Walker 1991). The dominance of convective phenom-ena in the Tropics and over the warm currents of thewestern subtropical oceans underscores the importanceof mesoscale weather systems in surface analysis andweather forecasting there. In the less balanced (i.e., non-gradient) conditions of the Tropics, streamlines havebeen demonstrated to be at least as useful as isobariccontours (Saucier 1955; Riehl 1954). Thus, such ubiq-uitous surface analysis problems as the tracking of ill-defined tropical cyclones, convective lines, and con-vergence zones require observations of surface winddirection with much higher resolution than has so farbeen routinely available.

Similarly, the severity of polar lows and other me-soscale features of higher latitudes makes mesoscaleresolution of the wind direction field in these regionshighly desirable for the preparation of surface analyses.Given better data than is available from the operationalsources described above, one could hope to analyze andforecast these severe mesoscale phenomena at sea withsome degree of skill. Thus, considerable improvementin the detail and accuracy of over-ocean surface analysisin general, and streamline analyses in particular, aredesirable at all latitudes. To achieve these goals, higher-resolution, more reliable surface wind direction obser-vations are needed.

Over-the-horizon (OTH) radar offers a partial solutionto this over-ocean surface analysis problem by providingsurface wind directions at mesoscale resolutions. Thepresent generation of military OTH radars offers a nom-inal horizontal resolution of 15 km at ranges from 800out to 3000 km from the ground-based radar site. Inaddition, OTH radars can see through clouds and rain.

In this paper, the focus is on methods for operationallyanalyzing and interpreting OTH radar data for over-ocean surface analysis. Background information is pre-sented on how OTH radar measures ocean-surface winddirection, with attention paid to the ambiguity inherentin this measurement. Next, new procedures for quicklyresolving the ambiguity and rendering these data into aform usable by meteorological analysts and operationalnumerical model initialization are discussed. Then thedata obtained with a military OTH radar system are usedto illustrate what a meteorological analyst can accom-plish. This is illustrated by presenting a short case studyof a synoptically interesting sequence of events in thetropical and subtropical Atlantic.

2. Background: Ocean remote sensing with OTHradar

Almost all the OTH radars in the world are built andused for military air defense. They illuminate naturaland artificial targets far beyond the optical horizon byreflecting high-frequency (HF: 3–30 MHz) radio waves

from the ionosphere (Georges and Harlan 1994b). Theyemploy high-power transmitters (up to 1 MW) andlarge-aperture receiving antenna arrays (up to 2.5 kmlong) to achieve ranges up to 3500 km in one ‘‘iono-spheric hop.’’ With the end of the Cold War, some OTHradars have been deactivated, most notably the six radarsknown collectively as OTH-B on the U.S. east and westcoasts, which were deployed by the U.S. Air Force toprovide early warning of Soviet bomber attacks onNorth America.

Since 1991, the National Oceanic and AtmosphericAdministration (NOAA) has been given limited accessto these six radars to perform tests of their ocean-mon-itoring potential. The results of these tests have rein-forced earlier findings that OTH radar can map oceanwinds, waves, and surface currents with mesoscale res-olution over basin-scale ocean areas (Georges and Har-lan 1994a,b; Georges et al. 1993). In this paper, theutility of radar measurements of wind direction at thesea surface are examined. The principles of this OTHradar application are reviewed below. The reader is re-ferred to Georges and Harlan (1994a) for a more ex-haustive coverage of these topics.

a. Wind direction measurements

The method by which OTH radar maps surface winddirections is often misunderstood. Unlike other mete-orological Doppler radars, OTH radar does not measurethe radial component of the wind. Wind direction isinferred from the directionality of decametric (approx-imately 10-m wavelength) ocean waves in each radarcell, because waves of this length are closely coupledto local surface winds as discussed in section 2b.

OTH radar extracts information about the ocean sur-face from the minute amount of energy, called ‘‘seaclutter’’ in military circles, scattered back to the radarby ocean surface waves (Stewart and Barnum 1975). AtHF, most of this energy is backscattered by Bragg-res-onant ocean waves, that is, those with one-half the radarwavelength and traveling exactly toward and away fromthe radar (Stewart and Barnum 1975). For example,10-m-wavelength ocean waves backscatter 15-MHz ra-dio waves. Radially traveling gravity waves Dopplershift the backscattered energy by an amount propor-tional to their phase velocity (Stewart and Barnum1975). The spectrum of a sea echo at these HF bandfrequencies exhibits a surprisingly simple structure: twosharp Doppler-shifted lines, one positively shifted echofrom the Bragg-resonant waves traveling toward the ra-dio source and one a negatively shifted line from thosereceding from the source (Stewart and Barnum 1975).

