Image Interpretation for Weather Analysis Part 2 27 February 2008 Dr. Steve Decker.

Image Interpretation for Image Interpretation for Weather AnalysisWeather Analysis

Part 2Part 2

27 February 200827 February 2008

Dr. Steve DeckerDr. Steve Decker

Improvement ExampleImprovement Example

Registration GOES-12 vs. GOES-13Registration GOES-12 vs. GOES-13 Battery powerBattery power

Severe Thunderstorm DetectionSevere Thunderstorm Detection

Severe thunderstorms Severe thunderstorms often have notable often have notable overshooting topsovershooting tops

Vis: Shadow effectsVis: Shadow effects IR: “Enhanced-V” IR: “Enhanced-V”

signaturesignature Example: Example: VisVis IRIR

Boundary DetectionBoundary Detection

Boundary: Subtle separation between two Boundary: Subtle separation between two air massesair masses

Region of enhanced liftingRegion of enhanced lifting– CloudsClouds– ThunderstormsThunderstorms

Best seen in VisBest seen in Vis Lake Breeze Lake Breeze exampleexample

Blowing SnowBlowing Snow

Can produce whiteout conditions, even with Can produce whiteout conditions, even with no precipitationno precipitation

Vis exampleVis example

Common ChannelsCommon Channels

VisibleVisible– 0.65 0.65 μμm (red)m (red)

Infrared (IR)Infrared (IR)– 10.7 10.7 μμmm

Water VaporWater Vapor– 6.7 6.7 μμmm

Shortwave IRShortwave IR– 3.9 3.9 μμmm

Atmospheric AbsorptivityAtmospheric Absorptivity

Shortwave IRShortwave IR

An infrared window channelAn infrared window channel– Just like “longwave” IRJust like “longwave” IR

Also sees solar radiation Also sees solar radiation (blackbody curve overlap)(blackbody curve overlap)

Works best for warmer tempsWorks best for warmer temps– > -30> -30°C°C– Cold clouds (e.g., cirrus) look mottledCold clouds (e.g., cirrus) look mottled– Good for fire detectionGood for fire detection

Fog detectionFog detection Supercooled vs. ice cloudsSupercooled vs. ice clouds Snow vs. cloudSnow vs. cloud

Fire Detection with Shortwave IRFire Detection with Shortwave IR Fires show up as “hot spots”Fires show up as “hot spots” SoCal fire SoCal fire exampleexample

Fog DetectionFog Detection

Emissivity of liquid water cloud at 3.9 Emissivity of liquid water cloud at 3.9 μμmm is is less than at longer wavelengths.less than at longer wavelengths.– Fog shows up as lower temperaturesFog shows up as lower temperatures– Appears brighterAppears brighter

Opposite true for ice crystals (cirrus)Opposite true for ice crystals (cirrus)

Fog DetectionFog Detection

Emissivity of liquid water cloud at 3.9 Emissivity of liquid water cloud at 3.9 μμmm is is less than at longer wavelengths.less than at longer wavelengths.– Fog shows up at lower temperaturesFog shows up at lower temperatures– Appears brighterAppears brighter

Differences can be maximized by taking the Differences can be maximized by taking the difference between the longwave and difference between the longwave and shortwave IR imagesshortwave IR images

Supercooled Cloud DetectionSupercooled Cloud Detection

Supercooled cloud droplets frequently occur Supercooled cloud droplets frequently occur for -20for -20°C°C < T < 0 < T < 0°C°C

Detection methodDetection method– Identify cloud-top temperatures conducive for Identify cloud-top temperatures conducive for

supercooled droplets using longwave IRsupercooled droplets using longwave IR– Just like fog/stratus droplets, supercooled Just like fog/stratus droplets, supercooled

droplets emit less radiationdroplets emit less radiation

Supercooled ExampleSupercooled Example

NESDIS Icing Product

Snow vs. CloudSnow vs. Cloud

During the day, low clouds will reflect more During the day, low clouds will reflect more solar radiation than snow at 3.9 solar radiation than snow at 3.9 μμmm, so low , so low clouds appear darker (more signal) than clouds appear darker (more signal) than snow.snow.

Urban Heat IslandsUrban Heat Islands

Shortwave IR is more Shortwave IR is more sensitive to emissions sensitive to emissions from warmer from warmer temperaturestemperatures– Urban heat islands Urban heat islands

show up bettershow up better

Water Vapor ChannelWater Vapor Channel

Not an IR windowNot an IR window– Does not see the ground (Does not see the ground (ExceptionException))

Absorbed/emitted by water vaporAbsorbed/emitted by water vapor Colder temperatures imply:Colder temperatures imply:

– More moisture in the mid and upper More moisture in the mid and upper tropospheretroposphere

– Possible regions of ascentPossible regions of ascent Temperature differences important; not their Temperature differences important; not their

magnitudesmagnitudes ExampleExample

Identifying Jet StreamsIdentifying Jet Streams

Jet StreamsJet Streams– Ribbons of quickly moving air near the tropopauseRibbons of quickly moving air near the tropopause– Separate air massesSeparate air masses– Support active weatherSupport active weather

Vis: Band of cirrus clouds on equatorward sideVis: Band of cirrus clouds on equatorward side Vapor: Strong moisture gradientVapor: Strong moisture gradient

– Dry air polewardDry air poleward– Moist air equatorwardMoist air equatorward

Locating Ridges and TroughsLocating Ridges and Troughs

Upper tropospheric flow often contains a Upper tropospheric flow often contains a ridge/trough patternridge/trough pattern

Clouds often occur downstream of troughs, but Clouds often occur downstream of troughs, but upstream of ridgesupstream of ridges

If ridge has small amplitude, clouds may “spill If ridge has small amplitude, clouds may “spill over” ridgeover” ridge

Cloud band ahead of trough often indicates “warm Cloud band ahead of trough often indicates “warm conveyor belt” immediately ahead of a surface conveyor belt” immediately ahead of a surface cold frontcold front– Southern extent of solid band marks trough axisSouthern extent of solid band marks trough axis

Water Vapor ExamplesWater Vapor Examples

EddiesEddies Cyclone developmentCyclone development

– Occlusion stage 1 2Occlusion stage 1 2

Mountain wavesMountain waves– Java exampleJava example

Current weatherCurrent weather

Many More ExamplesMany More Examples

CIMSS Satellite BlogCIMSS Satellite Blog