Combining GOES-R and GPM to Combining GOES-R and GPM to

improve GOES-R rainrate productimprove GOES-R rainrate product Nai-Yu Wang, University of Maryland, CICSNai-Yu Wang, University of Maryland, CICS

Kaushik Gopalan, ISRO, India*Kaushik Gopalan, ISRO, India*Rachel Albrecht, INPE, Brazil*Rachel Albrecht, INPE, Brazil*

Weixin Xu, University of Maryland, CICSWeixin Xu, University of Maryland, CICS

NOAA Collaborators: NOAA Collaborators:

Robert Kuligowski, Robert Kuligowski, NOAA/NESDIS/STARNOAA/NESDIS/STAR

Ralph Ferraro, Ralph Ferraro, NOAA/NESDIS/STARNOAA/NESDIS/STAR

* formerly with University of Maryland, CICS

Project ObjectivesProject Objectives• To improve To improve microwave-

based precipitation by connecting the ice-phased microphysics commonly observed by lightning sensors and microwave radiometers

• convective/stratiform partition in the precipitation systems

• To provide better microwave calibrations for GOES-R ABI rain-rate (QPE) algorithm.

StatusStatus

• starting the 2starting the 2ndnd year of a two-year project to improve year of a two-year project to improve microwave calibrator for ABI QPE algorithm with microwave calibrator for ABI QPE algorithm with lightning lightning

• Combined with a CICS new start “ Combining GLM Combined with a CICS new start “ Combining GLM and ABI Data for Enhanced GOES-R Rainfall and ABI Data for Enhanced GOES-R Rainfall Estimates” lead by Robert Adler (PI) and N. Wang Estimates” lead by Robert Adler (PI) and N. Wang (Co-PI), a new post-doc is hired(Co-PI), a new post-doc is hired

• Built a multi-year TRMM TMI/PR/LIS database (in Built a multi-year TRMM TMI/PR/LIS database (in 0.10.1oo grid resolution) to investigate lightning- grid resolution) to investigate lightning-microwave convection relationshipsmicrowave convection relationships

• Developed a preliminary method to use lightning Developed a preliminary method to use lightning info in microwave rainfall retrieval algorithminfo in microwave rainfall retrieval algorithm

Rain Feature Discrimination with LightningRain Feature Discrimination with Lightning

TPF: microwave precipitation feature

lightning information isvery helpful in discriminating

microwaveprecipitation feature of

different convective properties (indicated by

radar)

How to relate lightning to convective properties How to relate lightning to convective properties observed by microwave observed by microwave

TRMM October 10, 2004 over Brazil (TRMM orbit #39346)

Microwave + Lightning

LIS event rate(events/min)

LIS flash rate(flashes/min)

Rain Rate

DelineateConvective/Stratiform

Ice, mixed -phase

TMI 85 GHz V-pol TBs

Radar convective/stratiforn type

TRMM LIS/TMI/PR DatabaseTRMM LIS/TMI/PR Database((proxy for GOES-R and GPMproxy for GOES-R and GPM))

• Four years (2002-2005) of TRMM radar/radiometer/lightning data in 0.1° grid Four years (2002-2005) of TRMM radar/radiometer/lightning data in 0.1° grid resolution over landresolution over land

• PR convective fraction estimates, near surface rain rates, reflectivity profilesPR convective fraction estimates, near surface rain rates, reflectivity profiles• TMI TBs, convective fraction estimate (from 10/37/85 GHz), rain-rates (from 85 GHz)TMI TBs, convective fraction estimate (from 10/37/85 GHz), rain-rates (from 85 GHz)• LIS radiances, event rates, group rates and flash ratesLIS radiances, event rates, group rates and flash rates

• 14 millions14 millions raining pixels raining pixels are used to investigate relationships between lightning are used to investigate relationships between lightning frequency/occurrence and convective/statirom partition in the precipitation system observed by microwave frequency/occurrence and convective/statirom partition in the precipitation system observed by microwave

