Sizeable areas of Southern African Region experienced widespread flooding in 2000. Deployment of ... more Sizeable areas of Southern African Region experienced widespread flooding in 2000. Deployment of hydrologic models can help reduce the human and economic losses in the regions by providing improved monitoring and forecast information to guide relief activities. This study describes a hydrologic model developed for wide area flood risk monitoring for the Southern African region. The model is forced by daily estimates of rainfall and evapotranspiration derived from remotely sensed data and assimilation fields. Model predictive skills were verified with data observed stream flow data from locations within the Limpopo basin. The model performed well in simulating the timing and magnitude of the stream flow during a recent episode of flooding in Mozambique in 2000.
Ethiopia and South Sudan contain several population centers and important ecosystems that depend ... more Ethiopia and South Sudan contain several population centers and important ecosystems that depend on July–August rainfall. Here we use two models to understand current and future rainfall: the first ever pan-African numerical model of climate change with explicit convection and a parameterized model that resembles a typical regional climate model at 4.5 and 25 km horizontal grid-spacing, respectively. The explicit convection and higher resolution of the first model offer a greatly improved representation of both the frequency and intensity of rainfall, when compared to the parametrized convection model. Furthermore, only this model has success in capturing the east–west propagation of rainfall over the full diurnal cycle. Enhanced low-level westerlies were found for extremely wet days, though this response was weaker in the explicit convection model. The increased orographic detail in the explicit model resulted in the splitting of the low-level Turkana Jet core into smaller cores, a...
The aim of this study was to determine suitability zones of future banana growth under a changing... more The aim of this study was to determine suitability zones of future banana growth under a changing climate to guide the design of future adaptation options in the banana sub-sector of Uganda. The study used high resolution (~1 km) data on combined bioclimatic variables (rainfall and temperature) to map suitability zones of the banana crop while the Providing Regional Climate for Impacts Studies (PRECIS) regional climate model temperature simulations were used to estimate the effect of rising temperature on banana growth assuming other factors constant. The downscaled future climate projections were based on the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCPs, 2.6, 4.5, 6.0 and 8.5) and Special Report on Emission Scenarios (SRES, A1B and A2) across the period 2011–2090. The methodology involved identification of banana-climate growth thresholds and developing suitability indices for banana production under the high mitigation (RCP 2.6, less adaptation), medium mitigation (RCP 4.5 and RCP 6.0, medium adaptation), no mitigation (RCP 8.5, very high adaptation) scenarios, SRES A1B and A2 scenarios. The FAO ECO-Crop tool was used to determine and map future suitability of banana growth. Banana production indices were determined using a suitability model in the Geographical Information System (GIS) spatial analyst tool. The non-linear banana-temperature regression model was used to assess the impact of future changes in temperature on banana growth. The results revealed unique and distinct banana production suitability and growth patterns for each climate scenario in the sub-periods. RCPs 2.6 and 6.5 are likely to be associated with higher levels of banana production than RCPs 4.5 and 8.5. The results further showed that projected temperature increase under SRES A1B will promote banana growth. In contrast, expected increases in temperatures under SRES A2 are likely to retard banana growth due to high moisture deficits. There is need to develop adaptation option for farming communities to maximize their agricultural production and incomes. The effectiveness of adaptation options needed to combat the impacts will be influenced by the magnitude of the expected climatic changes associated with each scenario, the timing of expected climate change extremes and sensitivity of the crop to climate. This study has provided critical information that will be useful for planning integrated adaptation practices in the banana farming subsector to promote productivity.
The skill of precipitation forecasts from global prediction systems has a strong regional and sea... more The skill of precipitation forecasts from global prediction systems has a strong regional and seasonal dependence. Quantifying the skill of models for different regions and timescales is important, not only to improve forecast skill, but to enhance the effective uptake of forecast information. The sub-seasonal to seasonal prediction (S2S) database contains near real-time forecasts and re-forecasts from 11 operational centres and provides a great opportunity to evaluate and compare the skill of operational S2S systems. This study evaluates the skill of these state-of-the-art global prediction systems in predicting monthly precipitation over the Greater Horn of Africa. This comprehensive evaluation was performed using deterministic and probabilistic forecast verification metrics. Results from the analysis showed that the prediction skill varies with months and region. Generally, the models show high prediction skill during the start of the rainfall season in March and lower prediction...
Climate models are becoming evermore complex and increasingly relied upon to inform climate chang... more Climate models are becoming evermore complex and increasingly relied upon to inform climate change adaptation. Yet progress in model development is lagging behind in many of the regions that need the information most, including in Africa. Targeted model development for Africa is crucial and so too is targeted model evaluation. Assessment of model performance in specific regions often follows a “validation” approach, focusing on mean biases, but if models are to be improved, it is important to understand how they simulate regional climate dynamics: to move from validation to process-based evaluation. This evaluation may be different for every region and requires local weather and climate expertise: a “one size fits all” approach could overlook important, region-specific phenomena. So which are the important processes in African regions? And how might they be evaluated? This paper addresses these questions, drawing on the expertise of a team of scientists from Central, East, southern,...
