1. CHARACTERIZATION OF INTER-SATELLITE DIFFERENCES IN RETRIEVED RAINFALL Dr. F. Joseph (Joe) Turk Naval Research Laboratory, Marine Meteorology Division Monterey, CA 93943 (831)-656-4888 turk@nrlmry.navy.mil Third IPWG Workshop Melbourne, Australia 23-27 October 2006

2.  In light of program changes, launch delays, etc, the future microwave (MW) sensor suite likely to be composed of different sensor types (as it is today)  Radar/radiometer, different channels on MW radiometers, conical & cross track scanning instruments, spatial resolutions, etc.  Retrieved rainfall characteristics likely to be different between sensors – varying as a function of rainfall rate, latitude, season, background, etc.  Combining MW sensors is an ongoing research topic for GPM (in radiance space and rainfall space)  Data assimilation techniques may assimilate “rainy radiances” from a suite of inter-calibrated MW sensors; however,  High Resolution Precipitation Products (HRPP) will need to blend/merge these sets of disparate observations Inter-Sensor Rainfall Characteristics

3. PEHRPP Suite 4: "Big picture" comparisons (coordinator: ?) Catch any artifacts not noticed in detailed statistics of above suites Catch any artifacts not noticed in detailed statistics of above suites obvious systematic changes on a latitude line, related to availability of certain data typesobvious systematic changes on a latitude line, related to availability of certain data types changes in time series, related to data availabilitychanges in time series, related to data availability Validation of large-scale quantities and characteristics against bulk quantities, existing products (GPCP, CMAP, etc.), streamflow data sets, water budgets, and subjective judgment Validation of large-scale quantities and characteristics against bulk quantities, existing products (GPCP, CMAP, etc.), streamflow data sets, water budgets, and subjective judgment Focus on thousands of kilometers and monthly time scales Focus on thousands of kilometers and monthly time scales

4. LOCAL OBSERVATION TIMES OF DMSP and NOAA SATELLITES NOAA Satellites as of Late 2006 Ascending Descending 0 6 12 18 NOAA-15 NOAA-16 NOAA-18 NOAA-17 DMSP Satellites as of Late 2006 Ascending Descending 0 6 12 18 F-14 F-13 F-16 F-15

5. Dataset Preparation  Nearly three years (2004-current) of DMSP, NOAA, TRMM (WindSat since 6/06, Aqua since 4/05, F-16 since 2/06, NOAA-18 since 11/05)  From each orbit file, rain histogram is binned by date, latitude and surface (0.2 mm hr -1 steps)  First step is to analyze up-front rain/no-rain screening differences amongst various sensors  Second step is to analyze (non-zero) light rain differences

6. Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S Middle Latitudes Rain/No-Rain Discrimination

7. Rain Detection - Middle Latitudes - Over Ocean DMSP F-13, F-14, F-15 (SSMI), F-16 (SSMIS) Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND F-13 (SSMI) F-14 (SSMI) F15 (SSMI) F-16 (SSMIS) winter summer More “no-rain” events in summer seasons SSMI’s well matched SSMIS flags more no-rain values in both hemispheres F-15 RADCAL issue apparent after mid-August 2006 summer winter

8. Rain Detection - Middle Latitudes - Over Ocean TRMM-TMI/PR, Aqua-AMSR-E, Coriolis-WindSat Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND TRMM (PR) TRMM (TMI) Aqua (AMSR-E) Coriolis (WindSat) winter summer PR has about 2-3% more no- rain events than TMI TMI & AMSR-E well matched WindSat lacks 85 GHz capability which improves rain screening summer winter

9. Rain Detection - Middle Latitudes - Over Ocean NOAA-15, NOAA-16, NOAA-17 (AMSU), NOAA-18 (MHS) Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND NOAA-15 (AMSU) NOAA-16 (AMSU) NOAA-17 (AMSU) NOAA-18 (MHS) winter summer Seasonality signal not well represented at high latitudes AMSU and MHS well- matched Slight differences likely due to AM and PM crossing time difference summer winter

10. The Problem At the direction of US Strategic Command (USSTRATCOM) and in coordination with the NPOESS IPO-ADO for DMSP operations, the satellite operations control center activated the radar calibration (RADCAL) suite on DMSP F15, August 14, 2006. The RADCAL beacon operates at 150MHz & 400 MHz. On-orbit testing conducted in August 2005, confirmed that transmissions from the RADCAL 150Mhz Beacon produced interference in the SSMI 22GHz vertical polarization (22V) channel and that the 400Mhz Beacon interfered with SSMT-2 channel 4 performance. The SSMT-2 on F15 has since been declared "red" or non-operational due to an unrelated component failure. Users of the SSMI data must be aware that the 22V channel used in, ocean surface wind speeds, snow classification and depth, and rain rate calculations, etc., will be dramatically degraded during RADCAL Beacon transmission