Some interesting lightning StatisticsSome interesting lightning Statistics

• From four years of From four years of TRMM satellite TRMM satellite observations, total of observations, total of 14 millions rain pixels 14 millions rain pixels over land (0.1over land (0.1oo grid grid resolution), 7% resolution), 7% detects lightning (total detects lightning (total lightning)lightning)

• 13.5% of the lightning 13.5% of the lightning occur in stratiform, occur in stratiform, 86.5% in convective86.5% in convective

Lightning frequency of incidence and Lightning frequency of incidence and flash rateflash rate

Raining pixels from Jan 2002 – Dec 2004

Lightning frequency of occurrence and flash rates increase with cooler 85 GHz TB and stronger convection (indicated by

radar reflectivity).

Lightning Intensity, radar Reflectivity, and Lightning Intensity, radar Reflectivity, and microwave 85 GHz relationships microwave 85 GHz relationships

Median radar reflectivity vertical profilesfor different convective strength, indicated

by flash rates

Frequency distribution of 85 GHz TBs for different convective strength,

indicated by flash rates

How are lightning data used in microwave How are lightning data used in microwave rainfall estimatesrainfall estimates

• Microwave rain-rate at 85 GHzMicrowave rain-rate at 85 GHz

RR = RRconv P(C) +RRstrat (1 - P(C))RR = RRconv P(C) +RRstrat (1 - P(C))

P(C) : convective fractionP(C) : convective fraction

P(C) = aP(C) = a11 TB10V + a TB10V + a22 (TB37V+TB85V)/2 (TB37V+TB85V)/2

+ a+ a33 NPOL + a NPOL + a44 STDEV + a STDEV + a55 MINIMA +k MINIMA +k

• Sorting microwave TBs and convective Sorting microwave TBs and convective fractions P(C) with increasing lightning flash fractions P(C) with increasing lightning flash rates. rates.

• Convective Fraction P(C) becomes a function of Convective Fraction P(C) becomes a function of lightning flash rateslightning flash rates

Effect of Lightning in the microwave Effect of Lightning in the microwave convective fractionconvective fraction

TMI P(C) TMI-LIS P(C)

5 PCTILE MEDIAN 95 PCTILE 5 PCTILE MEDIAN 95 PCTILE

CAT0

no flash 0 0.10 0.51 0 0.09 0.47

CAT1

0-1 fl/min 0.11 0.41 0.71 0.29 0.54 0.75

CAT2

1-2 fl/min 0.16 0.50 0.76 0.45 0.68 0.84

CAT3

>2 fl/min 0.24 0.59 0.83 0.98 0.996 1

An example: lightning info on defining convective fractionAn example: lightning info on defining convective fractionLIS flash rates

radar microwave microwave + lightning

Lightning makes a difference on the microwave

convection classification, particularly

on strong convection

An example: lightning on rain rate estimatesAn example: lightning on rain rate estimates

P(C)

rain rate

radar microwave microwave + lightning

Summary and Future WorkSummary and Future Work• Build a database of 7 yrs of co-located microwave/radar/lightning dataBuild a database of 7 yrs of co-located microwave/radar/lightning data

in 0.1 grid resolutionin 0.1 grid resolution• Statistical relationships between the absence/presence of Statistical relationships between the absence/presence of

lightning and flash rates, convection properties (by radar), and lightning and flash rates, convection properties (by radar), and

microwave TBs. microwave TBs. • A preliminary method is developed statistically using lightning info to A preliminary method is developed statistically using lightning info to

sort microwave data with lightning flash rates as a indicator for sort microwave data with lightning flash rates as a indicator for

convection strength.convection strength.• The preliminary lightning-enhanced microwave rainfall algorithm The preliminary lightning-enhanced microwave rainfall algorithm

shows improvement in strong convection (P(C) 0.5-1). shows improvement in strong convection (P(C) 0.5-1).

Lightning improve (5-10%) microwave’s ability to identify heavy Lightning improve (5-10%) microwave’s ability to identify heavy

convection areas.convection areas.• Next, we’ll explore different microwave convection definitions Next, we’ll explore different microwave convection definitions

with radar convection properties and lightning info.with radar convection properties and lightning info.