use of humidity data from mt and other platforms for science projects on monsoon cloud systems...

Use of Humidity data from MT and other platforms for

Science projects on

Monsoon Cloud systems

KUSUMA G RAOSpace Sciences

Indian Space Research Organization Bangalore, India

“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

Cloudiness - Precipitation organization

during

Southwest Monsoon Season

“Impact of Humidity variations”

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 resolution2. TRMM PR (Precipitation radar) Rain 3. NCEP Re-Analysis, 4. PW from SSMI5. Temp and Hum profiles from Radiosonde 1999 &1998

75 85EArea AverageIRBRT > 270K Break< 270K Active

Active1: 10-24 JuneBreak: 26 June-4 JulyActive2:9 July-10 AugIMD Break:20 June-4 July

25N

15

Kusuma Rao, M Desbois, R Roca, K Nakamura, GRL, 2004

Spatial cloud pictures

TRMM pictures on ran and sampling Active

Days=48

In 1999

Active spells

10-24 June

9 July-10 Aug

Break:

26 June-4

JulyKusuma Rao and K Nakamura

Active

Days=48

In 1999

Active

Days=38

In 1998

Active spells

26 June-6 July

2-27 Aug

Break:

13 - 19 July

Active

Days=38

Active

spells

26 June-6 July

2-27 Aug

Break:

13 - 19 July

Break

Days=18

Break:

26 June-6 July, 1999

13 - 19 July,

1998

Deep clouds like to travel 100~1000 km per day, both over land and ocean

“Y” pattern“X” pattern

Webster et al, 2002Ohsawa et al.,2000

Central India

Indian Ocean

Indian Ocean

Rain superimposed on cloud

Kusuma Rao and K Nakamura, GRL (Submitted)

Overlapping TRMM passesOn METEOSATCloudImageries

Kusuma Rao and K Nakamura, GRL (Submitted)

Latitudinal Variation of PR Rain rate, mm/hour

Averaged[75-80E]

Kusuma Rao and K Nakamura, GRL (Submitted)

Vertical Distribution of PR Rain rate, mm/hour

Averaged[75-80E]And overLatitudinalExtentOf each TRMM pass

Kusuma Rao and K Nakamura

TRMM PR METEOSAT

Kusuma Rao and K Nakamura

Near simultaneous Rain-Cloudiness association

Individual Cloud system

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

UTH derived from WV Brightness Temperatures

Schmetz et al, 1998

UTH is Mean HumidityBetween 600 to 200 mb

Drying sets inActiveSpell

Drying sets in Clear sky

Middle level clouds

Break

Kusuma Rao, M Desbois, R Roca, K Nakamura, GRL, 2004

Active

Number of Clear Sky Pixels

Transition to Clear SkyDrying Sets In

PRECIPITABLE WATER

Data Source: NCEP for land SSMI for Sea

Drying sets in

Break phaseActive phases

NCEP Humidity Profiles

Impact of Vertical Humidity Distribution on Precipitation

“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” (13.5N, 79.2E) East coast of southern Indian Peninsula

Investigators: Kusuma G Rao P B Rao A R Jain S C Chakravarty

GADANKI

ISRO LABORATORY“National Atmospheric Research Laboratory”Indian MST RadarWind ProfilerLidarDisdrometerOptical Rain GaugeAutomated Weather System

Specific Humidity distribution, 17 July-14 August

METEOSATBrightness Temperatures

Rain rate, from ORG

Gadanki

RADIO OCCULTATION TECHNIQUEThe GPS technology is anActive system A receiver on a Low EarthOrbit 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 transmitterand an orbiting receiver, as it traverses the Earth’s atmosphere, getsrefracted primarily by the vertical gradient of atmospheric refractivity. From the Doppler shift in the refracted wave, the bending angle can be derived

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

COSMIC Global Coverage

Typical Daily COSMIC Soundings- in Green,Locations of Radiosondes- in RedGlobal Snapshots with ~ 4000 profiles per day

Anthes, Rocken, Kuo, Special issue on COSMIC of Terrestrial, Atmospheric and Oceanic Sciences.

Constellation of8 LEO’s

Megha-Tropiques Coverage

M.R.Sivaraman, SAC, Ahmedabad

Advanced Microwave Sounding Unit (AMSU)

AMSU-A Operate on board NOAAAMSU-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

Clay B. Blankenship*, Edward Barker, and Nancy L. Baker NRL, Monterey,California

Naval Research Laboratory, Monterey,California

Bakground: Navy Operational Global Atmospheric Prediction System1-D variational retrievals of humidityProfiles ( Clouds are turned off)

Observed GOES 6.7 μmTB’s for 12 March 2004

Simulated TB’s from NOGAPS background and retrievals relative to GOES Obs TB’s

Simulated 6.7 μm TB’sAt 15:00 UTC

From a retrieved atmosphere usingRTTOV-7 forward model (No clouds)

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

Zonal mean specific humidity difference, Control - AMSU-B

ITCZ is more moist

Drier Sub tropics

Addition of AMSU-B Observations strengthens model moistureGradients, counteracting the model tendency to smooth out moisture

Clay B. Blankenship*, Edward Barker, and Nancy L. Baker

Location Error over a Number of forecasts ~106 at 24 hours to32 at 120 hoursReduced by an average of 6.9 %

Central PressureErrorReduced by 1.24 mbOn average

Validated against Best tracks reported byJoint Typhoon Warning Center and National Hurricane Center

Tropical Cyclone Simulation

GENESIS & PROPAGATION CHARECTERISTICS OF

DEEP CLOUDS

ACCURATE HUMIDITY MEASUREMENTSPARTICULARLY over OCEANS

Is Megha-Tropiques the Solution?Thank you

Profiles of Area Average Humidity based on NCEP data

Dry Midtroposphere

NCEP Data

Break

Active

Clear Sky Non-Precipitating cumulus Precipitating cumulus

Intense rain after launch