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We evaluate the ability of ten regional climate models (RCMs) to simulate precipitation over southern Africa within the Cordex framework. An ensemble of ten regional climate simulations and the ensemble average is analysed to evaluate the model's ability to reproduce seasonal and interannual rainfall characteristics over regions of the subcontinent. All the RCMs use a similar domain, have a spatial resolution of ~50km and are driven by the ERA-Interim reanalysis (1989-2008). Results are compared against a number of observational datasets. The spatial and temporal nature of rainfall over the region is captured by all RCMs, however, 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 the positioning of the ITCZ as well as moisture transport. The multi-model ensemble mean generally out-performs individual models, with bias magnitudes similar to differences across the observational data sets. In the northern parts of the domain some of the RCMs and the ensemble average improve the precipitation climate compared to that of the ERA-Interim reanalysis. 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, we suggest that the present set of RCMs can be used to provide useful information on climate projections of rainfall over southern Africa., JRC.H.7-Climate Risk Management

Includes bibliographical references (leaves 87-91)., The work presented in this dissertation stems from the link that exists between meteorological conditions and the significant accumulation of air pollutants in large urban agglomerations. The research focuses on the Greater Cape Town Area (GCTA), where temperature inversions lead to high air pollutant concentrations and episodes of air pollution. As local meteorological conditions are often manifestations of larger weather producing phenomena (e.g. anticyclones), the work presented studies the changes that may occur in the synoptic conditions associated with temperature inversions, which will consequently affect the rate of occurrence of air pollution episodes. After a brief introduction of the topic, background information on the relevant legislation and the actions taken towards an air pollution abatement strategy and a detailed literature review, the high levels of air pollution in the GCT A during winter and especially during the morning peak hour traffic and their link to temperature inversions are studied in detail for the year 2002. The large scale circulation and its link to temperature inversions are studied through the application of the Self-Organizing Maps technique using NCEP-DOE Reanalysis 2 data and making use of the findings for the year 2002. The synoptic states most associated with temperature inversions are found to be the anticyclonic conditions caused by the South Atlantic High Pressure (SAHP) system and the west coast trough associated with berg winds bringing dry continental air towards the GCT A. The 2002 data also show that more air pollution episode days are associated with west coast troughs than with the SAHP system and the average strength of the temperature inversions associated with west coast troughs is found to be approximately 50 % higher than that associated with the SAHP system. The Global Circulation Models (GCMs) ECHAM5, CNRM-CM3 and CSIRO-MK3.5 are used to study the potential changes in the future climate of the area under the IPCC A2 emissions scenario. ECHAM5 shows a small increase in the synoptic states associated with anticyclonic influence over the south western part of South Africa and CNRM-CM3 shows a small increase in both the synoptic states associated with anticyclonic influence and those associated with a west coast trough. Both models show a small decrease in the synoptic states associated with cold fronts. CSIRO-MK3.5 was not found to adequately reflect the current climatology in the domain, making it difficult to distinguish between model bias and future climate trends.

The modelling of the atmospheric composition on global scales has been significantly advanced during the last decade. A variety of processes are inherent in climate-chemistry models (CCMs), either resolved, parameterized or forced by boundary conditions. This ensures a better representation of the observed atmospheric composition and its variations, such as large scale climate phenomena (North-Atlantic Oscillation, El Nino/ La Nina, etc), volcanic eruptions, solar effects, etc. Additionally, feedbacks between processes are included, like the impact of ozone, methane, and other species on radiation and dynamics, dynamics on emissions (e.g. lightning), and many others. Dameris et al. (2005) present a troposphere-stratosphere simulation of the time period 1960 to 2000 using the CCM E39/C. This simulation includes observed sea-surface temperatures to account for effects like El Nino, and realistic planetary wave forcings, three major volcanic eruptions, the 11-year solar cycle, the Quasi-Biannual Oscillation (QBO), and varying emission of NOx and CFCs. The results show a good representation of the stratospheric and tropospheric dynamics, such as temperature trends, but also of the ozone layer, the development of the ozone hole, and tropospheric ozone in terms of composition and trend. The application of a number of diagnostics (e.g. marked ozone tracers) allows the separation of the impact of various processes/emissions on tropospheric ozone. The simulated Northern Hemisphere tropospheric ozone budget is not only dominated by nitrogen oxide emissions and other ozone pre-cursors, but also by changes of the stratospheric ozone budget and the its flux into the troposphere, which tends to reduce the positive trend in ozone due to emissions from industry and traffic during the late 80s and early 90s. Although the horizontal resolution is rather coarse in comparison to regional models, such kind of simulations provide useful and necessary information on the impact of large-scale processes and inter-annual / decadal variations on regional air quality