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Dynamic and Thermodynamic Contributions to Late 21st Century Projected Rainfall Change in the Congo Basin: Impact of a Regional Climate Model’s Formulation

Climate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, 20095 Hamburg, Germany
European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy
Laboratory for Environmental Modelling and Atmospheric Physics (LEMAP), Physics Department, University of Yaoundé 1, Yaoundé P.O. Box 812, Cameroon
Author to whom correspondence should be addressed.
Atmosphere 2023, 14(12), 1808;
Submission received: 13 November 2023 / Revised: 1 December 2023 / Accepted: 8 December 2023 / Published: 9 December 2023
(This article belongs to the Special Issue Simulation and Analysis of Hydroclimate)


Addressing the impacts of climate change requires, first of all, understanding the mechanisms driving changes, especially at the regional scale. In particular, policymakers and other stakeholders need physically robust climate change information to drive societal responses to a changing climate. This study analyses late 21st-century (2071–2100) precipitation projections for the Congo Basin under representative concentration pathway (RCP) 8.5, using the Rossby Centre Regional Climate Model (RCM) RCA4. Specifically, we examine the impact of the RCM formulation (reduction of turbulent mixing) on future change in seasonal mean precipitation by comparing the results of the modified model version (RCA4-v4) with those of the standard version (RCA4-v1) used in CORDEX (Coordinated Regional Climate Downscaling Experiment). The two RCM versions are driven by two global climate models participating in the Coupled Model Intercomparison Project phase 5 (CMIP5). The results show that seasonal precipitation is largely affected by modifications in the atmospheric column moisture convergence or divergence, and, in turn, associated with changes in the dynamic (ΔDY) and thermodynamic (ΔTH) components of the moisture-budget equation. Projected decreased precipitation in the dry seasons (December–January–February and June–July–August) is linked to increased moisture divergence driven by dynamic effects (changes in circulation), with most experiments showing ΔDY as the main contributor (>60%) to the total moisture budget. Overall, precipitation is projected to increase in the wet seasons (March–April–May and September–October–November), which can be attributed to both dynamic and thermodynamic effects, but with a larger thermodynamic contribution (changes in specific humidity, ΔTH > 45%), compared to the dynamic one (ΔDY > 40%). Through a comparison of the two model versions, we found that the formulation (reducing turbulent mixing) and boundary conditions (driving GCM) strongly influence precipitation projections. This result holds substantial value for ensuring the fitness of models for future projections intended for decision-makers.

1. Introduction

The formulation (including physical parameterization and tuning) of a climate model plays a paramount role in the representation of regional processes, especially those underpinning the rainfall system [1,2]. For instance, incorporating additional components of the Earth system, such as coupling with an oceanic model, can result in the significantly enhanced credibility of climate projections in regions where air–sea interaction is strong [3,4,5,6]; introducing aerosol interactions substantially influences regional patterns’ change of both temperature and precipitation [7,8]; neglecting the physiological response of plants to the increase in greenhouse gases in the atmosphere results in a substantial underestimation of extreme temperature increases across Europe [9]; mixing in stable boundary layers, in particular, the momentum mixing which has a strong impact on the surface heat, significantly modifies surface–atmosphere interactions [2,10].
To properly assess how formulations designed and validated using historical climatology can impact the future climate, it is essential to evaluate how the physical processes most relevant for a region’s climate are simulated, and how they are modified under future warming [11]. Such process-based evaluations and analyses are becoming more and more common, as they can provide insight into understanding the relevant processes driving e.g., the projected changes, and, hence, provide more confidence in the projections [12,13,14,15,16,17]. For instance, References [14,15] investigated processes driving changes in the Congo Basin in December-February (one of the dry seasons) and September-November (one of the wet seasons), respectively, using a set of coarse resolution global climate models (GCMs) participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5, [18]). They found that, in DJF, the region is projected to become wetter due to increased convection and changes in atmospheric patterns. In SON, the west experiences wetter conditions in the north and dri