4.6 Article

Land-Atmosphere Coupling in CORDEX-Africa: Hindcast Regional Climate Simulations

Journal

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
Volume 123, Issue 19, Pages 11048-11067

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2018JD028378

Keywords

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Funding

  1. Portuguese Foundation for Science and Technology [PTDC/GEOMET/7078/2014]
  2. project FCT [UID/GEO/50019/2013]

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Soil moisture is one of the most important variables of the climate system as it constrains evapotranspiration, affecting the surface energy and water balance. It is of particular importance over transition regions between humid and dry climates as lower evapotranspiration rates lead to higher surface air temperatures thought strong soil moisture-temperature coupling. A new and more extensive evaluation of the surface energy balance, for the Africa Coordinated Regional Downscaling Experiment, is performed for hindcast simulations, where different Regional Climate Models are driven by ERA-Interim reanalysis (1990-2008). A new validation is carried out, with Regional Climate Models displaying a good agreement with observations. However, large biases are found over the Sahel and southern Africa for precipitation. All models tend to underestimate maximum temperature, whereas minimum temperature is overestimated for large regions. A multimodel mean ensemble is found to outperform individual models in almost all situations, representing the best estimate of present climate. The seasonal coupling strength as determined by a correlation between latent and sensible heat fluxes indicates Sahel and western Africa as strong coupling for boreal and austral summer, respectively. Also, the strong coupling areas match the transition regions identified by the intermediate values of the evaporative fraction, varying in the spatial extent. Additionally, a new soil moisture-temperature coupling metric is introduced, which highlights the regions where higher temperatures are influenced by evaporative stress. Therefore, this metric relates extreme daily maximum temperature with latent heat flux and is computed for monthly time scales, incorporating information from the recent past.

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