Using a regional climate model（RCM） is generally regarded as a promising approach in researching the climate of the Tibetan Plateau, due to the advantages provided by the high resolutions of these models. Whilst pre...Using a regional climate model（RCM） is generally regarded as a promising approach in researching the climate of the Tibetan Plateau, due to the advantages provided by the high resolutions of these models. Whilst previous studies have focused mostly on individual RCM simulations, here, multiple RCMs from the Coordinated Regional Climate Downscaling Experiment are evaluated in simulating surface air temperature and precipitation changes over the Tibetan Plateau using station and gridded observations. The results show the following：（1） All RCMs consistently show similar spatial patterns, but a mean cold（wet） bias in the temperature（precipitation） climatology compared to station observations. The RCMs fail to reproduce the observed spatial patterns of temperature and precipitation trends, and on average produce greater trends in temperature and smaller trends in precipitation than observed results. The multi-model ensemble overall produces superior trends in both simulated temperature and precipitation relative to individual models. Meanwhile, Reg CM4 presents the most reasonable simulated trends among the five RCMs.（2） Considerable dissimilarities are shown in the simulated quantitative results from the different RCMs, which indicates a large model dependency in the simulation of climate over the Tibetan Plateau. This implies that caution may be needed when an individual RCM is used to estimate the amplitude of climate change over the Tibetan Plateau.（3） The temperature（precipitation） in 2016–35, relative to 1986–2005, is projected by the multi-model ensemble to increase by 1.38 ± 0.09 °C（0.8% ± 4.0%） and 1.77 ± 0.28 °C（7.3% ± 2.5%） under the RCP4.5 and RCP8.5 scenario, respectively. The results of this study advance our understanding of the applicability of RCMs in studies of climate change over the Tibetan Plateau from a multiple-RCM perspective.展开更多
This study assessed the regional climate models (RCMs) employed in the Coordinated Regional climate Downscaling Experiment (CORDEX) South Asia framework to investigate the qualitative aspects of future change in seaso...This study assessed the regional climate models (RCMs) employed in the Coordinated Regional climate Downscaling Experiment (CORDEX) South Asia framework to investigate the qualitative aspects of future change in seasonal mean near surface air temperature and precipitation over the Hindu Kush Himalayan (HKH) region. These RCMs downscaled a subset of atmosphere ocean coupled global climate models (AOGCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5) to higher 50 km spatial resolution over a large domain covering South Asia for two representation concentration pathways (RCP4.5 and RCP8.5) future scenarios. The analysis specifically examined and evaluated multi-model and multi-scenario climate change projections over the hilly sub-regions within HKH for the near-future (2036e2065) and far-future (2066e2095) periods. The downscaled multi-RCMs provide relatively better confidence than their driving AOGCMs in projecting the magnitude of seasonal warming for the hilly sub-region within the Karakoram and northwestern Himalaya, with higher projected change of 5.4 C during winter than of 4.9 C during summer monsoon season by the end of 21st century under the high-end emissions (RCP8.5) scenario. There is less agreement among these RCMs on the magnitude of the projected warming over the other sub-regions within HKH for both seasons, particularly associated with higher RCM uncertainty for the hilly sub-region within the central Himalaya. The downscaled multi-RCMs show good consensus and low RCM uncertainty in projecting that the summer monsoon precipitation will intensify by about 22% in the hilly subregion within the southeastern Himalaya and Tibetan Plateau for the far-future period under the RCP8.5 scenario. There is low confidence in the projected changes in the summer monsoon and winter season precipitation over the central Himalaya and in the Karakoram and northwestern Himalaya due to poor consensus and moderate to high RCM uncertainty among the downscaled multi-RCMs. Finally, the RCM related uncertainty is found to be large for the projected changes in seasonal temperature and precipitation over the hilly sub-regions within HKH by the end of this century, suggesting that improving the regional processes and feedbacks in RCMs are essential for narrowing the uncertainty, and for providing more reliable regional climate change projections suitable for impact assessments in HKH region.展开更多