Directional wind–wave energy is known to fall offmonotonically with angle from the wind direction, sothat significant wave energy travels at large angles withthe wind, even nearly upwind (Stewart and Barnum1975). The exact form of this falloff (or directionalspreading) is poorly understood and depends on the de-



tails of the forcing wind and sea state (Stewart andBarnum 1975). Simple geometric forms of this spread-ing have been assumed, such as coss(u/2), where u isthe angle between the wind and the wave component,and s is a spreading parameter whose value increaseswith wind speed and decreases with frequency (Stewartand Barnum 1975). Values between 2 and 4 have beensuggested for decametric waves (Stewart and Barnum1975).

The relative amplitudes of the two ‘‘Bragg lines’’ inthe sea echo spectrum, specifically, the advancing-to-receding ratio, R, indicate the relative fractions of thedecametric ocean wave energy traveling toward andaway from the radar (Stewart and Barnum 1975). Forexample, a wind blowing toward the radar generatespredominantly approaching waves and almost no re-ceding waves, producing a large positive R. Windsblowing at right angles to the radar radial generate ap-proaching and receding waves of equal energy, pro-ducing Bragg lines of equal intensity (R 5 1). Inter-mediate wind directions produce intermediate values ofR. The radar, therefore, samples two angles 1808 aparton the Bragg-resonant waves’ directional spreadingfunction. If the function is known and monotonic, theangle is determined. An analytical form for this functionis assumed (Long and Trizna 1973), or an empiricalrelation is established by making many measurementsof R and comparing them with independent wind di-rection estimates (Harlan and Georges 1994). The lattermethod is used in this paper, although the results ob-tained using the two methods do not differ appreciably.

b. Wind–wave coupling

A remaining question concerns the relation betweenthe wind direction and the direction of the dominantdecametric ocean waves, as measured by the radar. Arethe two, in fact, closely coupled, as previously sug-gested? This question has been answered empirically,for example, by Masson (1990), who used data frompitch-and-roll buoys to measure the time for waves withup to 0.54-Hz frequency to reach equilibrium with turn-ing surface winds. Formulas given by van Vledder andHolthuijsen (1993), assuming an 8 m s21 wind, giveabout a 36-min response time for 10-m waves. Riederet al. (1994, Fig. 5) measured the directional responseof wind waves of different lengths and found that waveswith 2–4-s periods (those measured by OTH radars)appear to track near-surface wind directions withinabout 208. Harlan and Georges (1994) empiricallychecked the assumptions and quantified the errors inthis methodology. They also showed that good qualityOTH radar-derived wind directions agree with NationalCenters for Environmental Prediction (NCEP, formerlyknown as National Meteorological Center) Global DataAssimilation System (GDAS) analyses (238 rms) betterthan either ship or buoy directions do.

c. Directional ambiguity

It is clear from the preceding arguments that mea-surements of R using only one radar cannot uniquelydetermine wind direction. For example, if the radar de-termines that R 5 1, then the wind is blowing at rightangles to the radar radial, but this information does notresolve whether the wind is blowing from the left orright. In other words, the sign of the transverse windcomponent is ambiguous, so that the radar offers achoice of two directions that are reflections in the radarradial. This twofold ambiguity is resolved using eitherindependent information about the wind direction ormeasurements with a second radar that illuminates theocean cell from another direction. Because OTH radarsare expensive to build and operate, it is desirable toexplore methods for removing the single-radar ambi-guity.

3. Analysis of OTH-B wind direction data

The OTH-B East Coast Radar System consists ofthree collocated radars in Maine, which illuminate vir-tually the entire North Atlantic Ocean in an arc ex-tending from Greenland through the United Kingdomand western Africa to northern South America and theCaribbean Sea [see Fig. 1 of Georges and Harlan(1994b) or on-line at http://www1.etl.noaa.gov/othr/othb.htm]. Radar illumination of the tropical and sub-tropical Atlantic for approximately 1 h each day between22 August and 30 September 1994 was requested forthe purpose of providing near-real-time surface winddirections in the tropical and subtropical Atlantic to theNational Hurricane Center (NHC). During this 40-dayperiod, radar data were processed once a day using aNOAA work station at the radar site, transmitted toBoulder, Colorado, for conversion to a suitable graphicsformat, then transmitted to forecasters’ work stations atthe NHC, all within an hour or so of data collection.The data, which were presented both as arrays of winddirection arrows and as streamlines, were subsequentlypublished as Georges et al. (1995).

