Use of Humidity data from MT and other platforms for Science projects on Monsoon Cloud systems

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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
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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 Tens 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(425
  Days)
• Bi-weekly
• 35 Days

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Cloudiness - Precipitation organizationduringSo
uthwest Monsoon Season Impact of Humidity
variations
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• 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
• UTH (Upper Tropospheric Humidity)-
• at every hour, 150x150 km resolution
• TRMM PR (Precipitation radar) Rain
• NCEP Re-Analysis,
• PW from SSMI
• Temp and Hum profiles from Radiosonde
• 1999 1998

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25N 15
75 85E Area Average IRBRT gt
270K Break lt 270K Active Active1 10-24
June Break 26 June-4 July Active2 9 July-10
Aug IMD Break 20 June-4 July
Kusuma Rao, M Desbois, R Roca, K Nakamura, GRL,
2004
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Spatial cloud pictures
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TRMM pictures on ran and sampling
Active Days48 In 1999 Active spells 10-24
June 9 July-10 Aug Break 26 June-4
July
Kusuma Rao and K Nakamura
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Active Days48 In 1999
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Active Days38 In 1998 Active spells 26 June-6
July 2-27 Aug Break 13 - 19 July
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Active Days38 Active spells 26 June-6
July 2-27 Aug Break 13 - 19 July
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Break Days18 Break 26 June-6 July, 1999 13 -
19 July, 1998
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Central India
Webster et al, 2002 Ohsawa et al.,2000
Indian Ocean
X pattern
Y pattern
Indian Ocean
Deep clouds like to travel 1001000 km per day,
both over land and ocean
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Rain superimposed on cloud
Overlapping TRMM passes On METEOSAT Cloud Imageri
es
Kusuma Rao and K Nakamura, GRL
(Submitted)
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Kusuma Rao and K Nakamura, GRL
(Submitted)
Latitudinal Variation of PR Rain rate, mm/hour
Averaged 75-80E
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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
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Kusuma Rao and K Nakamura
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TRMM PR METEOSAT
Near simultaneous Rain-Cloudiness
association Individual Cloud system
Kusuma Rao and K Nakamura
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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
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UTH derived from WV Brightness Temperatures
UTH is Mean Humidity Between 600 to 200 mb
Schmetz et al, 1998
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Middle level clouds
Drying sets in
Clear sky
Break
Active Spell
Drying sets in
Kusuma Rao, M Desbois, R Roca, K Nakamura, GRL,
2004
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Number of Clear Sky Pixels
Transition to Clear Sky
Drying Sets In
Active
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PRECIPITABLE WATER
Drying sets in
Data Source NCEP for land
SSMI for Sea
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NCEP Humidity Profiles
Break phase
Active phases
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Impact of Vertical Humidity Distribution on
Precipitation
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A Special Experiment Convection in Asian
Monsoon System (CAMS98) 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
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ISRO LABORATORY National Atmospheric Research
Laboratory Indian MST Radar Wind
Profiler Lidar Disdrometer Optical Rain
Gauge Automated Weather System
GADANKI
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Specific Humidity distribution, 17 July-14 August
METEOSAT Brightness Temperatures Rain rate,
from ORG
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Gadanki
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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 Earths 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
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• /- 1 K, green
• gt1 K, red
• lt -1 k, blue

Inter-comparison between GPS/MET and Other
measurements Anthes, Rocken, Kuo, Special issue
on COSMIC of Terrestrial, Atmospheric and
Oceanic Sciences
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COSMIC Global Coverage
Constellation of 8 LEOs
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.
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Megha-Tropiques Coverage
M.R.Sivaraman, SAC, Ahmedabad
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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 GHZ 4
window channels 23.8, 31.4, 50.3, 89GHZ
Resolution at nadir 48
km AMSU-B 3 Channels at 183.31 1,
3, 7 GHZ, centered
around Water Vapour line,
2 window channels 89 and 150
GHZ Resolution at nadir 16 km
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Clay B. Blankenship, Edward Barker, and Nancy
L. Baker NRL, Monterey,California
Observed GOES 6.7 µm TBs for 12 March 2004
Naval Research Laboratory, Monterey,California Ba
kground Navy Operational Global Atmospheric
Prediction System 1-D variational retrievals of
humidity Profiles ( Clouds are turned off)
Simulated TBs from NOGAPS background and
retrievals relative to GOES Obs TBs
Simulated 6.7 µm TBs At 1500 UTC
From a retrieved atmosphere using RTTOV-7 forward
model (No clouds)
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NAVDAS- NRL Atmospheric Data Assimilation System
The retrieved humidity profiles are assimilated
in to NOGAPS
At 400 mb Control- AMSU-B For Sept 2003 AMSU-B
is Drier in middle upper levels
Rejections Data over land, coast, sea ice,
heavy cloud and precipitation scenes
NOAA-16 17, 9000 profiles at 9 layers from
1005 to 122 mb Per update cycle
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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
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Clay B. Blankenship, Edward Barker,
and Nancy L. Baker
Tropical Cyclone Simulation
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

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GENESIS PROPAGATION CHARECTERISTICS OF DEEP
CLOUDS ACCURATE HUMIDITY MEASUREMENTSPARTICULA
RLY over OCEANSIs Megha-Tropiques the
Solution?Thank you
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Profiles of Area Average Humidity based on NCEP
data
Active
Dry Midtroposphere NCEP Data
Break
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Clear Sky Non-Precipitating cumulus
Precipitating cumulus
Intense rain after launch