The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
The PERSIANN family of global satellite precipitation data: a review and evaluation of products
Open accessAbstract
Abstract. 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.
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Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F., Gu, G., Hong, Y., Bowman, K. P., & Stocker, E. F. (2007) · Journal of Hydrometeorology · doi:10.1175/jhm560.1 · Cited by 6,767
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The Global Precipitation Measurement Mission
Hou, A. Y., Kakar, R. K., Neeck, S., Azarbarzin, A. A., Kummerow, C. D., Kojima, M., Oki, R., Nakamura, K., & Iguchi, T. (2014) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-13-00164.1 · Cited by 2,766
The Tropical Rainfall Measuring Mission (TRMM) Sensor Package
Kummerow, C., Barnes, W., Kozu, T., Shiue, J., & Simpson, J. (1998) · Journal of Atmospheric and Oceanic Technology · doi:10.1175/1520-0426(1998)015<0809:ttrmmt>2.0.co;2 · Cited by 2,424
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Ashouri, H., Hsu, K.-L., Sorooshian, S., Braithwaite, D. K., Knapp, K. R., Cecil, L. D., Nelson, B. R., & Prat, O. P. (2015) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-13-00068.1 · Cited by 1,384
Self-citationAssessing objective techniques for gauge‐based analyses of global daily precipitation
Chen, M., Shi, W., Xie, P., Silva, V. B. S., Kousky, V. E., Wayne Higgins, R., & Janowiak, J. E. (2008) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2007jd009132 · Cited by 1,250
Evaluation of PERSIANN System Satellite–Based Estimates of Tropical Rainfall
Sorooshian, S., Hsu, K.-L., Gao, X., Gupta, H. V., Imam, B., & Braithwaite, D. (2000) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477(2000)081<2035:eopsse>2.3.co;2 · Cited by 1,237
Self-citationThe Status of the Tropical Rainfall Measuring Mission (TRMM) after Two Years in Orbit
Kummerow, C., Simpson, J., Thiele, O., Barnes, W., Chang, A. T. C., Stocker, E., Adler, R. F., Hou, A., Kakar, R., Wentz, F., et al. (2000) · Journal of Applied Meteorology · doi:10.1175/1520-0450(2001)040<1965:tsottr>2.0.co;2 · Cited by 1,235
Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks
Hsu, K.-L., Gao, X., Sorooshian, S., & Gupta, H. V. (1997) · Journal of Applied Meteorology · doi:10.1175/1520-0450(1997)036<1176:pefrsi>2.0.co;2 · Cited by 1,096
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Machine learning and artificial intelligence to aid climate change research and preparedness
Huntingford, C., Jeffers, E. S., Bonsall, M. B., Christensen, H. M., Lees, T., & Yang, H. (2019) · Environmental Research Letters · doi:10.1088/1748-9326/ab4e55 · Cited by 469
Estébanez-Camarena, M., Taormina, R., van de Giesen, N., & ten Veldhuis, M.-C. (2023) · Remote Sensing · doi:10.3390/rs15071922 · Cited by 12
Metadata
- Authors
- Nguyen, P., Ombadi, M., Sorooshian, S., Hsu, K., AghaKouchak, A., Braithwaite, D., Ashouri, H., & Thorstensen, A. R.
- Venue
- Hydrology and Earth System Sciences
- Publisher
- Copernicus GmbH
- Published
- 2018-11-13
- Volume
- 22
- Issue
- 11
- Pages
- 5801-5816
- ISSN
- 1027-5606 (ISSN-L)
- 1607-7938
- OpenAlex
- W2797707900
- Cited by
- 264
- References
- 30
- FWCI
- 9.92
- Type
- journal article
- Language
- en
- Open access
- gold
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- Nguyen, P., Ombadi, M., Sorooshian, S., Hsu, K., AghaKouchak, A., Braithwaite, D., Ashouri, H., & Thorstensen, A. R. (2018). The PERSIANN family of global satellite precipitation data: a review and evaluation of products. Hydrology and Earth System Sciences. https://doi.org/10.5194/hess-22-5801-2018
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