Global Satellites Mapping of Precipitation Project in Japan GSMaP Microwave and Infrared combined al

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Global Satellites Mapping of Precipitation
Project in Japan(GSMaP)- Microwave and Infrared
combined algorithm -

• K. Okamoto, T. Ushio, T. Iguchi, N.
  Takahashi...../ Tomoo Ushio (Osaka Prefecture
  University)

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Algorithm inputs

• Microwave Radiometers
• TRMM/TMI from JAXA
• Aqua/AMSR-E from JAXA (not included yet)
• Infrared Radiometers
• Global Merged Geo-IR from TSDIS

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What, When, Where, and How do we analyze for?

• Purpose To draw the global precipitation map
  with 0.1 degree/1 hour resolution
• What 1hour global IR data from Goddard/DAAC
  and TMI/2A12 data
• When August 1 to 10, 2000
• Where -35 to 35 in latitude, 0 to 360 in
  longitude
• How By interpolating precipitation between
  TMI overpasses using the cloud motion
  inferred from 1 hour IR Tb.

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Algorithm outflow

Infrared (IR) Data
10.8 µm Geo IR Present
Split Window
11.4 µm Geo IR Present
1 hr Moving Vector
11.4 µm Geo IR 1 hour before
Microwave Radiometer (MWR) Data
Predicted GSMaP
1 hr MWR Present
GSMaP Data
GSMaP Present
GSMaP 1 hour before
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Typhoon JELAWAT
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Correlation between radar and the GSMaP product
as a function of the past microwave satellite
overpass
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Strength and weakness of underlying assumptions

• Strength
• We mainly use the MWR data which is proved to be
  excellent for rainfall estimation.
• Fast processing time (About 3 min.) for the real
  time operations
• Weakness
• Physically simple. (We do not think any phase
  change or so.)
• Only TRMM/TMI is used.
• Not use the backward process, resulting in large
  error.
• Moving vector is not validated at all.
• Any validations have not yet being done at all.

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Planned modifications/ Improvements

• Current to short term
• Introduce AMSR-E in addition to TRMM/TMI by the
  Aonashi algorithm
• Apply the Kalman filtering technique to adjust
  the interpolated precipitation rate between the
  microwave passes.
• Long term
• Apply the split window method by Inoue (1999)
• Introduce SSM/I (F13, 14, 15)
• Validation through the comparison with the
  radar-rain gauge network in Japan
• Cross comparison with another precipitation map
• Input to the global circulation model.

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Algorithm output information

• Spatial resolution 0.1 degree
• Spatial coverage
• -35 to 35 in latitude (TMI only)
• -60 to 60 in latitude (TMI AMSR-E)
• Update frequency 1 hour
• Date latency
• Our product is just made, and it is not
  operational now.
• Source of real time data/ Source of archive data
• Microwave Radiometers
• TRMM/TMI from JAXA
• Aqua/AMSR-E from JAXA
• Infrared Radiometers
• Global Merged Geo-IR from TSDIS
• Capability of producing retrospective data (data
  and resources required/ available)
• Currently we would go back to the 1998 (TRMM era)

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Radar rain gauge analysis in Japan

• Current Status
• Beth gave us the IDL code to process.
• My student, Mr. Yasuhida Iida, read the code and
  made some small modification.
• He could successfully draw the map for
  intercomparison.

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