PERSIANN 1°x1° TROPICAL RAINFALL DATA
6-Hourly, Daily, 5-Day, and Monthly Accumulations
80°E-10°W (270° Longitude), 35°S-35°N (70° Latitude)
August 1998 through July 1999
Product of NASA Funded Projects:
HyDIS, TRMM, and EOS IDS at
The Department of Hydrology and Water Resources
The University of Arizona
Tucson, AZ 85721
Principal Investigator: Soroosh Sorooshian
Co-PI's: Kuolin Hsu, Xiaogang Gao, Hoshin Gupta, and Bisher Imam
Contributors: David C. Goodrich, Shayesteh E. Mahani, Liming Xu, and Quanfu Fan
Product Development: Dan Braithwaite
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INTRODUCTION
This CD-ROM contains one full year (August 1, 1998 through July 31, 1999)
of tropical surface rainfall-rate estimates for the oceanic and continental
region encompassed by 80E-10W longitude and 35S-35N latitude. The estimates
(hereafter called "the data") are generated from remotely-sensed data from
multiple satellite sources-three geosynchronous satellites (GOES-8, GOES-10,
& GMS-5) and the EOS/TRMM satellite-by the PERSIANN system (Precipitation
Estimation from Remotely Sensed Information using Artificial Neural Networks)
(Hsu, et al., 1997; Hsu et al., 1999), developed at the
Department
of Hydrology and Water Resources, The University of Arizona.
To view a movie of the entire year of daily data select the format of
your choice [gif movie]
[QuickTime movie].
This data set is designed for use by various groups, including the large-scale
climate, weather and hydrology communities. In particular, the data was
processed at spatial and temporal resolutions compatible with atmospheric
modeling, with the intention that both the modeling and analysis communities
can use it in investigations of the evolution of tropical/subtropical rainfall
systems, their inter-annual, inter-seasonal and diurnal variations, the
difference in rainfall over oceans and over land, and the transition from
the 1998 El Niño to the 1999 La Niña.
This data set (Version 1.0) represents a first effort to implement the
PERSIANN system into development of an operational global-scale
database. This version omits the use of GOES daytime Visible imagery in
conditioning the estimates, and does not give special consideration to
explicitly discriminating between retrievals over land, coast and ocean
(see Sorooshian et al., 2000). Further, the regions covering Africa and
India (Meteosat) are not included. Extensions of the data set are ongoing,
and Version 2.0 is expected to incorporate these, and other, improvements
such as information about the uncertainty of the estimates. However, the
rainfall-rate estimates provided in this data set have been extensively
evaluated by comparison with ground based observations (gauge, radar) and
with TRMM rainfall products--see Sorooshian et al. (2000), and the page
on Data Evaluation in this document.
We sincerely welcome feedback about the usefulness of this CD-ROM and
the data product (see contact information below). News about product updates
can be obtained interactively via our web site:
Acknowledgements
Production of this data set and the methods used to develop it were supported
by the NASA/EOS IDS grant (NAG5-3640), the NASA/TRMM grant (NAG5-7716),
the NOAA/PACS grant (NA56GPO185), and the NASA grant for HyDIS (NAG-8503). The GOES and
GMS-5 data was obtained from The University of Hawaii/NASA
ftp://rsd.gsfc.nasa.gov/pub/Weather/;
the TRMM data was provided by the Goddard Distributed Active Archive Center
http://daac.gsfc.nasa.gov/;
the gage data was obtained from the NCDC global daily data web page
http://www.ncdc.noaa.gov/;
and the radar data was obtained from the NCEP web page
http://www.emc.ncep.noaa.gov/index.html.
Invaluable suggestions about the research methods that went into the PERSIANN
system were provided by Dr. R. Adler (NASA/Goddard Space Flight Center),
Dr. P.A. Arkin (International Research Institute for Climate Prediction,
Columbia University) and Dr. P. Xie (NOAA/National Meteorological Center).
This support is gratefully acknowledged.
References
Hsu, K., X. Gao, S. Sorooshian, and H. V. Gupta, "Precipitation Estimation
from remotely Sensed Information using Artificial Neural Networks", Journal
of Applied Meteorology, 36(9), pp. 1176-1190, September 1997.
Hsu,L., H.V. Gupta, X. Gao, and S. Sorooshian, "Estimation of Physical Variables
from Multi-Channel Remotely Sensed Imagery using a Neural Network: Application
to Rainfall Estimation", Water Resources Research, 35 (5), pp. 1605-1618,
1999.
Sorooshian, S., K. Hsu, X. Gao, H.V. Gupta, B. Imam and D. Braithwaite,
"Evaluation of Tropical Rainfall Estimates Derived Using TRMM and GOES
Satellite Data" in review, Bulletin of the American Meteorological Society,
1999.
Contact Information:
Dr. Kuo-lin Hsu,
Research Scientist,
Email: hsu@hwr.arizona.edu
Ph: (520) 621-1898, Fax: (520) 626-2488
Mr. Dan Braithwaite
Applications Systems Analyst,
email: dank@hwr.arizona.edu
Ph: (520) 621-9944, Fax: (520) 621-1422