The objective of this work is to analyze the spatial distribution of biases of nine (9) regional climate models (RCMs) and their ensemble average used under the framework of COordinated Regional climate Downscaling EX...The objective of this work is to analyze the spatial distribution of biases of nine (9) regional climate models (RCMs) and their ensemble average used under the framework of COordinated Regional climate Downscaling EXperiment (CORDEX) project over West Africa during the summer period. We assessed the ability of RCMs to represent adequately West African summer rainfall by analyzing some statistical parameters such as the relative bias, the standard deviation, the root mean square error (RMSE) and the correlation coefficient between observation data (GPCP used as reference) and regional climate models outputs. We first analyzed the relative bias between GPCP climatology and the other available observed data (CRU, CMAP, UDEL, GPCC, TRMM and their ensemble mean). This analysis highlights the big uncertainty on the quality of these observed rainfall data over West Africa which may be largely due to the rarity of?in situ?measurement data over this region. The statistical analysis with respect to GPCP rainfall shows the presence of large relative bias values over most part of West Africa for engaged RCMs. However their ensemble mean outperforms individual RCMs by exhibiting the weakest relative change. The RMSE values are weak over West Africa except over and off the Guinea highlands for RCMs and the Era-interim reanalysis. The spatial distribution of the coefficient of correlation between the observation data and RCMs shows that all models (except HIRHAM) present positive values over the Northern Sahel and the Gulf of Guinea. The model of the DMI exhibits the weakest values of correlation coefficient. This study shows that RCMs simulate West African climate in a satisfactory way despite the fact that they exhibit systematic biases.展开更多
The impacts of the reforestation of the Sahel-Sahara interface on the seasonal distribution of the surface temperature and thermal extremes are studied in the Sahel (West African region lying between 11°N and ...The impacts of the reforestation of the Sahel-Sahara interface on the seasonal distribution of the surface temperature and thermal extremes are studied in the Sahel (West African region lying between 11°N and 18°N). We performed a simulation with the standard version of the RegCM4 model followed by another one using the altered version of the same model taking into account an incorporated forest. The impacts of the vegetation change are assessed by analyzing the difference between the two runs. The reforestation may influence strongly the frequency of warm days (TG90P) and very warm days (TX90P) by decreasing it over the reforested zone from March to May (MAM) and the entire Sahel during the June-August (JJA) period. These TG90P and TX90P indices decrease may be due to the strengthening of the atmospheric moisture content over the whole Sahel region and the weakening of the sensible heat flux over the reforested zone. The analysis also shows a decrease of the TN90P indice (warm nights) over the Sahel during the wet season (JJA) which could be partly associated with the strengthening of the evapotranspiration over the whole Sahel domain. The analysis of additional thermal indices shows an increase of the tropical nights over the entire Sahel from December to February (DJF) and during the warm season (MAM). The strengthening of the tropical night is partly associated with an increase of the surface net downward shortwave flux over the reforested zone. When considering the heat waves, an increase (a decrease) of these events is recorded over the southern Sahel during JJA and SON periods (over the whole Sahelian region during DJF), respectively. Changes in latent heat flux appear to be largely responsible for these extreme temperatures change. This work shows that the vegetation change may impact positively some regions like the reforested area by reducing the occurrence of thermal extremes;while other Sahel regions (eastern part of the central Sahel) could suffer from it because of the strengthening of thermal extremes.展开更多
文摘The objective of this work is to analyze the spatial distribution of biases of nine (9) regional climate models (RCMs) and their ensemble average used under the framework of COordinated Regional climate Downscaling EXperiment (CORDEX) project over West Africa during the summer period. We assessed the ability of RCMs to represent adequately West African summer rainfall by analyzing some statistical parameters such as the relative bias, the standard deviation, the root mean square error (RMSE) and the correlation coefficient between observation data (GPCP used as reference) and regional climate models outputs. We first analyzed the relative bias between GPCP climatology and the other available observed data (CRU, CMAP, UDEL, GPCC, TRMM and their ensemble mean). This analysis highlights the big uncertainty on the quality of these observed rainfall data over West Africa which may be largely due to the rarity of?in situ?measurement data over this region. The statistical analysis with respect to GPCP rainfall shows the presence of large relative bias values over most part of West Africa for engaged RCMs. However their ensemble mean outperforms individual RCMs by exhibiting the weakest relative change. The RMSE values are weak over West Africa except over and off the Guinea highlands for RCMs and the Era-interim reanalysis. The spatial distribution of the coefficient of correlation between the observation data and RCMs shows that all models (except HIRHAM) present positive values over the Northern Sahel and the Gulf of Guinea. The model of the DMI exhibits the weakest values of correlation coefficient. This study shows that RCMs simulate West African climate in a satisfactory way despite the fact that they exhibit systematic biases.
文摘The impacts of the reforestation of the Sahel-Sahara interface on the seasonal distribution of the surface temperature and thermal extremes are studied in the Sahel (West African region lying between 11°N and 18°N). We performed a simulation with the standard version of the RegCM4 model followed by another one using the altered version of the same model taking into account an incorporated forest. The impacts of the vegetation change are assessed by analyzing the difference between the two runs. The reforestation may influence strongly the frequency of warm days (TG90P) and very warm days (TX90P) by decreasing it over the reforested zone from March to May (MAM) and the entire Sahel during the June-August (JJA) period. These TG90P and TX90P indices decrease may be due to the strengthening of the atmospheric moisture content over the whole Sahel region and the weakening of the sensible heat flux over the reforested zone. The analysis also shows a decrease of the TN90P indice (warm nights) over the Sahel during the wet season (JJA) which could be partly associated with the strengthening of the evapotranspiration over the whole Sahel domain. The analysis of additional thermal indices shows an increase of the tropical nights over the entire Sahel from December to February (DJF) and during the warm season (MAM). The strengthening of the tropical night is partly associated with an increase of the surface net downward shortwave flux over the reforested zone. When considering the heat waves, an increase (a decrease) of these events is recorded over the southern Sahel during JJA and SON periods (over the whole Sahelian region during DJF), respectively. Changes in latent heat flux appear to be largely responsible for these extreme temperatures change. This work shows that the vegetation change may impact positively some regions like the reforested area by reducing the occurrence of thermal extremes;while other Sahel regions (eastern part of the central Sahel) could suffer from it because of the strengthening of thermal extremes.
