Abstract
Extreme Rainfall can be defined by percentiles of the overall rainfall distribution at a given temporal scale. Generally, the 90th percentile value and above can be considered extreme. While satellite measurements of rainfall provide estimates at global scales and for ever increasing spatial resolution (currently 0.1 km2), the many flavors of satellite precipitation measurement vary widely from algorithm to algorithm especially at the 90th percentile and above. Satellite estimates of extreme rainfall also vary widely based on certain conditions such as over land versus over ocean, over mountainous terrain versus flat terrain, and high latitudes versus the tropics. Finally, all satellite quantitative precipitation estimates are based on algorithms which ultimately include blending and adjustment using rain gauges. Therefore, satellite estimates of extreme rainfall can vary widely based on the algorithm. This chapter provides an overview of extreme rainfall characterization derived from satellite measurements.
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Abdalla, O., & Al-Abri, R. Y. (2011). Groundwater recharge in arid areas induced by tropical cyclones: Lessons learned from Gonu 2007 in Sultanate of Oman. Environment and Earth Science, 63, 229–239. https://doi.org/10.1007/s12665-010-0688-y.
AghaKouchak, A., Behrangi, A., Sorooshian, S., Hsu, K.-L., & Amitai, E. (2011). Evaluation of satellite-retrieved extreme precipitation rates across the Central United States. Journal of Geophysical Research, 116, D02115. https://doi.org/10.1029/2010JD014741.
Ashouri, H., Hsu, K.-L., Sorooshian, S., Braithwaite, D. K., Knapp, K. R., Cecil, L. D., Nelson, B. R., & Prat, O. P. (2015). PERSIANN-CDR daily precipitation climate data record from multisatellite observations for hydrological and climate studies. Bulletin of the American Meteorological Society, 96, 69–83. https://doi.org/10.1175/BAMS-D-13-00068.1.
Behrangi, A., Guan, B., Neiman, P. J., Schreier, M., & Lambrigtsen, B. (2016). On the quantification of atmospheric rivers precipitation from space: Composite assessments and case studies over the Eastern North Pacific Ocean and the Western United States. Journal of Hydrometeorology, 17, 369–382. https://doi.org/10.1175/JHM-D-15-0061.1.
Bharti, V., Singh, C., Ettema, J., & Turkington, T. A. R. (2016). Spatiotemporal characteristics of extreme rainfall events over the Northwest Himalaya using satellite data. International Journal of Climatology, 36, 3949–3962. https://doi.org/10.1002/joc.4605.
Breña-Naranjo, J. A., Pedrozo-Acuna, A., & Rico-Ramirez, M. A. (2015). World’s greatest rainfall intensities observed by satellites. Atmospheric Science Letters, 16, 420–424. https://doi.org/10.1002/asl2.546.
Chen, S., Hong, Y., Cao, Q., Kirstetter, P.-E., Gourley, J. J., Qi, Y. C., Zhang, J., Howard, K., Hu, J. J., & Wang, J. (2013). Performance evaluation of radar and satellite rainfalls for Typhoon Morakot over Taiwan: Are remote-sensing products ready for gauge denial scenario of extreme events? Journal of Hydrology, 506, 4–13. https://doi.org/10.1016/j.jhydrol.2012.12.026.
Ciach, G. J., & Krajewski, W. F. (1999). On the estimation of rainfall error variance. Advances in Water Resources, 22, 585–595. https://doi.org/10.1016/S0309-1708(98)00043-8.
Ciach, G. J., Habib, E., & Krajewski, W. F. (2003). Zero-covariance hypothesis in the error variance separation method of radar rainfall verification. Advances in Water Resources, 26, 573–580. https://doi.org/10.1016/S0309-1708(02)00163-X.
Ciach, G. J., Krajewski, W. F., & Villarini, G. (2007). Product-error-driven uncertainty model for probabilistic quantitative precipitation estimation with NEXRAD data. Journal of Hydrometeorology, 8, 1325–1347. https://doi.org/10.1175/2007JHM814.1.
Curtis, S., Salahuddin, A., Adler, R. F., Huffman, G. J., Gu, G. J., & Hong, Y. (2007). Precipitation extremes estimated by GPCP and TRMM: ENSO relationships. Journal of Hydrometeorology, 8, 678–689. https://doi.org/10.1175/JHM601.1.