We investigated the performance of 12 different physics configurations of the climate version of the Weather, Research and Forecasting (WRF) Model over the Middle East and North Africa (MENA) domain. Possible combinat...We investigated the performance of 12 different physics configurations of the climate version of the Weather, Research and Forecasting (WRF) Model over the Middle East and North Africa (MENA) domain. Possible combinations among two Planetary Boundary Layer (PBL), three Cumulus (CUM) and two Microphysics (MIC) schemes were tested. The 2-year simulations (December 1988-November 1990) have been compared with gridded observational data and station measurements for several variables, including total precipitation and maximum and minimum 2-meter air temperature. An objective ranking method of the 12 different simulations and the selection procedure of the best performing configuration for the MENA domain are based on several statistical metrics and carried out for relevant sub-domains and individual stations. The setup for cloud microphysics is found to have the strongest impact on temperature biases while precipitation is most sensitive to the cumulus parameterization scheme and mainly in the tropics.展开更多
This study aims to evaluate the performance of the individual Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX) and the ensemble average of the four RCMs to feign the ...This study aims to evaluate the performance of the individual Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX) and the ensemble average of the four RCMs to feign the characteristics of the rainfall pattern for the Mbarali River catchment in Rufiji Basin for the period of 1979 to 2005. Statistical analysis for model performance such as Root mean square error, Mean error, Pearson correlation coefficient, Mean, Median, standard deviation and trend analysis are used. In addition to the statistical measure of model performance, the models are tested on their ability to capture the observed annual cycles and interannual variability of rainfall. Results indicated that the RCMs from the CORDEX indicated a better performance to reproduce the rainfall characteristics over Mbarali River catchment in Rufiji Basin. They reproduced fairly the Era Interim annual cycle and inter-annual variability of rainfall. The ensemble average performed better than individual models in representing rainfall over Mbarali River catchment in Rufiji Basin. These suggest that rainfall simulation from the ensemble average will be used for the assessment of the hydrological impact studies over Mbarali River catchment in Rufiji Basin.展开更多
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
This paper investigates how well the rainfall regime on which many livelihoods depend, in Ghanais well represented by the Coordinated Regional Climate Downscaling Experiment (CORDEX). The objective of the study is to ...This paper investigates how well the rainfall regime on which many livelihoods depend, in Ghanais well represented by the Coordinated Regional Climate Downscaling Experiment (CORDEX). The objective of the study is to demonstrate how well the ten CORDEX models are able to capture the spatial and temporal rainfall seasonality over the southern and northern sub-sections ofGhana. The choice of the sub-sections is based on the fact that south of 8°N experiences a bi-modal rainfall regime while the north has a uni-modal regime. The results indicate that the rainfall overGhanais associated with high levels of variability at the inter-annual time scale. Particularly over the southern part ofGhana, all the models follow the same trend as represented overGhanawith similar rainfall values as the observation. Over the northern part ofGhana, models record relatively low rainfall agreeing with the observation. However, most of the models overestimate the northern region rainfall as it is in the case of the southern Ghana. CORDEX as shown in this analysis could be useful in providing Ghana with at least 10 different model outputs for impact analysis. Caution is however given that, since individual models give different performance and the fact that models in general have their inherent deficiencies, an ensemble mean of the models could provide a better result.展开更多
Developing reliable adaptation and mitigation strategies to combat climate change is necessary at regional and local scales. The present study analyses the ability of the multi-model ensemble (MME) composed of fourtee...Developing reliable adaptation and mitigation strategies to combat climate change is necessary at regional and local scales. The present study analyses the ability of the multi-model ensemble (MME) composed of fourteen (14) CORDEX-Africa simulations to capture characteristics of the mean temperature for the present day (1979-2005) and associated extremes over Côte d’Ivoire. For this end, the analysis uses the mean variables of the temperature (i.e., minimum temperature (TMIN), mean temperature (TMEAN) and maximum temperature (TMAX)) as well as associated extremes such as intra-period extreme temperature range (ETR), warm spell duration index (HWFI) and warm days index (TX90P) during January-February-March (JFM), April-May-June (AMJ), July-August-September (JAS) and October-November-December (OND) seasons. The results indicate that mean temperature variables (TMIN, TMEAN and TMAX) are underestimated by CORDEX MME in general, except TMEAN in the centre of Côte d’Ivoire. On the other hand, extreme temperature indices are overestimated over Côte d’Ivoire, except ETR in JAS with an underestimation of about 2˚C and TX90P during JAS in the