DOI: 10.1002/jgrd.50607
论文题名: Inferring the uncertainty of satellite precipitation estimates in data-sparse regions over land
作者: Bytheway J.L. ; Kummerow C.D.
刊名: Journal of Geophysical Research Atmospheres
ISSN: 21698996
出版年: 2013
卷: 118, 期: 17 起始页码: 9524
结束页码: 9533
语种: 英语
英文关键词: precipitation
; remote sensing
; uncertainty
Scopus关键词: Geographical distribution
; Precipitation (chemical)
; Probability distributions
; Rain gages
; Remote sensing
; Uncertainty analysis
; Ground-based observations
; Multi-sensor precipitations
; National centers for environmental predictions
; Precipitation characteristics
; Satellite precipitation
; Satellite precipitation estimates
; Tropical rainfall measurement missions
; uncertainty
; Rain
; data set
; energy budget
; error analysis
; estimation method
; geoaccumulation
; precipitation (climatology)
; radar
; rainfall
; remote sensing
; satellite imagery
; timescale
; uncertainty analysis
; United States
英文摘要: The global distribution of precipitation is essential to understanding earth's water and energy budgets. While developed countries often have reliable precipitation observation networks, our understanding of the distribution of precipitation in data-sparse regions relies on sporadic rain gauges and information gathered by spaceborne sensors. Several multisensor data sets attempt to represent the global distribution of precipitation on subdaily time scales by combining multiple satellite and ground-based observations. Due to limited validation sources and highly variable nature of precipitation, it is difficult to assess the performance of multisensor precipitation products globally. Here, we introduce a methodology to infer the uncertainty of satellite precipitation measurements globally based on similarities between precipitation characteristics in data-sparse and data-rich regions. Five generalized global rainfall regimes are determined based on the probability distribution of 3-hourly accumulated rainfall in 0.25° grid boxes using the Tropical Rainfall Measurement Mission 3B42 product. Uncertainty characteristics for each regime are determined over the United States using the high-quality National Centers for Environmental Prediction Stage IV radar product. The results indicate that the frequency of occurrence of zero and little accumulated rainfall is the key difference between the regimes and that differences in error characteristics are most prevalent at accumulations below ~4 mm/h. At higher accumulations, uncertainty in 3-hourly accumulation converges to ~80%. Using the self-similarity in the five rainfall regimes along with the error characteristics observed for each regime, the uncertainty in 3-hourly precipitation estimates can be inferred in regions that lack quality ground validation sources. Key Points Global precipitation can be categorized by 3-hour accumulated precipitationSimilar observed precipitation types imply similar measurement uncertaintiesGlobal measurement error is inferred from calculated error in data-rich areas ©2013. American Geophysical Union. All Rights Reserved.
资助项目: NNH06ZDA001N
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/63358
Appears in Collections: 影响、适应和脆弱性 气候减缓与适应
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作者单位: Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, United States
Recommended Citation:
Bytheway J.L.,Kummerow C.D.. Inferring the uncertainty of satellite precipitation estimates in data-sparse regions over land[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(17)