A New Inter-Comparison of Three Global Monthly SSM/I Precipitation Datasets Matt Sapiano, Phil Arkin and Tom Smith Earth Systems Science Interdisciplinary Center, University of Maryland

2 Motivation Currently working on a new reanalysis of precipitation –Aim to use Optimal Interpolation to combine data sources Special Sensor Microwave/Imager (SSM/I) –One definite constituent of the reanalysis –Longest MW precipitation dataset (starts 1987) Several algorithms exist for estimation of precipitation –Goddard Profiling algorithm –NOAA/NESDIS algorithm (Ferraro) –Remote Sensing Systems algorithm (Wentz) Last comparison of these data was several years ago –So: compare them to inform precipitation analysis → Monthly averages, 2.5º resolution

3 Some SSM/I facts… Defense Meteorological Satellite Program Special Sensor Microwave/Imager –7 channels: (H+V), (V), 37.0 (H+V), 85.5 (H+V) Data from present F08 Jul 1987 – Dec 1991 F10 Dec 1990 – Nov 1997 F11 Dec 1991 – May 2000 F13 May 1995 – present F14 May 1997 – present F15 Dec 1999 – Aug 2006 F16 Oct 2003 – present Note: Not all channels were available during the record; notably, the 85GHz channel onboard the F08 satellite was unavailable from June 1990.

4 NOAA/NESDIS (Ferraro) Scattering technique over land –Grody Scattering Index (SI) from 19, 22 & 85 GHz channels –Precip occurrence determined by SI>10 –Screening for snow and ice –Precip empirically estimated from SI Scattering and emission over ocean –Precip occurrence from SI or emission (Q) –Precip empirically estimated from SI or Q Used 37GHz channel when 85GHz unavailable in No overlapping periods for satellites that have similar local equator crossing times

5 RSS (Wentz) Physically based retrieval of rain, wind, water vapor –Estimate transmittance of liquid water from brightness temperature, apply beam filling correction and derive atmospheric attenuation –Mie scattering theory used to estimate columnar rain rate –Columnar rain rate converted to surface rain rate using assumed column height from SST New version of algorithm released September 2006 (Version 06) –Improved beam filling –Improved relationship between column height and SST

6 GPROF SSM/I Version 6 Goddard Profiling algorithm –Inversion scheme to retrieve vertical structure Instantaneous rainfall rates calculated from weighted average of existing hydrometeor profiles created using numerical cloud model –Goddard Cumulus Ensemble Model Land: Scattering technique Ocean: Emission technique Most recent version (V7) not applied to full SSM/I dataset, so V6 is used here –Don’t be confused by naming conventions!!!

7 GPROF V6 Sea Ice Issue Problem of sea ice contamination in GPROF SSM/I Version 6 –First NH (20-60º) EOF shows unphysical anomalies –Clearly an artifact (larger over Sea of Okhotsk) Correction applied here to remove anomalously large values –Gridpoint mean plus five times the zonal mean standard deviation Precipitation, mm day -1

8 Between satellite comparisons Same local crossing times RSS (Wentz) has more consistently higher correlations and lower bias GPROF V6 SSM/I F11 – F13 RSS V06 (Wentz) F14 – F15 GPROF r(F11,F13) after spatial smoothing → Small spatial errors cause noisy correlation field mm day -1

9 Some SSM/I facts… Defense Meteorological Satellite Program Special Sensor Microwave/Imager –7 channels: (H+V), (V), 37.0 (H+V), 85.5 (H+V) Data from present F08 Jul 1987 – Dec 1991 F10 Dec 1990 – Nov 1997 F11 Dec 1991 – May 2000 F13 May 1995 – present F14 May 1997 – present F15 Dec 1999 – Aug 2006 F16 Oct 2003 – present Note: Not all channels were available during the record; notably, the 85GHz channel onboard the F08 satellite was unavailable from June 1990.

10 Different time measurement - correlations Correlations from different overpass times for overlapping periods Differences reflect diurnal cycle F13 vs F14F10 vs F11 NOAA/NESDISGPROF V6 SSM/I RSS V06 (Wentz)

11 Different time measurement - bias F13 vs F14F10 vs F11 NOAA/NESDISGPROF V6 SSM/I RSS V06 (Wentz) Bias from different overpass times Wentz has good agreement between satellites Different biases over land and ocean –High tropical land diurnal variability is of consistent sign –Problem with biases at high latitudes in GPROF due to sea ice

12 Algorithm comparison - ocean Zonal mean precipitation from all three algos –Multiple lines represent the different satellites – diurnal cycle is evident Good agreement between Ferraro and Wentz Annual cycle dominates extra-tropics Ocean only GPROF SSM/I Wentz Ferraro 20ºN – 60ºN 20ºS – 20ºN 60ºS – 20ºS

13 Wentz comparison Wentz algorithm is quite different Good advertisement for the benefits of re-processing Ocean only GPROF SSM/I Wentz Ferraro Wentz V05 Wentz V06

14 Algorithm comparison - Land Only NOA/NESDIS and GPROF V6 as RSS is ocean only Good agreement in annual cycle at higher latitudes, but magnitudes disagree – GPROF V6 gives higher winter precipitation –Is this a problem with snow contamination? Land only GPROF SSM/I Ferraro 20ºN – 60ºN 20ºS – 20ºN 60ºS – 20ºS

15 Gauge validation Correlation with Chen et al. (2002) [GHCN+CAMS] and GPCC gauge analyses (monitoring product) NOAA/NESDIS data better correlated with gauges at higher latitudes –Lack of profiles at high latitudes for GPROF V6? –Snow contamination problem again? NOAA/NESDISGPROF V6 SSM/I Chen et al. GPCC

16 TAO buoy validation Correlations with TAO/TRITON buoy rain gauge data –Data from ATLAS 2 self siphoning gauges –Data has been quality controlled and an empirical wind correction was applied All three algorithms have high correlations with oceanic precipitation RSS (Wentz) V06 data has the highest correlations (not statistically significant though!) NOAA/NESDIS GPROF V6 RSS V06 GPROF SSM/I Wentz Ferraro

17 Conclusions and Further Work SSM/I data continues to increase in value as a climate data record RSS V6 algorithm performs well over oceans –RSS also most homogeneous over the changing satellite record –RSS V06 bias appears to be superior to V05 bias Over land, NOAA/NESDIS appears to have better properties than GPROF SSM/I V6 at higher latitudes –GPROF SSM/I V6 is more homogeneous over the tropics –Lower correlations at mid/high latitudes is a problem Results from GPROF V6 SSM/I not applicable to most recent TMI product –Need for reprocessing of SSM/I using most recent GPROF algorithm [This would make a nice recommendation for this workshop!] Single satellite available before 1992 –Is data homogeneous? Effect of 85GHz failure?