Evaluating land-atmosphere interactions controlling precipitation over Central Africa in CESM

Tropical precipitation is closely linked to the land surface through the exchange of water and energy between the surface and atmosphere, regulating boundary layer moistening and convective instability. In Central Africa, particularly the Congo Basin, the extensive rainforest contributes a substantial amount of moisture to the atmosphere through evaporation, enhancing convective activity and shaping the region’s seasonal and daily rainfall. In this study, we evaluate the ability of the Community Earth System Model (CESM) can represent these coupled land-atmosphere-convection processes and their control on precipitation across Central Africa.

 

CESM estimates of rainfall over the past 30 years are compared with multiple observational products (including IMERG, CHIRPS, and MSWEP) to assess whether the model reproduces the magnitude, variability, and spatial distribution of rainfall at daily and seasonal timescales. The same evaluation framework is applied to evaporation, with CESM estimates assessed against L-SAF, CERES, X-base, and GLEAM across consistent spatial and temporal scales. Beyond surface rainfall and evaporation, we analyse CESM’s column-integrated atmospheric moisture budget over the Congo Basin, including diagnostics of convective mass flux, against ERA5, to quantify the contributions of local evaporation, large-scale moisture convergence, and convective transport to precipitation. This approach allows us to identify whether CESM rainfall biases originate from misrepresented land surface fluxes, deficiencies in hydrometeorological parameterisation, or errors in large-scale moisture transport.

 

The analysis is conducted on both daily and seasonal timescales, to separate fast land-atmosphere coupling from slower circulation-driven controls. By combining evaluations of precipitation and evaporation with a process-oriented decomposition of moisture supply and convective response, this work assesses whether CESM can reliably represent land-driven rainfall variability, moisture recycling, and the emergence of hydroclimatic extremes in Central Africa.