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 RadiometersTRMM/TMI from JAXAAqua/AMSR-E from JAXA (not included yet)

Infrared RadiometersGlobal 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.

11.4 μm Geo IR1 hour before

10.8 μm Geo IRPresent

11.4 μm Geo IRPresent

Infrared (IR) Data

Microwave Radiometer (MWR) Data

1 hr Moving Vector

GSMaP Data

Split Window

GSMaPPresent

GSMaP1 hour before

1 hr MWRPresent

Algorithm outflow

Predicted GSMaP

Typhoon JELAWAT

地域　：　太平洋北部

ＴＲＭＭ観測数　：　１２

Correlation between radar and the GSMaP product Correlation between radar and the GSMaP product as a function of the past microwave satellite as a function of the past microwave satellite overpassoverpass

0

0.10.2

0.30.4

0.5

0.60.7

0.8

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14Time (hour)

Corre

lation

coeffi

cient

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 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)

Radar rain gauge analysis in Japan

Current StatusBeth 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.