Potential Improvements to the AMSR-E L2 Rain over Land Algorithm*

1. Potential Improvements to the AMSR-E L2 Rain over Land Algorithm* Ralph Ferraro and Arief Sudradjat NOAA/NESDIS, College Park, MD Cooperative Institute for Climate Studies, College Park, MD *Portions of this talk were presented at the 3rd TRMM Scientific Conference, February 2008 AMSR-E Science Team Meeting Telluride, CO

2. Outline • GPROF/land algorithm history • Current status/evaluation • Areas for improvement & possible solutions • Screening and standardization of flagging • Diversify the land data base and better utilization of Bayesian retrieval • Convective classification (warm season bias) • Anomalous surfaces: • Semi-arid land & deserts • Coastlines/small water bodies • Snow within convective cells • Summary AMSR-E Science Team Meeting Telluride, CO

3. GPROF-Land Background* *Easier to explain versions in terms of TRMM 2A12 product • 2A12 V4 • GSCAT • 2A12 V5 • Retrofit/Engineer/Force/Replicate… NESDIS algorithm within GPROF • Find profiles that match 22V-85V in NESDIS “calibration” relationship • 2A12 V6 (current) • Address deficiencies in unrealistic database and NESDIS relationship through match ups with PR and TMI • Convective/Stratiform relationships • Improved overall performance in terms of bias and correlation • (Improvement) coastline rainfall • 2A12 V7 (next version) • Revisit some basic principles • Will be carried out under auspices of both AMSR-E and PMM (focus on HF/cold season) AMSR-E Science Team Meeting Telluride, CO

4. Examples of Good Results… • Produces realistic rainfall fields when compared with radar, gauges, climatology, etc. • GPROF-land is used in virtually all “blended” rainfall products (3B42, CMORPH, CHOMPS, etc.) Bottom two plots Dave Wolff, GSFC AMSR-E Science Team Meeting Telluride, CO

5. Examples of Problems… • Regional biases • Compared to PR • Compared to gauges • Unrealistic rain rate PDF’s in various regions? • “Strange” conditional rates • Underlying surface • Systematic biases. Why? • Unrealistic profiles in database • Bias towards tropical, ocean type systems • Not enough precip. regimes • Other “dirty laundry” • Surface snow • Inland water bodies Liu and Zipser AMSR-E Science Team Meeting Telluride, CO

6. Some “old” questions… Courtesy of G. Huffman • Complex, outdated, “engineered” screening • How did we get here? • Developed for SSM/I • Different FOV size, etc. • Confusion over zero rain and indeterminate rain. Example: • Limitations over cold, dry land. Is this an indeterminate rain rate or assumed to be zero? • Surface εeffects • Evaporation in dryer climate regimes • Vastly different ice scattering to rain rate relationships ! 11/02 Set pixel_status to invalid surface type and the ! surface rainrate its negative value for ambiguous ! rain retrievals ! 03/03 Assigned covect the probable convective rain. If type of rain ! cannot be determined, convect is left as missing. ! 09/03 Pixel_status is no longer set to -21 for ambiguous rain_status ! All retrieved fields are set to their negative value for ! pixels with an ambiguous rain_status ! 03/04 All retrieved fields for a pixel with an ambiguous rain_status ! are no longer set to their negative value AMSR-E Science Team Meeting Telluride, CO

7. Improvement Philosophy • We will not be developing “quick fixes” • Experience shows its not real effective… • Look at GPROF improvements across ALL platforms • GPM era • Need to think “out of the box” • “Things get old, fast” • Past screening concept now archaic • Relied on SSM/I and discriminant functions • Did not want to rely on “others” • Radiometer only • Data production and delivery reliability • Lack of experience in the user community • Synergy with other data centers/research groups AMSR-E Science Team Meeting Telluride, CO

8. Areas for Improvement • Screening • “Modernize” • Standardization of use of flags • GPM era, need commonality across platforms! • Diversify the land data base & better utilization of Bayesian retrieval • Land systems, all seasons • Emissivity models • All useable measurements • Convective classification (warm season bias) • Anomalous surfaces • Semi-arid land & deserts • Coastlines/small water bodies • Snow within convective cells AMSR-E Science Team Meeting Telluride, CO

9. Current GPROF Screening Courtesy of G. Huffman/GSFC MASKS = -21 MASKP = -41 MASKI = -31 MASKO = -51 MASKC = -61 Land (sfc=1) Warm 85H,cold 22V MASKO Other 85H,cold 22V Grody polarization MASKP Ice polarization MASKP Arid polarization MASKP Not ambiguous 0 Grody cold sfc. MASKI Grody polarization MASKP Ice polarization MASKP Arid polarization MASKP “missing” in 5x5 33 Low sd Intermediate sd 13 Not ambiguous 0 Compute sd[T(85h)] Confused yet? Really cold sfc. MASKI Ambiguous 14 After this, screening code tries to resolve the ambiguous regions. Non-scattering zero-rain flags (-51, -61) aren’t treated. Regions of positive (ambiguous) flags are evaluated for surrounding flag values: If perimeter is all negative, the area is set to the first negative found; if perimeter is zero and negative, the area is set to 13; if perimeter is zero, the area is set to 0. Unresolved ambiguous values are set to -15. After this, “enough scattering” is checked in the rain code. AMSR-E Science Team Meeting Telluride, CO

