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The relationship between the Madden-Julian oscillation and the land surface soil moisture

MPG-Autoren
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Peng,  Jian
Terrestrial Remote Sensing / HOAPS, The Land in the Earth System, MPI for Meteorology, Max Planck Society;

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Loew,  Alexander
Terrestrial Remote Sensing / HOAPS, The Land in the Earth System, MPI for Meteorology, Max Planck Society;

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Crueger,  Traute
Climate Modelling, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;
A 2 - Climate Processes and Feedbacks, Research Area A: Climate Dynamics and Variability, The CliSAP Cluster of Excellence, External Organizations;

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Zitation

Peng, J., Loew, A., & Crueger, T. (2017). The relationship between the Madden-Julian oscillation and the land surface soil moisture. Remote Sensing of Environment, corr. proof, available online. doi:10.1016/j.rse.2017.07.004.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-002D-CC0A-8
Zusammenfassung
The impact of the Madden–Julian oscillation (MJO) on the global land surface soil moisture was explored in the study. The MJO index was calculated from long term 1997–2013 GPCP precipitation and ERA-Interim 850-hPa and 250-hPa zonal winds. The composites of soil moisture anomalies over eight MJO phases were mapped and analyzed. In order to distinguish the MJO signal with other patterns of climate variability, only MJO event days are used in the composites. In addition, the statistical significance of the anomaly composites is estimated using the Student's t-test. The MJO has been found to be the prominent source of the intraseasonal variation of the monsoon systems, which induces the variations of precipitation. Our results show that the variation of soil moisture between MJO phases also agrees well with the variation of the monsoon systems. In addition to the monsoon regions, the MJO also affects soil moisture over other areas such as East Africa. The relation between the soil moisture and precipitation anomaly composites across the MJO phases was also investigated. The results show that the variation of soil moisture over MJO phases is related to its connection to precipitation. In addition, large similarities were found between the GPCP-derived MJO index and the corresponding ESA CCI soil moisture composites, and ERA-Interim-derived MJO index and corresponding ERA-Interim soil moisture composites. This proves the feasibility of ERA-Interim datasets for MJO related studies. Owing to the different resolutions of the CCI and ERA-Interim soil moisture, CCI is more appropriate for regional and ERA-Interim dataset for large-scale MJO related analysis.