1. Use of Humidity data from MT and other platforms for Science projects on Monsoon Cloud systems KUSUMA G RAO Space Sciences Indian Space Research Organization Bangalore, India

2. “Life Cycle of Tropical Cloud Systems” Indian Monsoon Variability as “manifestation” of the life cycle of these Tropical cloud systems. Tropical Cloud  Mesoscale  Monsoon Systems Convective Systems Variability Horizontal Scale: Ten’s of kilometers to several hundreds Life span: several hours to ~2 days “Quasi permanent feature” observed every year Quasi-biennial Interannual Intra-seasonal-Active and Break Spells(4~25 Days) Bi-weekly 3~5 Days

3. Cloudiness - Precipitation organization during Southwest Monsoon Season “Impact of Humidity variations”

4. DATA: METEOSAT measurements-- IR channel in the window region 10.5--12.5  m WV channel at 6.3μm 5x5km resolution, 1/2 hourly time interval 2.UTH (Upper Tropospheric Humidity)- at every hour, 150x150 km resolution 2.TRMM PR (Precipitation radar) Rain 3.NCEP Re-Analysis, 4.PW from SSMI 5.Temp and Hum profiles from Radiosonde 1999 &1998

5. 75 85E Area Average IRBRT > 270K Break < 270K Active Active1: 10-24 June Break: 26 June-4 July Active2: 9 July-10 Aug IMD Break: 20 June-4 July 25N 15 Kusuma Rao, M Desbois, R Roca, K Nakamura, GRL, 2004

6. Spatial cloud pictures

9. TRMM pictures on ran and sampling Active Days=48 In 1999 Active spells 10-24 June 9 July-10 Aug Break: 26 June-4 July Kusuma Rao and K Nakamura

10. Active Days=48 In 1999

11. Active Days=38 In 1998 Active spells 26 June-6 July 2-27 Aug Break: 13 - 19 July

12. Active Days=38 Active spells 26 June-6 July 2-27 Aug Break: 13 - 19 July

13. Break Days=18 Break: 26 June-6 July, 1999 13 - 19 July, 1998

15. Deep clouds like to travel 100~1000 km per day, both over land and ocean “Y” pattern “X” pattern Webster et al, 2002 Ohsawa et al.,2000 Central India Indian Ocean

16. Rain superimposed on cloud Kusuma Rao and K Nakamura, GRL (Submitted) Overlapping TRMM passes On METEOSAT Cloud Imageries

17. Kusuma Rao and K Nakamura, GRL (Submitted) Latitudinal Variation of PR Rain rate, mm/hour Averaged [75-80E]

18. Kusuma Rao and K Nakamura, GRL (Submitted) Vertical Distribution of PR Rain rate, mm/hour Averaged [75-80E] And over Latitudinal Extent Of each TRMM pass

19. Kusuma Rao and K Nakamura

20. TRMM PR METEOSAT Kusuma Rao and K Nakamura Near simultaneous Rain-Cloudiness association Individual Cloud system

21. Impact of Humidity variations on Monsoon Convection Monsoon Variability on “Active” and “Break” spells “Individual transitions from Active to Break conditions and Vice Versa” -------MORE COMPLEX

23. UTH derived from WV Brightness Temperatures Schmetz et al, 1998 UTH is Mean Humidity Between 600 to 200 mb

24. Drying sets in Active Spell Drying sets in Clear sky Middle level clouds Break Kusuma Rao, M Desbois, R Roca, K Nakamura, GRL, 2004

25. Active Number of Clear Sky Pixels Transition to Clear Sky Drying Sets In

26. PRECIPITABLE WATER Data Source: NCEP for land SSMI for Sea Drying sets in

27. Break phase Active phases NCEP Humidity Profiles

28. Impact of Vertical Humidity Distribution on Precipitation

29. “A Special Experiment: Convection in Asian Monsoon System (CAMS–98)” 17 July- 14 August Under the International GAME Programme MST Radar Facility at station “GADANKI” (13.5  N, 79.2  E) East coast of southern Indian Peninsula Investigators: Kusuma G Rao P B Rao A R Jain S C Chakravarty

