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Publication Date
22 March 2019

Elucidating Observed Land Surface Feedbacks Across Sub-Saharan Africa

Subtitle
Observed African land surface feedbacks.
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Science

We developed and applied a statistical method to observational data that decomposed land surface feedbacks over sub-Saharan Africa into those driven by anomalies in soil moisture versus vegetation.

Impact

The study's results both deepen our understanding of observed terrestrial feedbacks on African climate and permit a rigorous evaluation of state-of-the-art coupled climate models.

Summary

This study examines the role of land surface forcings on sub-Saharan climate through the application of an advanced statistical method to an array of observational datasets.  By applying multiple datasets, data uncertainty and the robustness of assessed land surface feedbacks are considered.  Our prior approach is expanded to decompose the relative contribution of vegetation, soil moisture, and oceanic forcings; investigate the role of evapotranspiration partitioning in land surface feedbacks; and compare land surface feedbacks among four regions (Sahel, Greater Horn of Africa, West African monsoon region, and Congo).  Across sub-Saharan Africa, oceanic and terrestrial forcings impose a relatively comparable impact on year-round atmospheric conditions.  The land surface feedbacks are most pronounced across the semi-arid Sahel and Greater Horn of Africa, although with unique seasonality of such feedbacks between regions.  Moisture recycling is the dominant mechanism in these regions.  The direct feedback of soil moisture anomalies on atmospheric conditions outweighed that of leaf area index anomalies.  There is a clear need for more extensive observations of evapotranspiration, its partitioning, and soil moisture across sub-Saharan Africa, as these data uncertainties propagate into the reliability of assessed soil moisture-evapotranspiration feedbacks, particularly across the Sahel.  Successful decomposition of terrestrial feedbacks into those driven by soil moisture versus vegetation anomalies will facilitate detailed evaluation of state-of-the-art coupled climate models.

Point of Contact
Michael Notaro
Institution(s)
University of Wisconsin Madison
Funding Program Area(s)
Publication