Abstract
Rainfall over Rwanda is highly variable both in space and time. This variability leads to chronic food insecurity due to the overdependence of the economy on rain-fed agriculture systems. This study aims to evaluate the skills of Rossby Centre Regional Climate Model (RCA4) simulations driven by 10 GCMs for the period 1951-2005 using the Global Precipitation Climatology Centre (GPCC v8) as a reference. Different statistical and geospatial metrics were used to deduce the model’s skills in simulating seasonal and annual rainfall. Results show that the country received bimodal rainfall pattern; March-May (MAM) and September-December (SOND). The RCA4 models are inconsistent in simulating the MAM rainy peak. However, the models are coherent in simulating SOND seasonal peak despite exhibiting wet bias. The models show reasonable skills in simulating mean annual cycle than interannual variability as depicted by insignificant correlation and different signs of rainfall trend. Conclusively, the performance of RCA4 models in simulating observed rainfall characteristics over Rwanda is relatively weak. The performance of the models differs at various time scales. Nevertheless, the models can be ranked from the best performing to the least as; CSIRO, CanESM2, CNRM, GFDL, MIROC5, ENS, EC-Earth, HadGEM2, IPSL, MPI, and NorESM1. Ranking the performance of RCA4 historical models acts as a basis for future climate model’s selection depending on the purpose of the study. The findings of this study may help in devising appropriate climate adaptation measures to respond to the ongoing global warming for sustainable economic and livelihood development. Additionally, modelers may improve the model’s parametrization schemes and lessen the inherent chronic biases for a better presentation of the future.
Highlights
Understanding the current and future rainfall trends, and its variability over Rwanda is paramount
This study aims to evaluate the skills of Rossby Centre Regional Climate Model (RCA4) simulations driven by 10 General Circulation Models (GCMs) for the period 1951-2005 using the Global Precipitation Climatology Centre (GPCC v8) as a reference
The present study aims at ranking the performance of ten RCA4 historical models that were driven by CMIP5 climate models against the observed gridded datasets as obtained from GPCC from 1951-2005 over Rwanda
Summary
Understanding the current and future rainfall trends, and its variability over Rwanda is paramount. The footprints of climate change and variability are evidenced over the region due to increased occurrence of extreme climate events [1] [2] [3]. Rainfed agriculture is the core of the economy rainfall variability has detrimental impacts on the socioeconomic of the country [4]. Food insecurity and clashes over natural resources have been witnessed over East Africa region due to limited resources. Prevalence of pests and diseases due to climate change like the recent invasion of desert locust over the East Africa region has threatened many people’s livelihood and the economy at large. Gauging the skills of the current RCA4 historical models is crucial in selecting the best performing model that can be used for future climate projections and impacts studies
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