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
The magnitude and trend of temperature and rainfall extremes as indicators of climate variability and change were investigated in the Arid and Semi-Arid Lands (ASALs) of Kenya using in-situ measurements and gridded cl...The magnitude and trend of temperature and rainfall extremes as indicators of climate variability and change were investigated in the Arid and Semi-Arid Lands (ASALs) of Kenya using in-situ measurements and gridded climate proxy datasets, and analysed using the Gaussian-Kernel analysis and the Mann-Kendall statistics. The results show that the maximum and minimum temperatures have been increasing, with warmer temperatures being experienced mostly at night time. The average change in the mean maximum and minimum seasonal surface air temperature for the region were 0.74°C and 0.60°C, respectively between the 1961-1990 and 1991-2013 periods. Decreasing but statistically insignificant trends in the seasonal rainfall were noted in the area, but with mixed patterns in variability. The March-April-May rainfall season indicated the highest decrease in the seasonal rainfall amounts. The southern parts of the region had a decreasing trend in rainfall that was greater than that of the northern areas. The results of this study are expected to support sustainable pastoralism system prevalent with the local communities in the ASALs.展开更多
Rangelands dominate arid and semi-arid lands of the Greater Horn of Africa(GHA)region,whereby pastoralism being the primary source of livelihood.The pastoral livelihood is affected by the seasonal variability of pastu...Rangelands dominate arid and semi-arid lands of the Greater Horn of Africa(GHA)region,whereby pastoralism being the primary source of livelihood.The pastoral livelihood is affected by the seasonal variability of pasture and water resources.This research sought to design a grid-based forage monitoring and prediction model for the cross-border areas of the GHA region.A technique known as Geographically Weighted Regression was used in developing the model with monthly rainfall,temperature,soil moisture,and the Normalized Difference Vegetation Index(NDVI).Rainfall and soil moisture had a high correlation with NDVI,and thus formed the model development parameters.The model performed well in predicting the available forage biomass at each grid-cell with March-May and October-December seasons depicting a similar pattern but with a different magnitude in ton/ha.The output is critical for actionable early warning over the GHA region’s rangeland areas.It is expected that this mode can be used operationally for forage monitoring and prediction over the eastern Africa region and further guide the regional,national,sub-national actors and policymakers on issuing advisories before the season.展开更多
<div style="text-align:justify;"> <span style="font-family:Verdana;"></span>Recent trends show that in the coming decades, Kenya’s natural resources will continue to face signifi...<div style="text-align:justify;"> <span style="font-family:Verdana;"></span>Recent trends show that in the coming decades, Kenya’s natural resources will continue to face significant pressure due to both anthropogenic and natural stressors, and this will have greater negative impacts on socio-economic development including food security and livelihoods. Understanding the impacts of these stressors is an important step to developing coping and adaptation strategies at every level. The Water Towers of Kenya play a critical role in supplying ecosystems services such as water supply, timber and non-timber forest products and regulating services such as climate and water quantity and quality. To assess the vulnerability of the Water Towers to climate change, the study adopted the IPCC AR4 framework that defines vulnerability as a function of exposure, sensitivity, and adaptive capacity. The historical trends in rainfall indicate that the three Water Towers show a declining rainfall trend during the March-April-May (MAM) main rainy season, while the October-November-December (OND) short rainy season shows an increase. The temperature patterns are consistent with the domain having a common rising trend with a rate in the range of 0.3<span style="color:#4F4F4F;font-family:-apple-system, "font-size:14px;white-space:normal;background-color:#FFFFFF;">°</span>C to 0.5<span style="color:#4F4F4F;font-family:-apple-system, "font-size:14px;white-space:normal;background-color:#FFFFFF;">°</span>C per decade. Projection analysis considered three emissions scenarios: low-emission (mitigation) scenario (RCP2.6), a medium-level emission scenario (RCP4.5), and a high-emission (business as usual) scenario (RCP8.5). The results of the high-emission scenario show that the annual temperature over the Water Towers could rise by 3.0<span style="color:#4F4F4F;font-family:-apple-system, "font-size:14px;white-space:normal;background-color:#FFFFFF;">°</span>C to 3.5<span style="color:#4F4F4F;font-family:-apple-system, "font-size:14px;white-space:normal;background-color:#FFFFFF;">°</span>C by the 2050s (2036-2065) and 3.6<span style="color:#4F4F4F;font-family:-apple-system, "font-size:14px;white-space:normal;background-color:#FFFFFF;">°</span>C to 4.8<span style="color:#4F4F4F;font-family:-apple-system, "font-size:14px;white-space:normal;background-color:#FFFFFF;">°</span>C by the 2070s (2055-2085 results not presented), relative to the baseline period 1970-2000. The findings indicate that exposure, sensitivity, and adaptive capacity vary in magnitude, as well as spatially across the Water Towers. This is reflected in the spatially variable vulnerability index across the Water Towers. Overall vulnerability will increase in the water towers leading to erosion of the resilience of the exposed ecosystems and the communities that rely on ecosystem services these landscapes provide. </div>展开更多
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The magnitude and trend of temperature and rainfall extremes as indicators of climate variability and change were investigated in the Arid and Semi-Arid Lands (ASALs) of Kenya using in-situ measurements and gridded climate proxy datasets, and analysed using the Gaussian-Kernel analysis and the Mann-Kendall statistics. The results show that the maximum and minimum temperatures have been increasing, with warmer temperatures being experienced mostly at night time. The average change in the mean maximum and minimum seasonal surface air temperature for the region were 0.74°C and 0.60°C, respectively between the 1961-1990 and 1991-2013 periods. Decreasing but statistically insignificant trends in the seasonal rainfall were noted in the area, but with mixed patterns in variability. The March-April-May rainfall season indicated the highest decrease in the seasonal rainfall amounts. The southern parts of the region had a decreasing trend in rainfall that was greater than that of the northern areas. The results of this study are expected to support sustainable pastoralism system prevalent with the local communities in the ASALs.
