Articles | Volume 17, issue 7
https://doi.org/10.5194/gmd-17-3025-2024
https://doi.org/10.5194/gmd-17-3025-2024
Development and technical paper
 | 
16 Apr 2024
Development and technical paper |  | 16 Apr 2024

The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2

Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang

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Cited articles

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Balmaseda, M. A., Alves, O. J., Arribas, A., Awaji, T., Behringer, D. W., Ferry, N., Fujii, Y., Lee, T., Rienecker, M., Rosati, T., and Stammer, D.: Ocean initialization for seasonal forecasts, Oceanography, 22, 154–159, https://doi.org/10.5670/oceanog.2009.73, 2009. 
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Boer, G. J., Smith, D. M., Cassou, C., Doblas-Reyes, F., Danabasoglu, G., Kirtman, B., Kushnir, Y., Kimoto, M., Meehl, G. A., Msadek, R., Mueller, W. A., Taylor, K. E., Zwiers, F., Rixen, M., Ruprich-Robert, Y., and Eade, R.: The Decadal Climate Prediction Project (DCPP) contribution to CMIP6, Geosci. Model Dev., 9, 3751–3777, https://doi.org/10.5194/gmd-9-3751-2016, 2016. 
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Short summary
Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
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