Notes for reprocessing in
GSMaP version05/Algorithm version8
Japan Aerospace Exploration Agency (JAXA)
Earth Observation Research Center (EORC)

July 2023

Notes for reprocessing in
GSMaP version05/Algorithm version8
GSMaP had a major update in Dec. 2021 (version05/Algorithm version8), andre-processing of the GSMaP products was completed in July 2023.
Past GSMaP products did not cover the first 2 years of TRMM era (1998-Mar.
2000) due to lack of CPC-4km Global IR dataset (Janowiak et al. 2001).
In the new version of the GSMaP, GridSat-B1 data (Knapp et al. 2011) wereused to fill the lack of period as follows (Kubota et al. 2023).
GridSat-B1 during a period from Jan. 1998 to Jan. 2000
GridSat-B1 & CPC-4km during Feb. 2000
CPC-4km after Mar. 2000
GSMaP data using the GridSat-B1 (1998-2000) have not been fully evaluatedyet, and users need to be cautious about them.
•••Janowiak J. E., R. J. Joyce, and Y. Yarosh, 2001: A Real-Time Global Half-hourly Pixel-Resolution Infrared Dataset and Its Applications. (Bull. Amer. Meteor. Soc., vol.
82, No.3., 205-217.)
Knapp, K. R., S. Ansari, C. L. Bain, M. A. Bourassa, M. J. Dickinson, C. Funk, C. N. Helms, C. C. Hennon, C. D. Holmes, G. J. Huffman, J. P. Kossin, H.-T. Lee, A. Loew, andG. Magnusdottir, 2011: Globally gridded satellite (GridSat) observations for climate studies. Bulletin of the American Meteorological Society, 92, 893907. doi:10.1175/2011BAMS3039.1
Kubota, T., M. K. Yamamoto, and M. Yamaji, 2023: Reprocessing of Global Satellite Mapping of Precipitation (GSMaP) Product, AOGS2023, AS02-A019, Singapore.

2

Data Specifications

No Indian Ocean Data Coverage(~Jul. 1998)

CPC-4km

GridSatSpatial Resolution

0.036 deg (~4 km)

0.07 deg (~8km)

Temporal Resolution

30 min

180 min

Channels

IR (11 μm)

IR (11 μm)
WV (6.7 μm)
VIS (0.6 μm)

Period of record

Early-Feb. 2000-present

Jan. 1981-present

Coverage

60N to 60S

70N to 70S

Scale

1K

0.01 KIntersatellite
normalization

Yes

Yes

Temporal normalization

No

Yes

Format

Unformatted binary

netCDF

Reference

Janowiak et al. (2001, BAMS)

Knapp et al. (2011, BAMS)

Target period (1998-2000)

TRMM era (after 2000)(ISCCP & HIRS calibration)

GPM eraModified Knapp et al. (2011, BAMS)
International Satellite Cloud Climatology Project (ISCCP) B1 Data | National Centers for Environmental Information (NCEI) (noaa.gov)

3Flowchart of Blended MWR-IR algorithm(GSMaP_MVK algorithm)
Ushio et al. (2009)

GEO IR data
Zonal

Present IR
Cloud motion vectors

1-hour-before IR

CPC IR
30 min → 60 min
Use data at 30 min of
every hour.
If no data pixel isfound, the pixel isreplaced with 0 mindata.

Meridional

Past GSMaP data
1-hour-before GSMaP

GSMaP interpolatedby the motion vectors

Kalman filter
Present MWR data

(Outsides MWR overpasses)

MWR data observed during present 1 hour

(MWR overpasses)
PresentGSMaP

GridSat-B1Format conversion toCPC-4km(bilinearinterpolation)
netCDF → binary
0.01 K → 1 K
7 km → 4 km
180 min → 60 min

4CPC 4km and GridSat-B1 (IR Image & motion vector)

5

Discussion
There are so many papers related to large discrepancies between TRMM
Precipitation Radar (PR) and TRMM Microwave Imager (TMI) (e.g., Berg et al.,2002, 2006, Robertson et al. 2003, Shige et al. 2008) during the 1997/1998 El Niño
event.
Fig. 7 of Shige et al. 2008

Shige, S., Watanabe, T., Sasaki, H., Kubota, T., Kida, S., and Okamoto, K. (2008), Validation of western and eastern Pacific rainfall estimates from the TRMM PR
using a radiative transfer model, J. Geophys. Res., 113, D15116, doi:10.1029/2007JD009002.

This may be also connected with a year of 1998 by the GSMaP.

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