30. GADANKI ISRO LABORATORY “National Atmospheric Research Laboratory” Indian MST Radar Wind Profiler Lidar Disdrometer Optical Rain Gauge Automated Weather System

31. Specific Humidity distribution, 17 July-14 August METEOSAT Brightness Temperatures Rain rate, from ORG

32. Gadanki

33. RADIO OCCULTATION TECHNIQUE The GPS technology is an Active system A receiver on a Low Earth Orbit satellite measures the coherent GPS signals in the two carrier frequencies, L1 = 1575.42 MHz, L2 = 1227.6 MHz broadcasted fromGPS satellites. In radio occultation, the radio path between an orbiting transmitter and an orbiting receiver, as it traverses the Earth’s atmosphere, gets refracted primarily by the vertical gradient of atmospheric refractivity. From the Doppler shift in the refracted wave, the bending angle can be derived

34. Inter-comparison between GPS/MET and Other measurements Anthes, Rocken, Kuo, Special issue on COSMIC of Terrestrial, Atmospheric and Oceanic Sciences +/- 1 K, green >1 K, red < -1 k, blue

35. COSMIC Global Coverage Typical Daily COSMIC Soundings- in Green, Locations of Radiosondes- in Red Global Snapshots with ~ 4000 profiles per day Anthes, Rocken, Kuo, Special issue on COSMIC of Terrestrial, Atmospheric and Oceanic Sciences. Constellation of 8 LEO’s

36. Megha-Tropiques Coverage M.R.Sivaraman, SAC, Ahmedabad

37. Advanced Microwave Sounding Unit (AMSU) AMSU-A Operate on board NOAA AMSU-B Satellites since 1998 AMSU-A 12 Channels close to the Oxygen band below 60 GH Z 4 window channels 23.8, 31.4, 50.3, 89 GH Z Resolution at nadir ~ 48 km AMSU-B 3 Channels at 183.31 ±1, 3, 7 GH Z, centered around Water Vapour line, 2 window channels 89 and 150 GH Z Resolution at nadir ~ 16 km

38. Clay B. Blankenship *, Edward Barker, and Nancy L. Baker NRL, Monterey,California Naval Research Laboratory, Monterey, California Bakground: Navy Operational Global Atmospheric Prediction System 1-D variational retrievals of humidity Profiles ( Clouds are turned off) Observed GOES 6.7 μm TB’s for 12 March 2004 Simulated TB’s from NOGAPS background and retrievals relative to GOES Obs TB’s Simulated 6.7 μm TB’s At 15:00 UTC From a retrieved atmosphere using RTTOV-7 forward model (No clouds)

39. NAVDAS- NRL Atmospheric Data Assimilation System: The retrieved humidity profiles are assimilated in to NOGAPS NOAA-16 & 17, ~ 9000 profiles at ~9 layers from 1005 to 122 mb Per update cycle Rejections: Data over land, coast, sea ice, heavy cloud and precipitation scenes At 400 mb Control- AMSU-B For Sept 2003 AMSU-B is Drier in middle & upper levels

40. Zonal mean specific humidity difference, Control - AMSU-B ITCZ is more moist Drier Sub tropics Addition of AMSU-B Observations strengthens model moisture Gradients, counteracting the model tendency to smooth out moisture

41. Clay B. Blankenship *, Edward Barker, and Nancy L. Baker Location Error over a Number of forecasts ~106 at 24 hours to 32 at 120 hours Reduced by an average of 6.9 % Central Pressure Error Reduced by 1.24 mb On average Validated against Best tracks reported by Joint Typhoon Warning Center and National Hurricane Center Tropical Cyclone Simulation

42. GENESIS & PROPAGATION CHARECTERISTICS OF DEEP CLOUDS ACCURATE HUMIDITY MEASUREMENTS PARTICULARLY over OCEANS Is Megha-Tropiques the Solution? Thank you

44. Profiles of Area Average Humidity based on NCEP data Dry Midtroposphere NCEP Data Break Active

48. Clear Sky Non-Precipitating cumulus Precipitating cumulus Intense rain after launch