globalchange  > 气候变化与战略
DOI: 10.5194/hess-22-5801-2018
论文题名:
The PERSIANN family of global satellite precipitation data: A review and evaluation of products
作者: Nguyen P.; Ombadi M.; Sorooshian S.; Hsu K.; AghaKouchak A.; Braithwaite D.; Ashouri H.; Rose Thorstensen A.
刊名: Hydrology and Earth System Sciences
ISSN: 1027-5606
出版年: 2018
卷: 22, 期:11
起始页码: 5801
结束页码: 5816
语种: 英语
Scopus关键词: Earth sciences ; Hydrology ; Climate prediction centers ; Operational products ; Precipitation estimation from remotely sensed information ; Precipitation products ; Precipitation retrievals ; Satellite precipitation ; Spatial and temporal scale ; Temporal scale ; Neural networks ; algorithm ; artificial neural network ; benchmarking ; comparative study ; data set ; gauge ; literature review ; precipitation (climatology) ; remote sensing ; satellite altimetry
英文摘要: Over the past 2 decades, a wide range of studies have incorporated Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) products. Currently, PERSIANN offers several precipitation products based on different algorithms available at various spatial and temporal scales, namely PERSIANN, PERSIANN-CCS, and PERSIANN-CDR. The goal of this article is to first provide an overview of the available PERSIANN precipitation retrieval algorithms and their differences. Secondly, we offer an evaluation of the available operational products over the contiguous US (CONUS) at different spatial and temporal scales using Climate Prediction Center (CPC) unified gauge-based analysis as a benchmark. Due to limitations of the baseline dataset (CPC), daily scale is the finest temporal scale used for the evaluation over CONUS. Additionally, we provide a comparison of the available products at a quasi-global scale. Finally, we highlight the strengths and limitations of the PERSIANN products and briefly discuss expected future developments. © 2018 Author(s).
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/163142
Appears in Collections:气候变化与战略

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作者单位: Nguyen, P., Center for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California, Irvine, CA, United States, Department of Water Management, Nong Lam University, Ho Chi Minh City, Viet Nam; Ombadi, M., Center for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California, Irvine, CA, United States; Sorooshian, S., Center for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California, Irvine, CA, United States; Hsu, K., Center for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California, Irvine, CA, United States, Center of Excellence for Ocean Engineering (CEOE), National Taiwan Ocean University (NTOU), Keelung, Taiwan; AghaKouchak, A., Center for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California, Irvine, CA, United States; Braithwaite, D., Center for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California, Irvine, CA, United States; Ashouri, H., Center for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California, Irvine, CA, United States; Rose Thorstensen, A., Center for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California, Irvine, CA, United States

Recommended Citation:
Nguyen P.,Ombadi M.,Sorooshian S.,et al. The PERSIANN family of global satellite precipitation data: A review and evaluation of products[J]. Hydrology and Earth System Sciences,2018-01-01,22(11)
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