1. 25-28 October 2004 2nd IPWG Monterey, CA The Status of the NOAA/NESDIS Operational AMSU Precipitation Algorithm Ralph Ferraro NOAA/NESDIS College Park, MD USA Fuzhong Weng, Norman Grody, Limin Zhao, Paul Pellegrino, Cezar Kongoli, Huan Meng, Mark Liu

2. 25-28 October 2004 2nd IPWG Monterey, CA Outline Review of AMSU and NOAA POES Current AMSU Algorithm –89/150 GHz Scattering Technique Performance and limitations –Applications Example: Tropical Rainfall Potential –Solid Precipitation over land Performance and limitations Future: –Algorithm improvements –NOAA-N, N’ and METOP

3. 25-28 October 2004 2nd IPWG Monterey, CA NOAA AMSU Sensor Flown on NOAA-15 (5/98), NOAA-16 (9/00) & NOAA-17 (5/02) satellites Contains 20 channels: AMSU-A (45 km nadir FOV) 15 channels 23 – 89 GHz AMSU-B (15 km nadir FOV) 5 channels 89 – 183 GHz Operational “imaging” products: TPW, CLW, rain rate, snow cover, sea-ice, etc. ~4-hour temporal sampling: 130, 730, 1030, 1330, 1930, 2230 LST

4. 25-28 October 2004 2nd IPWG Monterey, CA

5. 25-28 October 2004 2nd IPWG Monterey, CA AMSU Rain Rate Algorithm Basis for algorithm – work of Weng, Grody and Zhao –Physical retrieval of IWP and D e – 89 & 150 GHz Algorithm adopted for use with AMSU-B –Use of other window and sounding channels Derive needed parameters Filters for false signatures –Use of ancillary data –Use of other AMSU derived products IWP to rain rate based on limited MM5 model data and RTE calculations: – RR = A 0 + A 1 *IWP + A 2 *IWP 2

6. 25-28 October 2004 2nd IPWG Monterey, CA

7. 25-28 October 2004 2nd IPWG Monterey, CA

8. 25-28 October 2004 2nd IPWG Monterey, CA AMSU-A Tb’s AMSU-B Tb’s Ancillary Land or Water? Land or Water? Land Water Sea-Ice Conc. TPW & CLW Ice? No Yes Emissivity Surface Temperature AMSU-A Swath LandWater AMSU-B Swath IWP & De Snow Ice? No Snow? Yes No Rain Rate IWP & De Precipitation Rate

9. 25-28 October 2004 2nd IPWG Monterey, CA

10. 25-28 October 2004 2nd IPWG Monterey, CA AMSU Rain Rate Algorithm - Chronology Original algorithm suffered from several problems –Unrealistic PDF’s in IWP and rain rate –Too low rain in convection, too high in stratiform –Large discontinuities between land and ocean –Over sensitivity to small IWP Improvements developed and implemented 8/03: –Two stream corrections for TB 89 & TB 150 as function of Θ –Two sets of coefficients based on size of D e –Utilization of 183 GHz bands to determine depth of precipitation Developed a “Convective Index” (CI) based on differences and magnitudes of TB 183+1, TB 183+3, TB 183 +7 Developed two IWP to RR relationships based on CI

11. 25-28 October 2004 2nd IPWG Monterey, CA Example of Real Time Data

12. 25-28 October 2004 2nd IPWG Monterey, CA Example of Monthly Data

13. 25-28 October 2004 2nd IPWG Monterey, CA Web Site http://www.orbit.nesdis.noaa.gov/corp/scsb/mspps/main.html

14. 25-28 October 2004 2nd IPWG Monterey, CA Validation/Evaluation Land: –Instantaneous – NCEP Stage IV (Janowiak) –Monthly – GPCC Gauges (Rudolph) & SSM/I –Monthly – Australia (Ebert) –Monthly - AMSR-E Ocean: –Monthly – SSM/I –Monthly – AMSR-E User Feedback –Joyce, Huffman, Turk, etc.

