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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]

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]