The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data

The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data
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DOI:
10.1038/sdata.2018.296
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发表时间:
2019-01
期刊:
影响因子:
9.8
通讯作者:
P. Nguyen;E. Shearer;H. Tran;Mohammed Ombadi;N. Hayatbini;T. Palacios;P. Huynh;D. Braithwaite;G. Updegraff;K. Hsu;B. Kuligowski;W. Logan;S. Sorooshian
P. Nguyen;E. Shearer;H. Tran;Mohammed Ombadi;N. Hayatbini;T. Palacios;P. Huynh;D. Braithwaite;G. Updegraff;K. Hsu;B. Kuligowski;W. Logan;S. Sorooshian
中科院分区:
综合性期刊2区
文献类型:
--
作者:
P. Nguyen;E. Shearer;H. Tran;Mohammed Ombadi;N. Hayatbini;T. Palacios;P. Huynh;D. Braithwaite;G. Updegraff;K. Hsu;B. Kuligowski;W. Logan;S. Sorooshian

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水文气象和遥感中心(CHRS)创建了CHRS数据门户,以方便访问我们使用人工神经网络(PERSIANN)系统从遥感信息估计降水量生成的三个开放数据许可的卫星降水数据集:PERSIANN、PERSIANN-云分类系统(CCS)和PERSIANN-气候数据记录(CDR)。这些数据集有可能被各种研究人员、专业人士(包括工程师、城市规划师等)以及整个社区广泛使用。CHRS的研究人员创建了CHRS数据门户,强调简单性,并打算促进与来自世界各地的科学家和专家的协同关系。以下白皮书概述了CHRS数据门户上提供的托管数据集和功能,审查了方便访问公共数据的必要性,全面概述了PERSIANN算法和数据集,并详细介绍了访问和获取数据的程序。
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.