HR: 1330h
AN: H22D-0961 [PDF]
TI: Intercomparison and Validation of GPCP One-Degree Daily Rainfall Estimates with Surface-based Radar
Estimates in the Mississippi River Basin
AU: * Gebremichael, M
EM: mgwoldem@engineering.uiowa.edu
AF: IIHR - Hydroscience & Engineering, The University of Iowa,
C. Maxwell Stanley Hydraulics Laboratory, Iowa City, IA 52242 United States
AU: Krajewski, W
EM: witold-krajewski@uiowa.edu
AF: IIHR - Hydroscience & Engineering, The University of Iowa,
C. Maxwell Stanley Hydraulics Laboratory, Iowa City, IA 52242 United States
AB:
The Global Precipitation Climatology Project (GPCP) has been producing truly global daily precipitation estimates at 1-degree
resolution (1DD) for the period of January 1997 - to date by combining data from different satellite sensors. Quantification
of the errors in such estimates, through direct comparisons with independent high-quality surface-based rainfall estimates,
is essential to provide a quantitative confidence level on the estimates and to further improve the quality of such
estimates. The purpose of this study is to perform extensive quantitative assessment of the GPCP-1DD estimates by comparing
them with independent radar-based rainfall estimates over the Mississippi river basin, for the period 1997-2000. The archive
of radar-based estimates used, conveniently referred to as the MRB hereafter, is suitable to perform validation studies in
view of its high space-time resolution, large areal coverage, and relatively long time series. The Mississippi river basin
covers 435 one-degree grids. The authors used several comparison statistics which fall into unconditional continuous
statistics, conditional (quasi-)continuous statistics, and categorical statistics. The analyses include annual and seasonal
time periods. The results are presented for each 1-degree grid and for a combination of these grids in certain regions.
Highlights of the results are as follows. (1) There is a very good correspondence between the GPCP and MRB estimates both
spatially and temporally, as evidenced by correlations in excess of 0.90 mostly. (2) The GPCP has a very high skill in
discriminating rainy from nonrainy days as reported by the MRB estimates, at a large range of rainfall thresholds. (3) There
is a systematic difference between the two estimates, with the GPCP overestimating at almost all locations and seasons. Both
the bias and the root-mean-square difference consistently increase with increasing rain rate. The bias varies from 0.09 to
7.21 mm day-1, at the MRB-estimated means of 0.10 and 17.26 mm day-1, respectively. The bias-adjusted root-mean-square
difference varies from 0.22 to 5.87 mm day-1, at the MRB-estimated means of 0.10 and 17.26 mm day-1, respectively. (4) The
GPCP estimates for winter show slightly larger systematic error and less rain presence/absence diagnosis skill compared to
other seasons. Finally, although the errors in the MRB estimates are expected to be relatively small, the authors acknowledge
that the MRB estimates are subject to error sources, and they describe how the statistics of the GPCP-MRB difference are
partitioned into the GPCP error and the MRB error components.
DE: 1854 Precipitation (3354)
DE: 3354 Precipitation (1854)
SC: Hydrology [H]
MN: 2003 Fall Meeting