Anthony DeAngelisAnthony DeAngelis

AbstractAbstract

Estimation of precipitation provides useful climatological Estimation of precipitation provides useful climatological data for researchers; as well as invaluable guidance for forecasters data for researchers; as well as invaluable guidance for forecasters of flash floods, widespread heavy rain, and heavy snow. Satellites of flash floods, widespread heavy rain, and heavy snow. Satellites present one of the many tools used to provide spatial present one of the many tools used to provide spatial representations of precipitation rates and totals from past events. representations of precipitation rates and totals from past events. Satellite based precipitation measurements are needed because Satellite based precipitation measurements are needed because ground based radar and rain gauges have spatial and technical ground based radar and rain gauges have spatial and technical limitations. Satellite precipitation estimates are derived from limitations. Satellite precipitation estimates are derived from common satellite parameters, such as GOES 11 and 12 cloud-top common satellite parameters, such as GOES 11 and 12 cloud-top temperatures, and brightness temperature at various wavelengths temperatures, and brightness temperature at various wavelengths from several microwave satellites- to name a few. The infrared from several microwave satellites- to name a few. The infrared theory relies on the relationship between cloud-top temperature theory relies on the relationship between cloud-top temperature and precipitation rate, while the microwave theory depends on the and precipitation rate, while the microwave theory depends on the relationship between ice and water content in clouds and relationship between ice and water content in clouds and precipitation. By combining both theories into one algorithm, the precipitation. By combining both theories into one algorithm, the future of space based precipitation estimation appears promising. future of space based precipitation estimation appears promising.

OutlineOutline

Why use satellites to estimate Why use satellites to estimate precipitation?precipitation?

Satellites used in precipitation Satellites used in precipitation estimationestimation GOES Auto-Estimator AlgorithmGOES Auto-Estimator Algorithm

ApplicationsApplications

OutlineOutline

Why use satellites to estimate Why use satellites to estimate precipitation?precipitation?

Satellites used in precipitation Satellites used in precipitation estimationestimation GOES Auto-Estimator AlgorithmGOES Auto-Estimator Algorithm

ApplicationsApplications

Ways to Estimate Ways to Estimate PrecipitationPrecipitation

Ground based radar (ie. NEXRAD)Ground based radar (ie. NEXRAD) Network of Rain GaugesNetwork of Rain Gauges SatellitesSatellites

Why Use Satellites?Why Use Satellites?

Significantly expands spatial Significantly expands spatial coverage- within US, outside US, coverage- within US, outside US, and over oceansand over oceans

US NEXRAD “Gaps” US NEXRAD “Gaps” (West)(West)

http://www.wunderground.com/radar/map.asp

Why Use Satellites?Why Use Satellites?

Significantly expands spatial Significantly expands spatial coverage- within US, outside US, coverage- within US, outside US, and over oceansand over oceans

No beam block (mountains, No beam block (mountains, buildings, insects)buildings, insects)

NEXRAD Beam Block NEXRAD Beam Block (West)(West)

http://www.wunderground.com/radar/map.asp

Why Use Satellites?Why Use Satellites?

Significantly expands spatial Significantly expands spatial coverage- within US, outside US, coverage- within US, outside US, and over oceansand over oceans

No beam block (mountains, No beam block (mountains, buildings, insects)buildings, insects)

No signal attenuation effectsNo signal attenuation effects

Ground Based Radar Ground Based Radar Signal AttenuationSignal Attenuation

http://www.weathertap.com/protected/static/nexrad.html

Why Use Satellites?Why Use Satellites?

Significantly expands spatial Significantly expands spatial coverage- within US, outside US, and coverage- within US, outside US, and over oceansover oceans

No beam block (mountains, buildings, No beam block (mountains, buildings, insects)insects)

No signal attenuation effectsNo signal attenuation effects Less need for calibration- often using Less need for calibration- often using

only one instrument (such as GOES)only one instrument (such as GOES)

Why Use Satellites?Why Use Satellites?

Significantly expands spatial coverage- Significantly expands spatial coverage- within US, outside US, and over oceanswithin US, outside US, and over oceans

No beam block (mountains, buildings, No beam block (mountains, buildings, insects)insects)

No signal attenuation effectsNo signal attenuation effects Less need for calibration- often using Less need for calibration- often using

only one instrument (such as GOES)only one instrument (such as GOES) Supplements ground based radar and Supplements ground based radar and

rain gauge estimatesrain gauge estimates

OutlineOutline

Why use satellites to estimate Why use satellites to estimate precipitation?precipitation?

