Remote Sensing of Water-Related Hazards. Группа авторов

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capture rainstorms and guide flood warning for the 2016 summer in south China? IEEE Geoscience and Remote Sensing Letters, 14(8), 1208–1212. https://doi.org/10.1109/lgrs.2017.2702137

      33 Tang, G., Clark, M. P., Papalexiou, S. M., Ma, Z., & Hong, Y. (2020). Have satellite precipitation products improved over last two decades? A comprehensive comparison of GPM IMERG with nine satellite and reanalysis datasets. Remote Sensing of Environment, 240, 111697. https://doi.org/10.1016/j.rse.2020.111697

      34 Trenberth, K. E., Dai, A., Rasmussen, R. M., & Parsons, D. B. (2003). The changing character of precipitation. Bulletin of the American Meteorological Society, 84(9), 1205–1218. https://doi.org/10.1175/BAMS‐84‐9‐1205

      35 Vionnet, V., Fortin, V., Gaborit, E., Roy, G., Abrahamowicz, M., Gasset, N., & Pomeroy, J. W. (2019). High‐resolution hydrometeorological modelling of the June 2013 flood in southern Alberta, Canada. Hydrology and Earth System Sciences Discussions, 1–36. https://doi.org/10.5194/hess‐2019‐152

      36 Wang, C., Tang, G., Han, Z., Guo, X., & Hong, Y. (2018). Global intercomparison and regional evaluation of GPM IMERG Version‐03, Version‐04 and its latest Version‐05 precipitation products: Similarity, difference and improvements. Journal of Hydrology, 564, 342–356. https://doi.org/10.1016/j.jhydrol.2018.06.064

      37 Yang, D., Kane, D., Zhang, Z., Legates, D., & Goodison, B. (2005). Bias corrections of long‐term (1973‐2004) daily precipitation data over the northern regions. Geophysical Research Letters, 32(19). https://doi.org/10.1029/2005gl024057

      38 Yong, B., Ren, L., Hong, Y., Gourley, J. J., Tian, Y., Huffman, G. J., et al. (2013). First evaluation of the climatological calibration algorithm in the real‐time TMPA precipitation estimates over two basins at high and low latitudes. Water Resources Research, 49(5), 2461–2472. https://doi.org/10.1002/wrcr.20246

      39 Zeng, Z., Tang, G., Hong, Y., Zeng, C., & Yang, Y. (2017). Development of an NRCS curve number global dataset using the latest geospatial remote sensing data for worldwide hydrologic applications. Remote Sensing Letters, 8(6), 528–536. https://doi.org/10.1080/2150704x.2017.1297544

      40 Zhang, Y., Hong, Y., Wang, X., Gourley, J. J., Xue, X., Saharia, M., et al. (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(1), 381–395. https://doi.org/10.1175/jhm‐d‐14‐0048.1

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