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)
Algorithm inputs

Microwave Radiometers
 TRMM/TMI
from JAXA
 Aqua/AMSR-E from JAXA (not included yet)

Infrared Radiometers
 Global
Merged Geo-IR from TSDIS
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.
Algorithm outflow
Infrared (IR) Data
10.8 μm Geo IR
Present
Split Window
11.4 μm Geo IR
Present
11.4 μm Geo IR
1 hour before
1 hr Moving Vector
Microwave Radiometer (MWR) Data
Predicted GSMaP
1 hr MWR
Present
GSMaP Data
GSMaP
1 hour before
GSMaP
Present
Typhoon JELAWAT
地域 ： 太平洋北部
ＴＲＭＭ観測数 ： １２
Correlation between radar and the GSMaP product
as a function of the past microwave satellite
overpass
0.8
Correlation coefficient
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
1
2
3
4
5
6
7
8
Time (hour)
9
10 11 12 13 14
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.
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.
Algorithm output information


Spatial resolution
Spatial coverage





-35 to 35 in latitude (TMI only)
-60 to 60 in latitude (TMI + AMSR-E)
Update frequency
Date latency

1 hour
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


0.1 degree
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)
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.