The development of adaptation measures to climate change relies on data from climate models or impact models. In order to analyze these large data sets or an ensemble of these data sets, the use of statistical methods...The development of adaptation measures to climate change relies on data from climate models or impact models. In order to analyze these large data sets or an ensemble of these data sets, the use of statistical methods is required. In this paper, the methodological approach to collecting, structuring and publishing the methods, which have been used or developed by former or present adaptation initiatives, is described. The intention is to communicate achieved knowledge and thus support future users. A key component is the participation of users in the development process. Main elements of the approach are standardized, template-based descriptions of the methods including the specific applications, references, and method assessment. All contributions have been quality checked, sorted, and placed in a larger context. The result is a report on statistical methods which is freely available as printed or online version. Examples of how to use the methods are presented in this paper and are also included in the brochure.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
This study assesses the potential impacts of climate change on water resources and the effect of statistical bias correction on the projected climate change signal in hydrological variables over the Upper Senegal Basi...This study assesses the potential impacts of climate change on water resources and the effect of statistical bias correction on the projected climate change signal in hydrological variables over the Upper Senegal Basin (West Africa). Original and bias corrected climate data from the regional climate model REMO were used as input for the Max Planck Institute for Meteorology-Hydrology Model (MPI-HM) to simulate river discharge, runoff, soil moisture and evapotranspiration. The results during the historical period (1971-2000) show that using the bias corrected input yields a better representation of the mean river flow regimes and the 10th and 90th percentiles of river flow at the outlet of the Upper Senegal Basin (USB). The Nash-Sutcliffe efficiency coefficient is 0.92 using the bias corrected input, which demonstrates the ability of the model in simulating river flow. The percent bias of 3.88% indicates a slight overestimation of the river flow by the model using the corrected input. The evaluation demonstrates the ability of the bias correction and its necessity for the simulation of historical river regimes. As for the potential changes of hydrological variables by the end of 21st century (2071-2100), a general decrease of river discharge, runoff, actual evapotranspiration, soil moisture is found under two Representative Concentration Pathways (RCP4.5 and RCP8.5) in all simulations. The decrease is higher under RCP8.5 with uncorrected data in the northern basin. However, there are some localized increases in some parts of the basin (e.g. Guinean Highlands). The projected climate change signal of these above variables has the same spatial pattern and tendency for the uncorrected and bias corrected data although the magnitude of the corrected signal is somewhat lower than that uncorrected. Furthermore, the available water resources are projected to substantially decrease by more than -50% in the majority of the basin (especially in driest and hottest northern basin with RCP8.5 scenario) for all data, except the Guinean highlands where no change is projected. The comparison of simulations driven with uncorrected and bias corrected input reveals that the bias correction does not substantially change the signal of future changes of hydrological variables for both scenarios over the USB even though there are differences in magnitude and deviations in some parts of the basin.展开更多
The internal variability of a ten-member ensemble of the regional climate model REMO over Europe is investigated. It is shown that the annual cycle of internal variability behaves differently compared to earlier studi...The internal variability of a ten-member ensemble of the regional climate model REMO over Europe is investigated. It is shown that the annual cycle of internal variability behaves differently compared to earlier studies that focused on other regions. To gain better insight into the dependence of the internal variability on the boundary forcing variability, a circulation type classification is performed on the forcing data. It can be shown that especially in the winter season internal variability is dependent on the circulation type included in the boundary forcing, whereas in the summer season the level and pattern of internal variability is rather independent from the circulation type of the driving field. It is concluded that for Europe the internal variability of REMO in winter is governed by circulation patterns related to the North-Atlantic Oscillation, whereas in summer local processes play a bigger role.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
文摘The development of adaptation measures to climate change relies on data from climate models or impact models. In order to analyze these large data sets or an ensemble of these data sets, the use of statistical methods is required. In this paper, the methodological approach to collecting, structuring and publishing the methods, which have been used or developed by former or present adaptation initiatives, is described. The intention is to communicate achieved knowledge and thus support future users. A key component is the participation of users in the development process. Main elements of the approach are standardized, template-based descriptions of the methods including the specific applications, references, and method assessment. All contributions have been quality checked, sorted, and placed in a larger context. The result is a report on statistical methods which is freely available as printed or online version. Examples of how to use the methods are presented in this paper and are also included in the brochure.
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This study assesses the potential impacts of climate change on water resources and the effect of statistical bias correction on the projected climate change signal in hydrological variables over the Upper Senegal Basin (West Africa). Original and bias corrected climate data from the regional climate model REMO were used as input for the Max Planck Institute for Meteorology-Hydrology Model (MPI-HM) to simulate river discharge, runoff, soil moisture and evapotranspiration. The results during the historical period (1971-2000) show that using the bias corrected input yields a better representation of the mean river flow regimes and the 10th and 90th percentiles of river flow at the outlet of the Upper Senegal Basin (USB). The Nash-Sutcliffe efficiency coefficient is 0.92 using the bias corrected input, which demonstrates the ability of the model in simulating river flow. The percent bias of 3.88% indicates a slight overestimation of the river flow by the model using the corrected input. The evaluation demonstrates the ability of the bias correction and its necessity for the simulation of historical river regimes. As for the potential changes of hydrological variables by the end of 21st century (2071-2100), a general decrease of river discharge, runoff, actual evapotranspiration, soil moisture is found under two Representative Concentration Pathways (RCP4.5 and RCP8.5) in all simulations. The decrease is higher under RCP8.5 with uncorrected data in the northern basin. However, there are some localized increases in some parts of the basin (e.g. Guinean Highlands). The projected climate change signal of these above variables has the same spatial pattern and tendency for the uncorrected and bias corrected data although the magnitude of the corrected signal is somewhat lower than that uncorrected. Furthermore, the available water resources are projected to substantially decrease by more than -50% in the majority of the basin (especially in driest and hottest northern basin with RCP8.5 scenario) for all data, except the Guinean highlands where no change is projected. The comparison of simulations driven with uncorrected and bias corrected input reveals that the bias correction does not substantially change the signal of future changes of hydrological variables for both scenarios over the USB even though there are differences in magnitude and deviations in some parts of the basin.
文摘The internal variability of a ten-member ensemble of the regional climate model REMO over Europe is investigated. It is shown that the annual cycle of internal variability behaves differently compared to earlier studies that focused on other regions. To gain better insight into the dependence of the internal variability on the boundary forcing variability, a circulation type classification is performed on the forcing data. It can be shown that especially in the winter season internal variability is dependent on the circulation type included in the boundary forcing, whereas in the summer season the level and pattern of internal variability is rather independent from the circulation type of the driving field. It is concluded that for Europe the internal variability of REMO in winter is governed by circulation patterns related to the North-Atlantic Oscillation, whereas in summer local processes play a bigger role.
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.