Generally, surface wind directions in the Tropics andsubtropics are dominated by the easterly trades. Direc-tional ambiguity is therefore initially resolved selectingeasterly flow over the entire radar coverage area. Thisturned out to be the correct choice most of the timeexcept in the northeastern quadrant of the coverage.[The corrected maps can be viewed on the Environ-mental Technology Laboratory World Wide Web(WWW) home page at http://www1.etl.noaa.gov/othr/othdata.htm.] This dataset then is used as a test bed forremoving the directional ambiguity.

a. First-guess procedures

The first-guess removal of OTH radar wind directionambiguity uses the nearest NCEP/GDAS analysis. At



each radar data point, the radar direction is selected thatis the closer of the two choices to the direction givenby the NWP model at the nearest model grid point. Thisstep by itself is not sufficient to produce a wind directionfield of significant utility to the synoptic and mesoscaleanalyst. The low resolution of NCEP/GDAS relative tothat of the OTH radar leads to an uncertainty of onemodel grid space (about 18 in latitude and longitude) inthe location of boundaries between winds angled rightof the radar beam radials and those angled left of theradials. Moreover, gross errors in the model analysisdue to sparse input data and erroneous first guess (i.e.,using the model forecast) easily result in a mistakenchoice of wind directions. Thus, the model analysismethod yields a first-guess resolution of the OTH di-rectional ambiguity problem that is no better than themodel analysis itself in terms of horizontal resolutionand accuracy. Fine-tuning of the directional ambiguityresolution is needed before the OTH radar wind direc-tion fields can make a significant independent contri-bution to the over-ocean synoptic and mesoscale surfaceanalysis problems.

b. Fine-tuning procedures

Fine-tuning requires intelligence and insight into me-teorological phenomena. Ultimately, the full potentialof the OTH datasets will be realized only with the fullysuccessful objective implementation of these single-ra-dar techniques or with widespread dual-radar coverage.For the foreseeable future, however, single-radar anal-ysis will remain chiefly the province of the human an-alyst because expert systems developed for this task arenot likely to be as accurate or sophisticated for sometime to come. Thus, what is currently needed to makeOTH radar data meteorologically useful is computersupport for the human analyst rather than computationalreplacement of the human analyst. The tools and pro-cedures discussed below help the human analyst rapidlyrefine the first-guess directional ambiguity solution ofan OTH radar wind field while making only minor de-mands on the analyst’s already heavily committed time.The resulting wind direction product offers meso-g scaleresolution (15 km) over an area of roughly 10 Mkm2

for an expenditure of approximately 10 min of the an-alyst’s time.

c. Graphical editing procedures

The primary tool in ambiguity resolution of the windfield analysis is a specialized graphical editor for flip-ping selected regions of the analysis between the twopossible directions offered by the OTH radar observa-tions. The graphical editor displays the OTH wind barbson a geographic grid and color codes them accordingto which of the two possible directions is currently se-lected at each point. This display helps the analyst vi-sualize the radar-derived flow pattern, use the appro-

priate conceptual models of meteorological phenomenato resolve the directional ambiguity, and edit the datawith a minimum of effort. Flipping analyzed winds be-tween the two possible observed directions takes onlythe click of a mouse. The influence radius for this editingaction is quickly reset by the analyst as the editing pro-gresses from broad area corrections to local fine-tuning.

Refinement of this first guess proceeds in two phases:a first pass corrects synoptic-scale regions at severaldozen points at a time, and the second pass tunes me-soscale detail a point or two at a time. The automatedfirst-guess, NWP-based direction field generally handleslarger synoptic-scale flow fields well, providing the an-alyst with the correct choice in areas of weak gradients.The analyst needs only make a cursory check of thefirst-guess results before proceeding to fine-tune regionsof sharp wind shifts. In our experience, most of theanalyst’s attention is focused on making the correct winddirection choice in such wind shift zones as ridges,trough lines, and fronts.

d. Conceptual models procedures

As in the classic approach to streamline analysis, asdiscussed in the texts of Petterssen (1956) and Saucier(1955), the analyst’s conceptual model of the flow fieldsin common atmospheric phenomena is the critical ele-ment in making this choice. While these methods havetraditionally been used to overcome data scarcity, theyare equally applicable to the OTH radar problem ofabundant but potentially ambiguous data. The key ineither situation is to position correctly the streamlinesingularities (anticyclones, cyclones, col points) andfrontal confluence lines. When this task is accomplishedin a way that brings the analysis into agreement withboth the analyst’s conceptual models and the OTH radarobservations, flow consistency suffices to guide analysisof the remainder of the streamline field.