Sizeable areas of Southern African Region experienced widespread flooding in 2000. Deployment of ... more Sizeable areas of Southern African Region experienced widespread flooding in 2000. Deployment of hydrologic models can help reduce the human and economic losses in the regions by providing improved monitoring and forecast information to guide relief activities. This study describes a hydrologic model developed for wide area flood risk monitoring for the Southern African region. The model is forced by daily estimates of rainfall and evapotranspiration derived from remotely sensed data and assimilation fields. Model predictive skills were verified with data observed stream flow data from locations within the Limpopo basin. The model performed well in simulating the timing and magnitude of the stream flow during a recent episode of flooding in Mozambique in 2000.
Ethiopia and South Sudan contain several population centers and important ecosystems that depend ... more Ethiopia and South Sudan contain several population centers and important ecosystems that depend on July–August rainfall. Here we use two models to understand current and future rainfall: the first ever pan-African numerical model of climate change with explicit convection and a parameterized model that resembles a typical regional climate model at 4.5 and 25 km horizontal grid-spacing, respectively. The explicit convection and higher resolution of the first model offer a greatly improved representation of both the frequency and intensity of rainfall, when compared to the parametrized convection model. Furthermore, only this model has success in capturing the east–west propagation of rainfall over the full diurnal cycle. Enhanced low-level westerlies were found for extremely wet days, though this response was weaker in the explicit convection model. The increased orographic detail in the explicit model resulted in the splitting of the low-level Turkana Jet core into smaller cores, a...
The aim of this study was to determine suitability zones of future banana growth under a changing... more The aim of this study was to determine suitability zones of future banana growth under a changing climate to guide the design of future adaptation options in the banana sub-sector of Uganda. The study used high resolution (~1 km) data on combined bioclimatic variables (rainfall and temperature) to map suitability zones of the banana crop while the Providing Regional Climate for Impacts Studies (PRECIS) regional climate model temperature simulations were used to estimate the effect of rising temperature on banana growth assuming other factors constant. The downscaled future climate projections were based on the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCPs, 2.6, 4.5, 6.0 and 8.5) and Special Report on Emission Scenarios (SRES, A1B and A2) across the period 2011–2090. The methodology involved identification of banana-climate growth thresholds and developing suitability indices for banana production under the high mitigation (RCP 2.6, less adaptation), medium mitigation (RCP 4.5 and RCP 6.0, medium adaptation), no mitigation (RCP 8.5, very high adaptation) scenarios, SRES A1B and A2 scenarios. The FAO ECO-Crop tool was used to determine and map future suitability of banana growth. Banana production indices were determined using a suitability model in the Geographical Information System (GIS) spatial analyst tool. The non-linear banana-temperature regression model was used to assess the impact of future changes in temperature on banana growth. The results revealed unique and distinct banana production suitability and growth patterns for each climate scenario in the sub-periods. RCPs 2.6 and 6.5 are likely to be associated with higher levels of banana production than RCPs 4.5 and 8.5. The results further showed that projected temperature increase under SRES A1B will promote banana growth. In contrast, expected increases in temperatures under SRES A2 are likely to retard banana growth due to high moisture deficits. There is need to develop adaptation option for farming communities to maximize their agricultural production and incomes. The effectiveness of adaptation options needed to combat the impacts will be influenced by the magnitude of the expected climatic changes associated with each scenario, the timing of expected climate change extremes and sensitivity of the crop to climate. This study has provided critical information that will be useful for planning integrated adaptation practices in the banana farming subsector to promote productivity.
The skill of precipitation forecasts from global prediction systems has a strong regional and sea... more The skill of precipitation forecasts from global prediction systems has a strong regional and seasonal dependence. Quantifying the skill of models for different regions and timescales is important, not only to improve forecast skill, but to enhance the effective uptake of forecast information. The sub-seasonal to seasonal prediction (S2S) database contains near real-time forecasts and re-forecasts from 11 operational centres and provides a great opportunity to evaluate and compare the skill of operational S2S systems. This study evaluates the skill of these state-of-the-art global prediction systems in predicting monthly precipitation over the Greater Horn of Africa. This comprehensive evaluation was performed using deterministic and probabilistic forecast verification metrics. Results from the analysis showed that the prediction skill varies with months and region. Generally, the models show high prediction skill during the start of the rainfall season in March and lower prediction...
Climate models are becoming evermore complex and increasingly relied upon to inform climate chang... more Climate models are becoming evermore complex and increasingly relied upon to inform climate change adaptation. Yet progress in model development is lagging behind in many of the regions that need the information most, including in Africa. Targeted model development for Africa is crucial and so too is targeted model evaluation. Assessment of model performance in specific regions often follows a “validation” approach, focusing on mean biases, but if models are to be improved, it is important to understand how they simulate regional climate dynamics: to move from validation to process-based evaluation. This evaluation may be different for every region and requires local weather and climate expertise: a “one size fits all” approach could overlook important, region-specific phenomena. So which are the important processes in African regions? And how might they be evaluated? This paper addresses these questions, drawing on the expertise of a team of scientists from Central, East, southern,...
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