Satellites used in precipitation Satellites used in precipitation estimationestimation GOES Auto-Estimator AlgorithmGOES Auto-Estimator Algorithm

ApplicationsApplications

Main Satellites UsedMain Satellites Used

InfraredInfrared GOES 11 and 12GOES 11 and 12

MicrowaveMicrowave DMSP SSM/IDMSP SSM/I NOAA AMSU-ANOAA AMSU-A NOAA AMSU-BNOAA AMSU-B NASA AMSR-ENASA AMSR-E

Satellite RadarSatellite Radar NASA TRMMNASA TRMM

Infrared TheoryInfrared Theory

Relationship between cloud-top Relationship between cloud-top temperature, cloud-top thickness, and temperature, cloud-top thickness, and precipitation:precipitation: Colder cloud-top temperatures imply higher Colder cloud-top temperatures imply higher

and thicker clouds, which imply heavier and thicker clouds, which imply heavier precipitationprecipitation

Relationship between changes in cloud-Relationship between changes in cloud-top surface and precipitationtop surface and precipitation Vertically growing clouds are associated with Vertically growing clouds are associated with

precipitation while decaying clouds are notprecipitation while decaying clouds are not

Microwave TheoryMicrowave Theory

Direct relationship between ice in cold Direct relationship between ice in cold clouds and precipitationclouds and precipitation Ice scatters terrestrial radiation back down to Ice scatters terrestrial radiation back down to

the surface, making microwave imagery appear the surface, making microwave imagery appear “cold” where ice clouds are present (passive)“cold” where ice clouds are present (passive)

Direct relationship between water content Direct relationship between water content in clouds and precipitationin clouds and precipitation Water in clouds emits microwave radiation, Water in clouds emits microwave radiation,

making microwave imagery relatively “warm” making microwave imagery relatively “warm” where high water content clouds are present where high water content clouds are present (passive)(passive)

OutlineOutline

Why use satellites to estimate Why use satellites to estimate precipitation?precipitation?

Satellites used in precipitation Satellites used in precipitation estimationestimation GOES Auto-Estimator AlgorithmGOES Auto-Estimator Algorithm

ApplicationsApplications

GOES ReviewGOES Review

Geostationary- stays over the same Geostationary- stays over the same place 24/7, semi-major altitude of ~ place 24/7, semi-major altitude of ~ 42,000km42,000km

GOES 11- W. Hem., GOES 12- E. GOES 11- W. Hem., GOES 12- E. Hem.Hem.

http://celebrating200years.noaa.gov/historymakers/johnson/goes_spacecraft650.html

History of GOES History of GOES AlgorithmsAlgorithms

Interactive Flash Flood Analyzer (IFFA)- Interactive Flash Flood Analyzer (IFFA)- 19781978 Manual and time consumingManual and time consuming

Auto-Estimator (AE)- 1998 (GOES 11/12)Auto-Estimator (AE)- 1998 (GOES 11/12) Similar to IFFA but automated and more Similar to IFFA but automated and more

advancedadvanced Hydro-Estimator (HE)- 2002 (GOES 11/12)Hydro-Estimator (HE)- 2002 (GOES 11/12)

Similar AE but more advanced and operationalSimilar AE but more advanced and operational GOES Multi-Spectral Rainfall Algorithm GOES Multi-Spectral Rainfall Algorithm

(GMSRA)- 2001 (GOES 11/12)(GMSRA)- 2001 (GOES 11/12) Uses all 5 GOES imaging channelsUses all 5 GOES imaging channels

History of GOES History of GOES AlgorithmsAlgorithms

Interactive Flash Flood Analyzer (IFFA)- Interactive Flash Flood Analyzer (IFFA)- 19781978 Manual and time consumingManual and time consuming

Auto-Estimator (AE)- 1998 (GOES 11/12)Auto-Estimator (AE)- 1998 (GOES 11/12) Similar to IFFA but automated and more Similar to IFFA but automated and more

advancedadvanced Hydro-Estimator (HE)- 2002 (GOES 11/12)Hydro-Estimator (HE)- 2002 (GOES 11/12)

