Africa lags the rest of the world in climate model development. This paper explores the potential for region-specific, process-based evaluation to promote progress in modeling and confidence assessments.

A critical discussion of recent studies that analysed the effects of climate change on the water resources of the River Nile Basin (RNB) is presented. First, current water-related issues on the RNB showing the particular vulnerability to environmental changes of this large territory are described. Second, observed trends in hydrological data (such as temperature, precipitation, river discharge) as described in the recent literature are presented. Third, recent modelling exercises to quantify the effects of climate changes on the RNB are critically analysed. The many sources of uncertainty affecting the entire modelling chain, including climate modelling, spatial and temporal downscaling, hydrological modelling and impact assessment are also discussed. In particular, two contrasting issues are discussed: the need to better recognize and characterize the uncertainty of climate change impacts on the hydrology of the RNB, and the necessity to effectively support decision-makers and propose suitable adaptation strategies and measures. The principles of a code of good practice in climate change impact studies based on the explicit handling of various sources of uncertainty are outlined. Hydrologie et climat futurs dans le bassin du Nil: une revueRésumé Une discussion critique des études récentes qui ont analysé les effets du changement climatique sur les ressources en eau du bassin du Nil (RNB) est présentée. Premièrement, les problèmes actuels liés à l'eau dans le RNB montrant la vulnérabilité particulière de ce vaste territoire aux changements environnementaux sont décrits. Deuxièmement, les tendances observées dans les données hydrologiques (comme la température, les précipitations, le débit des rivières) sont présentées, telles qu'elles sont décrites dans la littérature récente. Troisièmement, les exercices récents de modélisation quantitative des effets des changements climatiques dans le RNB sont analysés de manière critique. Les nombreuses sources d'incertitude qui affectent toute la chaîne de modélisation, incluant la modélisation du climat, la descente d'échelles spatiale et temporelle, la modélisation hydrologique, et l'évaluation des impacts sont également discutées. En particulier, deux questions contrastées sont discutées: la nécessité de mieux identifier et caractériser l'incertitude des impacts du changement climatique sur l'hydrologie du RNB, et la nécessité de soutenir efficacement les décideurs et de proposer des stratégies d'adaptation et des mesures appropriées. Les principes d'un code de bonnes pratiques dans les études d'impact du changement climatique sont décrits, qui reposent sur le traitement explicite des diverses sources d'incertitude.

Africa is poised for a revolution in the quality and relevance of weather predictions, with potential for great benefits in terms of human and economic security. This revolution will be driven by recent international progress in nowcasting, numerical weather prediction, theoretical tropical dynamics and forecast communication, but will depend on suitable scientific investment being made. The commercial sector has recognized this opportunity and new forecast products are being made available to African stakeholders. At this time, it is vital that robust scientific methods are used to develop and evaluate the new generation of forecasts. The GCRF African SWIFT project represents an international effort to advance scientific solutions across the fields of nowcasting, synoptic and short-range severe weather prediction, subseasonal-to-seasonal (S2S) prediction, user engagement and forecast evaluation. This paper describes the opportunities facing African meteorology and the ways in which SWIFT is meeting those opportunities and identifying priority next steps.Delivery and maintenance of weather forecasting systems exploiting these new solutions requires a trained body of scientists with skills in research and training; modelling and operational prediction; communications and leadership. By supporting partnerships between academia and operational agencies in four African partner countries, the SWIFT project is helping to build capacity and capability in African forecasting science. A highlight of SWIFT is the coordination of three weather-forecasting “Testbeds” – the first of their kind in Africa – which have been used to bring new evaluation tools, research insights, user perspectives and communications pathways into a semi-operational forecasting environment.

There is a great demand to improve predictions of high‐impact weather across the African continent. This is because of the high frequency of intense convective storms that often produce severe flooding, strong winds and lightning, combined with the vulnerability of people, infrastructure and businesses to such hazards. The skill of numerical weather prediction over Africa is still low, even for lead times of less than 24 hours. Therefore, there is a particular need to deliver nowcasting of events as they occur. However, there remains a widespread lack of provision of nowcasting across Africa and virtually no use of automated nowcasting systems or tools. This limits the ability of national meteorological services to issue warnings and therefore potentially prevent the loss of life and significant financial losses. Coverage by meteorological radars is still very limited, but geostationary satellites provide regular high resolution data of the often large and long‐lived storms. As such, there is an opportunity to improve satellite‐based nowcasting capability in Africa. Work being undertaken as part of the Global Challenges Research Fund African SWIFT (Science for Weather Information and Forecasting Techniques) project is starting to improve the nowcasting of African convective systems and so the ability to provide timely warnings of extreme weather providing a wide range of benefits.

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The study explored the ability of four cumulus parameterization schemes (CPSs) from Weather and Research Forecasting model (WRF) to simulate mean rainfall patterns, number of rainy days (NRD) and vertically integrated moisture flux (VIMF) during the composite of wet years for the core rainfall seasons of March-April-May (MAM;, 1998 and October-November-December (OND;1997, 2006 seasons. The CPSs used were Kain-Fritsch (KF), Kain-Fritsch with a moisture-advection based trigger function (KFT), Grell Dévényi (GRELL) and Betts Miller Janjic (BML). The simulations by the GRELL and KF schemes were clearly separated by the dry and wet rainfall gradient in the simulations. For example, the GRELL scheme rainfall simulations were drier over the eastern parts of the region better. The KF and KFT schemes generated wetter rainfall conditions mainly confined to the western parts of the region. The BML scheme simulations were not consistent with the observations. The western and eastern parts of the region were characterized by more and fewer NRD, in both the KF and GRELL schemes. The root mean square error (RMSE) and spatial correlation by KF scheme was 2 mm/day and 0.6. The GRELL scheme however simulated low correlation of 0.45 and RMSE of about 3.0 mm/day over most of the sub-domains. The moisture convergence biases were found to be larger continentally and parts of the nearby Indian Ocean. The persisting rainfall biases constituting of too wet and dry conditions were associated with the KF and GRELL cumulus schemes. The findings from the current study are very fundamental for the improvement of numerical weather prediction (NWP) tools and cumulus modification processes over the region. The accurate and higher skill rainfall forecasts would provide early warning information for disaster risk reduction and the related risks on the livelihoods.