southern part of the country in JFM, AMJ and OND with an underestimation varying between 1% to 4%. In addition, CORDEX MME and observational datasets (CPC and NCEP) have a significant correlation in simulating temperature variables (TMIN, TMEAN, TMIN), while this correlation is not significant in general for extreme temperature, except ETR and HWFI. Furthermore, extreme temperatures (TX90P and HWFI) are characterized by more important interannual variability in the observations CPC and NCEP for ETR. Moreover, mean temperature variables (TMIN, TMEAN, TMAX) show slight interannual variability with respect to the observations CPC and NCEP, which are characterized by the most variability. Overall, CORDEX MME outperforms the seasonal and spatial variability of the temperature and associated extremes over Côte d’Ivoire, although some biases in representing their magnitudes. Thus, the results of the present study will help take appropriate adaptation and mitigation strategies against heatwaves and extreme temperature advent over Côte d’Ivoire as these climate extremes are projected to increase over the country.展开更多
Under the Coordinated Regional Climate Downscaling Experiment East Asia(CORDEX-EA)framework,two regional climate simulations were conducted at a very high resolution(12.5 km)using the Regional Climate Model version 4(...Under the Coordinated Regional Climate Downscaling Experiment East Asia(CORDEX-EA)framework,two regional climate simulations were conducted at a very high resolution(12.5 km)using the Regional Climate Model version 4(RegCM4)and the Weather Research and Forecasting(WRF)model,driven by the fifth generation ECMWF atmospheric reanalysis(ERA5)from 1980 to 2019.Evaluation against observations indicates that both RegCM4 and WRF can reproduce the mean climatology,interannual variability,and annual cycle of precipitation and surface air temperature(T2m),although some biases exist.WRF demonstrates skill in simulating the spatial pattern of annual and seasonal mean precipitation and T2m by reducing wet biases over land and warm biases in winter.RegCM4 can better capture the interannual variability of precipitation and T2m,exhibiting higher temporal correlation,while WRF tends to overestimate the interannual variability.Additionally,assessment of the simulated circulations against ERA5 reveals that the wet bias in summer is mainly attributed to the enhanced low-level southwesterly jet.In general,compared with the results at 50-and 25-km resolutions in the first and second phases of CORDEX-EA,the higher resolution(12.5 km)has effectively improved the interannual variability of the regional climate simulations.展开更多
We analysed nine simulations from dynamic downscaling to a horizontal resolution of approximately 25 km of three general circulation models (GCMs). These GCMs use three regional climate models (RCMs) that participated...We analysed nine simulations from dynamic downscaling to a horizontal resolution of approximately 25 km of three general circulation models (GCMs). These GCMs use three regional climate models (RCMs) that participated in the coordinated downscaling experiment (CORDEX-CORE). These simulations were compared to three datasets of reanalysis. The ERA5 for temperature at 2 metres and for precipitation, Climate Hazards Center InfraRed Precipitation with Stations (CHIRPS) and African Rainfall Climatology from the Famine Early Warning System (FEWS-ARC) were used. To give an overview of these nine model experiments, we presented and compared the results of the latter with the reanalysis taken into account for the period 1983 - 2005. The results indicated that the nine models correctly reproduced the temperature and rainfall in West Africa during the historical period. In the Guinean coast region, REMO-NorESM1 and RegCM4-MPI-MR models well simulated precipitation and temperature during the historical period. In the Savannah region, RegCM4-NorESM1, CCLM5-MPI-LR, REMO-NorESM1, CCLM5-NorESM1 and CCLM5-HadGEM2 model gave best result. In the Sahel region, the RegCM4-HadGEM2 model gave a good correlation. Using the Taylor diagram in the historical period, all CORDEX-CORE RCMs had a strong relationship with temperature.展开更多
In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
Somalia has faced severe challenges linked to climate variability, which has been exacerbated by conflict and limited governance that persisted for decades. Today climate extremes such as floods, drought, and coastal ...Somalia has faced severe challenges linked to climate variability, which has been exacerbated by conflict and limited governance that persisted for decades. Today climate extremes such as floods, drought, and coastal marine severe systems among others are always associated with the destruction of property and livelihoods;losses of lives lost, migrations, and resource based conflicts among many other miseries. Intergovernmental Panel on Climate Change (IPCC) has shown that climate change is real and requires sound knowledge of local future climate change scenarios. The study attempted to provide projected rainfall and temperature change scenarios over Lower Jubba, Somalia. This was done using the