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Influence of persistence and oceanic forcing on global soil moisture predictability

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Abstract

Soil moisture is a key variable of the land surface and its variations are an important issue in climate studies. In this study, we employed the Community Earth System Model (CESM) for 20 ensemble member simulations of the 50-year period from 1965 to 2014 and used canonical correlation analysis (CCA) and multiple regression to analyze the spatiotemporal characteristics of soil moisture predictability. The effects of soil moisture persistence and sea surface temperature (SST) as an external forcing on its predictability were analyzed. Results show that the soil moisture predictability due to its persistence is 1–2 months and considering SST as an external forcing can significantly increase its predictability. Regions that exhibit a significant increase in predictability are mainly tropical regions, North America and Western Asia during winter and spring. In tropical regions, SST increases the predictability of soil moisture by influencing the local surface temperature and precipitation. In other regions, the effects of SST on wind speed, cloud cover, and surface evaporation also contribute significantly to the increase in soil moisture predictability. The results were validated through the analysis based on soil moisture data from land data assimilation system and observed precipitation.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (41625019 and 41905075) and China Postdoctoral Science Foundation (2018M632335). The GLDAS soil moisture data were achieved from https://disc.gsfc.nasa.gov, the CESM model code can be achieved from https://svn-ccsm-models.cgd.ucar.edu/cesm1/release_tags/cesm1_2_2/, and the datasets used for running this model can be downloaded at https://svn-ccsm-inputdata.cgd.ucar.edu/trunk/inputdata/.

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  1. Key Laboratory of Meteorological Disaster, Ministry of Education (KLME) / International Joint Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology (NUIST), Nanjing, China

    Siguang Zhu, Haishan Chen, Xuan Dong & Jiangfeng Wei

  2. School of Atmospheric Sciences, NUIST, Nanjing, 210044, China

    Siguang Zhu, Haishan Chen, Xuan Dong & Jiangfeng Wei

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  1. Siguang Zhu
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Correspondence to Haishan Chen.

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Zhu, S., Chen, H., Dong, X. et al. Influence of persistence and oceanic forcing on global soil moisture predictability. Clim Dyn 54, 3375–3385 (2020). https://doi.org/10.1007/s00382-020-05184-8

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