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

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 (PER...

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Autores principales: Nguyen, Phu, Shearer, Eric J., Tran, Hoang, Ombadi, Mohammed, Hayatbini, Negin, Palacios, Thanh, Huynh, Phat, Braithwaite, Dan, Updegraff, Garr, Hsu, Kuolin, Kuligowski, Bob, Logan, Will S., Sorooshian, Soroosh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326112/
https://www.ncbi.nlm.nih.gov/pubmed/30620343
http://dx.doi.org/10.1038/sdata.2018.296
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author Nguyen, Phu
Shearer, Eric J.
Tran, Hoang
Ombadi, Mohammed
Hayatbini, Negin
Palacios, Thanh
Huynh, Phat
Braithwaite, Dan
Updegraff, Garr
Hsu, Kuolin
Kuligowski, Bob
Logan, Will S.
Sorooshian, Soroosh
author_facet Nguyen, Phu
Shearer, Eric J.
Tran, Hoang
Ombadi, Mohammed
Hayatbini, Negin
Palacios, Thanh
Huynh, Phat
Braithwaite, Dan
Updegraff, Garr
Hsu, Kuolin
Kuligowski, Bob
Logan, Will S.
Sorooshian, Soroosh
author_sort Nguyen, Phu
collection PubMed
description 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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spelling pubmed-63261122019-01-10 The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data Nguyen, Phu Shearer, Eric J. Tran, Hoang Ombadi, Mohammed Hayatbini, Negin Palacios, Thanh Huynh, Phat Braithwaite, Dan Updegraff, Garr Hsu, Kuolin Kuligowski, Bob Logan, Will S. Sorooshian, Soroosh Sci Data Article 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. Nature Publishing Group 2019-01-08 /pmc/articles/PMC6326112/ /pubmed/30620343 http://dx.doi.org/10.1038/sdata.2018.296 Text en Copyright © 2019, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Nguyen, Phu
Shearer, Eric J.
Tran, Hoang
Ombadi, Mohammed
Hayatbini, Negin
Palacios, Thanh
Huynh, Phat
Braithwaite, Dan
Updegraff, Garr
Hsu, Kuolin
Kuligowski, Bob
Logan, Will S.
Sorooshian, Soroosh
The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data
title The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data
title_full The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data
title_fullStr The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data
title_full_unstemmed The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data
title_short The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data
title_sort chrs data portal, an easily accessible public repository for persiann global satellite precipitation data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326112/
https://www.ncbi.nlm.nih.gov/pubmed/30620343
http://dx.doi.org/10.1038/sdata.2018.296
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