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Publication Date
5 February 2018

Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model



Generalized Equilibrium Feedback Assessment (GEFA) is a potentially valuable multivariate statistical tool for extracting vegetation feedbacks to the atmosphere in either observations or coupled Earth System Models. The reliability of GEFA at capturing the terrestrial impacts on regional climate is demonstrated here using the National Center for Atmospheric Research - Community Earth System Model (CESM), with a focus on North Africa. The feedback is assessed statistically by applying GEFA to output from a fully coupled control run. In order to reduce the sampling error caused by short data records, the traditional full GEFA is refined through stepwise GEFA by dropping unimportant forcings. Two ensembles of dynamical experiments, against which GEFA-based vegetation feedbacks are evaluated, are developed for the Sahel or West African monsoon region. In these dynamical experiments, regional leaf area index (LAI) is modified either alone or in conjunction with soil moisture, with the latter runs motivated by strong regional soil moisture-LAI coupling. Stepwise GEFA boasts higher consistency between statistically- and dynamically-assessed atmospheric responses to land surface anomalies than full GEFA, especially with short data records. GEFA-based atmospheric responses are more consistent with the coupled soil moisture-LAI experiments, indicating that GEFA is assessing the combined impacts of coupled vegetation and soil moisture. Both the statistical and dynamical assessments reveal a negative vegetation-rainfall feedback in the Sahel, associated with an atmospheric stability mechanism, versus a weaker, positive feedback in the West African monsoon region, associated with a moisture recycling mechanism, in CESM.

“Validation Of A Statistical Methodology For Extracting Vegetation Feedbacks: Focus On North African Ecosystems In The Community Earth System Model”. 2018. Journal Of Climate 31. doi:10.1175/JCLI-D-17-0220.1.
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