Diamond, H. J., Karl, T. R., Palecki, M. A., Baker, C. B., Bell, J. E., Leeper, R. D., Easterling, D. R., Lawrimore, J. H., Meyers, T. P., Helfert, M. R., Goodge, G., & Thorne, P. W. (2013). U.S. Climate Reference Network after one decade of operations: Status and assessment. Bulletin of the American Meteorological Society, 94, 485–498. https://doi.org/10.1175/BAMS-D-12-00170.1.
Dube, S. K., Jain, I., Rao, A. D., & Murty, T. S. (2009). Storm surge modelling for the Bay of Bengal and Arabian Sea. Natural Hazards, 51, 3–27. https://doi.org/10.1007/s11069-009-9397-9.
Endreny, T. A., & Imbeah, N. (2009). Generating robust rainfall intensity-duration-frequency estimates with short-record satellite data. Journal of Hydrology, 371, 182–191. https://doi.org/10.1016/j.jhydrol.2009.03.027.
Faridzad, M., Yang, T., Hsu, K.-L., Sorooshian, S., & Xiao, C. (2018). Rainfall frequency analysis for ungauged regions using remotely sensed precipitation information. Journal of Hydrology, 563, 123–142. https://doi.org/10.1016/j.jhydrol.2018.05.071.
Gado, T. A., Hsu, K.-L., & Sorooshian, S. (2017). Rainfall frequency analysis for ungauged sites using satellite precipitation products. Journal of Hydrology, 554, 646–665. https://doi.org/10.1016/j.jhydrol.2017.09.043.
Gao, Y. C., & Liu, M. F. (2013). Evaluation of high-resolution satellite precipitation products using rain gauge observations over the Tibetan Plateau. Hydrology and Earth System Sciences, 17, 837–849. https://doi.org/10.5194/hess-17-837-2013,2013.
Gebremichael, M., Bitew, M. M., Hirpa, F. A., & Tesfay, G. N. (2014). Accuracy of satellite rainfall estimates in the Blue Nile Basin: Lowland plain versus highland mountain. Water Resources Research, 50, 8775–8790. https://doi.org/10.1002/2013WR014500.
Gosset, M., Viarre, J., Quantin, G., & Alcoba, M. (2013). Evaluation of several rainfall products used for hydrological applications over West Africa using two high-resolution gauge networks. Quarterly Journal of the Royal Meteorological Society, 139, 923–940. https://doi.org/10.1002/qj.2130.
Gutowski, W. J., Jr., Decker, S. G., Donavon, R. A., Pan, Z., Arritt, R. W., & Takle, E. S. (2003). Temporal–spatial scales of observed and simulated precipitation in central U.S. climate. J. Climate, 16, 3841–3847. https://doi.org/10.1175/1520-0442(2003)016<3841:TSOOAS>2.0.CO;2.
Habib, E., Ciach, G. J., & Krajewski, W. F. (2004). A method for filtering out raingauge representativeness errors from the verification distributions of radar and raingauge rainfall. Advances in Water Resources, 27, 967–980. https://doi.org/10.1016/j.advwatres.2004.08.003.
Hirose, M., Oki, R., Short, D. A., & Nakamura, K. (2009). Regional characteristics of scale-based precipitation systems from ten years of TRMM PR data. Journal of the Meteorological Society of Japan, 87A, 353–368. https://doi.org/10.2151/jmsj.87A.353.
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, 95, 701–722. https://doi.org/10.1175/BAMS-D-13-00164.1.
Huffman, G. J., Adler, R. F., Morrissey, M., Bolvin, D. T., Curtis, S., Joyce, R., McGavock, B., & Susskind, J. (2001). Global precipitation at one-degree daily resolution from multi-satellite observations. Journal of Hydrometeorology, 2, 36–50. https://doi.org/10.1175/1525-7541(2001)002<0036:GPAODD>2.0.CO;2.
Huffman, G. J., Adler, R. F., Bolvin, D. T., Gu, G., Nelkin, E. J., Bowman, K., Hong, Y., Stocker, E. F., & Wolf, D. B. (2007). The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of Hydrometeorology, 8, 38–55. https://doi.org/10.1175/JHM560.1.
Huffman, G. J., Bolvin, D. T, Braithwaite, D., Hsu, K., Joyce, R., Kidd, C., Nelkin, E. J., Sorooshian, S., Tan, J., & Xie, P. (2018, February 2018). NASA Global Precipitation Measurement (GPM) Integrated MultisatellitE Retrievals for GPM (IMERG). IMERG Algorithm Theoretical Basis Document (ATBD), version 5.2, 35 pp. Available at https://pmm.nasa.gov/sites/default/files/document_files/IMERG_ATBD_V5.2_0.pdf. Last Accessed 21 Nov 2018.
