Bias correction of CORDEX-Africa regional climate model simulations for trend analysis in northeastern Lake Chad: Comparison of three bias correction methods

In order to better adapt to the consequences of climate change, regional climate models (RCMs) have been set up for simulations. However, these simulations are often subject to biases, making it difficult to use them directly in studies of the impact of climate change. It is therefore necessary to use bias correction methods to reduce discrepancies between observed data and the data simulated by RCMs. The aim of this study is to analyse the results of three bias correction techniques (scaling, EQM and GQM) applied to rainfall data and mean minimum and maximum temperatures from CORDEX-Africa Regional Climate Models (RCMs), specifically in the north-eastern region of Lake Chad. Various statistical measures such as Pbiais, RMSE, R2 and EAM were used to assess the performance of each bias correction method in this study. In addition, the adjusted Mann-Kendall test and the Sen slope estimator were used to examine trends and their magnitude over the recent (1975-2004) and future (2021-2050) periods with a significance level of 5%. Overall, based on the statistical measures evaluating the effectiveness of the bias correction techniques, this study shows that all the methods tested were able to reduce the biases of the RCM outputs satisfactorily. In particular, the linear scaling approach proved to be more effective in correcting biases than the EQM and GQM methods. Therefore, an analysis of future trends in mean annual precipitation and temperature (minimum and maximum) was carried out for the RCP4.5 and RCP8.5 scenarios using the linear scaling method to correct for data biases. An increase in precipitation and temperature was observed in the study area over the recent period. The results of multi-model averaging of regional climate change for the RCP4.5 and RCP8.5 scenarios indicate a significant increase in mean annual temperatures (minimum and maximum) in the future. As far as annual precipitation is concerned, only an increase is forecast under the RCP4.5 scenarios. Under the RCP8.5 scenarios, a trend towards stable precipitation is predominant, with the exception of the south of the zone, where an increase has been observed. In the light of these results, it is clear that the impact of climate change will intensify in the region studied in the future

Bias correction of CORDEX-Africa regional climate model simulations for climate change projections in northeastern Lake Chad: Comparative analysis of three bias correction methods

Climate model simulations are frequently affected by biases, which makes it difficult to incorporate them directly into analyses of the impact of climate change. It is therefore essential to use bias correction methods to minimize discrepancies between real data and that generated by Regional Climate Models (RCMs). This study aims to analyze the results of three bias correction methods (LS, MQE, and MQG) applied to the processing of mean rainfall and temperature data from CORDEX-Africa's Regional Climate Models (RCMs), specifically in the north-eastern region of Lake Chad. Four statistical measures (bias, RMSE, r2, and MEA) were used to assess the effectiveness of each bias correction method. In addition, adjusted Mann-Kendall analysis and the Sen slope estimation method were applied to study trends and their magnitude over the recent (1975-2020) and future (2021-2050) periods, using a 5% significance level. The results highlight the existence of significant biases between the uncorrected RCM outputs and the observed data. After applying the bias correction, significant reductions in bias and comparable performance between the different bias correction methods were observed, with the LS method performing slightly better in correcting biases in monthly mean precipitation and temperature. Consequently, the LS method was selectively applied to correct the biases in the RCM monthly mean precipitation and temperature projections for the 2021-2050 period under the RCP4.5 and RCP8.5 scenarios using the 1975-2004 reference period. The results of multi-model averaging of RCMs under the RCP4.5 and RCP8.5 scenarios indicate a significant increase in mean annual temperatures over the period 2021-2050. As far as annual precipitation is concerned, only an increase is forecast under the RCP4.5 scenario. Under the RCP8.5 scenario, the absence of a precipitation trend is predominant, with the exception of the south of the zone, where an increasing trend has been observed. In light of these results, it is clear that the impact of climate change will intensify in the study area in the future. It is imperative to develop strategies to adapt and reduce the impacts in order to manage the availability of water resources efficiently