11. ChannelF-15 SSMI Mean T B F-16 SSMIS Mean T B F-15 SSMI Std Dev F-16 SSMIS Std Dev 19V198.7199.413.313.2 19H137.4136.920.520.3 22V237.5225.922.221.8 37V217.2217.710.09.9 37H162.6162.318.318.0 85V 91V*258.8259.112.8 85H 91H*231.3230.724.023.7 F-15 and F-16 Intercomparison (Post-RADCAL) 16 September 2006 Ocean-Only Center Beam Position Data courtesy of Gene Poe, NRL F-15 and F-16 synchronization: F-13: 1833 local F-14: 1758 local F-15: 2010 local F-16: 2012 local Good agreement at non-22 channels, max 0.7K difference However, the statistics are dominated by no- rain pixels (~ 95%) *85 GHz on SSMI, 91 GHz on SSMIS

12. DMSP F15-F16 22V Channel Statistics Pre-RADCAL 01-13 August 2006 DMSP F15-F16 22V Channel Statistics Post-RADCAL 15-28 August 2006 +/-70 Latitudes Over-Water F-15 RADCAL Beacon Activated 14 Aug 2006

13. Impacts of Radcal Beacon Interference on F15 SSM/I Products Saturated water vaporMissing clouds and precipitation

14. Scattering Index Conceptualized scattering materials: T v (22) > T v (85) precipitation, dry snow, aged sea ice, glacial ice, deserts absorbing materials: T v (22) < T v (85) clouds, melting snow, new sea ice, vegetation, wet soil 19 GHz 2285 shading denotes water vapor thermal emission 19 GHz 2285 (typical values) Material19V22V85V Precip over water240270< 240 Precip over land260 < 240 Dry Snow250240210 Clouds over land275 280 New sea ice250245255 Wet soil265270275 Warmer TB as frequency increases Colder TB as frequency increases 91 91 GHz scatters a little more than 85 GHz 91

15. Scattering Index Computation scattering materials: T v (22) > T v (85) precipitation, dry snow, aged sea ice, glacial ice, deserts absorbing materials: T v (22) < T v (85) clouds, melting snow, new sea ice, vegetation, wet soil Oceanic: SI85= (-174.4 + 0.715*TB19v + 2.439*TB22v - 0.00504*TB22v*TB22v) - TB85v Land: SI85= (451.9 - 0.44*TB19v - 1.775*TB22v + 0.00574*TB22v*TB22v) - TB85v Estimation of the non- scattering contribution of the 85 GHz measurements If SI85 > 10 then Rain ~ log(SI85) (after screens for ice, deserts, etc using polarization checks) SSMIS vs. SSMI: For scattering materials, 91 GHz scatters a bit more than 85 GHz For absorbing materials, 91 GHz emits (absorbs) more than at 85 GHz

16. Cyclone Xangsane F-15 SSMI 85H 25 minutes time separation Cyclone Xangsane F-16 SSMIS 91H SSMI-SSMIS High Frequency Channel Differences Most Pronounced Over Heavy Convection

17. Cyclone Xangsane F-15 SSMI 85H 34 minutes time separation Cyclone Xangsane F-16 SSMIS 91H SSMI-SSMIS High Frequency Channel Differences Most Pronounced Over Heavy Convection

18. Rain Detection - Middle Latitudes - Over Land DMSP F-13, F-14, F-15 (SSMI), F-16 (SSMIS) Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND F-13 (SSMI) F-14 (SSMI) F15 (SSMI) F-16 (SSMIS) winter summer More “no-rain” events in winter seasons SSMI’s well matched SSMI and SSMIS similar F-15 RADCAL issue apparent after mid-August 2006 summer winter

19. Rain Detection - Middle Latitudes - Over Land TRMM-TMI/PR, Aqua-AMSR-E, Coriolis-WindSat Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND TRMM (PR) TRMM (TMI) Aqua (AMSR-E) Coriolis (WindSat) winter summer Very similar to DMSP TMI “oscillation” likely due to sampling repeat cycle summer winter