When using these procedures to remove the ambiguityin OTH radar wind directions, begin in the regionswhere a conceptual model, or incidental data, such assurface observations, permits only one of the two pos-sible directions at each data point. By working outwardfrom these nuclei of ‘‘correct’’ winds, a direction isselected at each point that minimizes the wind shift fromadjacent, already corrected, points. As the analysis pro-gresses into active regions possessing mesoscale windvelocity gradients, where true wind directions shift be-tween data points can become large, the analyst mustmake a transition from this principle of flow consistencyto a conceptual modeling approach. At this stage, flip-ping a group of data points between the two possiblewind directions often acts to move a singularity acrossthe analysis. The analyst’s task in this situation is to flipthe analysis between the two possible wind directionsat just those points required to correctly position thestreamline singularities. For instance, col points can beparticularly helpful in OTH radar wind direction anal-



FIG

.1.



FIG. 1. (Continued). (a) The operational National Weather ServiceAnalysis for 1800 UTC 20 September 1994. The wind barbs denotedby stars are low-level satellite cloud-tracked winds. (b) Subjectivestreamline analysis based on the observations plotted in (a). In (b),the two anticyclone centers are marked with points labeled A andthe col point is marked with a point labeled C. The cold front isdepicted with conventional symbology and is labeled.

FIG. 2. An example of the effect of directional ambiguity on OTHradar observations of surface wind directions taken at 1300 UTC 20September 1994. (a) The unedited (ambiguous) observations, and (b)the final edited observations with the directional ambiguity resolved.

ysis, as even small errors in positioning them often resultin very distorted and unrealistic flow fields. Achievinga physically reasonable col point correctly positionsboth the col point and the associated confluence line forsome distance on either side of it.

4. Examples

a. Tropical analysis, 20 September 1994

We demonstrate this method using OTH radar ob-servations of the wind direction over the tropical At-lantic Ocean made by the air force OTH-B radar inMaine at 1300 UTC 20 September 1994. For compar-ison, Fig. 1a shows the 1800 UTC operational NationalWeather Service (NWS) surface analysis, and Fig. 1b asubjective hand analysis of the corresponding stream-lines based solely on the operational data (surface ob-servations and satellite cloud-track winds) plotted onthis NWS chart. The flow field over the tropical Atlanticis dominated by the three phenomena typical of theregion: the subtropical anticyclone, the trade winds withembedded easterly waves, and a dying polar front.

Figure 2a shows the completely unedited (i.e., en-tirely westward) OTH radar wind direction field, whileFig. 2b shows the wind field after editing by a humananalyst, resolving the directional ambiguity in a wayconsistent with the analyst’s conceptual models of thesephenomena and guidelines discussed above. The editedwind directions closely resemble the widely scatteredsurface observations and satellite cloud-track windsplotted on the operational analysis. Moreover, the OTHwind directions are in generally good agreement withthe synoptic-scale subjective streamline analysis createdusing only these operational data (Fig. 1b). The anti-cyclone at 248N 60.58W and the col point at 248N 518W

are both positioned identically in the two independentanalyses. On the synoptic scale, the OTH wind direc-tions generally follow the streamlines in Fig. 1b, whileon the mesoscale, locally systematic departures of 108–308 can be observed, presumably in response to me-soscale systems not resolved by the sparse operationaldata. A notable region of disagreement does exist near308N 508W, where a weak and variable pressure gradientand winds of 5 kt were observed. This suggests theexistence of a minimum wind speed of .5 kt but ,10kt for reliable OTH wind direction estimation. The trop-ical waves are also very well resolved in the OTH-basedanalysis, despite some data dropouts in the southeastpart of the analysis due to ionospheric propagation con-ditions. Thus, the OTH-based surface wind directionanalysis correctly depicted the synoptic-scale flow fieldbut contains much more detailed mesoscale informationthan the 1800 UTC operational surface analysis, shownin Fig. 1 for comparison. This mesoscale informationwould be a particularly useful addition to the guidancesuite for short-term convective forecasts, as it captureswell the locations of the confluence lines and tropicalwaves that trigger deep convection in the Tropics. Otherrelevant quantities not, of course, measurable by OTH



FIG. 3. (a) The surface streamline analysis based on edited OTH radar data from 1600 UTC 14September 1994; (b) the corresponding Meteosat visible image. The polar front is depicted as aheavy line in (a).

radar include convective available potential energy andconvective inhibition.

