Radar-guided interpolation of climatological precipitation data

被引:36
作者
DeGaetano, Arthur T. [1 ]
Wilks, Daniel S. [1 ]
机构
[1] Cornell Univ, Dept Earth & Atmospher Sci, NE Reg Climate Ctr, Ithaca, NY 14853 USA
关键词
radar; rainfall; rainfall estimation; rain gauge; REAL-TIME ESTIMATION; RAIN-GAUGE DATA; SPATIAL INTERPOLATION; WSR-88D; FIELDS;
D O I
10.1002/joc.1714
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
A refined approach for interpolating daily precipitation accumulations is presented, which combines radar-based information to characterize the spatial distribution and gross accumulation of precipitation with observed daily rain-gauge data to adjust for spatially varying errors in the radar estimates. Considering the rain gauge observations to be true values at each measurement location, daily radar errors are calculated at these points. These errors are then interpolated back to the radar grid. providing a spatially varying daily adjustment that can be applied across the radar domain. In contrast to similar techniques that are employed at hourly intervals to adjust radar-rainfall estimates operationally, this refined approach is intended to provide high-spatial-resolution precipitation data for climatological purposes, such as drought and environmental monitoring. retrospective impact analyses. and (when time series of Sufficient length become available) assessment of temporal precipitation variations at high-spatial-resolution. Compared to the Multisensor Precipitation Estimators (MPEs) used operationally, the refined method yields lower cross-validated interpolation errors regardless of season or daily precipitation amount. Comparisons between cross-validated C radar estimates aggregated to monthly totals with operational (non-cross-validated) Parameter-elevation Regressions oil Independent Slopes Model (PRISM) precipitation estimates are also favourable. The new method provides a radar-based alternative to similar climatologies based oil the spatial interpolation of gauge data alone (e.g. PRISM). Copyright (c) 2008 Royal Meteorological Society
引用
收藏
页码:185 / 196
页数:12
相关论文
共 50 条
[1]  
Anagnostou EN, 1999, J ATMOS OCEAN TECH, V16, P189, DOI 10.1175/1520-0426(1999)016<0189:RTRREP>2.0.CO
[2]  
2
[3]  
[Anonymous], 1993, DOPPLER RADAR WEATHE, DOI DOI 10.1016/B978-0-12-221422-6.50010-3
[4]  
AUSTIN PM, 1987, MON WEATHER REV, V115, P1053, DOI 10.1175/1520-0493(1987)115<1053:RBMRRA>2.0.CO
[5]  
2
[6]  
BRANDES EA, 1975, J APPL METEOROL, V14, P1339, DOI 10.1175/1520-0450(1975)014<1339:OREWTA>2.0.CO
[7]  
2
[8]  
Chen MY, 2002, J HYDROMETEOROL, V3, P249, DOI 10.1175/1525-7541(2002)003<0249:GLPAYM>2.0.CO
[9]  
2
[10]   LOCALLY WEIGHTED REGRESSION - AN APPROACH TO REGRESSION-ANALYSIS BY LOCAL FITTING [J].
CLEVELAND, WS ;
DEVLIN, SJ .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1988, 83 (403) :596-610