20. Rain Detection - Middle Latitudes - Over Land NOAA-15, NOAA-16, NOAA-17 (AMSU), NOAA-18 (MHS) Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND NOAA-15 (AMSU) NOAA-16 (AMSU) NOAA-17 (AMSU) NOAA-18 (MHS) winter summer 2-3% less no-rain events than DMSP shows NOAA-17 crossing time difference evident NOAA-15: 1736 local NOAA-16: 1526 local NOAA-17: 2219 local NOAA-18: 1343 local summer winter

21. Northern Hemisphere 10N-20N Southern Hemisphere 20S-10S Sub-Tropical Latitudes Rain/No-Rain Discrimination

22. Rain Detection – Sub Tropics - Over Ocean DMSP F-13, F-14, F-15 (SSMI), F-16 (SSMIS) Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND F-13 (SSMI) F-14 (SSMI) F15 (SSMI) F-16 (SSMIS) winter summer More “no-rain” events in winter-spring seasons SSMI’s well matched except F-15 post-RADCAL SSMIS flags more no-rain values in both hemispheres summer winter

23. Rain Detection – Sub Tropics - Over Ocean TRMM-TMI/PR, Aqua-AMSR-E, Coriolis-WindSat Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND TRMM (PR) TRMM (TMI) Aqua (AMSR-E) Coriolis (WindSat) winter summer PR and TMI are closer than they are in mid latitudes TMI & AMSR-E well matched WindSat screening better in sub-tropics than in mid- latitudes summer winter

24. Rain Detection – Sub Tropics - Over Ocean NOAA-15, NOAA-16, NOAA-17 (AMSU), NOAA-18 (MHS) Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S winter summer NOAA datasets begin to show some seasonality and are well-matched About 3% more no-rain pixels flagged relative to TMI summer winter COLOR LEGEND NOAA-15 (AMSU) NOAA-16 (AMSU) NOAA-17 (AMSU) NOAA-18 (MHS)

25. Northern and Southern Hemispheres 5S-5N Tropical Latitudes Rain/No-Rain Discrimination

26. Rain Detection – Tropics - Over Ocean DMSP F-13, F-14, F-15 (SSMI), F-16 (SSMIS) COLOR LEGEND F-13 (SSMI) F-14 (SSMI) F15 (SSMI) F-16 (SSMIS) SSMI’s well matched SSMIS flags more no-rain values in both hemispheres F-15 RADCAL issue apparent after mid-August 2006

27. Rain Detection – Tropics - Over Ocean TRMM-TMI/PR, Aqua-AMSR-E, Coriolis-WindSat COLOR LEGEND TRMM (PR) TRMM (TMI) Aqua (AMSR-E) Coriolis (WindSat) PR and TMI are closer than they are in mid latitudes TMI & AMSR-E well matched WindSat screening gradually improves moving from mid- latitudes to the tropics

28. Rain Detection – Tropics - Over Ocean NOAA-15, NOAA-16, NOAA-17 (AMSU), NOAA-18 (MHS) About 3% more no-rain pixels flagged relative to TMI COLOR LEGEND NOAA-15 (AMSU) NOAA-16 (AMSU) NOAA-17 (AMSU) NOAA-18 (MHS)

29. Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S Middle Latitudes Light Rain Detection (Non-zero rain < 2 mm hr -1 )

30. Light Rain Detection - Middle Latitudes - Over Ocean DMSP F-13, F-14, F-15 (SSMI), F-16 (SSMIS) Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND F-13 (SSMI) F-14 (SSMI) F15 (SSMI) F-16 (SSMIS) winter summer SSMIS picks up about half as much “light rain” relative to the SSMI’s, in both hemispheres summer winter

31. Light Rain Detection - Middle Latitudes - Over Ocean TRMM-TMI/PR, Aqua-AMSR-E, Coriolis-WindSat Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND TRMM (PR) TRMM (TMI) Aqua (AMSR-E) Coriolis (WindSat) winter summer TMI and AMSR-E detect about twice as much rain in this interval relative to PR WindSat detects much more owing to a looser rain/no-rain screen Not sure about N-S hemisphere differences summer winter

32. Light Rain Detection - Middle Latitudes - Over Ocean NOAA-15, NOAA-16, NOAA-17 (AMSU), NOAA-18 (MHS) Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND NOAA-15 (AMSU) NOAA-16 (AMSU) NOAA-17 (AMSU) NOAA-18 (MHS) winter summer Little to no sensitivity to light rain over ocean at these latitudes (over land better) summer winter