Jiang, H., & Zipser, E. D. (2010). Contribution of tropical cyclones to global precipitation from eight seasons of TRMM data: Regional, seasonal, and interannual variations. Journal of Climate, 23, 1526–1543. https://doi.org/10.1175/2009JCLI3303.1.
Jiang, D., Zhang, H., & Li, R. (2017). Performance evaluation of TMPA version 7 estimates for precipitation and its extremes in Circum-Bohai-Sea region, China. Theoretical and Applied Climatology, 130, 1021–1033. https://doi.org/10.1007/s00704-016-1929-0.
Joyce, R., Janowiak, J., Arkin, P., & Xie, P. (2004). CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. Journal of Hydrometeorology, 5, 487–503. https://doi.org/10.1175/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2.
Kachi, M., Oki, R., Shimizu, S., & Kojima, M. (2006, November 13–14). Global Precipitation Measurement (GPM) mission and its application for flood monitoring. In Proceedings of the SPIE, conference on GEOSS and next-generation sensors and missions, Goa, India, 6407, 64070A. https://doi.org/10.1117/12.694043.
Katiraie-Boroujerdy, P.-S., Asanjan, A. A., Hsu, K.-L., & Sorooshian, S. (2017a). Intercomparison of PERSIANN-CDR and TRMM-3B42V7 precipitation estimates at monthly and daily time scales. Atmospheric Research, 193, 36–49. https://doi.org/10.1016/j.atmosres.2017.04.005.
Katiraie-Boroujerdy, P.-S., Ashouri, H., Hsu, K.-L., & Sorooshian, S. (2017b). Trends of precipitation extreme indices over a subtropical semi-arid area using PERSIANN-CDR. Theoretical and Applied Climatology, 130, 249–260. https://doi.org/10.1007/s00704-016-1884-9.
Keim, B. D., Muller, R. A., & Stone, G. W. (2007). Spatiotemporal patterns and return periods of tropical storm and hurricane strikes from Texas to Maine. Journal of Climate, 20, 3498–3509. https://doi.org/10.1175/JCLI4187.1.
Kidd, C., Levizzani, V., & Laviola, S. (2010). Quantitative precipitation estimation from earth observation satellites. In F. Y. Testik, & M. Gebremichael (Eds.), Rainfall: State of the science (Geophysical monograph, Vol. 161, pp. 127–158). American Geophysical Union. https://doi.org/10.1029/2009GM000920.
Kirschbaum, D., Adler, R. F., Adler, D., Peters-Lidard, C., & Huffman, G. J. (2012). Global distribution of extreme precipitation and high-impact landslides in 2010 relative to previous years. Journal of Hydrometeorology, 13, 1536–1551. https://doi.org/10.1175/JHM-D-12-02.1.
Koriche, S. A., & Rientjes, T. H. M. (2016). Application of satellite products and hydrological modelling for flood early warning. Physics and Chemistry of the Earth, 93, 12–23. https://doi.org/10.1016/j.pce.2016.03.007.
Levizzani, V., Laviola, S., Cattani, E., & Costa, M. J. (2013). Extreme precipitation on the island of Madeira on 20 February 2010 as seen by satellite passive microwave sounders. European Journal of Remote Sensing, 46, 475–489. https://doi.org/10.5721/EuJRS20134628.
Libertino, A., Sharma, A., Lakshmi, V., & Claps, P. (2016). Global assessment of the timing of extreme rainfall from TRMM and GPM for improving hydrologic design. Environmental Research Letters, 11, 054003. https://doi.org/10.1088/1748-9326/11/5/054003.
Liu, C. T., & Zipser, E. J. (2015). The global distribution of largest, deepest, and most intense precipitation systems. Geophysical Research Letters, 42, 3591–3595. https://doi.org/10.1002/2015GL063776.
Lockhoff, M., Zolina, O., Simmer, C., & Schulz, J. (2014). Evaluation of satellite-retrieved extreme precipitation over Europe using gauge observations. Journal of Climate, 27(17), 607–623. https://doi.org/10.1175/JCLI-D-13-00194.1.