Because this approach to editing wind direction datarelies on the same techniques as conventional streamlineanalysis, the level of meteorological expertise requiredfor this procedure is that of a typical operational me-teorologist. Thus, given ready access to the OTH radarobservations, current NWP surface analyses, and thegraphical editor used in this example, an operationalanalyst could routinely achieve a useful mesoscalestreamline analysis over the tropical Atlantic with rel-atively few minutes of effort. The potential rewards ofsuch an effort are demonstrated in the case study in thenext section.

b. Tropical–subtropical analysis, 14–16 September1994

To demonstrate this method, OTH radar observationsare presented for wind direction over the tropical At-lantic for a case study of the interaction of a polar front

with tropical synoptic-scale phenomena. Figures 3a, 4a,and 5a show the edited OTH radar wind analyses for1600 UTC 14 September, 1300 UTC 15 September, and1300 UTC 16 September. Figures 3b, 4b, and 5b showthe corresponding Meteosat visible images. The OTHradar wind analyses clearly capture both the generalcirculation around the western end of the subtropicalhigh and mesoscale details of the synoptic phenomenain both the trade wind belt and the subtropics. The west-ward propagation of a tropical wave across the upper-left quadrant of the domain is particularly well depicted,as is its changing structure with time. Similarly, thelocation and evolution of an old polar front in the north-ern half of the domain can be monitored as it interactsstrongly with the tropical wave.

The satellite images in Figs. 3b–5b provide more de-tailed verification of these OTH radar wind analysesthan do the scattered ship observations. The satelliteimage for 14 September is dominated by bands of en-hanced convection along the axis of the tropical waveand the cold front. These two convective features are



FIG. 4. As in Fig. 3 but at 1300 UTC 15 September 1994.

each over 1000 km long but only about 100 km wideand are poorly resolved by the existing surface obser-vations. The OTH radar wind analysis, on the otherhand, easily resolves the wind shifts associated withthese features and places them accurately within thesatellite-observed convective cloud bands. The front isresolved as a confluence line extending the width of thedomain. The OTH radar wind field also explains boththe existence and curvature of the second band of en-hanced deep convection, which is associated with thetropical wave axis. The wave axis in the OTH analysisis seen to curve progressively to the east at higher lat-itudes, just as the corresponding cloud band does. With-out OTH radar wind data, it is difficult, if not impos-sible, to map the internal structure of this tropical waveat a fine enough horizontal resolution to reveal the closecorrespondence between this fine structure and the cur-vature of the resulting convective band.

By 15 September, the tropical wave has progressedfarther northwest, pushing up against the polar front.As a result of this collision between synoptic-scale phe-nomena of the Tropics and subtropics, the tropical wavebecomes even more elongated and tilted, with its axis

curving from near 278N 658W to near 238N, 718W. Abroken line of cumulocongestus and cumulonimbus isseen in the corresponding satellite image. As on 14 Sep-tember, this weather feature lies along the curving axisof the tropical wave. The confluence line of the polarfront and its corresponding cloud line now lie little morethan 100 km to the northwest of the wave axis. Boththe OTH radar wind analysis and the satellite imageshow that these two features have become nearly par-allel, yet the wind shift zones and the cloud bands ofthese two phenomena remain spatially distinct at thistime.

Note that neither the NCEP pressure analysis nor theOTH wind directions reveal any confluence in associ-ation with the vigorous convective cloud cluster near188N 648W. From the satellite image this feature appearsto be a downstream extension of the active ITCZ eastof 508W (off the side of this OTH domain). A singleship observation suggests that the storm’s convergenceis being provided by a local gust front that is not beingcaptured by the OTH radar.

This situation changed a day later, on 16 September.The convective band of the tropical wave has collapsed



FIG. 5. As in Fig. 3 but at 1300 UTC 16 September 1994.

FIG. 6. As in Fig. 3a but at 1300 UTC on 20 September 1994.

into the front along much of its length. The northwardflow upstream of the tropical wave axis thus becomesthe inflow into the polar front. The front is still clearlyresolved as a domain-spanning confluence line on theOTH radar wind analysis and a corresponding line ofdeep convection on the satellite image. The sharp kinkin the front near 27.58N 708W is clearly visible in bothproducts.