10. Standardization of Flags • Current flags were designed to: • “Diagnostics” for algorithm developers • Geared for limited set of “early” users • GPCP - Key concern was zero rain vs. indeterminate rain • New, desired attributes include: • Proper survey of user community of their needs • A nomenclature that everyone can understand • A set of flags that is useful for everyone • Commonality across all sensors in GPM era • Will be handled through PMM AMSR-E Science Team Meeting Telluride, CO

11. New Approaches for Sfc. Identification Through utilization of both operational and research data sets that are routinely available, we should be able to conquer the land surface screening problem with relative ease. 85 GHz Emissivity AMSR-E Science Team Meeting Telluride, CO

12. Convective/Stratiform Courtesy of Liu and Zipser • Current method (a combination of 3 published methods) was improvement in V6 from V5, but still has problems. This is the culprit of the warm season bias. • Why? • Resolution – TMI is coarser than PR? Spreads out rain? • Beam filling? Underestimate intense rain AMSR-E Science Team Meeting Telluride, CO

13. GPROF databases and Rain Retrieval • Examine and improve land databases • GPROF land profiles are limited in diversity • Predominantly from tropical oceanic systems • Not diverse nor realistic enough for true physical retrieval • Look at excellent data sets from a variety of sources • C3VP, CloudSat, NOAA’s HMT (West Coast U.S./Winter) • Expand previous TMI/PR studies with full 10-year data • Working with PMM science team members… • Retrieval needs to expand to more than just 22V-85V • Published studies show other combinations are better in different precipitation regimes AMSR-E Science Team Meeting Telluride, CO

14. Special (Seasonal) Situations • False snow (ambiguous) inside of thunderstorm: • Usually the heaviest RR’s in storm system • V6 attempts to filter these out, but it doesn’t always work • Why? Ice scattering at 22V (rare); similar characteristic to snow cover • Solution  use of snowcover climatology and land surface temperature • Arid regions (e.g., Sahel) • Screening removes potential rain areas BUT… • Also isn’t 100% effective, so false alarms result • Also removes true rain in other regions • False alarms create unrealistic conditional rain rates • Solution better utilization of emissivity calculations and surface type information • What’s going on with small water bodies? • Is it called coast or land? • Applying the wrong algorithm to the wrong surface type? OR • Is it a mixed pixel effect? • Does it have seasonal effects due to vegetation cover? • Impact is at the low end (onset) of rainfall • Solution Examine current land/sea/coast mask as a starting point… AMSR-E Science Team Meeting Telluride, CO

15. AMSR-E – L, W, C Are inland water bodies important? Coastline “improvement” not intended here! Impact of “thick” coast on retrievals? AMSR-E Science Team Meeting Telluride, CO

16. Preliminary investigation – Rain/No Rain Global Africa Rain Rain No Rain No Rain Snow Cover Snow Cover Grody Rule: Rain if TB22V>264 K and TB22V>175+.49*TB85V GPROF uses TB21V-TB89V>5 K + Grody rule + GSCAT rule + spatial filter AMSR-E Science Team Meeting Telluride, CO

17. Preliminary investigation – Desert/Semi-Arid Global Africa ARID DESERT ARID DESERT ARID DESERT No rain if PD19>20 OR TB85>253 K and PD19>7 AMSR-E Science Team Meeting Telluride, CO

18. Summary • GPROF-land is utilized in a number of applications and has proven useful • Despite this, feedback of current version by the user community suggest several critical issues that need to be resolved for next upgrade • We will try to prioritize which problems we can solve • Looking towards more generic fixes for GPM era rather than band aids for TRMM and AMSR-E… • PMM Team Meeting (August 2008) plans to address some of these through WG’s: • Land surface/emissivity WG (Gail S-J./Christa P-L./Ralph F.) • Rain detection WG (Guosheng L./Grant P.) AMSR-E Science Team Meeting Telluride, CO

19. Backup Slides AMSR-E Science Team Meeting Telluride, CO

20. NOAA HMT 2005 T and q profiles from HMT RAOB and current land database HMT S-band radar reflectivity Freezing level is around 2.5 km Database lacks such profiles AMSR-E Science Team Meeting Telluride, CO

21. TRMM Courtesy of M. Diederich AMSR-E SSM/I AMSR-E Science Team Meeting Telluride, CO

22. High Resolution Land/Water Mask AMSR-E Science Team Meeting Telluride, CO

23. Filtering out smaller water bodies AMSR-E Science Team Meeting Telluride, CO

24. B02 2002-06-18 (23:40) to 2004-09-24(14:04) B03 2004-09-24(14:04) to 2004-11-04(00:46) B04 2004-11-04(00:46) to 2005-04-01(4:28) B05 2005-04-01(4:28) to 2005-07-06 (4:28) B06 2005-07-06 (4:28) to 2005-08-23 (4:27) B07 2005-08-23 (4:27) to 2006-03-10 (9:31) B08 2006-03-10 (9:31) to 2006-11-13 (02:58) v9 2002-06-18 (23:40) to 2003-12-31(23:59) AMSR-E Science Team Meeting Telluride, CO

25. AMSR-E Science Team Meeting Telluride, CO