Marra, F., Morin, E., Peleg, N., Mei, Y. W., & Anagnostou, E. N. (2017). Intensity-duration-frequency curves from remote sensing rainfall estimates: Comparing satellite and weather radar over the eastern Mediterranean. Hydrology and Earth System Sciences, 21, 2389–2404. https://doi.org/10.5194/hess-21-2389-2017.
Menne, M. J., Durre, I., Vose, S., Gleason, B. E., & Houston, T. G. (2012). An overview of the global historical climatology network-daily database. Journal of Atmospheric and Oceanic Technology, 29, 897–910. https://doi.org/10.1175/JTECH-D-11-00103.1.
Nastos, P. T., Kapsomenakis, J., & Douvis, K. C. (2013). Analysis of precipitation extremes based on satellite and high-resolution gridded data set over Mediterranean basin. Atmospheric Research, 131, 46–59. https://doi.org/10.1016/j.atmosres.2013.04.009.
National Research Council (NRC). (1994). Estimating bounds on extreme precipitation events – A brief assessment (p. 30). Washington, DC: National Academy Press. https://doi.org/10.17226/9195.
Nayak, M. A., & Villarini, G. (2018). Remote sensing-based characterization of rainfall during atmospheric rivers over the Central United States. Journal of Hydrology, 556, 1038–1049. https://doi.org/10.1016/j.jhydrol.2016.09.039.
Nesbitt, S. W., & Zipser, E. J. (2003). The diurnal cycle of rainfall and convective intensity according to three years of TRMM measurements. Journal of Climate, 16, 1456–1475. https://doi.org/10.1175/1520-0442-16.10.1456.
Nesbitt, S. W., & Anders, A. M. (2009). Very high-resolution precipitation climatologies from the Tropical Rainfall Measuring Mission precipitation radar. Geophysical Research Letters, 36, L15815. https://doi.org/10.1029/2009GL038026.
Nguyen, P., Ombadi, M., Sorooshian, S., Hsu, K.-L., 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, 22, 5801–5816. https://doi.org/10.5194/hess-22-58-1-2018.
Ombadi, M., Nguyen, P., Sorooshian, S., & Hsu, K.-L. (2018). Developing Intensity-Duration-Frequency (IDF) curves from satellite-based precipitation: Methodology and evaluation. Water Resources Research, 54, 7752–7766. https://doi.org/10.1029/2018WR022929.
Panegrossi, G., Casella, D., Dietrich, S., Marra, A. C., Sanò, P., Mugnai, A., Baldini, L., Roberto, N., Adirosi, E., Cremonini, R., Bechini, R., Vulpiani, G., Petracca, M., & Porcù, F. (2016). Use of the GPM constellation for monitoring heavy precipitation events over the Mediterranean region. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9, 2733–2753. https://doi.org/10.1109/JSTARS.2016.2520660.
Pombo, S., & de Oliveira, R. P. (2015). Evaluation of extreme precipitation estimates from TRMM in Angola. Journal of Hydrology, 523, 663–679. https://doi.org/10.1016/j.jhydrol.2015.02.014.
Prakash, S., Mahesh, C., Gairola, R. M., & Pal, P. K. (2012). Comparison of high-resolution TRMM-based precipitation products during tropical cyclones in the North Indian Ocean. Natural Hazards, 61, 689–701. https://doi.org/10.1007/s11069-011-0055-7.
Prakash, S., Mitra, A. K., Pai, D. S., & AghaKouchak, A. (2016). From TRMM to GPM: How well can heavy rainfall be detected from space? Advances in Water Resources, 88, 1–7. https://doi.org/10.1016/j.advwatres.2015.11.008.
Prasanna, V. (2016). Heavy precipitation characteristics over India during the summer monsoon season using rain gauge, satellite and reanalysis products. Natural Hazards, 83, 253–292. https://doi.org/10.1007/s11069-016-2315-z.
Prat, O. P., & Barros, A. P. (2010). Assessing satellite-based precipitation estimates in the Southern Appalachian Mountains using rain gauges and TRMM PR. Advances in Geosciences, 25, 143–153. https://doi.org/10.5194/adgeo-25-143-2010.
Prat, O. P., & Nelson, B. R. (2013a). Precipitation contribution of tropical cyclones in the Southeastern United States from 1998 to 2009 using TRMM satellite data. Journal of Climate, 26, 1047–1062. https://doi.org/10.1175/JCLI-D-11-00736.1.
