Process-based assessment of the impact of reduced turbulent mixing on Congo Basin precipitation in the RCA4 Regional Climate Model

Abstract

In regions featuring strong convective activity (such as the Congo Basin, CB), turbulent mixing in the planetary boundary layer strongly affects the water budget. In this study, we use a process-based evaluation to assess the performance of the Rossby Centre Regional Climate Model (RCM) RCA4 in simulating the September-November CB rainfall, under conditions of strong and weak turbulent mixing. To this regard, results from two different versions of model are analysed: the version used in the COordinated Regional climate Downscaling EXperiment framework (RCA4-v1), and a modified version (RCA4-v4), in which turbulent mixing is reduced. Experiments are driven with boundary conditions from the ERA-Interim reanalysis. Results show that RCA4-v4 improves the CB rainfall climatology compared to RCA4-v1. This result is further related to the models' different representations of the relevant driving mechanisms and processes. The model version with a reduced turbulent mixing (RCA4-v4) shifts less moisture from the lower troposphere towards the free troposphere. As the shallow convective mixing is reduced (owing to the reduction of the turbulent mixing), lower layers are moistened, and low level cloud fraction increases over Equatorial Africa. This increase is stronger over the West Equatorial African (WEA) coast than over the CB. The result is that surface solar radiation decreases more over the WEA coast than over the CB, which would result in a lower surface temperature over WEA coast than over the CB. An enhanced pressure gradient between the WEA and the CB is created as a result, thus enhancing the Congo low level cell, and low level westerlies (LLWs). LLWs are faster, meaning that more moisture flows through the CB Cell, is uplifted in eastern up-branch, and enters African Easterly Jets (AEJs), which, in turn, are intensified due to the increase in the surface temperature gradient. Intensification of the CB cell and mesoscale convective systems (MCSs) is the cause of the higher rainfall and is what improves the CB rainfall climatology in RCA4-v4. In addition, the increase in rainfall causes an increase in soil moisture in RCA4-v4 in both the north and south of the CB. Higher soil moisture does not affect evaporation in the north as soils are already saturated in RCA4-v1. However, the increase in rainfall increases soil moisture in the south in RCA4-v4, which increases evaporation as soils were initially unsaturated. This higher evaporation is exported out of the basin towards Southern Africa, does not recirculate through the Cell, and does not therefore contribute to further improving the rainfall bias over the Congo. Our results show that reducing turbulent mixing results in a better representation of the dynamics of the climate system over the CB and, in turn, improved precipitation.

What Can We Know About Recent Past Precipitation Over Africa? Daily Characteristics of African Precipitation From a Large Ensemble of Observational Products for Model Evaluation

“…Similarly to Pendergrass et al (2020) we argue that evaluating model performances would greatly benefit from the use of process-oriented, regime-oriented, and use-inspired metrics. For instance, process-based model evaluation, that is, the analysis of the underlying drivers and physical processes (e.g., Pinto et al, 2018;Tamoffo et al, 2019Tamoffo et al, , 2021) is a promising approach, but such evaluation relies on reanalysis data sets as reference (given the need of three-dimensional fields of several variables), whose performances over tropical Africa are largely dependent on their representation of the hydrological cycle (Hua et al, 2019).…”

“…Reliable observational data sets are also of paramount importance in the evaluation of climate models (e.g., Maidment et al., 2015; Tapiador et al., 2017). In fact, both general circulation models (GCMs) and regional climate models (RCMs) still show limitations in simulating various aspects of the African precipitation (e.g., Akinsanola et al., 2018; Dosio et al., 2015; Gbobaniyi et al., 2014; Gibba et al., 2018; Kim et al., 2014; Kisembe et al., 2019; Nikulin et al., 2012; Panitz et al., 2014; Sow et al., 2020; Tamoffo et al., 2020, 2021) and large uncertainties still remain over the projected precipitation change, in particular over West and Central Africa (Dosio & Panitz, 2016; Dosio et al., 2019, 2020; Klutse et al., 2018; Mba et al., 2018; Monerie et al., 2017; Tamoffo et al., 2019). The models ability at reproducing the physical processes and drivers of the African climate is a task even more challenging when available observational data sets are scarce and incomplete.…”

Projected future daily characteristics of African precipitation based on global (CMIP5, CMIP6) and regional (CORDEX, CORDEX-CORE) climate models

“…In the framework of the COordinated Regional-climate Downscaling EXperiment, (CORDEX, Giorgi and Gutowski 2015), Regional Climate Models (RCMs) have been used to dynamically downscale the results of CMIP5 GCMs to generate high-resolution (0.44°, around 50 km) historical and future climate projections over Africa. CORDEX future climate projections for Africa have been analyzed in several studies (Laprise et al 2013;Haensler et al 2013;Saeed et al 2013;Mariotti et al 2014;Dosio and Panitz 2016;Pinto et al 2016;Diallo et al 2016;Akinsanola and Zhou 2019;Endris et al 2019;Dosio et al 2019;Bichet et al 2020;Tamoffo et al 2021;Mengistu et al 2021;among others). Although CORDEX produced a relatively large ensemble (> 20) of multi GCM-RCM simulations, most of these studies are based on the results of a single RCM downscaling an ensemble of GCMs, or on a small ensemble of RCMs downscaling a small ensemble of GCMs.…”

The ERA5's diurnal cycle of low-level clouds over Western Central Africa during June–September: Dynamic and thermodynamic processes

“…Most of the studies dedicated to the climate of Central Africa revolve around numerical simulations with the main objectives of evaluating climate models (Mba et al 2018;Fotso et al 2016Fotso et al , 2017Sonkoue et al 2018;Tamoffo et al 2019a). For instance, Tamoffo et al (2021) used process-based evaluations to assess the performance of two versions of Rossby Centre Regional Climate Model (RCA4) in simulating rainfall over Congo Basin. The two versions are RCA4 version 1 (RCA4-v1) with strong turbulent mixing and the modified one, RCA4 version 4 (RCA4-v4), with reduced turbulent mixing.…”