Seasonal and Annual Validation of Operational Satellite Precipitation Estimates

被引:0
|
作者
Rudlosky, Scott D. [1 ]
Nichols, Meredith A. [2 ]
Meyers, Patrick C. [2 ]
Wheeler, David F. [3 ]
机构
[1] NOAA NESDIS STAR, College Pk, MD USA
[2] Univ Maryland, College Pk, MD 20742 USA
[3] Iteris Inc, Grand Forks, ND USA
关键词
D O I
10.15191/nwajom.2016.0405
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This study analyzes the performance of five satellite-derived precipitation products relative to ground-based gauge observations. The satellite products estimate precipitation using passive microwave (PMW) and/or infrared (IR) observations. Differences in these observation methods lead to seasonal and regional biases that influence the operational utility of the satellite precipitation estimates. In turn, these products require informed interpretation by forecasters. Five years of daily satellite precipitation estimates (2010-14) are composited into two types of seasonal and annual maps to characterize performance. The seasonal composites reveal positive biases during summer and greater variability among satellite products during winter. Each satellite product overestimates the maximum daily precipitation relative to gauge throughout much of the central and eastern United States. In this region, the 95th percentile of gauge-reported daily precipitation values generally range between 20 and 40 mm day(-1), whereas the satellite-reported values generally exceed 40 mm day(-1). Winter exhibits greater variability among satellite products with a mix of both positive and negative biases. The bias magnitudes are greater and the spatial correlations are lower (i.e., the composite maps are less similar) during winter than during summer. The IR-based products generally overestimate winter precipitation north of 36 degrees N, and the PMW-based products performed poorly in mountainous regions along the West Coast. These results characterize biases in satellite precipitation estimates to better inform the user community and help researchers improve future versions of their operational products.
引用
收藏
页码:58 / 74
页数:17
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