Prat, O. P., & Nelson, B. R. (2013b). Mapping the world’s tropical cyclone rainfall contribution over land using the TRMM multi-satellite precipitation analysis. Water Resources Research, 49, 7236–7254. https://doi.org/10.1002/wrcr.20527.
Prat, O. P., & Nelson, B. R. (2014). Characteristics of annual, seasonal, and diurnal precipitation in the Southeastern United States derived from long-term remotely sensed data. Atmospheric Research, 144, 4–20. https://doi.org/10.1016/j.atmosres.2013.07.022.
Prat, O. P., & Nelson, B. R. (2015). Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002–2012). Hydrology and Earth System Sciences, 19, 2037–2056. https://doi.org/10.5194/hess-19-2037-2015.
Prat, O. P., & Nelson, B. R. (2016). On the link between tropical cyclones and daily rainfall extremes derived from global satellite observations. Journal of Climate, 29, 6127–6135. https://doi.org/10.1175/JCLI-D-16-0289.1.
Prat, O. P., Nelson, B. R., Nick, E., & Ferraro, R. R. (2017, December 11–15). Evaluation of daily extreme precipitation derived from long-term global satellite Quantitative Precipitation Estimates (QPEs). Abstract H53Q-06. 2017, AGU Fall Meeting, New Orleans, LA, USA.
Rapp, A. D., Peterson, A. G., Frauenfeld, O. W., Quiring, S. M., & Roark, E. B. (2014). Climatology of storm characteristics in Costa Rica using the TRMM precipitation radar. Journal of Hydrometeorology, 15, 2615–2633. https://doi.org/10.1175/JHM-D-13-0174.1.
Rasmussen, K. L., & Houze, R. A. (2011). Orogenic convection in subtropical South America as seen by the TRMM satellite. Monthly Weather Review, 139, 2399–2420. https://doi.org/10.1175/MWR-D-10-05006.1.
Rasmussen, K. L., Choi, S. L., Zuluaga, M. D., & Houze, R. A. (2013). TRMM precipitation bias in extreme storms in South America. Geophysical Research Letters, 40, 3457–3461. https://doi.org/10.1002/grl.50651.
Ricko, M., Adler, R. F., & Huffman, G. J. (2016). Climatology and interannual variability of quasi-global intense precipitation using satellite observations. Journal of Climate, 29, 5447–5468. https://doi.org/10.1175/JCLI-D-15-0662.1.
Romatschke, U., Medina, S., & Houze, R. A. (2010). Regional, seasonal, and diurnal variations of extreme convection in the South Asian region. Journal of Climate, 23, 419–439. https://doi.org/10.1175/2009JCLI3140.1.
Shepherd, J. M., Grundstein, A., & Mote, T. L. (2007). Quantifying the contribution of tropical cyclones to extreme rainfall along the coastal southeastern United States. Geophysical Research Letters, 34, L23810. https://doi.org/10.1029/2007GL031694.
Skofronick-Jackson, G., Petersen, W. A., Berg, W., Kidd, C., Stocker, E. F., Kirschbaum, D. B., Kakar, R., Braun, S. A., Huffman, G. J., Iguchi, T., Kirstetter, P. E., Kummerow, C., Meneghini, R., Oki, R., Olson, W. S., Takayabu, Y. N., Furukawa, K., & Wilheit, T. (2017). The global precipitation measurement (GPM) mission for science and society. Bulletin of the American Meteorological Society, 98, 1679–1695. https://doi.org/10.1175/BAMS-D-1500306.1.
Su, J. B., Lu, H. S., Wang, J. Q., Sadeghi, A. M., & Zhu, Y. H. (2017). Evaluating the applicability of four latest satellite-gauge combined precipitation estimates for extreme precipitation and streamflow predictions over the upper Yellow River basins in China. Remote Sensing, 9, 1176. https://doi.org/10.3390/rs9111176.
Su, X. L., Shum, C. K., & Luo, Z. C. (2018). Evaluating IMERG V04 final run for monitoring three heavy rain events over mainland China in 2016. IEEE Geoscience and Remote Sensing Letters, 15, 444–448. https://doi.org/10.1109/LGRS.2018.2793897.
Sun, Q., Miao, C., Duan, Q., Ashouri, H., Sorooshian, S., & Hsu, K.-L. (2018). A review of global precipitation data sets: Data sources, estimation, and intercomparisons. Reviews of Geophysics, 56, 79–107. https://doi.org/10.1002/2017RG000574.