Throughout this synoptically complex sequence ofevents, the OTH radar wind analysis consistently cap-tured and correctly located the wind shift features as-sociated with these convective bands. In a situation withsuch synoptic complexity and this much mesoscalestructure, conventional surface observations are inade-quate to explain or forecast these convective cloudbands. Thus, the OTH radar wind analyses provide animportant contribution to developing a rigorous under-standing of the ongoing synoptic events.

A similar but more extreme example of cold frontalpenetration into the Tropics and interaction with a trop-ical wave was captured by the radar on 20–22 Septem-ber. The 22 September OTH radar wind analysis in Fig.6 shows the same curvature of the tropical wave axisand kinking of the polar front seen in Fig. 5. For thiscase, however, these phenomena dominate the entireOTH radar domain. Comparison of Fig. 6 with the cor-responding analysis from 2 days before (Fig. 2b) showsthe degree to which interaction with the polar front hasaffected the structure of the tropical wave. A great re-duction in wavelength and longitudinal tilting of the axisare both evident. Judging from the available OTH radar



observations, these interactions between tropical wavesand those low-latitude polar fronts are rather common,playing a major role in the evolution of convectiveweather in the tropical Atlantic. The importance of thisinteraction between disparate synoptic-scale features isfar less obvious with the limited analyses possible withconventional surface observations than with radar-basedmesoscale wind analysis.

c. Discussion of case study analyses

This analysis has demonstrated, by example, the util-ity of OTH radar wind analyses in operational mete-orology. With OTH radar wind analyses or other prod-ucts of equivalent resolution and accuracy, a forecastercan resolve mesoscale details of the interaction betweensynoptic-scale features that control the distribution ofconvection over the tropical and subtropical Atlantic.The key to the utility of this class of data lies not inconvective nowcasting, as satellite imagery already fillsthis role. Rather, OTH radar wind direction fields findtheir greatest potential utility in forecast preparation,where they can aid the forecaster in development of theunderstanding of the synoptic situation required formaking an accurate forecast. Using OTH radar winddata to assist in developing this understanding offersgreat advantages over the open ocean, where forecastershave heretofore been forced to rely chiefly on modelanalyses of questionable validity and satellite cloud-track winds with their inherent coverage problems. Thecombination of OTH and satellite winds would allowthe forecaster to check each against the other and helpfill the data void that occasionally occurs with both datasources. These remotely sensed wind direction fields notonly provide observed wind directions at mesoscale res-olution, but they also let forecasters evaluate just howwell the model analyses placed these features so theycan decide whether to trust the model forecasts whenmaking convective and cyclone development forecasts.For both human forecasters and NWP models, bad anal-yses yield bad forecasts.

A few caveats apply to the rosy picture painted above.There are some situations in which the ambiguity ofOTH wind directions simply cannot be resolved withoutindependent information. This section will discuss theselimitations and explain how understanding and a carefulsiting of the radars relative to the synoptic-scale flowcan minimize their impact and the analyses’ complete-ness.

As with any source of wind observations, weak windsyield meaningless streamlines as demonstrated in sec-tion 4a. Unfortunately, the OTH wind direction barbs(which so far display no speed information) look soauthoritative that the analyst is tempted to struggle withthem even in regions of near calm where a ‘‘perfect’’streamline product would still be of no relevance to theanalysis/forecast problem. Wind speeds have been ex-perimentally extracted from OTH radar data (Maresca

and Georges 1980), but the process is not as robust asthat for wind direction. Work is under way to derive atleast crude wind speed estimates from OTH observa-tions, so that regions of weak winds can be flagged,allowing them to be ignored by the analyst. Wind speeddata from satellite scatterometers and radiometers, whenand where available, could also be folded into the anal-ysis. Appropriate changes will be made in the graphicaldata editor as such information becomes available. Theproblem does not seem to be pronounced in the lowlatitudes, even near the middle of the subtropical high,but it has been problematic in some high-latitude anal-yses.

Regions where two air masses meet do not presentproblems unless they have differing wind directions thathappen to be symmetric with respect to the radar radial.In that case, the alternate (erroneous) wind direction forone region is the correct wind direction for the other,and vice versa. Thus, for this case, the OTH radar winddata provide no insight into where to put the boundarybetween the two regions (i.e., where to stop acceptingthe left-of-radial wind and start accepting the right-of-radial wind). This problem can be addressed with properradar siting. For example, it rarely occurs when usingthe OTH-B radar in Maine to look southward at thetropical Atlantic.