downscaled Coordinated Regional Downscaling Experiment (CORDEX) RCMs data. The simulated temperature and rainfall data derived from the CORDEX RCMs ensemble were compared with the observed data. The study focused on the IPCC projected periods of 2030, 2050 and 2070 benchmarks. Analysis of the projected rainfall indicated a decreasing trend in rainfall leading up to 2030 followed by an increase in rainfall with the 2050 and 2070 scenarios. In the case of temperature, the projections from all the models showed increase in minimum and maximum temperatures in all seasons and sub periods, like being observed by temperature projection over other parts of the world. The 2030, 2050 and 2070 projected rainfall and temperature change scenarios show that Somalia future development and livelihoods will in future face increased threats of climate extremes unless effective climate smart adaptation systems form integral components of national development strategies.展开更多
<p align="justify"> <span style="font-family:Verdana;">This study sought to determine the spatial and temporal variability of rainfall under past and future climate scenarios. The data ...<p align="justify"> <span style="font-family:Verdana;">This study sought to determine the spatial and temporal variability of rainfall under past and future climate scenarios. The data used comprised station-based monthly gridded rainfall data sourced from the Climate Research </span><span style="font-family:Verdana;">Unit (CRU) and monthly model outputs from the Fourth Edition of the Rossby Centre (RCA4) Regional Climate Model (RCM), which has scaled-down </span><span style="font-family:Verdana;">nine GCMs for Africa. Although the 9 Global Climate Models (GCMs) downscaled by the RCA4 model was not very good at simulating rainfall in Kenya, the ensemble of the 9 models performed better and could be used for further studies. The ensemble of the models was thus bias-corrected using the scaling method to reduce the error;lower values of bias and Normalized Root Mean Square Error (NRMSE) w</span></span><span style="font-family:Verdana;">ere</span><span style="font-family:'Minion Pro Capt','serif';"><span style="font-family:Verdana;"> recorded when compared to the uncorrected models. The bias-corrected ensemble was used to study the spatial and temporal behaviour of rainfall under baseline (1971 to 2000) and future RCP 4.5 and 8.5 scenarios (2021 to 2050). An insignificant trend was noted under the </span><span style="font-family:Verdana;">baseline condition during the March-May (MAM) and October-December</span> <span style="font-family:Verdana;">(OND) rainfall seasons. A positive significant trend at 5% level was noted</span><span style="font-family:Verdana;"> under RCP 4.5 and 8.5 scenarios in some stations during both MAM and OND seasons. The increase in rainfall was attributed to global warming due to increased anthropogenic emissions of greenhouse gases. Results on the spatial variability of rainfall indicate the spatial extent of rainfall will increase under both RCP 4.5 and RCP 8.5 scenario when compared to the baseline;the increase is higher under the RCP 8.5 scenario. Overall rainfall was found to be highly variable in space and time, there is a need to invest in the early dissemination of weather forecasts to help farmers adequately prepare in case of unfavorable weather. Concerning the expected increase in rainfall in the future, policymakers need to consider the results of this study while preparing mitigation strategies against the effects of changing rainfall patterns.</span></span> </p>展开更多
In the particular context of climate change in Côte d’Ivoire and the vulnerability of farmers to its effects, one of the major issues is how these changes could impact cocoa yields of cocoa production areas....In the particular context of climate change in Côte d’Ivoire and the vulnerability of farmers to its effects, one of the major issues is how these changes could impact cocoa yields of cocoa production areas. Thus, the objective of this study is to sustainably increase the resilience of all cocoa farming stakeholders to the impacts of climate change. The study was carried out in the central and southern areas of Côte d’Ivoire with a focus on eleven localities that have many communities of cocoa producers and a humid climate. The rainfall and temperature observation data using come from the CRU, they cover the historical period from 1971 to 2000 at 0.5<sup>o</sup> × 0.5<sup>o</sup> horizontal scale. As for the RCP4.5 and RCP8.5 climate scenarios, they come from the CORDEX database and cover the 2021-2050 period. The methodology is based on the calculation of climatic indices sensitive to cocoa cultivation which are the number of consecutive dry days (CDD), the number of consecutive wet days (CWD), the amount of rain during the rainy season and the maximum temperature above 33℃. The results show that for all the localities studied, indices such as CDD and CWD could experience an increase. In addition, the total amount of rain during the long rainy season (April to June) is calculated on the basis of the threshold of 700 mm representing the minimum annual precipitation during the rainy season necessary for good growth of the cocoa tree. It reveals that for the two scenarios the cumulative rainfall will all be greater than 700 mm. Regarding temperatures, the central and southern areas could have a low number of hot days (temperature greater than or equal to 33℃ which is the tolerable threshold for cocoa cultivation). The eleven localities, therefore, remain favorable areas for cocoa cultivation in terms of climatic conditions based on temperature and rainfall, despite the regional dimension of the effects of climate change and the associated constraints.展开更多