Tan, M. L., & Santo, H. (2018). Comparison of GPM IMERG, TMPA 3B42 and PERSIANN-CDR satellite precipitation products over Malaysia. Atmospheric Research, 202, 63–76. https://doi.org/10.1016/j.atmosres.2017.11.006.
Taylor, C. M., Belusic, D., Guichard, F., Arker, D. J. P., Vischel, T., Bock, O., Harris, P. P., Janicot, S., Klein, C., & Panthou, G. (2017). Frequency of extreme Sahelian storms tripled since 1982 in satellite observations. Nature, 544, 475–478. https://doi.org/10.1038/nature22069.
Tekeli, A. E., & Fouli, H. (2016). Evaluation of TRMM satellite-based precipitation indexes for flood forecasting over Riyadh City, Saudi Arabia. Journal of Hydrology, 541, 471–479. https://doi.org/10.1016/j.jhydrol.2016.01.014.
Villarini, G., Smith, J. A., Baeck, M. L., Marchok, T., & Vecchi, G. A. (2011). Characterization of rainfall distribution and flooding associated with U.S. landfalling tropical cyclones: Analyses of Hurricanes Frances, Ivan, and Jeanne (2004). Journal of Geophysical Research, 116, D23116. https://doi.org/10.1029/2011JD016175.
Wolff, D. B., & Fisher, B. L. (2008). Comparisons of instantaneous TRMM ground validation and satellite rain-rate estimates at different spatial scales. Journal of Applied Meteorology and Climatology, 47(8), 2215–2237. https://doi.org/10.1175/2008JAMC1875.1.
World Meteorological Organization (WMO). (2009). Manual on estimation of Probable Maximum Precipitation (PMP) (3rd edn.), WMO-No. 1045, Geneva, Switzerland, 291 pp. Available at https://library.wmo.int/pmb_ged/wmo_1045_en.pdf
Xie, P., Joyce, R., Wu, S., Yoo, S.-H., Yarosh, Y., Sun, F., & Lin, R. (2017). Reprocessed, bias-corrected CMORPH global high-resolution precipitation estimates from 1998. Journal of Hydrometeorology, 18, 1617–1641. https://doi.org/10.1175/JHM-D-16-0168.1.
Yang, Y., Tang, G. Q., Lei, X. H., Hong, Y., & Yang, N. (2018). Can satellite precipitation products estimate probable maximum precipitation: A comparative investigation with gauge data in the Dadu River basin. Remote Sensing, 10, 41. https://doi.org/10.3390/rs10010041.
Yong, B., Chen, B., Gourley, J. J., Ren, L., Hong, Y., Chen, X., Wang, W., Chen, S., & Gong, L. (2014). Intercomparison of the Version-6 and Version-7 TMPA precipitation products over high and low latitudes basins with independent gauge networks: Is the newer version better in both real-time and post-real-time analysis for water resources and hydrologic extremes? Journal of Hydrology, 508, 77–87. https://doi.org/10.1016/j.jhydrol.2013.10.050.
Zhang, Y., Hong, Y., Wang, X. G., Gourley, J. J., Xue, X. W., Saharia, M., Ni, G. H., Wang, G. L., Huang, Y., Chen, S., & Tang, G. Q. (2015). Hydrometeorological analysis and remote sensing of extremes: Was the July 2012 Beijing flood event detectable and predictable by global satellite observing and global weather modeling systems? Journal of Hydrometeorology, 16, 381–395. https://doi.org/10.1175/JHM-D-14-0048.1.
Zhou, Y. P., Lau, W. K. M., & Huffman, G. J. (2015). Mapping TRMM TMPA into average recurrence interval for monitoring extreme precipitation events. Journal of Applied Meteorology and Climatology, 54, 979–995. https://doi.org/10.1175/JAMC-D-14-0269.1.
Zipser, E. J., Cecil, D. J., Liu, C., Nesbitt, S. W., & Yorty, D. P. (2006). Where are the most intense thunderstorms on earth? Bulletin of the American Meteorological Society, 87(8), 1057–1071. https://doi.org/10.1175/BAMS-87-8-1057.
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Prat, O.P., Nelson, B.R. (2020). Satellite Precipitation Measurement and Extreme Rainfall. In: Levizzani, V., Kidd, C., Kirschbaum, D., Kummerow, C., Nakamura, K., Turk, F. (eds) Satellite Precipitation Measurement. Advances in Global Change Research, vol 69. Springer, Cham. https://doi.org/10.1007/978-3-030-35798-6_16
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