Precipitation Retrievals Over Land Using SSMIS Nai-Yu Wang 1 and Ralph R. Ferraro 2 1 University of Maryland/ESSIC/CICS 2 NOAA/NESDIS/STAR

Outline Motivation Motivation Current status of GPROF land Current status of GPROF land Profiling approach Profiling approach High frequency and temperature sounding channels from SSMIS High frequency and temperature sounding channels from SSMIS Land precipitation retrievals in complex terrain Land precipitation retrievals in complex terrain Conclusions and future work Conclusions and future work

Motivation Improve current precipitation retrievals over land (TMI GPROF 6.5 land) Improve current precipitation retrievals over land (TMI GPROF 6.5 land) Explore mid-latitude precipitation retrieval using passive microwave radiometer high frequency and sounding channels, in preparations for GPM Explore mid-latitude precipitation retrieval using passive microwave radiometer high frequency and sounding channels, in preparations for GPM High frequency bands between 150 and 183 GHz High frequency bands between 150 and 183 GHz Less sensitive to surface emissivity variations Less sensitive to surface emissivity variations Respond to thick clouds, water vapor, and precipitation Respond to thick clouds, water vapor, and precipitation Oxygen absorption bands between 50 and 60 GHz Oxygen absorption bands between 50 and 60 GHz Primarily probe atmospheric temperature and moisture profiles, might be critical in classifying different climate regimes (e.g., freezing height) Primarily probe atmospheric temperature and moisture profiles, might be critical in classifying different climate regimes (e.g., freezing height)

Current status of GPROF Land TMI GPROF 6.5 land TMI GPROF 6.5 land Ferraro’s scattering index (SI) and rainrate algorithm for SSMI and TMI, utilize 22 and 85 GHz Ferraro’s scattering index (SI) and rainrate algorithm for SSMI and TMI, utilize 22 and 85 GHz TRMM TMI SI and PR rainrate matchups, convective probability, separate convective and stratiform in the database; coastline improvements (McCollum and Ferraro) TRMM TMI SI and PR rainrate matchups, convective probability, separate convective and stratiform in the database; coastline improvements (McCollum and Ferraro) Retrieve Surface rainrate Retrieve Surface rainrate

Profiling Approach Retrieve hydrometeor profiles using GHz and GHz brightness temperatures Retrieve hydrometeor profiles using GHz and GHz brightness temperatures Bayesian framework Bayesian framework Employ cloud resolving models (CRM), coupling CRM outputs with radiative transfer calculations to construct an a priori database of brightness temperatures and the hydrometeor profiles over land Employ cloud resolving models (CRM), coupling CRM outputs with radiative transfer calculations to construct an a priori database of brightness temperatures and the hydrometeor profiles over land

Profiling Approach Use a probabilistic approach to calculate the most likely a posteriori distribution constrained by actual satellite measured brightness temperatures Use a probabilistic approach to calculate the most likely a posteriori distribution constrained by actual satellite measured brightness temperatures Precipitation estimates are weighted averages of the mean precipitation values corresponding to the classes in the database Precipitation estimates are weighted averages of the mean precipitation values corresponding to the classes in the database R: retrieved hydrometeor profile

Surface Screening Hydrometeor Microphysical schemes Radiative Transfer Model TOA multichannel Brightness Temperatures/ Hydrometeor Vertical profiles Observed Multichannel Brightness Temperatures Observations Convective Stratiform ? Best matched Brightness Temperatures Hydrometeor profiles Surface rainrate Generate Database