33. Light Rain Detection - Middle Latitudes - Over Land DMSP F-13, F-14, F-15 (SSMI), F-16 (SSMIS) Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND F-13 (SSMI) F-14 (SSMI) F15 (SSMI) F-16 (SSMIS) winter summer SSMI’s well matched SSMI-SSMIS difference much smaller F-15 RADCAL issue more apparent over-land than over- ocean summer winter

34. Light Rain Detection - Middle Latitudes - Over Land TRMM-TMI/PR, Aqua-AMSR-E, Coriolis-WindSat Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND TRMM (PR) TRMM (TMI) Aqua (AMSR-E) Coriolis (WindSat) winter summer Slightly more light rain detected by PR than TMI No WindSat data over land summer winter

35. Light Rain Detection - Middle Latitudes - Over Land NOAA-15, NOAA-16, NOAA-17 (AMSU), NOAA-18 (MHS) Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND NOAA-15 (AMSU) NOAA-16 (AMSU) NOAA-17 (AMSU) NOAA-18 (MHS) winter summer Over land and at middle latitudes, AMSU/MHS light rain detection is very similar to DMSP summer winter

36. Northern and Southern Hemispheres 5S-5N Tropical Latitudes Heavy Rain Detection (Non-zero rain > 5 mm hr-1)

37. Heavy Rain Detection - Tropics - Over Ocean DMSP F-13, F-14, F-15 (SSMI), F-16 (SSMIS) Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND F-13 (SSMI) F-14 (SSMI) F15 (SSMI) F-16 (SSMIS) winter summer Difficult to assess- since even with a 30-day running average there are relatively few pixels > 5 mm hr -1 summer winter

38. Heavy Rain Detection - Tropics - Over Ocean TRMM-TMI/PR, Aqua-AMSR-E, Coriolis-WindSat Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND TRMM (PR) TRMM (TMI) Aqua (AMSR-E) Coriolis (WindSat) winter summer PR has about 2-3% more no- rain events than TMI TMI & AMSR-E well matched WindSat lacks 85 GHz capability which improves rain screening summer winter

39. Heavy Rain Detection - Tropics - Over Ocean NOAA-15, NOAA-16, NOAA-17 (AMSU), NOAA-18 (MHS) Northern Hemisphere 30N-40N Southern Hemisphere 40S-30S COLOR LEGEND NOAA-15 (AMSU) NOAA-16 (AMSU) NOAA-17 (AMSU) NOAA-18 (MHS) winter summer Seasonality signal not picked up at these latitudes AMSU and MHS well- matched Slight differences likely due to AM and PM crossing time difference summer winter

40. Summary  A rich “GPM” constellation exists today – employ current systems to address issues related to merging MW datasets  NESDIS algorithm for over-ocean high latitudes: Issues known and being improved – also should examine other AMSU-based algorithms  DMSP F-15 RADCAL issue: Radiance-level offset being characterized and a “fix” may be possible for precipitation datasets  Bring in light rain statistics from CloudSat - averaged across long timescales  May develop on improved SSMIS EDR suite after F-17 launch All of these topics are relevant to the GPM

41. F15 – F14 Differences For Two-Week Periods Before and After RADCAL Activation on 14 August 2006 Pre-RADCAL SDR differences being fixed

42. Passive Microwave Constellation Local Observation Times Jakarta, Indonesia (6.1S 106.8E)

43. Passive Microwave Constellation Revisit Times (Including NOAA Cross-Track Sounders) Jakarta, Indonesia (6.1S 106.8E) 6-Hour Level 6 (97%) 5 (94%) 4 (81%) 3 (52%) Percent of Year That Revisit Is Less Than (Hours): NOTE: Percent of year, not percent of total points

44. Passive Microwave Constellation Observation Times San Francisco, California (37.8N 122.4W)

45. Passive Microwave Constellation Revisit Times (Including NOAA Cross-Track Sounders) San Francisco, California (37.8N 122.4W) 6 (100%) 5 (98%) 4 (89%) 3 (69%) 6-Hour Level Percent of Year That Revisit Is Less Than (Hours): Aqua and NOAA-18 to the rescue

46. Passive Microwave Constellation Observation Times Helsinki, Finland (60.1N 25.0E) No TRMM Coverage

47. Passive Microwave Constellation Revisit Times (Including NOAA Cross-Track Sounders) Helsinki, Finland (60.1N 25.0E) No TRMM Coverage 6 (100%) 5 (97%) 4 (88%) 3 (81%) 6-Hour Level Percent of Year That Revisit Is Less Than (Hours):