The PERSIANN family of global satellite precipitation data: a review and evaluation of products
<p>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...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-11-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://www.hydrol-earth-syst-sci.net/22/5801/2018/hess-22-5801-2018.pdf |
| _version_ | 1819075327665635328 |
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| author | P. Nguyen P. Nguyen M. Ombadi S. Sorooshian K. Hsu K. Hsu A. AghaKouchak D. Braithwaite H. Ashouri A. R. Thorstensen |
| author_facet | P. Nguyen P. Nguyen M. Ombadi S. Sorooshian K. Hsu K. Hsu A. AghaKouchak D. Braithwaite H. Ashouri A. R. Thorstensen |
| author_sort | P. Nguyen |
| collection | DOAJ |
| description | <p>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.</p> |
| first_indexed | 2024-12-21T18:23:39Z |
| format | Article |
| id | doaj.art-fc0a0a1eb58a489ebb3a4b2403d1b094 |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-12-21T18:23:39Z |
| publishDate | 2018-11-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-fc0a0a1eb58a489ebb3a4b2403d1b0942022-12-21T18:54:29ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382018-11-01225801581610.5194/hess-22-5801-2018The PERSIANN family of global satellite precipitation data: a review and evaluation of productsP. Nguyen0P. Nguyen1M. Ombadi2S. Sorooshian3K. Hsu4K. Hsu5A. AghaKouchak6D. Braithwaite7H. Ashouri8A. R. Thorstensen9Center for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California Irvine, Irvine, CA, USADepartment of Water Management, Nong Lam University, Ho Chi Minh City, VietnamCenter for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California Irvine, Irvine, CA, USACenter for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California Irvine, Irvine, CA, USACenter for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California Irvine, Irvine, CA, USACenter of Excellence for Ocean Engineering, National Taiwan Ocean University (CEOE, NTOU), Keelung, TaiwanCenter for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California Irvine, Irvine, CA, USACenter for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California Irvine, Irvine, CA, USACenter for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California Irvine, Irvine, CA, USACenter for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California Irvine, Irvine, CA, USA<p>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.</p>https://www.hydrol-earth-syst-sci.net/22/5801/2018/hess-22-5801-2018.pdf |
| spellingShingle | P. Nguyen P. Nguyen M. Ombadi S. Sorooshian K. Hsu K. Hsu A. AghaKouchak D. Braithwaite H. Ashouri A. R. Thorstensen The PERSIANN family of global satellite precipitation data: a review and evaluation of products Hydrology and Earth System Sciences |
| title | The PERSIANN family of global satellite precipitation data: a review and evaluation of products |
| title_full | The PERSIANN family of global satellite precipitation data: a review and evaluation of products |
| title_fullStr | The PERSIANN family of global satellite precipitation data: a review and evaluation of products |
| title_full_unstemmed | The PERSIANN family of global satellite precipitation data: a review and evaluation of products |
| title_short | The PERSIANN family of global satellite precipitation data: a review and evaluation of products |
| title_sort | persiann family of global satellite precipitation data a review and evaluation of products |
| url | https://www.hydrol-earth-syst-sci.net/22/5801/2018/hess-22-5801-2018.pdf |
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