基金supported by the National Key R&D Program of China[grant number 2016YFA0600704]the External Cooperation Program of BIC,Chinese Academy of Sciences[grant number 134111KYSB20150016]+1 种基金the National Natural Science Foundation of China[grant number 41775076]Youth Innovation Promotion Association CAS
文摘Using a regional climate model（RCM） is generally regarded as a promising approach in researching the climate of the Tibetan Plateau, due to the advantages provided by the high resolutions of these models. Whilst previous studies have focused mostly on individual RCM simulations, here, multiple RCMs from the Coordinated Regional Climate Downscaling Experiment are evaluated in simulating surface air temperature and precipitation changes over the Tibetan Plateau using station and gridded observations. The results show the following：（1） All RCMs consistently show similar spatial patterns, but a mean cold（wet） bias in the temperature（precipitation） climatology compared to station observations. The RCMs fail to reproduce the observed spatial patterns of temperature and precipitation trends, and on average produce greater trends in temperature and smaller trends in precipitation than observed results. The multi-model ensemble overall produces superior trends in both simulated temperature and precipitation relative to individual models. Meanwhile, Reg CM4 presents the most reasonable simulated trends among the five RCMs.（2） Considerable dissimilarities are shown in the simulated quantitative results from the different RCMs, which indicates a large model dependency in the simulation of climate over the Tibetan Plateau. This implies that caution may be needed when an individual RCM is used to estimate the amplitude of climate change over the Tibetan Plateau.（3） The temperature（precipitation） in 2016–35, relative to 1986–2005, is projected by the multi-model ensemble to increase by 1.38 ± 0.09 °C（0.8% ± 4.0%） and 1.77 ± 0.28 °C（7.3% ± 2.5%） under the RCP4.5 and RCP8.5 scenario, respectively. The results of this study advance our understanding of the applicability of RCMs in studies of climate change over the Tibetan Plateau from a multiple-RCM perspective.
文摘This study assessed the regional climate models (RCMs) employed in the Coordinated Regional climate Downscaling Experiment (CORDEX) South Asia framework to investigate the qualitative aspects of future change in seasonal mean near surface air temperature and precipitation over the Hindu Kush Himalayan (HKH) region. These RCMs downscaled a subset of atmosphere ocean coupled global climate models (AOGCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5) to higher 50 km spatial resolution over a large domain covering South Asia for two representation concentration pathways (RCP4.5 and RCP8.5) future scenarios. The analysis specifically examined and evaluated multi-model and multi-scenario climate change projections over the hilly sub-regions within HKH for the near-future (2036e2065) and far-future (2066e2095) periods. The downscaled multi-RCMs provide relatively better confidence than their driving AOGCMs in projecting the magnitude of seasonal warming for the hilly sub-region within the Karakoram and northwestern Himalaya, with higher projected change of 5.4 C during winter than of 4.9 C during summer monsoon season by the end of 21st century under the high-end emissions (RCP8.5) scenario. There is less agreement among these RCMs on the magnitude of the projected warming over the other sub-regions within HKH for both seasons, particularly associated with higher RCM uncertainty for the hilly sub-region within the central Himalaya. The downscaled multi-RCMs show good consensus and low RCM uncertainty in projecting that the summer monsoon precipitation will intensify by about 22% in the hilly subregion within the southeastern Himalaya and Tibetan Plateau for the far-future period under the RCP8.5 scenario. There is low confidence in the projected changes in the summer monsoon and winter season precipitation over the central Himalaya and in the Karakoram and northwestern Himalaya due to poor consensus and moderate to high RCM uncertainty among the downscaled multi-RCMs. Finally, the RCM related uncertainty is found to be large for the projected changes in seasonal temperature and precipitation over the hilly sub-regions within HKH by the end of this century, suggesting that improving the regional processes and feedbacks in RCMs are essential for narrowing the uncertainty, and for providing more reliable regional climate change projections suitable for impact assessments in HKH region.
