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In this study, three regional climate models (RCMs), CCLM5‐0‐15, RegCM4‐7 and REMO2015, from CORDEX‐CORE (AFR‐22) are evaluated in their ability to reproduce rainfall variability in Rwanda for the period 1981–2005. They are driven by three different global climate models (GCMs), namely MPI‐M‐MPI‐ESM‐LR, NCC‐NorESM1‐M and MOHC‐HadGEM2‐ES, and the European Centre for Medium‐Range Weather Forecasts Reanalysis (ECMWF‐ERAINT). Simulated rainfall is evaluated against observations from Rwanda Meteorology Agency to assess models' performance. A set of metrics are used to quantify discrepancies of models' simulations from observations. A possible association of El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) to rainfall over Rwanda is investigated. It is found that in general, all RCMs, their ensemble and multimodel ensemble means reproduce satisfactorily the spatial distribution of the mean seasonal rainfall (MSR), the mean rainfall annual cycle, and the interannual variability of the MSR for both March–April–May (MAM) and October–November–December (OND). However, significant biases in individual RCMs are observed with varying magnitude of bias in space. Observed MSR indicates a positive trend of 0.045 and 0.058 mm·day·year−1, respectively, for MAM and OND at 0.05 significance level, but almost all models indicate no significant trend (at 0.05 significance level). The seasonal correlations between observed rainfall anomalies and sea surface temperature (SST) anomalies indices across the tropical Pacific (Niño1+2 and Niño3.4) and Indian Oceans associated, respectively, with ENSO and IOD, although relatively weak, are reproduced by the three RCMs driven by ECMWF‐ERAINT and the multimodel ensemble means of ECMWF‐ERAINT and MPI‐M‐MPI‐ESM‐LR. Analysis of the Taylor diagram indicates that CCLM5‐0‐15_MPI‐M‐MPI‐ESM‐LR and the multimodel ensemble mean of MPI‐M‐MPI‐ESM‐LR outperform individual models. Overall, the evaluation finds reasonable model skill in representing seasonal rainfall climatology and variability, suggesting the potential use of CORDEX‐CORE (AFR‐22) RCMs for the assessment of future climate projections in Rwanda. [ABSTRACT FROM AUTHOR]

There were a large number of active meteorological stations in Rwanda prior to the mid‐1990s and since around 2010. However, from around the time of the Rwandan genocide in 1994 throughout the late 2000s, the number of active stations was greatly reduced. To address temporal and spatial gaps in meteorological observation in several African nations (including Rwanda), the ENACTS (Enhancing National Climate Services) initiative reconstructs rainfall and temperature data by combining station data with satellite rainfall estimates, and with reanalysis products for temperature. Bias correction factors are applied to the satellite and reanalysis data and the merged final product is spatiotemporally complete from the early 1980s to the present at a high spatial resolution (4–5 km). This paper offers the first analysis of Rwanda's climatology using this new ENACTS data set for 1981–2016. The temperature and rainfall climatology of Rwanda are analysed at both annual and seasonal timescales as are the climatological influences of topography and regional winds. Climatology maps of mean rainfall intensity, rainy day, 5‐day dry spell and extreme rain day (20+mm) frequency are shown, and spatial pattern correlations are analysed. The rainfall climatology of Rwanda exhibits a clear seasonal bimodality typical of the East Africa region. Topography has a significant effect with the more mountainous, higher‐elevation western part of the country being consistently cooler and wetter than the lower, flatter eastern region. Southeasterly winds tend to prevail over Rwanda, but in some seasons, the climatological winds weaken and shift direction. While spatial patterns of rainy day and dry spell frequency are consistent with the spatial patterns of the seasonal rainfall total, climatologically drier regions have a higher mean rainfall intensity on rainy days. This analysis demonstrates the value of the ENACTS product and illustrates climatological patterns in Rwanda over the last 30 years. [ABSTRACT FROM AUTHOR]

How much should the present generations sacrifice to reduce emissions today, in order to reduce the future harms of climate change? Within climate economics, debate on this question has been focused on so-called "ethical parameters" of social time preference and inequality aversion. We show that optimal climate policy similarly importantly depends on the future of the developing world. In particular, although global poverty is falling and the economic lives of the poor are improving worldwide, leading models of climate economics may be too optimistic about two central predictions: future population growth in poor countries, and future convergence in total factor productivity (TFP). We report results of small modifications to a standard model: under plausible scenarios for high future population growth (especially in sub-Saharan Africa) and for low future TFP convergence, we find that optimal near-term carbon taxes could be substantially larger. [ABSTRACT FROM AUTHOR]

Flooding and low-flow events along the Niger River in West Africa have major societal impacts, motivating this paper’s historical flow analysis and stochastic simulation of plausible future flow scenarios. The known epochal evolution of mean streamflow since 1950 (wet epoch, dry epoch and moderate recovery) is analyzed, with a focus on climatological flood month at three representative locations, and on associated changes in distribution (e.g. standard deviation and percentiles). We especially note the relatively small change in the (high flow) 90th percentile across the three epochs. Following the historical analysis, a statistical simulation framework is developed to explore the sensitivity of threshold-crossing events (TCEs) to plausible assumptions about hydroclimatic evolution over 2010–2040. The flow changes are assumed to reflect varying combinations of the following: systematic global change (GC), natural multidecadal variability (MDV) and interannual variability (IV). Results show that for a 1 in 10 TCE in the historical period, a 20% streamflow trend over 2010–2040 (no change in IV) can produce a factor four difference in average TCE frequency. Adding MDV signals of magnitudes that may be considered conservative for the region, enhances the sensitivity further (>50%). The results highlight how risk management strategies need to integrate GC and MDV impacts. [ABSTRACT FROM PUBLISHER]

Studies of climate change from both natural science and social science disciplines are increasingly turning their focus to the issue of extreme events. Extreme heat waves, storms, droughts, and coastal inundations pose a disproportionate risk to human life, livelihood, and capital across the world. In the Global South, including Africa, much of the adverse impacts come from hydroclimate extremes as people with limited means are often highly vulnerable to climate shocks. The focus of this review paper will be on hydroclimate extremes in Africa. This paper will consider observations and modeling studies of heat extremes, drought, and flooding from heavy rainfall, along with observations and modeling studies of extreme streamflow events in major rivers and extremes of lake level. This being said, observations of trends in extreme events need to be situated in a context of understanding regional hydroclimate variability. There is tremendous diversity and variability in the hydroclimate of Africa and many extreme events, especially of precipitation and streamflow are associated with patterns of natural variability on a range of time scales. [ABSTRACT FROM AUTHOR]