Articles | Volume 30, issue 4
https://doi.org/10.5194/npg-30-457-2023
https://doi.org/10.5194/npg-30-457-2023
Research article
 | 
23 Oct 2023
Research article |  | 23 Oct 2023

Comparative study of strongly and weakly coupled data assimilation with a global land–atmosphere coupled model

Kenta Kurosawa, Shunji Kotsuki, and Takemasa Miyoshi

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Subject: Predictability, probabilistic forecasts, data assimilation, inverse problems | Topic: Climate, atmosphere, ocean, hydrology, cryosphere, biosphere | Techniques: Simulation
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Cited articles

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Bi, H., Ma, J., Zheng, W., and Zeng, J.: Comparison of soil moisture in GLDAS model simulations and in situ observations over the Tibetan Plateau, J. Geophys. Res.-Atmos., 121, 2658–2678, https://doi.org/10.1002/2015JD024131, 2016. 
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This study aimed to enhance weather and hydrological forecasts by integrating soil moisture data into a global weather model. By assimilating atmospheric observations and soil moisture data, the accuracy of forecasts was improved, and certain biases were reduced. The method was found to be particularly beneficial in areas like the Sahel and equatorial Africa, where precipitation patterns vary seasonally. This new approach has the potential to improve the precision of weather predictions.