A more reliable, albeit costly, solution is dual-radarcoverage of large ocean regions using two widely sep-arated OTH radars, each of which obtains one pair ofwind direction estimates. If the two radar radials crossat significant angles, only one direction of each pair willgenerally closely match one of the other. The match isthe correct choice of wind direction. This approach hasbeen tried with considerable success using two navyOTH radars with overlapping coverage of the CaribbeanSea. While the dual-radar approach is clearly superior,the current catch-as-catch-can nature of OTH radar windobservations using military radars dictates that the sin-gle-radar analysis procedures and tools described in thispaper will be necessary in many cases.

5. Conclusions and outlook

The goal of this work is to show how over-the-horizon(OTH) radar could contribute to the creation of accuratesurface streamline analyses with mesoscale resolution.A case study of a complex synoptic situation in thetropical North Atlantic Ocean is used to demonstratethe potential utility of the resulting analyses. The OTHradar-derived wind direction field offers much betterresolution than the operational analysis based on surfaceobservations and operational cloud-track winds. More-over, in this case study, the OTH analysis did a betterjob of explaining the locations of the subtropical con-vective features observed by satellite than is possiblewith these conventional data sources alone. Thus, withmore extensive operational testing, OTH radar wind di-rection analyses may provide the basis for improved



convective forecasts and forecasts of tropical cyclonegenesis via either human ‘‘nowcasts’’ or improved NWPinitialization.

The directional-ambiguity problem is solved eitherby analysis of data from two spatially separated OTHradars or by human analysis of the flow field. The lattermethod provides a more economical solution that ex-tends the utility of OTH radar wind direction analysesto regions covered by only a single radar. The resultingOTH data-editing procedure for resolving this direc-tional ambiguity sets a premium on meteorological in-sight, while requiring very little user overhead for theactual data manipulation. The latter criterion, critical forthe operational feasibility of the method, is satisfied bya simple graphical editor for OTH wind direction plots.

Long-term enhancements for OTH radar productsshould include the addition of wind speed. In the nearerterm, however, this wind speed information can be pro-vided by the SSM/I or the scatterometer on ERS-1, forexample. These two remote-sensing instruments com-plement each other because the scatterometer measureswind speeds with comparative reliability but, so far,resolves directions poorly. OTH radar measures direc-tions reliably, assuming that the ambiguity is resolved,but determines speeds less reliably. Further comple-mentarity exists in the space–time coverage providedby space-based and ground-based techniques. Throughthe cooperation of the National Environmental Satellite,Data and Information System (NESDIS), ERS-1 windspeeds have already been merged with OTH-B winddirections and were provided to the NHC during the1994 hurricane season test. (These archival merged datacan be viewed on the NESDIS WWW home page athttp://manati.wwb.noaa.gov/doc/oth.html.)

Progress toward routine application of OTH radar tomarine meteorology would depend to a large degree onthe availability of existing OTH radars, the siting chosenfor future ones, and forming partnerships with otherusers of these multimission sensors. Our tests thus farshow that military radar resources require some in-vestment, however.

What is the present availability of military OTH ra-dars for meteorological services? The air force has de-activated its OTH-B system and now maintains the sixEast Coast and West Coast OTH-B radars in a statecalled ‘‘warm storage,’’ which preserves the physicaland electrical integrity of the system and permits recall,should a threat, research, or forecast mission arise.Georges (1995) has examined the incremental cost ofoperating the OTH-B system for environmental researchand services. He concluded that, for $1.0 to $1.5M yr21,daily ocean-surface wind directions could be mappedover most of the Atlantic coverage area. Similar cov-erage in the eastern Pacific could be obtained at aboutthe same cost.

With the deployment of a second relocatable OTHradar (ROTHR) in Texas (the first is in Virginia) by theU.S. Navy, a dual-OTH radar capability now exists for

the first time in the Gulf of Mexico, Caribbean Sea, andtropical Atlantic Ocean. These dual-radar data offerunique accuracy and density of wind observations with-out requiring the skills of a human analyst. The resultinghigh-resolution streamline analyses should prove veryuseful for both the forecasting problems discussed aboveand for verification of the new mesoscale-resolution op-erational models as they come on line. Dual-radar anal-yses can be extended into the single-radar coverage areaby the editing procedures covered in this paper. The twoROTHRs are presently in full-time military service, butbrief environmental-monitoring tests are permitted(Georges et al. 1996). Because the strength of sea echoesobserved with military OTH radars (which typically ra-diate 100 kW) is often 60 dB or more above atmosphericnoise, consideration should also be given to designinglow-power, low-cost OTH radars optimally located forocean monitoring.