Land Database GPROF land profiles are selected exclusively from GPROF land profiles are selected exclusively from GPROF CRM simulations that are predominantly from tropical oceanic systems GPROF CRM simulations that are predominantly from tropical oceanic systems Profiles tested: Profiles tested: GCE TRMM LBA: simulations of mesoscale convective system during Jan-Feb in Brazil GCE TRMM LBA: simulations of mesoscale convective system during Jan-Feb in Brazil MM5 MIDACF: mid-Atlantic ocean cold front system MM5 MIDACF: mid-Atlantic ocean cold front system 5 classes of hydrometeor: cloud water, cloud ice, rain, ice and graupel 5 classes of hydrometeor: cloud water, cloud ice, rain, ice and graupel km horizontal resolution, averaged to individual SSMIS resolutions (15 km for 150, 183 GHz) km horizontal resolution, averaged to individual SSMIS resolutions (15 km for 150, 183 GHz) Radiative transfer model: Eddington two-stream approximation (Kummerow) Radiative transfer model: Eddington two-stream approximation (Kummerow)

Land database issues Bayesian approach Bayesian approach Strength : direct use Strength : direct use of explicit microphysical mechanisms in CRM Disadvantage: Disadvantage: susceptible to errors in the a priori database in terms of the accuracy of microphysical details, and the fidelity with which the model outputs capture differences in climate regimes. An example.

Observations: SSMIS Conical scanned passive microwave radiometer, launched in Oct 2003 Conical scanned passive microwave radiometer, launched in Oct 2003 SSMI heritage channels GHz SSMI heritage channels GHz Air temperature sounding channels near 60 GHz oxygen absorption band Air temperature sounding channels near 60 GHz oxygen absorption band 150 GHz imaging channel and three 183 (+-1, +-3, +-6.6) GHz troposphere water vapor sounding channels 150 GHz imaging channel and three 183 (+-1, +-3, +-6.6) GHz troposphere water vapor sounding channels

SSMIS IFOV SSMIS IFOV Freq Footprint Sampling interval Freq Footprint Sampling interval GHz (km) (km) GHz (km) (km) 22 73X X X X X X X X X X Grid all channels to 0.15 deg in latitude/longitude grids Grid all channels to 0.15 deg in latitude/longitude grids Courtesy of Dr. Joe Turk

NOAA HMT 2006 site Complex terrain Complex terrain Off coast of California Off coast of California American river basin American river basin Sierra mountain Sierra mountain Winter time flooding Winter time flooding Instrumentations Instrumentations Radar profilers Radar profilers X-band polarimetric X-band polarimetric radar radar GPS sounde GPS sounde Disdrometer Disdrometer Rain gauges Rain gauges IOP4 : DEC 30-31, 2005 Cold frontal system, moist oceanic air mass crossed the area, small scale rain band structure, high snow level on the ground

High Frequency Precipitation signals SSMIS Dec 31, Z

Surface Screening Surface ice and snow, Surface ice and snow, and sand yield similar scattering signatures as precipitation Screening surface scatters Screening surface scatters “scattering index” SI to locate “scattering index” SI to locate high scatters combinations of low/high combinations of low/high frequency channels to differentiate frequency channels to differentiate precipitation from surface scatters precipitation from surface scatters TB(22 GHz) TB(22 GHz) TB( GHz) TB( GHz)  GHz)  GHz)

Preliminary Rain Retrieval December 31, 2005 SSMIS retrieved rainrates from 50, 150, /+-7 GHz at 1637Z Composite radar reflectivity at 1700Z

Conclusions and Future Work A framework of land precipitation profiling retrieval algorithm using passive microwave high frequency is established A framework of land precipitation profiling retrieval algorithm using passive microwave high frequency is established Currently, retrieval does not have the ability to locate the freezing level and differentiate convective and stratiform systems from brightness temperatures Currently, retrieval does not have the ability to locate the freezing level and differentiate convective and stratiform systems from brightness temperatures plan to gather large number of matchups between SSMIS, TRMM PR and CloudSat for different climate regimes to enhance the retrieval skill plan to gather large number of matchups between SSMIS, TRMM PR and CloudSat for different climate regimes to enhance the retrieval skill Radar reflectivity/hydrometeor profiles will also used to build up hydrometeor database for land Radar reflectivity/hydrometeor profiles will also used to build up hydrometeor database for land Validate radiative transfer model with HMT ground radars and satellite radar matchups Validate radiative transfer model with HMT ground radars and satellite radar matchups