文摘We investigated the performance of 12 different physics configurations of the climate version of the Weather, Research and Forecasting (WRF) Model over the Middle East and North Africa (MENA) domain. Possible combinations among two Planetary Boundary Layer (PBL), three Cumulus (CUM) and two Microphysics (MIC) schemes were tested. The 2-year simulations (December 1988-November 1990) have been compared with gridded observational data and station measurements for several variables, including total precipitation and maximum and minimum 2-meter air temperature. An objective ranking method of the 12 different simulations and the selection procedure of the best performing configuration for the MENA domain are based on several statistical metrics and carried out for relevant sub-domains and individual stations. The setup for cloud microphysics is found to have the strongest impact on temperature biases while precipitation is most sensitive to the cumulus parameterization scheme and mainly in the tropics.
文摘This study aims to evaluate the performance of the individual Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX) and the ensemble average of the four RCMs to feign the characteristics of the rainfall pattern for the Mbarali River catchment in Rufiji Basin for the period of 1979 to 2005. Statistical analysis for model performance such as Root mean square error, Mean error, Pearson correlation coefficient, Mean, Median, standard deviation and trend analysis are used. In addition to the statistical measure of model performance, the models are tested on their ability to capture the observed annual cycles and interannual variability of rainfall. Results indicated that the RCMs from the CORDEX indicated a better performance to reproduce the rainfall characteristics over Mbarali River catchment in Rufiji Basin. They reproduced fairly the Era Interim annual cycle and inter-annual variability of rainfall. The ensemble average performed better than individual models in representing rainfall over Mbarali River catchment in Rufiji Basin. These suggest that rainfall simulation from the ensemble average will be used for the assessment of the hydrological impact studies over Mbarali River catchment in Rufiji Basin.
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This paper investigates how well the rainfall regime on which many livelihoods depend, in Ghanais well represented by the Coordinated Regional Climate Downscaling Experiment (CORDEX). The objective of the study is to demonstrate how well the ten CORDEX models are able to capture the spatial and temporal rainfall seasonality over the southern and northern sub-sections ofGhana. The choice of the sub-sections is based on the fact that south of 8°N experiences a bi-modal rainfall regime while the north has a uni-modal regime. The results indicate that the rainfall overGhanais associated with high levels of variability at the inter-annual time scale. Particularly over the southern part ofGhana, all the models follow the same trend as represented overGhanawith similar rainfall values as the observation. Over the northern part ofGhana, models record relatively low rainfall agreeing with the observation. However, most of the models overestimate the northern region rainfall as it is in the case of the southern Ghana. CORDEX as shown in this analysis could be useful in providing Ghana with at least 10 different model outputs for impact analysis. Caution is however given that, since individual models give different performance and the fact that models in general have their inherent deficiencies, an ensemble mean of the models could provide a better result.
文摘Developing reliable adaptation and mitigation strategies to combat climate change is necessary at regional and local scales. The present study analyses the ability of the multi-model ensemble (MME) composed of fourteen (14) CORDEX-Africa simulations to capture characteristics of the mean temperature for the present day (1979-2005) and associated extremes over Côte d’Ivoire. For this end, the analysis uses the mean variables of the temperature (i.e., minimum temperature (TMIN), mean temperature (TMEAN) and maximum temperature (TMAX)) as well as associated extremes such as intra-period extreme temperature range (ETR), warm spell duration index (HWFI) and warm days index (TX90P) during January-February-March (JFM), April-May-June (AMJ), July-August-September (JAS) and October-November-December (OND) seasons. The results indicate that mean temperature variables (TMIN, TMEAN and TMAX) are underestimated by CORDEX MME in general, except TMEAN in the centre of Côte d’Ivoire. On the other hand, extreme temperature indices are overestimated over Côte d’Ivoire, except ETR in JAS with an underestimation of about 2˚C and TX90P during JAS in the southern part of the country in JFM, AMJ and OND with an underestimation varying between 1% to 4%. In addition, CORDEX MME and observational datasets (CPC and NCEP) have a significant correlation in simulating temperature variables (TMIN, TMEAN, TMIN), while this correlation is not significant in general for extreme temperature, except ETR and HWFI. Furthermore, extreme temperatures (TX90P and HWFI) are characterized by more important interannual variability in the observations CPC and NCEP for ETR. Moreover, mean temperature variables (TMIN, TMEAN, TMAX) show slight interannual variability with respect to the observations CPC and NCEP, which are characterized by the most variability. Overall, CORDEX MME outperforms the seasonal and spatial variability of the temperature and associated extremes over Côte d’Ivoire, although some biases in representing their magnitudes. Thus, the results of the present study will help take appropriate adaptation and mitigation strategies against heatwaves and extreme temperature advent over Côte d’Ivoire as these climate extremes are projected to increase over the country.