Acknowledgments. We thank the U.S. Air Force forgranting access to its OTH-B radar system at no cost.The Lockheed Martin radar crew, led by L. R. Meyer,skillfully operated the radars for these tests. We alsothank two anonymous reviewers and Paul Neiman fortheir wise and thorough reviews. Support for G. S.Young was provided by Office of Naval Research GrantN00014-90-J-4012.

REFERENCES

Atlas, R., R. N. Hoffman, and S. C. Bloom, 1993: Surface windvelocity over the oceans. Atlas of Satellite Observations Relatedto Global Change, R. J. Gurney et al., Eds., Cambridge Uni-versity Press, 129–140.

Georges, T. M., 1995: Costs and benefits of using the Air Force over-the-horizon radar system for environmental research and ser-vices. NOAA Tech. Memo. ERL ETL-254, 39 pp., and J. A. Harlan, 1994a: Military over-the-horizon radars turnto ocean monitoring. Mar. Technol. Soc. J., 27(4), 31–38., and , 1994b: New horizons for over-the-horizon radar?IEEE Antennas Propag. Mag., 36(4), 14–24., , and R. A. Lematta, 1996: Large-scale mapping of ocean-surface currents with dual over-the-horizon radars. Nature, 379,434., , L. R. Meyer, and R. G. Peer, 1993: Tracking HurricaneClaudette with the U.S. Air Force over-the-horizon radar. J. At-mos. Oceanic Technol., 10, 441–451., , , and C. A. Grunden, 1995: Ocean-surface winddirections measured by the Air Force over-the-horizon radar dur-ing the 1994 hurricane season. NOAA Tech. Memo. ERL ETL-246, 93 pp.

Goodberlet, M. A., C. T. Swift, and J. C. Wilkerson, 1989: Remotesensing of ocean surface winds with the Special Sensor Micro-wave/Imager. J. Geophys. Res., 94, 14 547–14 555.

Harlan, J. A., and T. M. Georges, 1994: An empirical relation betweenocean-surface wind direction and the Bragg-line ratio of HF radarsea-echo spectra. J. Geophys. Res., 99 (C4), 7971–7978.

Long, A. E., and D. B. Trizna, 1973: Mapping of North Atlanticwinds by HF radar backscatter interpretation. IEEE Trans. An-tennas Propag., AP-21, 680–685.

Maresca, J. W., Jr., and T. M. Georges, 1980: Measuring rms waveheight and the scalar ocean wave spectrum with HF skywaveradar. J. Geophys. Res., 85, 2759–2771.



Masson, D., 1990: Observations of the response of sea waves toveering winds. J. Phys. Oceanogr., 20, 1876–1885.

Offiler, D., 1994: The calibration of ERS-1 satellite scatterometerwinds. J. Atmos. Oceanic Technol., 11, 1002–1017.

Petterssen, S., 1956: Motion and Motion Systems. Vol. 1, WeatherAnalysis and Forecasting, McGraw-Hill, 428 pp.

Pierson, W. J., Jr., 1983: The measurement of synoptic scale windover the ocean. J. Geophys Res., 88, 1683–1708.

Rao, P. K., S. J. Holmes, R. K. Anderson, J. S. Winston, and P. E.Lehr, 1990: Weather Satellites: Systems, Data, and Environ-mental Applications. Amer. Meteor. Soc., 503 pp.

Rieder, K. F., J. A. Smith, and R. A. Weller, 1994: Observed direc-tional characteristics of the wind, wind stress, and surface waveson the open ocean. J. Geophys. Res., 99 (C11), 22 589–22 596.

Riehl, H., 1954: Tropical Meteorology. McGraw-Hill, 392 pp.

Saucier, W. J., 1955: Principles of Meteorological Analysis. Univer-sity of Chicago Press, 438 pp.

Stewart, R. H., and J. R. Barnum, 1975: Radio measurements ofoceanic winds at long ranges: An evaluation. Radio Sci., 10,853–857.

van Vledder, G. P., and L. H. Holthuijsen, 1993: The directionalresponse of ocean waves to turning winds. J. Phys. Oceanogr.,23, 177–192.

Velden, C. S., C. M. Hayden, W. P. Menzel, J. L. Franklin, and J. S.Lynch, 1992: The impact of satellite-derived winds on numericalhurricane track forecasting. Wea. Forecasting, 7, 107–118.

Walker, J. M., 1991: Compendium of lecture notes on marine me-teorology for class III and class IV personnel. WMO No-434,320 pp. [Available from World Meteorological Organization,Case Postale 2300, CH-1211, Geneva 2, Switzerland.]


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