The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
An Intercomparison and Validation of High-Resolution Satellite Precipitation Estimates with 3-Hourly Gauge Data
Abstract
The last several years have seen the development of a number of new satellite-derived, globally complete, high-resolution precipitation products with a spatial resolution of at least 0.25° and a temporal resolution of at least 3-hourly. These products generally merge geostationary infrared data and polar-orbiting passive microwave data to take advantage of the frequent sampling of the infrared and the superior quality of the microwave. The Program to Evaluate High Resolution Precipitation Products (PEHRPP) was established to evaluate and intercompare these datasets at a variety of spatial and temporal resolutions with the intent of guiding dataset developers and informing the user community regarding the error characteristics of the products. As part of this project, the authors have performed a subdaily intercomparison of five high-resolution datasets [Climate Prediction Center morphing (CMORPH) technique; Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA); Naval Research Laboratory (NRL) blended technique; National Environmental Satellite, Data, and Information Service Hydro-Estimator; and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN)] with existing subdaily gauge data over the United States and the Pacific Ocean. Results show that these data are effective at representing high-resolution precipitation, with correlations against 3-hourly gauge data as high as 0.7 for CMORPH, which had the highest correlations with the validation data. Biases are relatively high for most of the datasets over land (apart from the TMPA, which is gauge adjusted) and ocean, with a general tendency to overestimate warm season rainfall over the United States and to underestimate rainfall over the tropical Pacific Ocean. Additionally, all the products studied faithfully resolve the diurnal cycle of precipitation when compared with the validation data.
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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
Adler, R. F., Huffman, G. J., Chang, A. T. C., Ferraro, R. R., Xie, P., Janowiak, J. E., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D. T., et al. (2003) · Journal of Hydrometeorology · doi:10.1175/1525-7541(2003)004<1147:tvgpcp>2.0.co;2 · Cited by 5,425
Self-citationXie, P., & Arkin, P. A. (1997) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477(1997)078<2539:gpayma>2.0.co;2 · Cited by 4,307
Self-citationJoyce, R. J., Janowiak, J. E., Arkin, P. A., & Xie, P. (2004) · Journal of Hydrometeorology · doi:10.1175/1525-7541(2004)005<0487:camtpg>2.0.co;2 · Cited by 3,208
Self-citationGlobal Precipitation at One-Degree Daily Resolution from Multisatellite Observations
Huffman, G. J., Adler, R. F., Morrissey, M. M., Bolvin, D. T., Curtis, S., Joyce, R., McGavock, B., & Susskind, J. (2001) · Journal of Hydrometeorology · doi:10.1175/1525-7541(2001)002<0036:gpaodd>2.0.co;2 · Cited by 1,854
The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset
Huffman, G. J., Adler, R. F., Arkin, P., Chang, A., Ferraro, R., Gruber, A., Janowiak, J., McNab, A., Rudolf, B., & Schneider, U. (1997) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477(1997)078<0005:tgpcpg>2.0.co;2 · Cited by 1,723
Self-citationForecast Verification: A Practitioner's Guide in Atmospheric Science
(2011) · Wiley eBooks · doi:10.1002/9781119960003 · Cited by 1,267
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
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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Cited by
Maggioni, V., Meyers, P. C., & Robinson, M. D. (2016) · Journal of Hydrometeorology · doi:10.1175/jhm-d-15-0190.1 · Cited by 448
Component analysis of errors in satellite‐based precipitation estimates
Tian, Y., Peters‐Lidard, C. D., Eylander, J. B., Joyce, R. J., Huffman, G. J., Adler, R. F., Hsu, K., Turk, F. J., Garcia, M., & Zeng, J. (2009) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2009jd011949 · Cited by 431
Evaluation of satellite-retrieved extreme precipitation rates across the central United States
AghaKouchak, A., Behrangi, A., Sorooshian, S., Hsu, K., & Amitai, E. (2011) · Journal of Geophysical Research · doi:10.1029/2010jd014741 · Cited by 323
Gridded Ensemble Precipitation and Temperature Estimates for the Contiguous United States
Newman, A. J., Clark, M. P., Craig, J., Nijssen, B., Wood, A., Gutmann, E., Mizukami, N., Brekke, L., & Arnold, J. R. (2015) · Journal of Hydrometeorology · doi:10.1175/jhm-d-15-0026.1 · Cited by 184
Diurnal rainfall variability over the Upper Blue Nile Basin: A remote sensing based approach
Rientjes, T., Haile, A. T., & Fenta, A. A. (2013) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2012.07.009 · Cited by 46
Metadata
- Authors
- Sapiano, M. R. P., & Arkin, P. A.
- Venue
- Journal of Hydrometeorology
- Publisher
- American Meteorological Society
- Published
- 2009-02-01
- Volume
- 10
- Issue
- 1
- Pages
- 149-166
- ISSN
- 1525-7541 (ISSN-L)
- 1525-755X
- OpenAlex
- W2082872569
- Cited by
- 351
- References
- 27
- FWCI
- 10.57
- Type
- journal article
- Language
- en
- Open access
- closed
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- Sapiano, M. R. P., & Arkin, P. A. (2009). An Intercomparison and Validation of High-Resolution Satellite Precipitation Estimates with 3-Hourly Gauge Data. Journal of Hydrometeorology. https://doi.org/10.1175/2008jhm1052.1
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