Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 25, issue 1
Articles | Volume 25, issue 1
https://doi.org/10.5194/hess-25-359-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-359-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 1
Research article
 | 
21 Jan 2021
Research article |  | 21 Jan 2021

A two-stage blending approach for merging multiple satellite precipitation estimates and rain gauge observations: an experiment in the northeastern Tibetan Plateau

Yingzhao Ma, Xun Sun, Haonan Chen, Yang Hong, and Yinsheng Zhang

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Cited articles

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Bartsotas, N. S., Anagnostou, E. N., Nikolopoulos, E. I., and Kallos, G.: Investigating satellite precipitation uncertainty over complex terrain, J. Geophys. Res.-Atmos., 123, 5346–5369, 2018. 
Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles, D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25∘ global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data, Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, 2017. 
Cuo, L., Zhang, Y., Gao, Y., Hao, Z., and Cairang, L.: The impacts of climate change and land cover/use transition on the hydrology in the upper Yellow River Basin, China, J. Hydrol., 502, 37–52, 2013. 
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A two-stage blending approach is proposed for the data fusion of multiple satellite precipitation estimates (SPEs), which firstly reduces the systematic errors of original SPEs based on a Bayesian correction model and then merges the bias-corrected SPEs with a Bayesian weighting model. The model is evaluated in the warm season of 2010–2014 in the northeastern Tibetan Plateau. Results show that the blended SPE is greatly improved compared with the original SPEs, even in heavy rainfall events.
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