Updates on Rain over Land Algorithm

1. Updates on Rain over Land Algorithm Ralph Ferraro, Nai-Yu Wang, Kaushik Gopalan and Arief Sudradjat NOAA/NESDIS, College Park, MD Cooperative Institute for Climate Studies, College Park, MD Significant contributions from Chuntao Liu and Dan Cecil AMSR-E Science Team Meeting Huntsville, AL

2. Outline • TMI V7 GPROF/land algorithm update • Reduction in warm season bias • Surface screening not addressed • Prototype, unified land surface identification • Elimination of surface screening with ancillary data • Future plans • What we can do in next year • Beyond AMSR-E Science Team Meeting Huntsville, AL

3. Algorithm Development • Used TMI-PR matchups 2002-2008 from the Utah Precipitation Feature database • Filter out co-locations: • Warm rain (no TB85 depressions) • Anomalous scattering due to surface • Improve TB-RR relationships • Improve Convective-Stratiform separation Caveat – used V6 data; V7 PR is now coming in and is vastly different – will repeat process using subset to see what differences might exist. AMSR-E Science Team Meeting Huntsville, AL

4. Convective Regional/Seasonal differences not significant enough to warrant partitioning for TRMM V7 AMSR-E Science Team Meeting Huntsville, AL

5. Stratiform Regional/Seasonal differences not significant enough to warrant partitioning for TRMM V7 AMSR-E Science Team Meeting Huntsville, AL

6. Final regressions As in TRMM V6, single curves used Cubic fit Linear fit AMSR-E Science Team Meeting Huntsville, AL

7. P(Conv) - Convective ratio • Weighted average of several Conv. Storm indicators • PIWD • Based on 85V Tb gradients in along-scan and along track directions • Std. Dev. of 85V Tb in meso-scale • Npol • Normalized 85 GHz polarization RR = RR_conv*P(Conv) + RR_strat*(1-P(Conv)) AMSR-E Science Team Meeting Huntsville, AL

8. P(Conv) TMI V6 vs. PR V6 TMI V7 vs. PR V6 (PR V7 likely different) AMSR-E Science Team Meeting Huntsville, AL

9. Mean conditional monthly biases (Jan 2002 – Dec 2008) Avg. global bias for TMI – PR rain collocations AMSR-E Science Team Meeting Huntsville, AL

10. Mean unconditional monthly biases (Jan 2002 – Dec 2008) Includes non-raining pixels. Effect of screening errors is seen here. AMSR-E Science Team Meeting Huntsville, AL

11. Seasonal TMI – PR bias map : DJF AMSR-E Science Team Meeting Huntsville, AL

12. Seasonal TMI – PR bias map : JJA AMSR-E Science Team Meeting Huntsville, AL

13. Global RR Prob. density function AMSR-E Science Team Meeting Huntsville, AL

14. Global RR Cumulative distribution AMSR-E Science Team Meeting Huntsville, AL

15. TRMM V7 Check Out - Preliminary Having PR > TMI should be a desirable result assuming PR sees warm rain and TMI does not AMSR-E Science Team Meeting Huntsville, AL

16. Prototype, Generic Land Surface Classification Replace This ………………………………………………With This AMSR-E Science Team Meeting Huntsville, AL

17. Moveable vs. Fixed Grid AMSR-E Science Team Meeting Huntsville, AL

18. Features of a “Generic” Scheme AMSR-E Science Team Meeting Huntsville, AL

19. Impact on 85 GHz AMSR-E Science Team Meeting Huntsville, AL

20. Putting it all together…. AMSR-E Science Team Meeting Huntsville, AL

21. Another Example AMSR-E Science Team Meeting Huntsville, AL

22. Yet another one AMSR-E Science Team Meeting Huntsville, AL

23. JJA (2008) vs. PR V6 Prototype Elevation Mask Fixed Arid too rigid TMI too high TMI too low Values are (2A12-2A25)/2A25 AMSR-E Science Team Meeting Huntsville, AL

24. DJF (2007-8) vs. PR V6 Prototype Dynamic Snow Cover TMI too high TMI too low Values are (2A12-2A25)/2A25 AMSR-E Science Team Meeting Huntsville, AL

25. Comparisons vs. GPCP DJF JJA TMI too high V6 V6 TMI too low Prototype Prototype Values are (2A12-GPCP)/GPCP Note – GPCP – SSMI, IR, Gauges AMSR-E Science Team Meeting Huntsville, AL

26. Relevant Publications • Wang, N.-Y., C. Liu, R. Ferraro, D. Wolff, E. Zipser, and C. Kummerow, 2009: TRMM 2A12 Land Precipitation Product - Status and Future Plans. Journal of the Meteorological Society of Japan, 87, 237–253. • Gopalan, K., N-Y. Wang, R. Ferraro, C. Liu, 2010: Status of the TRMM 2A12 Land Precipitation Algorithm. In Press, J. Appl. Meteor. Climo. • Sudradjat, A., N-Y. Wang, K. Gopalan, R. Ferraro, 2010: Prototyping a Generic, Unified Land Surface Classification and Screening Methodology for GPM-era Microwave Land Precipitation Retrieval Algorithms, submitted, J. Appl. Meteor. Climo. AMSR-E Science Team Meeting Huntsville, AL

27. Next Steps – Short Term • Work with CSU team to insure GPROF2008 is implemented properly for AMSR-E • Depending on timing/needs for AMSR-E reprocessing, can incorporate some improvements for land surface screening • Elevation? • Other surfaces? • Through PMM Science Team, AMSR-E team/ this effort, begin to investigate rainfall regimes • AMSR-E channel co-variances • Use of ancillary information • Land surface temp, emissivity, etc. • Aqua products preferred AMSR-E Science Team Meeting Huntsville, AL

28. Next Steps – Long Term • If new proposal successful… • Fully develop generic land surface characterization/screening scheme for use in GPROF20xx • Restructure GPROF databases for rainfall regimes • Focus would be using Aqua products for the AMSR-E version • Continue to provide user support for product AMSR-E Science Team Meeting Huntsville, AL