Search

This study presents an evaluation of the ability of 10 regional climate models (RCMs) participating in the COordinated Regional climate Downscaling Experiment-Africa to reproduce the present-day spatial distribution of annual cycles of precipitation over the South African region and its borders. As found in previous studies, annual mean precipitation is quasi-systematically overestimated by the RCMs over a large part of southern Africa south of about 20°S and more strongly over South Africa. The spatial analysis of precipitation over the studied region shows that in most models the distribution of biases appears to be linked to orography. Wet biases are quasi-systematic in regions with higher elevation with inversely neutral to dry biases particularly in the coastal fringes. This spatial pattern of biases is particularly obvious during summer and specifically at the beginning of the rainy season (November and December) when the wet biases are found to be the strongest across all models. Applying a k-means algorithm, a classification of annual cycles is performed using observed precipitation data, and is compared with those derived from modeled data. It is found that the in-homogeneity of the spatial and temporal distribution of biases tends to impact the modeled seasonality of precipitation. Generally, the pattern of rainfall seasonality in the ensemble mean of the 10 RCMs tends to be shifted to the southwest. This spatial shift is mainly linked to a strong overestimation of convective precipitation at the beginning of the rainy season over the plateau inducing an early annual peak and to an underestimation of stratiform rainfall in winter and spring over southwestern South Africa. [ABSTRACT FROM AUTHOR]

This article evaluates the ability of the Coordinated Regional Downscaling Experiment ( CORDEX) regional climate models ( RCMs) in simulating monthly rainfall variation during the austral summer half year (October to March) over southern Africa, the timing of the rainy season and the relative frequencies of rainfall events of varying intensities. The phasing and amplitude of monthly rainfall evolution and the spatial progression of the wet season onset are well simulated by the models. Notwithstanding some systematic biases in a few models, the simulated onset and end of the rainy season and their interannual variability are highly correlated with those computed from the reference data. The strongest agreements between the reference and modelled precipitation patterns are found north of about 20°S in the vicinity of the Inter Tropical Convergence Zone. A majority of the RCMs adequately capture the reference precipitation probability density functions, with a few showing a bias towards excessive light rainfall events. [ABSTRACT FROM AUTHOR]

The authors evaluate the ability of 10 regional climate models (RCMs) to simulate precipitation over Southern Africa within the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework. An ensemble of 10 regional climate simulations and the ensemble average is analyzed to evaluate the models' ability to reproduce seasonal and interannual regional climatic features over regions of the subcontinent. All the RCMs use a similar domain, have a spatial resolution of ~50 km, and are driven by the Interim ECMWF Re-Analysis (ERA-Interim; 1989-2008). Results are compared against a number of observational datasets. In general, the spatial and temporal nature of rainfall over the region is captured by all RCMs, although individual models exhibit wet or dry biases over particular regions of the domain. Models generally produce lower seasonal variability of precipitation compared to observations and the magnitude of the variability varies in space and time. Model biases are related to model setup, simulated circulation anomalies, and moisture transport. The multimodel ensemble mean generally outperforms individual models, with bias magnitudes similar to differences across the observational datasets. In the northern parts of the domain, some of the RCMs and the ensemble average improve the precipitation climate compared to that of ERA-Interim. The models are generally able to capture the dry (wet) precipitation anomaly associated with El Niño (La Niña) events across the region. Based on this analysis, the authors suggest that the present set of RCMs can be used to provide useful information on climate projections of rainfall over Southern Africa. [ABSTRACT FROM AUTHOR]

This study aims at presenting a methodological approach in order to estimate health damages from particulate and photochemical urban air pollution and assess the order of magnitude as regards the corresponding social costs in urban scale. The analysis is conducted within an area of 50 × 50 km surrounding the city of Thessaloniki, Greece. The area is selected on the grounds that Thessaloniki is considered one of the most polluted cities within Europe, especially with respect to airborne particles. The methodology presented asserts with confidence that air pollution causes damage to human receptors at least as great as quantified, and that reductions in air pollution lead to widely accepted quantifiable benefits. Social cost of health damages in Thessaloniki turns out to be significant. The main contributor is by far premature mortality due to chronic exposure to anthropogenic PM. The results are very useful for highlighting the magnitude of the total impacts and costs of urban scale air pollution (as a percentage of an area's GDP) and can be used for comparison with relevant studies of other cities worldwide. Furthermore, they could be of importance for local authorities since they provide an insight on the economic social benefit of emission reductions in the area under consideration. [ABSTRACT FROM AUTHOR]