Similar AE but more advanced and operationalSimilar AE but more advanced and operational GOES Multi-Spectral Rainfall Algorithm GOES Multi-Spectral Rainfall Algorithm

(GMSRA)- 2001 (GOES 11/12)(GMSRA)- 2001 (GOES 11/12) Uses all 5 GOES imaging channelsUses all 5 GOES imaging channels

GOES Auto-Estimator GOES Auto-Estimator ProcedureProcedure

Step 1Step 1: Measure cloud-top : Measure cloud-top brightness temperature. Initiate brightness temperature. Initiate rainfall rate based on a non-rainfall rate based on a non-linear (power-law) relationship linear (power-law) relationship between cloud-top temperature between cloud-top temperature and rainfall rate produced by and rainfall rate produced by ground based radarground based radar Uses 10.7Uses 10.7μμm channelm channel

http://www.weatheroffice.gc.ca/data/satellite/goes_nam_1070_100.jpg

Nonlinear Power-Law Nonlinear Power-Law RelationshipRelationship

http://www.star.nesdis.noaa.gov/smcd/emb/ff/technique.html

R = 1.1183*1011 * exp (-3.6382 10-2* T1.2)R in mm/hour , T in °K, Developed in 1970s

GOES Auto-Estimator GOES Auto-Estimator ProcedureProcedure

Step 2Step 2: Account for the : Account for the availability of atmospheric availability of atmospheric moisture- where rainfall rate moisture- where rainfall rate obtained from the first step is obtained from the first step is multiplied by a correction factormultiplied by a correction factor Uses NCEP Eta model relative Uses NCEP Eta model relative

humidity (RH) and precipitable humidity (RH) and precipitable water (PW)water (PW)

Accounting for Accounting for Atmospheric MoistureAtmospheric Moisture

Determine a moisture correction factor Determine a moisture correction factor PWRH:PWRH: PWRH = PW (sfc. to 500mb) * RH (sfc. to 500mb)PWRH = PW (sfc. to 500mb) * RH (sfc. to 500mb) Scale PWRH empirically between 0.00 and 2.00Scale PWRH empirically between 0.00 and 2.00

Multiply precipitation rate by PWRHMultiply precipitation rate by PWRH If TIf TBB < 210K, do not multiply by PWRH < 210K, do not multiply by PWRH

(implies enough moisture)(implies enough moisture) If TIf TBB < 200K, rainfall rate limited to 72mm/hr < 200K, rainfall rate limited to 72mm/hr

(maximum average rainfall rate in US)(maximum average rainfall rate in US)

GOES Auto-Estimator GOES Auto-Estimator ProcedureProcedure

Step 3Step 3: Determine where rain : Determine where rain is actually falling -assume rain is actually falling -assume rain to be falling only where there to be falling only where there are growing clouds exhibiting are growing clouds exhibiting over-shooting tops over-shooting tops This uses consecutive half-hourly This uses consecutive half-hourly

IR imagesIR images

Screening Out Non-Screening Out Non-Raining PixelsRaining Pixels

Use consecutive images to see where Use consecutive images to see where cloud-tops are becoming colder cloud-tops are becoming colder (growing) or becoming warmer (growing) or becoming warmer (decaying)(decaying)

Establish cloud growth correction factor Establish cloud growth correction factor (CG) (CG) CG= 1, where cloud-tops are growingCG= 1, where cloud-tops are growing CG=0, where cloud-tops are decayingCG=0, where cloud-tops are decaying

Multiply precipitation rate by CG, acts Multiply precipitation rate by CG, acts like “rain mask”like “rain mask”

GOES Auto-Estimator GOES Auto-Estimator SummarySummary

Rainfall rate= power-law rainfall rate (R) * Rainfall rate= power-law rainfall rate (R) * moisture correction factor (PWRH) * cloud moisture correction factor (PWRH) * cloud growth correction factor (CG)growth correction factor (CG)

Products:Products: 15 minute rainfall rates15 minute rainfall rates 1 hr, 3hr, 6hr, 24hr totals1 hr, 3hr, 6hr, 24hr totals Mainly USMainly US

Mainly used for heavy convective Mainly used for heavy convective precipitationprecipitation

