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Fog and low cloud ceilings in the northeastern US: climatology and dedicated field study

Fog and low cloud ceilings in the northeastern US: climatology and dedicated field study

Robert TardifNational Center for Atmospheric ResearchResearch Applications Laboratory

Robert TardifNational Center for Atmospheric ResearchResearch Applications Laboratory

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Overview of projectOverview of projectObjectivesObjectives:

Improve short-term C&V forecastsIncrease understanding of physics of C&V in complex environments

Assess performance of NWP models and develop improved key parameterizations for C&VValidate current & develop improved C&V translation algorithmsSupport development of statistical forecast models

ActivitiesActivities:Climatology → scope out the extent and characteristics of the fog/low ceiling problem in the NE region (variability, type, main influences…) Field study/data analysis → gather specialized observations relevant to C&V. More in-depth look through case study analyses Numerical modeling → complement data analysis & gain greater insights into physics of C&V and model strengths/weaknesses

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Climatology of C&V in northeastern USClimatology of C&V in northeastern USCharacteristics of C&VCharacteristics of C&V:

Fog: ~50 to 300 hours/year in ~10 to 35 events/year

Low ceiling (< 300m): ~580 to 1100 hours/year in ~60 to 95 events/year

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Climatology of C&V in northeastern USClimatology of C&V in northeastern USFog Low ceiling

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Fog climatologyFog climatologyConditions at onset (wind direction) :

Evidence of onshore flow as fog enhancing factorNE flow

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Fog climatologyFog climatologyFog types => is there a prevailing fog type in the region?

Classification algorithm: Precipitation: If some type of precip. is observed at onset and/or 1hr beforeRadiation

• Cooling @ surface under calm or light winds• No ceiling hour before onset, or ceiling height increasing or cloud

cover decreasing just before onsetAdvection

• Significant wind speed• Sudden decrease in visibility and ceiling height

Cloud base lowering• Low ceiling (below 1km) w/ height gradually decreasing within 6

hours leading to fog onset“Morning evap. fog”

• Within 1hr of sunrise• Warming but larger increase in dew point

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Fog climatologyFog climatologyFog types - results

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Fog climatologyFog climatologyFog types – temporal variability

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Fog climatologyFog climatologySummary:

Low ceilings much more frequent than fogFog most common at coastal and inland locations (minimum in urban center)Overall “fog problem” in NE is multi-faceted (various fog regimes)

Precipitation-induced fog most frequent across region“Cloud base lowering” fog is another important componentMarine fog/stratus at coastal locationsRadiation fog inland

Distinct temporal variability according to fog typesFog onset: distinct flow regimes, but with various synop wx patterns

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C&V field study in northeastern USC&V field study in northeastern US

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C&V field program in Northeastern USC&V field program in Northeastern USCentral facility

90-m tower + surface-based instrumentationEast-central Long Island (Brookhaven Natl’ Lab.)Various fog types (climo)

Other available dataASOS network (1-min data)Twice-daily NWS soundings at Upton NYBuoys (hourly data)NEXRAD + satellite prod’s

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90-m tower 7 levels of T/Hum/Wind3 levels of visibility & present wx2 levels of fast-response T,Hum,Wind (fluxes) and radiation (LW↓↑ + SW↓↑)Fog spectrometer (32m)

Surface instrumentationT/Hum/PressureRain gaugeSoil T + Moisture (6 levels)

Remote sensingCeilometer (30 sec. cloud backscatter)Profiling Microwave Radiometer (1 min. profiles of T/Hum/Cloud water)

Central facility Central facility -- instrumentationinstrumentation

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Central facilityCentral facilityComplex environment @ various scales

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Highlights from data analysisHighlights from data analysis

Case studies

Variability in microphysical structure of fog layers

A look into translation algorithms (βext vs RH, βext vs LWC)

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Highlights from data analysisHighlights from data analysis

From Oct. 2003 to June 2005 ► 40 events of interest!

11 “cloud base lowering” fog10 “precipitation” fog6 radiation fog2 advection fog + 1 marine fog transforming into stratus during inland propagation1 “morning evaporation” fog7+ low ceiling without dense fog4+ “near radiation fog”

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Highlights from data analysisHighlights from data analysisObservations during an event (fog w/ precip):

Visibility

Precip.

Biral/HSS visibility /present

wxsensors

Ceilometer

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Highlights from data analysisHighlights from data analysisObservations during an event (fog w/ precip):

dense fog

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Highlights from data analysisHighlights from data analysisObservations during an event (fog w/ precip):

dense fog

wind shear turbulence intensityw

hVσ

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Microphysical variability (over life cycle)Highlights from data analysisHighlights from data analysis

LWC

Vsettl

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Microphysical variability (over life cycle)Highlights from data analysisHighlights from data analysis

dense fog

Visibility

Droplet spectra

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Microphysics variability (w.r.t. fog type)Highlights from data analysisHighlights from data analysis

Drop size distribution

βext vs LWC

Kunkel (1984)Visi=1kmVisi=0.4km

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Highlights from data analysisHighlights from data analysisTranslation algorithms (translating model parameters to visibility)

βext vs LWC & others (in fog) + βext vs RH (pre-fog)

( )2

0

2ext ext

rQ r n r drπβ πλ

∞

= ∫obs

obs βext vs LWC

- Limitation of instruments?- Importance of interstitial haze particles?

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Highlights from data analysisTranslation algorithms (translating model parameters to visibility)

Highlights from data analysis

βext vs others (in fog)

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Highlights from data analysisTranslation algorithms (translating model parameters to visibility)

Highlights from data analysis

βext vs RH (pre-fog)

(MVFR)(IFR)

(LIFR)

Huge variability!

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Highlights from data analysisTranslation algorithms (translating model parameters to visibility)

Highlights from data analysis

βext vs RH (pre-fog)

0730z

2300z

0730z

2300z

Problem more complexthan βext = βext(RH)!

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Summary and perspectivesSummary and perspectivesAnalysis of field data (specialized & operational) ongoingAnalysis provides some insights into complexity of physical processes involved in C&V events in NESignificant variability in fog microstructureBetter characterization and understanding of TA parameters needed (more observations)

What’s next?In-depth look at physical processes associated to precip-induced fogFurther analysis of microphysical data from fog spectrometer (variability + parameterizations + relationship to visibility (TA))

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Outstanding questions/challengesRoadmap toward better C&V forecasts?

Parameterizations of current NWP models adequate? –develop improved model physicsObservations required for assimilation? Identify sensitivity to physical processes/parameterizations

Basis for probability forecasts from ensembles – feasible?Predictability issues

Statistical forecast models capturing the physics. Which predictors are required?

Challenge => comprehensive dataset required!Boundary layer structure (temperature, moisture, flow)Cloud/fog structure (depth, LWC distribution)Mesoscale structure of coastal atmosphere Aerosol characteristics => variability in microphysical structure