15. 25-28 October 2004 2nd IPWG Monterey, CA

16. 25-28 October 2004 2nd IPWG Monterey, CA

17. 25-28 October 2004 2nd IPWG Monterey, CA

18. 25-28 October 2004 2nd IPWG Monterey, CA

19. 25-28 October 2004 2nd IPWG Monterey, CA Mean Bias SSMIAMSUGPCCSSMIAMSU 60S-60N58.5467.5074.840.780.90 40S-40N71.4380.7680.470.891.00 20S-20N98.25117.47128.870.760.91 RR SSMIAMSU 60S-60N0.660.71 40S-40N0.710.76 20S-20N0.760.79 Performance vs. GPCC (8/03 – 7/04)

20. 25-28 October 2004 2nd IPWG Monterey, CA

21. 25-28 October 2004 2nd IPWG Monterey, CA AMSR-E and SSM/I Comparisons

22. 25-28 October 2004 2nd IPWG Monterey, CA N-16 vs. AMSR-E Land Ocean

23. 25-28 October 2004 2nd IPWG Monterey, CA Summary/Limitations Land –In general, performs well Too high in convective situations? Regional biases (of course!), esp. too high in drier regimes –3-satellite estimates outperform (dual SSM/I) –Better sensitivity to lighter rain rates Ocean –Restricted to convective precipitation Overall, too low due to missing precipitation without ice (generally lighter rain intensities) Rain coverage less than other sensors –Conditional rain rates too high? Cloud base temperature estimate incorrect? Coastlines –Not adequately handled View angle dependencies –Larger FOV on scan edges results in varying rain rate distributions Larger errors due to beam filling likely Lower rain rates expected over larger area, but makes more difficult for users May miss detecting some rain at scan edge

24. 25-28 October 2004 2nd IPWG Monterey, CA Applications at NOAA Weather forecasting & analysis Tropical Cyclones Climate Monitoring Development of merged precipitation analysis

25. 25-28 October 2004 2nd IPWG Monterey, CA Hurricane Ivan – 15 Sept 04

26. 25-28 October 2004 2nd IPWG Monterey, CA NOAA/NESDIS TRaP Hurricane Ivan – 15 Sept 04

27. 25-28 October 2004 2nd IPWG Monterey, CA Ground Truth

28. 25-28 October 2004 2nd IPWG Monterey, CA Falling Snow over Land from AMSU Use of AMSU-B 183 GHz bands along with AMSU-A 53.6 GHz allows for expansion of current algorithm to over cold and snow covered surfaces: –AMSU-B channels allow for detection of scattering associated with precipitation, but surface blind when “sufficient moisture” exists –AMSU-A channel 5 allows for discrimination between “rain” and “snow” Feature added in 11/03, snowfall detection only (assigned arbitrary rate of 0.1 mm/hr) Validation over CONUS winter 2003-04

29. 25-28 October 2004 2nd IPWG Monterey, CA 1200 UTC 25 January 20041300 UTC 25 January 2004

30. 25-28 October 2004 2nd IPWG Monterey, CA Snowfall Detection Algorithm Snow on ground or Tsfc < 269K? MSPPS Land Rain Rate No Yes TB 54L < Cold Snow*? *Note: Cold Snow is 240 or 245 K Yes No TB 89 - TB 150 >4 ? No Precipitat ion Yes TB 176 < 255 and TB 180 < 253 and TB 182 <250? Yes TB 176 > 255 and TB 180 < 253 and TB 23 <262? No TB 150 -TB 176 > -16 and TB 176 -TB 180 > -3 and TB 89 -TB 150 <10 ? Yes No Precipitat ion= MSPPS Rain Rate Value Precipitat ion Is Indetermi nate Snow Is Falling No Yes

31. 25-28 October 2004 2nd IPWG Monterey, CA January 2004 – Snowfall Frequency ALG245 ALG240 x x x x x x

32. 25-28 October 2004 2nd IPWG Monterey, CA CONUS Validation Statistics ALG245ALG240ALG245ALG240ALG245ALG240 CXY ROA MIT POD0.480.520.690.640.170.07 FAR0.170.200.000.070.000.25 TS0.440.460.690.610.170.07 ETS0.410.430.680.590.160.05 HSS0.94 0.980.970.950.87

33. 25-28 October 2004 2nd IPWG Monterey, CA Summary/Limitations Algorithm Performance –Can detect snowfall associated with synoptic scale systems –Low false alarms –Can increase region of application by lowering TB 54L threshold up to 5 K Some increase in false alarms Limitations –Relative moist atmospheres - -5 to 0 C –Southern extent of snow pack/temperate latitudes –Precip layer needs to extend to ~4-5 km or higher –No signal in extreme cold climate regimes and shallow snow

34. 25-28 October 2004 2nd IPWG Monterey, CA Future Near term algorithm improvements –FOV issues – L3 nadir equivalent product –Coastlines –Incorporation of CLW into ocean (1DVar) –Snowfall rates; land & ocean Longer term –1DVar, including land surface emissivity (with JCSDA) –Climate regime classification –Snowfall rates Upcoming launches –NOAA-N (Feb 05) MHS replaces AMSU-B –METOP-1 (Jan 06?) Pipeline processing Continued interactions with NASA and international partners on GPM –NOAA funds FY08?