North Atlantic salinity as a predictor of Sahel rainfall
Schmitt, Raymond W.
Ummenhofer, Caroline C.
Karnauskas, Kristopher B.
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Water evaporating from the ocean sustains precipitation on land. This ocean-to-land moisture transport leaves an imprint on sea surface salinity (SSS). Thus, the question arises of whether variations in SSS can provide insight into terrestrial precipitation. This study provides evidence that springtime SSS in the subtropical North Atlantic ocean can be used as a predictor of terrestrial precipitation during the subsequent summer monsoon in Africa. Specifically, increased springtime SSS in the central to eastern subtropical North Atlantic tends to be followed by above-normal monsoon-season precipitation in the African Sahel. In the spring, high SSS is associated with enhanced moisture flux divergence from the subtropical oceans, which converges over the African Sahel and helps to elevate local soil moisture content. From spring to the summer monsoon season, the initial water cycling signal is preserved, amplified, and manifested in excessive precipitation. According to our analysis of currently available soil moisture data sets, this 3-month delay is attributable to a positive coupling between soil moisture, moisture flux convergence, and precipitation in the Sahel. Because of the physical connection between salinity, ocean-to-land moisture transport, and local soil moisture feedback, seasonal forecasts of Sahel precipitation can be improved by incorporating SSS into prediction models. Thus, expanded monitoring of ocean salinity should contribute to more skillful predictions of precipitation in vulnerable subtropical regions, such as the Sahel.
© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Science Advances 2 (2016): e1501588, doi:10.1126/sciadv.1501588.
Suggested CitationArticle: Li, Laifang, Schmitt, Raymond W., Ummenhofer, Caroline C., Karnauskas, Kristopher B., "North Atlantic salinity as a predictor of Sahel rainfall", Science Advances 2 (2016): e1501588, DOI:10.1126/sciadv.1501588, https://hdl.handle.net/1912/8102
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