基金Supported by the National Key Research and Development Program of China(2023YFF0805404)。
文摘Under the Coordinated Regional Climate Downscaling Experiment East Asia(CORDEX-EA)framework,two regional climate simulations were conducted at a very high resolution(12.5 km)using the Regional Climate Model version 4(RegCM4)and the Weather Research and Forecasting(WRF)model,driven by the fifth generation ECMWF atmospheric reanalysis(ERA5)from 1980 to 2019.Evaluation against observations indicates that both RegCM4 and WRF can reproduce the mean climatology,interannual variability,and annual cycle of precipitation and surface air temperature(T2m),although some biases exist.WRF demonstrates skill in simulating the spatial pattern of annual and seasonal mean precipitation and T2m by reducing wet biases over land and warm biases in winter.RegCM4 can better capture the interannual variability of precipitation and T2m,exhibiting higher temporal correlation,while WRF tends to overestimate the interannual variability.Additionally,assessment of the simulated circulations against ERA5 reveals that the wet bias in summer is mainly attributed to the enhanced low-level southwesterly jet.In general,compared with the results at 50-and 25-km resolutions in the first and second phases of CORDEX-EA,the higher resolution(12.5 km)has effectively improved the interannual variability of the regional climate simulations.
文摘We analysed nine simulations from dynamic downscaling to a horizontal resolution of approximately 25 km of three general circulation models (GCMs). These GCMs use three regional climate models (RCMs) that participated in the coordinated downscaling experiment (CORDEX-CORE). These simulations were compared to three datasets of reanalysis. The ERA5 for temperature at 2 metres and for precipitation, Climate Hazards Center InfraRed Precipitation with Stations (CHIRPS) and African Rainfall Climatology from the Famine Early Warning System (FEWS-ARC) were used. To give an overview of these nine model experiments, we presented and compared the results of the latter with the reanalysis taken into account for the period 1983 - 2005. The results indicated that the nine models correctly reproduced the temperature and rainfall in West Africa during the historical period. In the Guinean coast region, REMO-NorESM1 and RegCM4-MPI-MR models well simulated precipitation and temperature during the historical period. In the Savannah region, RegCM4-NorESM1, CCLM5-MPI-LR, REMO-NorESM1, CCLM5-NorESM1 and CCLM5-HadGEM2 model gave best result. In the Sahel region, the RegCM4-HadGEM2 model gave a good correlation. Using the Taylor diagram in the historical period, all CORDEX-CORE RCMs had a strong relationship with temperature.
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
文摘Somalia has faced severe challenges linked to climate variability, which has been exacerbated by conflict and limited governance that persisted for decades. Today climate extremes such as floods, drought, and coastal marine severe systems among others are always associated with the destruction of property and livelihoods;losses of lives lost, migrations, and resource based conflicts among many other miseries. Intergovernmental Panel on Climate Change (IPCC) has shown that climate change is real and requires sound knowledge of local future climate change scenarios. The study attempted to provide projected rainfall and temperature change scenarios over Lower Jubba, Somalia. This was done using the downscaled Coordinated Regional Downscaling Experiment (CORDEX) RCMs data. The simulated temperature and rainfall data derived from the CORDEX RCMs ensemble were compared with the observed data. The study focused on the IPCC projected periods of 2030, 2050 and 2070 benchmarks. Analysis of the projected rainfall indicated a decreasing trend in rainfall leading up to 2030 followed by an increase in rainfall with the 2050 and 2070 scenarios. In the case of temperature, the projections from all the models showed increase in minimum and maximum temperatures in all seasons and sub periods, like being observed by temperature projection over other parts of the world. The 2030, 2050 and 2070 projected rainfall and temperature change scenarios show that Somalia future development and livelihoods will in future face increased threats of climate extremes unless effective climate smart adaptation systems form integral components of national development strategies.
