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  • 标题:The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data
  • 本地全文:下载
  • 作者:Phu Nguyen ; Eric J. Shearer ; Hoang Tran
  • 期刊名称:Scientific Data
  • 电子版ISSN:2052-4463
  • 出版年度:2019
  • 卷号:6
  • DOI:10.1038/sdata.2018.296
  • 语种:English
  • 出版社:Nature Publishing Group
  • 摘要:The Center for Hydrometeorology and Remote Sensing (CHRS) has created the CHRS Data Portal to facilitate easy access to the three open data licensed satellite-based precipitation datasets generated by our Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) system: PERSIANN, PERSIANN-Cloud Classification System (CCS), and PERSIANN-Climate Data Record (CDR). These datasets have the potential for widespread use by various researchers, professionals including engineers, city planners, and so forth, as well as the community at large. Researchers at CHRS created the CHRS Data Portal with an emphasis on simplicity and the intention of fostering synergistic relationships with scientists and experts from around the world. The following paper presents an outline of the hosted datasets and features available on the CHRS Data Portal, an examination of the necessity of easily accessible public data, a comprehensive overview of the PERSIANN algorithms and datasets, and a walk-through of the procedure to access and obtain the data.
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