Process‐Based Analysis of the Added Value of Dynamical Downscaling Over Central Africa

Abstract

In this study, nine global climate models (GCMs) and corresponding downscaled runs by means of the regional climate model (RCM) RCA4 are used to investigate added value (AV) in precipitation and its some drivers over Central Africa (CA). By employing a process‐based analysis approach, we intercompare abilities of RCM to those of driving GCMs in representing the total atmospheric moisture flux convergence (TMFC), moisture transport, and African Easterly Jets (AEJs). Results indicate that simulations with highest AVs in the precipitation climatology also show improvements in the representation of the TMFC and AEJs. Degraded precipitation due to the downscaling is associated with deterioration of at least two of three analyzed mechanisms, and sometimes there is inconsistent AVs between precipitation and related drivers. This sustains that a realistic representation of the moisture transport and atmospheric circulation is of great importance for the correct simulation of present (and, consequently, future) precipitation over CA.

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

“…As mentioned previously, the ability of RCMs to add value to the driving GCM in simulating precipitation characteristics (especially higher order statistics) has been investigated in several studies (e.g. Dosio et al 2015;Pinto et al 2016;Nikiema et al 2017;Fotso-Nguemo et al 2017;Gibba et al 2019;Tamoffo et al 2020;Gnitou et al 2021). It must be noted that added value, i.e.…”

“…In fact, it is important to assess whether and to what extent the somehow limited size of the RCMs ensembles (CORDEX and, specially, CORE) is able to capture the entire range of future changes projected by the full CMIP ensemble. In addition, although RCMs were shown to better reproduce some aspects of precipitation climatology compared to their driving GCMs (e.g., Gibba et al 2019), this 'added value' is not always present (especially for mean quantities e.g., Dosio et al 2015) and it is often not straightforward to establish whether for instance improvements in the mean precipitation field are a result of a more realistic simulation of the physical processes (Dosio et al 2019;Tamoffo et al 2020).…”

Projections of indices of daily temperature and precipitation based on bias-adjusted CORDEX-Africa regional climate model simulations

“…non-negligible fine-scale information that is absent in the lower resolution simulations) to the driving GCM in simulating precipitation characteristics (especially higher order statistics) has been shown in several studies (e.g. Dosio et al, 2015;Pinto et al 2016;Nikiema et al 2017;Fotso-Nguemo et al 2017, Gibba et al 2019Tamoffo et al 2020).…”

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

“…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.…”