文摘<p align="justify"> <span style="font-family:Verdana;">This study sought to determine the spatial and temporal variability of rainfall under past and future climate scenarios. The data used comprised station-based monthly gridded rainfall data sourced from the Climate Research </span><span style="font-family:Verdana;">Unit (CRU) and monthly model outputs from the Fourth Edition of the Rossby Centre (RCA4) Regional Climate Model (RCM), which has scaled-down </span><span style="font-family:Verdana;">nine GCMs for Africa. Although the 9 Global Climate Models (GCMs) downscaled by the RCA4 model was not very good at simulating rainfall in Kenya, the ensemble of the 9 models performed better and could be used for further studies. The ensemble of the models was thus bias-corrected using the scaling method to reduce the error;lower values of bias and Normalized Root Mean Square Error (NRMSE) w</span></span><span style="font-family:Verdana;">ere</span><span style="font-family:'Minion Pro Capt','serif';"><span style="font-family:Verdana;"> recorded when compared to the uncorrected models. The bias-corrected ensemble was used to study the spatial and temporal behaviour of rainfall under baseline (1971 to 2000) and future RCP 4.5 and 8.5 scenarios (2021 to 2050). An insignificant trend was noted under the </span><span style="font-family:Verdana;">baseline condition during the March-May (MAM) and October-December</span> <span style="font-family:Verdana;">(OND) rainfall seasons. A positive significant trend at 5% level was noted</span><span style="font-family:Verdana;"> under RCP 4.5 and 8.5 scenarios in some stations during both MAM and OND seasons. The increase in rainfall was attributed to global warming due to increased anthropogenic emissions of greenhouse gases. Results on the spatial variability of rainfall indicate the spatial extent of rainfall will increase under both RCP 4.5 and RCP 8.5 scenario when compared to the baseline;the increase is higher under the RCP 8.5 scenario. Overall rainfall was found to be highly variable in space and time, there is a need to invest in the early dissemination of weather forecasts to help farmers adequately prepare in case of unfavorable weather. Concerning the expected increase in rainfall in the future, policymakers need to consider the results of this study while preparing mitigation strategies against the effects of changing rainfall patterns.</span></span> </p>
文摘In the particular context of climate change in Côte d’Ivoire and the vulnerability of farmers to its effects, one of the major issues is how these changes could impact cocoa yields of cocoa production areas. Thus, the objective of this study is to sustainably increase the resilience of all cocoa farming stakeholders to the impacts of climate change. The study was carried out in the central and southern areas of Côte d’Ivoire with a focus on eleven localities that have many communities of cocoa producers and a humid climate. The rainfall and temperature observation data using come from the CRU, they cover the historical period from 1971 to 2000 at 0.5<sup>o</sup> × 0.5<sup>o</sup> horizontal scale. As for the RCP4.5 and RCP8.5 climate scenarios, they come from the CORDEX database and cover the 2021-2050 period. The methodology is based on the calculation of climatic indices sensitive to cocoa cultivation which are the number of consecutive dry days (CDD), the number of consecutive wet days (CWD), the amount of rain during the rainy season and the maximum temperature above 33℃. The results show that for all the localities studied, indices such as CDD and CWD could experience an increase. In addition, the total amount of rain during the long rainy season (April to June) is calculated on the basis of the threshold of 700 mm representing the minimum annual precipitation during the rainy season necessary for good growth of the cocoa tree. It reveals that for the two scenarios the cumulative rainfall will all be greater than 700 mm. Regarding temperatures, the central and southern areas could have a low number of hot days (temperature greater than or equal to 33℃ which is the tolerable threshold for cocoa cultivation). The eleven localities, therefore, remain favorable areas for cocoa cultivation in terms of climatic conditions based on temperature and rainfall, despite the regional dimension of the effects of climate change and the associated constraints.
