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This study evaluates the performance of climate models in reproducing surface solar radiation (SSR) over Southern Africa (SA) by validating five Regional Climate Models (RCM, including CCLM4, HIRHAM5, RACMO22T, RCA4 and REMO2009) that participated in the Coordinated Regional Downscaling Experiment program over Africa (CORDEX-Africa) along with their ten driving General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 over SA. The model simulated SSR was thereby compared to reference data from ground-based measurements, satellite-derived products and reanalyses over the period 1990-2005. Results show that (1) the references obtained from satellite retrievals and reanalyses overall overestimate SSR by up to 10 W/m2 on average when compared to ground-based measurements from the Global Energy Balance Archive, which are located mainly over the eastern part of the southern African continent. (2) Compared to one of the satellite products (Surface Solar Radiation Data Set—Heliosat Edition 2; SARAH-2): GCMs overestimate SSR over SA in terms of their multi-model mean by about 1 W/m2 (compensation of opposite biases over sub-regions) and 7.5 W/m2 in austral summer and winter respectively; RCMs driven by GCMs show in their multimodel mean underestimations of SSR in both seasons with Mean Bias Errors (MBEs) of about − 30 W/m2 in austral summer and about − 14 W/m2 in winter compared to SARAH-2. This multi-model mean low bias is dominated by the simulations of the CCLM4, with negative biases up to − 76 W/m2 in summer and − 32 W/m2 in winter. (3) The discrepancies in the simulated SSR over SA are larger in the RCMs than in the GCMs. (4) In terms of trend during the "brightening" period 1990-2005, both GCMs and RCMs (driven by European Centre for Medium-Range Weather Forecasts Reanalysis ERA-Interim, short as ERAINT and GCMs) simulate an SSR trend of less than 1 W/m2 per decade. However, variations of SSR trend exist among different references data. (5) For individual RCM models, their SSR bias fields seem rather insensitive with respect to the different lateral forcings provided by ERAINT and various GCMs, in line with previous findings over Europe. (6) Biases in SSR are overall qualitatively consistent with those in total cloud cover. The information obtained in present study is of crucial importance for understanding future climate projections of SSR and for relevant impact studies. [ABSTRACT FROM AUTHOR]

This paper investigates and quantifies co-variability between large-scale convection in the South American and Southern African sectors at different timescales (interannual, intraseasonal and synoptic), during the austral summer seasons (November-February) from 1979 to 2012. Multivariate analyses (Canonical Correlation Analysis and Principal Component Analysis) are applied to daily outgoing longwave radiation (OLR, used as a proxy for atmospheric convection) anomalies to extract the principal modes of variability and co-variability in each and between both regions, filtered to consider the appropriate time-scales. At the interannual timescale, results confirm the predominant role of El Niño Southern Oscillation (ENSO), favoring enhanced convection over both southeastern Brazil and northern Argentina on the one hand, and tropical Africa and the western Indian Ocean on the other hand. At the intraseasonal timescale, the leading mode of co-variability is related to modulations of large-scale atmospheric convection over most of South America, and 10 days later, tropical Southern Africa. This mode accounts for the impacts of the Madden-Julian-oscillation (MJO) over these regions: identifying robust co-variability at the intraseasonal timescale between both regions require thus to consider a temporal shift between the two sectors. At the synoptic scale, however, co-variability consists mostly of a synchronous modulation of the large-scale atmospheric convection over the South American and Southern African sectors. This results from the development of concomitant Rossby waves forming a continuous wave train over the South Atlantic in the mid-latitudes, affecting both the South Atlantic and South Indian Convergence Zones. Among the days when convection shows significant anomalies (30 % of the total days in each sector), this synchronous mode occurs about 25 % of the time, individual Rossby waves modulating convection over one single region only during the remaining 75 % events. Another mode of co-variability, involving a single Rossby wave modulating the convection first over the Americas, and 4 days later over Africa, appears as sensibly weaker than the synchronous mode, suggesting that the 'wave train' mode occurs more frequently than the development and propagation of a single wave that could affect both regions. [ABSTRACT FROM AUTHOR]