Hydro-estimator- few extra steps Hydro-estimator- few extra steps

Example 24-hr TotalExample 24-hr Total

http://www.star.nesdis.noaa.gov/smcd/emb/ff/auto.html

GOES Precipitation GOES Precipitation OverviewOverview

Advantages:Advantages: High temporal resolution (geostationary)- High temporal resolution (geostationary)-

precipitation estimates every 15 minutesprecipitation estimates every 15 minutes Fairly high spatial resolution of about 4kmFairly high spatial resolution of about 4km

Disadvantages:Disadvantages: Crude scientific theory which doesn’t always Crude scientific theory which doesn’t always

holdhold Can mistake cumulonimbus for cold cirrusCan mistake cumulonimbus for cold cirrus Weaker performance for non-convective Weaker performance for non-convective

precipitationprecipitation

OutlineOutline

Why use satellites to estimate Why use satellites to estimate precipitation?precipitation?

Satellites used in precipitation Satellites used in precipitation estimationestimation GOES Auto-Estimator AlgorithmGOES Auto-Estimator Algorithm

ApplicationsApplications

ApplicationsApplications

Forecasting of heavy precipitationForecasting of heavy precipitation Use NOAA AMSU-B (microwave) hourly Use NOAA AMSU-B (microwave) hourly

rainfall rates as inputrainfall rates as input Uses TUses TBB at 89 and 150GHz regressed against at 89 and 150GHz regressed against

radar data over both land and ocean (scattering radar data over both land and ocean (scattering theory- passive)theory- passive)

Temporal resolution: 4 times a dayTemporal resolution: 4 times a day Spatial resolution: ~ 16kmSpatial resolution: ~ 16km

Use Tropical Rainfall Potential (TRaP) Use Tropical Rainfall Potential (TRaP) algorithm to produce a 24 hour algorithm to produce a 24 hour precipitation forecastprecipitation forecast

Satellite Precipitation Satellite Precipitation Forecasting OverviewForecasting Overview

Advantages: Does a fairly good job Advantages: Does a fairly good job forecasting the maximum amount of forecasting the maximum amount of rainfall expectedrainfall expected

Disadvantages: Does a poor job Disadvantages: Does a poor job forecasting the spatial extent of forecasting the spatial extent of heavy rainfallheavy rainfall

12UTC Jun 5 to 12UTC Jun 6 2001

24 h ending 12 UTC Jun 6 2001

24 h ending 12 UTC Jun 6 2001

12” max

TRaP Calculations

ETA Model Forecast

Stage III multi-sensor observations

Tropical Storm Allison

3”

12.5” max

ConclusionsConclusions Satellites are superior to alternative Satellites are superior to alternative

methods with respect to coverage and methods with respect to coverage and calibration.calibration.

Satellites supplement ground radar and Satellites supplement ground radar and rain gauges- they are all interconnected.rain gauges- they are all interconnected.

GOES products are superior to microwave GOES products are superior to microwave due to higher temporal and spatial due to higher temporal and spatial resolution.resolution.

Microwave products have more robust Microwave products have more robust scientific theory than GOES.scientific theory than GOES.

A combination of microwave and infrared A combination of microwave and infrared theory is promising for the future.theory is promising for the future.

Main ReferencesMain References

Vicente G.A., R.A. Scofield, and W.P. Menzel, Vicente G.A., R.A. Scofield, and W.P. Menzel, 1998: The Operational GOES Infrared 1998: The Operational GOES Infrared

Rainfall Rainfall Estimation technique. Estimation technique. Bulletin of the Bulletin of the American American Meteorological SocietyMeteorological Society, , 7979, 1883-, 1883-1898.1898.

www.comet.ucar.edu/class/rfc_hydromet/www.comet.ucar.edu/class/rfc_hydromet/03_Nov27_2001/docs/Kuligowski/hydromet02.ppt 03_Nov27_2001/docs/Kuligowski/hydromet02.ppt

www.ssd.noaa.gov/PS/TROP/NWAOct2001a.pptwww.ssd.noaa.gov/PS/TROP/NWAOct2001a.ppt http://www.star.nesdis.noaa.gov/smcd/emb/ff/http://www.star.nesdis.noaa.gov/smcd/emb/ff/

auto.htmlauto.html http://www.oso.noaa.gov/goes/http://www.oso.noaa.gov/goes/