The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
The Global Precipitation Measurement Mission
Open accessAbstract
Precipitation affects many aspects of our everyday life. It is the primary source of freshwater and has significant socioeconomic impacts resulting from natural hazards such as hurricanes, floods, droughts, and landslides. Fundamentally, precipitation is a critical component of the global water and energy cycle that governs the weather, climate, and ecological systems. Accurate and timely knowledge of when, where, and how much it rains or snows is essential for understanding how the Earth system functions and for improving the prediction of weather, climate, freshwater resources, and natural hazard events. The Global Precipitation Measurement (GPM) mission is an international satellite mission specifically designed to set a new standard for the measurement of precipitation from space and to provide a new generation of global rainfall and snowfall observations in all parts of the world every 3 h. The National Aeronautics and Space Administration (NASA) and the Japan Aerospace and Exploration Agency (JAXA) successfully launched the Core Observatory satellite on 28 February 2014 carrying advanced radar and radiometer systems to serve as a precipitation physics observatory. This will serve as a transfer standard for improving the accuracy and consistency of precipitation measurements from a constellation of research and operational satellites provided by a consortium of international partners. GPM will provide key measurements for understanding the global water and energy cycle in a changing climate as well as timely information useful for a range of regional and global societal applications such as numerical weather prediction, natural hazard monitoring, freshwater resource management, and crop forecasting.
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Cites
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
The Global Land Data Assimilation System
Rodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C.-J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., et al. (2004) · Bulletin of the American Meteorological Society · doi:10.1175/bams-85-3-381 · Cited by 5,614
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
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
Smoking Rain Clouds over the Amazon
Andreae, M. O., Rosenfeld, D., Artaxo, P., Costa, A. A., Frank, G. P., Longo, K. M., & Silva-Dias, M. A. F. (2004) · Science · doi:10.1126/science.1092779 · Cited by 1,489
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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
Rain-Profiling Algorithm for the TRMM Precipitation Radar
Iguchi, T., Kozu, T., Meneghini, R., Awaka, J., & Okamoto, K. (2000) · Journal of Applied Meteorology · doi:10.1175/1520-0450(2001)040<2038:rpaftt>2.0.co;2 · Cited by 989
Self-citationEstimates of the Global Water Budget and Its Annual Cycle Using Observational and Model Data
Trenberth, K. E., Smith, L., Qian, T., Dai, A., & Fasullo, J. (2007) · Journal of Hydrometeorology · doi:10.1175/jhm600.1 · Cited by 948
Kubota, T., Shige, S., Hashizume, H., Aonashi, K., Takahashi, N., Seto, S., Hirose, M., Takayabu, Y. N., Ushio, T., Nakagawa, K., et al. (2007) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2007.895337 · Cited by 844
Cited by
Sharifi, E., Steinacker, R., & Saghafian, B. (2016) · Remote Sensing · doi:10.3390/rs8020135 · Cited by 382
Tropical deforestation causes large reductions in observed precipitation
Smith, C., Baker, J. C. A., & Spracklen, D. V. (2023) · Nature · doi:10.1038/s41586-022-05690-1 · Cited by 270
Spatio‐temporal characteristics of the recent rainfall recovery in West Africa
Sanogo, S., Fink, A. H., Omotosho, J. A., Ba, A., Redl, R., & Ermert, V. (2015) · International Journal of Climatology · doi:10.1002/joc.4309 · Cited by 241
Fiedler, S., Crueger, T., D’Agostino, R., Peters, K., Becker, T., Leutwyler, D., Paccini, L., Burdanowitz, J., Buehler, S. A., Cortes, A. U., et al. (2020) · Monthly Weather Review · doi:10.1175/mwr-d-19-0404.1 · Cited by 166
Brocca, L., Massari, C., Pellarin, T., Filippucci, P., Ciabatta, L., Camici, S., Kerr, Y. H., & Fernández-Prieto, D. (2020) · Scientific Reports · doi:10.1038/s41598-020-69343-x · Cited by 109
Metadata
- Authors
- Hou, A. Y., Kakar, R. K., Neeck, S., Azarbarzin, A. A., Kummerow, C. D., Kojima, M., Oki, R., Nakamura, K., & Iguchi, T.
- Venue
- Bulletin of the American Meteorological Society
- Publisher
- American Meteorological Society
- Published
- 2014-05
- Volume
- 95
- Issue
- 5
- Pages
- 701-722
- ISSN
- 0003-0007 (ISSN-L)
- 1520-0477
- OpenAlex
- W2073298425
- Cited by
- 2,766
- References
- 42
- FWCI
- 56.90
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: The Global Precipitation Measurement Mission. https://app.cochat.ai/papers/10.1175/bams-d-13-00164.1
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- Hou, A. Y., Kakar, R. K., Neeck, S., Azarbarzin, A. A., Kummerow, C. D., Kojima, M., Oki, R., Nakamura, K., & Iguchi, T. (2014). The Global Precipitation Measurement Mission. Bulletin of the American Meteorological Society. https://doi.org/10.1175/bams-d-13-00164.1
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