This study documents methodological issues arising when downscaling modes of large-scale atmospheric variability with a regional climate model, over a remote region that is yet under their influence. The retained case study is El Niño Southern Oscillation and its impacts on Southern Africa and the South West Indian Ocean. Regional simulations are performed with WRF model, driven laterally by ERA40 reanalyses over the 1971-1998 period. We document the sensitivity of simulated climate variability to the model physics, the constraint of relaxing the model solutions towards reanalyses, the size of the relaxation buffer zone towards the lateral forcings and the forcing fields through ERA-Interim driven simulations. The model's internal variability is quantified using 15-member ensemble simulations for seasons of interest, single 30-year integrations appearing as inappropriate to investigate the simulated interannual variability properly. The incidence of SST prescription is also assessed through additional integrations using a simple ocean mixed-layer model. Results show a limited skill of the model to reproduce the seasonal droughts associated with El Niño conditions. The model deficiencies are found to result from biased atmospheric forcings and/or biased response to these forcings, whatever the physical package retained. In contrast, regional SST forcing over adjacent oceans favor realistic rainfall anomalies over the continent, although their amplitude remains too weak. These results confirm the significant contribution of nearby ocean SST to the regional effects of ENSO, but also illustrate that regionalizing large-scale climate variability can be a demanding exercise. [ABSTRACT FROM AUTHOR]

This study aims at quantifying seasonal biases of regional climate model outputs during southern African summer, against a dense in situ measurement network (daily rain-gauge and surface air temperature records, and 12 h UTC radiosondes), and uncertainties associated with some physical parameterizations. Using the non-hydrostatic Advanced Research Weather Forecast (WRF) laterally forced by ERA40 reanalysis, twenty-seven experiments configured with three schemes of cumulus (CU), planetary boundary layer (PBL) and microphysics (MP), are performed at 35 km horizontal resolution during the core of a summer rainy season (December 1993 to February 1994 season) representative of the South African rainfall climatology. WRF simulates accurately seasonal large-scale rainfall patterns, as well as seasonal gradients of South African rainfall and 2-m temperature, and seasonal vertical profiles of the air temperature and humidity. However seasonal biases fluctuate strongly from an experiment to another, denoting considerable uncertainties generated by the physical package. Rainfall amounts are the most sensitive parameter to the tested schemes. Their geography, intensity, and intraseasonal characteristics are predominantly sensitive to CU schemes, and much less to PBL and MP schemes. Some CU-PBL combinations produce additive effects, which can dramatically either reduce or increase biases. Satisfactory configurations are found for South African climate, which would not have been possible without testing numerous physical parameterizations. [ABSTRACT FROM AUTHOR]

The authors analyze to what extent the internal variability simulated by a regional climate model is sensitive to its physical parameterizations. The influence of two convection schemes is quantified over southern Africa, where convective rainfall predominates. Internal variability is much larger with the Kain-Fritsch scheme than for the Grell-Dévényi scheme at the seasonal, intraseasonal, and daily time scales, and from the regional to the local (grid point) spatial scales. Phenomenological analyses reveal that the core (periphery) of the rain-bearing systems tends to be highly (weakly) reproducible, showing that it is their morphological features that induce the largest internal variability in the model. In addition to the domain settings and the lateral forcing conditions extensively analyzed in the literature, the physical package appears thus as a key factor that modulates the reproducible and irreproducible components of regional climate variability. [ABSTRACT FROM AUTHOR]

This study aims at presenting various methodologies to separate the reproducible and irreproducible components of seasonal and intraseasonal climate variability simulated by a regional climate model over Southern Africa (south of 15°S), during an austral summer rainy season representative of the climatology. To that end, a 30-member ensemble simulation is performed using WRF laterally forced by the ERA40 reanalyses. Retained metrics include the analysis of weather regimes, signal-to-noise ratio, inter-member standard deviation and coefficient of variation. At the seasonal timescale, simulated rainfall amounts generally show a strong reproducibility, except in the subtropics and over the southern part of the Mozambique Channel. There, the number of rainy days is roughly similar in all members, while their average intensity varies extensively. At the intraseasonal timescale, the chronology of weather regimes, derived from the 500 hPa geopotential height, is highly reproducible. Rainfall variability is much less reproducible, especially in the central parts of the domain and near its outflow boundaries. Analysis of a South African regional index nonetheless indicates that both wet and dry spells tend to be accurately simulated and occur in phase in most members, demonstrating that they are embedded in large-scale variability patterns. Internal variability is lastly related to the lateral forcings along the domain boundaries. An objective classification of inflow/outflow mass fluxes allows identification of the recurrent synoptic configurations that favor strong or weak regional reproducibility. The main uncertainties concern the basic morphological features of rain-bearing systems (i.e., their spatial extension, location and propagation speed). Consequences for tropical-temperate interactions are then discussed. [ABSTRACT FROM AUTHOR]

A correction to the article "How do tropical temperate troughs form and develop over southern Africa?" that was published in a 2014 issue is presented.