气候变化领域集成服务门户(CCPortal): The PERSIANN family of global satellite precipitation data: A review and evaluation of products

CCPortal

DOI	10.5194/hess-22-5801-2018
	The PERSIANN family of global satellite precipitation data: A review and evaluation of products
	Nguyen P.; Ombadi M.; Sorooshian S.; Hsu K.; AghaKouchak A.; Braithwaite D.; Ashouri H.; Rose Thorstensen A.
发表日期	2018
ISSN	1027-5606
起始页码	5801
结束页码	5816
卷号	22 期号:11
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).
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
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159859
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; Brai...
推荐引用方式 GB/T 7714	Nguyen P.,Ombadi M.,Sorooshian S.,et al. The PERSIANN family of global satellite precipitation data: A review and evaluation of products[J],2018,22(11).
APA	Nguyen P..,Ombadi M..,Sorooshian S..,Hsu K..,AghaKouchak A..,...&Rose Thorstensen A..(2018).The PERSIANN family of global satellite precipitation data: A review and evaluation of products.Hydrology and Earth System Sciences,22(11).
MLA	Nguyen P.,et al."The PERSIANN family of global satellite precipitation data: A review and evaluation of products".Hydrology and Earth System Sciences 22.11(2018).