基金supported by the World Bank International Development Association(IDA)Grant No.:H9190,under the Regional Pastoral Livelihoods Resilience Project(RPLRP).
文摘Rangelands dominate arid and semi-arid lands of the Greater Horn of Africa(GHA)region,whereby pastoralism being the primary source of livelihood.The pastoral livelihood is affected by the seasonal variability of pasture and water resources.This research sought to design a grid-based forage monitoring and prediction model for the cross-border areas of the GHA region.A technique known as Geographically Weighted Regression was used in developing the model with monthly rainfall,temperature,soil moisture,and the Normalized Difference Vegetation Index(NDVI).Rainfall and soil moisture had a high correlation with NDVI,and thus formed the model development parameters.The model performed well in predicting the available forage biomass at each grid-cell with March-May and October-December seasons depicting a similar pattern but with a different magnitude in ton/ha.The output is critical for actionable early warning over the GHA region’s rangeland areas.It is expected that this mode can be used operationally for forage monitoring and prediction over the eastern Africa region and further guide the regional,national,sub-national actors and policymakers on issuing advisories before the season.
文摘<div style="text-align:justify;"> <span style="font-family:Verdana;"></span>Recent trends show that in the coming decades, Kenya’s natural resources will continue to face significant pressure due to both anthropogenic and natural stressors, and this will have greater negative impacts on socio-economic development including food security and livelihoods. Understanding the impacts of these stressors is an important step to developing coping and adaptation strategies at every level. The Water Towers of Kenya play a critical role in supplying ecosystems services such as water supply, timber and non-timber forest products and regulating services such as climate and water quantity and quality. To assess the vulnerability of the Water Towers to climate change, the study adopted the IPCC AR4 framework that defines vulnerability as a function of exposure, sensitivity, and adaptive capacity. The historical trends in rainfall indicate that the three Water Towers show a declining rainfall trend during the March-April-May (MAM) main rainy season, while the October-November-December (OND) short rainy season shows an increase. The temperature patterns are consistent with the domain having a common rising trend with a rate in the range of 0.3<span style="color:#4F4F4F;font-family:-apple-system, "font-size:14px;white-space:normal;background-color:#FFFFFF;">°</span>C to 0.5<span style="color:#4F4F4F;font-family:-apple-system, "font-size:14px;white-space:normal;background-color:#FFFFFF;">°</span>C per decade. Projection analysis considered three emissions scenarios: low-emission (mitigation) scenario (RCP2.6), a medium-level emission scenario (RCP4.5), and a high-emission (business as usual) scenario (RCP8.5). The results of the high-emission scenario show that the annual temperature over the Water Towers could rise by 3.0<span style="color:#4F4F4F;font-family:-apple-system, "font-size:14px;white-space:normal;background-color:#FFFFFF;">°</span>C to 3.5<span style="color:#4F4F4F;font-family:-apple-system, "font-size:14px;white-space:normal;background-color:#FFFFFF;">°</span>C by the 2050s (2036-2065) and 3.6<span style="color:#4F4F4F;font-family:-apple-system, "font-size:14px;white-space:normal;background-color:#FFFFFF;">°</span>C to 4.8<span style="color:#4F4F4F;font-family:-apple-system, "font-size:14px;white-space:normal;background-color:#FFFFFF;">°</span>C by the 2070s (2055-2085 results not presented), relative to the baseline period 1970-2000. The findings indicate that exposure, sensitivity, and adaptive capacity vary in magnitude, as well as spatially across the Water Towers. This is reflected in the spatially variable vulnerability index across the Water Towers. Overall vulnerability will increase in the water towers leading to erosion of the resilience of the exposed ecosystems and the communities that rely on ecosystem services these landscapes provide. </div>
