TRMM Ground Validation Some Lessons and Results

1. TRMM Ground ValidationSome Lessons and Results David B. Wolff, David Marks, David Silberstein & Richard Lawrence TRMM Satellite Validation Office NASA/GSFC

2. Summary • TRMM GV Data Processing is up-to-date • Major issues are gauge data problems and (especially at KWAJ) radar calibration uncertainties. • GSFC is developing an automated method of correcting relative calibration of the KWAJ radar to salvage historical KPOL data. • Comparisons of GV estimates to TRMM (3G68) show good agreement, when radar calibration is not major issue. • Comparisons of GV estimates to other datasets (e.g. MPA) also show good agreement and bode well for GPM era sampling expectations

3. Importance of Stable Calibration • Calibration is a Major Issue for TRMM GV • Houze et al. (2004) cite the error associated with a ± 2 dB calibration error is ± 30%, in rain rate, respectively. • Actual calibration uncertainty at KWAJ frequently well over ±2 dB and sometimes > 10 dB! • Absolutely critical that proper calibration procedures be in place for GPM. • Calibration uncertainty is the single largest source of error in Kwajalein rainfall estimates. • While absolute calibration is not always possible using conventional radars, stable calibration is essential. • GSFC is developing a method to correct historical calibration uncertainties using probability distributions of clutter area reflectivity.

4. Dependent Independent GV v5: Kwajalein Monthly Radar/Gauge Rainfall Statistics

5. Detrimental Effects of Unstable Radar Calibration Waveguide change occurred on or around July 1, 2003

6. 50 km 100 km Ground Clutter Locations Statistical/Automated Correction of Calibration TRMM GV uses a “clutter-map” in quality control step at KWAJ. • This map provides a lookup • table for areas (r, ) that have a • high probability of echo when • no precipitation is present. • Given KPOL resolution, there are ~4000 points per VOS. • Calculate daily PDF of Clutter Area Reflectivity (CAR). • Fond that upper percentiles (e.g. 95th) are remarkably stable when the radar calibration is stable, even when precipitation is present.

7. May 07, 2004 @ 2006 UTC May 07, 2004 @ 2052 UTC Statistical/Automated Correction of Calibration Calibration changes are often traceable to engineering changes to the radar system… here a +7 dB gain was applied.

8. 95th % Statistical/Automated Correction of Calibration 95th Percentile Reflectivity in Clutter Areas is Stable Silberstein et al. 2005 (32nd Radar Conference)

9. Calibration baseline (Aug 99 + 6 dBZ) PFN replaced (spare) 11/19/00 Calibration study; Antenna gain decrease Early April 2001 PFN replaced 12/12/00 Antenna gain increase Early June 2001 2000 2001 RCA vs. Engineering Changes • Relative Calibration Adjustment (RCA) http://trmm-fc.gsfc.nasa.gov/trmm_gv/gv_products/GVproducts.html

10. Statistical/Automated Correction of Calibration UW estimates based on comparison to TRMM PR (Houze et al. 2004)

11. Quantifying RCA Effects vs. Z-R Changes V5: 2002 WPMM, no RCA V6: Seasonal WPMM, RCA Marks et al. 2005 (32nd Radar Conference)

12. V5 Biases - KWAJ 1999-2004 GV vs. TRMM

13. V5 Monthly Means - KWAJ 1999-2004

14. V6r Biases - KWAJ 1999-2004

15. V6r Monthly Means - KWAJ 1999-2004

16. Comparing GV to Other Rain Estimates (MPA) • A similar comparison was done using the Multi-Satellite Precipitation Analysis (3B42) Rain Estimate (Huffman et al. 2005) • 0.25° x 0.25° gridded product, available every 3-hours • GV gridded similarly • Compared the 3-hour accumulations from both GV and MPA over these pixels.

17. KWAJ: Comparisons to Other Datasets (MPA)

18. MELB: Comparisons to Other Datasets (MPA)

19. Summary • TRMM GV data processing is current for all sites • Calibration issues at Kwajalein a major source of error • Relative Calibration Adjustment (RCA) shows promise but is still a work in development. • Comparisons to TRMM over MELB generally within ± 10% on year-to-year basis • Comparisons to other estimates (MPA) also show good agreement in MELB and KWAJ (during period when radar calibration is mitigated). • TRMM GV is providing GPM GV a significant number of “lessons learned”, which are being applied in GPM GV development

20. Backup Slides

21. Data was chosen from 1st 100 days in 2002 when radar calibration appeared stable Statistical/Automated Correction of Calibration Diurnal Differences in 95th Percentile Clutter Reflectivity

22. Comparison of Rain Intensity Distributions Probability distributions of rain rate were derived from TRMM (PR, TMI and COM) and GV estimates TRMM --> global (land or ocean) for Feb 1998 (ITE110 - official V6, thanks to S. Yang) GV --> KWAJ (Ocean) and MELB (Land) for period 07-12/1999 Over ocean all PDFs nearly log-normal with some exceptions. Over land, there remains work to be done, especially for 2A12 (TMI).

23. TRMM GV Processing Status

24. Statistical/Automated Correction of Calibration • Benefits of “clutter map” approach: • 95th percentile clutter-area reflectivity is remarkably stable even in the presence of precipitation. Little or no diurnal effect • Easily calculated for near-real-time monitoring of the current state of the relative radar calibration • Current effort: determine the best means of applying these relative calibration changes to historical data to develop improved GV products • Signal is strong, amplitude is in question. Under further investigation.

25. DARW HSTN KWAJ MELB Version 6 GV Site Surface Masks

26. 3G68 & GV Land/Coast/Ocean Masks

27. Comparing GV and TRMM Data • Notes on Bias Calculations • Two references (GV and Satellite) • GV_Ref = Mean 0.5° GV rain intensity • Sat_Ref = (PR + TMI + COM)/3 • Bias = (Reference - Measurement) / Measurement

28. Comparing TRMM and GV Rain Intensities • TRMM 3G68 (gridded PR, TMI and COM) rain intensity estimates compared to similarly gridded TRMM GV estimates. All TRMM estimates are Version 6! • 0.5° x 0.5° over land, coast and ocean • Analysis of 1999-2004 TRMM-v6 has been completed