Feedback of observed interannual vegetation change: a regional climate model analysis for the West African monsoon

West Africa is a hot spot region for land–atmosphere coupling where atmospheric conditions and convective rainfall can strongly depend on surface characteristics. To investigate the effect of natural interannual vegetation changes on the West African monsoon precipitation, we implement satellite-derived dynamical datasets for vegetation fraction (VF), albedo and leaf area index into the Weather Research and Forecasting model. Two sets of 4-member ensembles with dynamic and static land surface description are used to extract vegetation-related changes in the interannual difference between August–September 2009 and 2010. The observed vegetation patterns retain a significant long-term memory of preceding rainfall patterns of at least 2 months. The interannual vegetation changes exhibit the strongest effect on latent heat fluxes and associated surface temperatures. We find a decrease (increase) of rainy hours over regions with higher (lower) VF during the day and the opposite during the night. The probability that maximum precipitation is shifted to nighttime (daytime) over higher (lower) VF is 12 % higher than by chance. We attribute this behaviour to horizontal circulations driven by differential heating. Over more vegetated regions, the divergence of moist air together with lower sensible heat fluxes hinders the initiation of deep convection during the day. During the night, mature convective systems cause an increase in the number of rainy hours over these regions. We identify this feedback in both water- and energy-limited regions of West Africa. The inclusion of observed dynamical surface information improved the spatial distribution of modelled rainfall in the Sahel with respect to observations, illustrating the potential of satellite data as a boundary constraint for atmospheric models

Probabilistic forecast of daily areal precipitation focusing on extreme events

A dynamical downscaling scheme is usually used to provide a short range flood forecasting system with high-resolved precipitation fields. Unfortunately, a single forecast of this scheme has a high uncertainty concerning intensity and location especially during extreme events. Alternatively, statistical downscaling techniques like the analogue method can be used which can supply a probabilistic forecasts. However, the performance of the analogue method is affected by the similarity criterion, which is used to identify similar weather situations. To investigate this issue in this work, three different similarity measures are tested: the euclidean distance (1), the Pearson correlation (2) and a combination of both measures (3). The predictor variables are geopotential height at 1000 and 700 hPa-level and specific humidity fluxes at 700 hPa-level derived from the NCEP/NCAR-reanalysis project. The study is performed for three mesoscale catchments located in the Rhine basin in Germany. It is validated by a jackknife method for a period of 44 years (1958–2001). The ranked probability skill score, the Brier Skill score, the Heidke skill score and the confidence interval of the Cramer association coefficient are calculated to evaluate the system for extreme events. The results show that the combined similarity measure yields the best results in predicting extreme events. However, the confidence interval of the Cramer coefficient indicates that this improvement is only significant compared to the Pearson correlation but not for the euclidean distance. Furthermore, the performance of the presented forecasting system is very low during the summer and new predictors have to be tested to overcome this problem

The WASCAL high-resolution regional climate simulation ensemble for West Africa: concept, dissemination and assessment

Climate change and constant population growth pose severe challenges to 21st century rural Africa. Within the framework of the West African Science Service Center on Climate Change and Adapted Land Use (WASCAL), an ensemble of high-resolution regional climate change scenarios for the greater West African region is provided to support the development of effective adaptation and mitigation measures. This contribution presents the overall concept of the WASCAL regional climate simulations, as well as detailed information on the experimental design, and provides information on the format and dissemination of the available data. All data are made available to the public at the CERA long-term archive of the German Climate Computing Center (DKRZ) with a subset available at the PANGAEA Data Publisher for Earth & Environmental Science portal (https://doi.pangaea.de/10.1594/PANGAEA.880512). A brief assessment of the data are presented to provide guidance for future users. Regional climate projections are generated at high (12 km) and intermediate (60 km) resolution using the Weather Research and Forecasting Model (WRF). The simulations cover the validation period 1980–2010 and the two future periods 2020–2050 and 2070–2100. A brief comparison to observations and two climate change scenarios from the Coordinated Regional Downscaling Experiment (CORDEX) initiative is presented to provide guidance on the data set to future users and to assess their climate change signal. Under the RCP4.5 (Representative Concentration Pathway 4.5) scenario, the results suggest an increase in temperature by 1.5 °C at the coast of Guinea and by up to 3 °C in the northern Sahel by the end of the 21st century, in line with existing climate projections for the region. They also project an increase in precipitation by up to 300 mm per year along the coast of Guinea, by up to 150 mm per year in the Soudano region adjacent in the north and almost no change in precipitation in the Sahel. This stands in contrast to existing regional climate projections, which predict increasingly drier conditions. The high spatial and temporal resolution of the data, the extensive list of output variables, the large computational domain and the long time periods covered make this data set a unique resource for follow-up analyses and impact modelling studies over the greater West African region. The comprehensive documentation and standardisation of the data facilitate and encourage their use within and outside of the WASCAL community

Where should sports events be held under global warming? A case study of the African Cup of Nations

Africa is a global hotspot for climate change, affecting various sectors, including sports. Against this backdrop, major international sports events such as the African Cup of Nations (Afcon) could become more complex under global warming. This study examines projected changes in the wet-bulb globe temperature (WBGT) index used as a proxy to determine suitable Afcon host countries under climate change conditions. Using eleven CMIP6 simulations from NASA's NEX-GDDP-CMIP6, downscaled to a 25 km resolution, the analysis covers three shared socioeconomic pathways (SSP1–2.6, SSP2–4.5, and SSP5–8.5) climate change scenarios for the near future (2031–2060) and far future (2071–2100), relative to 1985–2014. The model ensemble mean reproduced the spatial distribution of the WBGT index and related variables well with the reference datasets over Africa but with some biases. Projections indicate a significant WBGT increase across Africa under all scenarios and periods, especially under SSP5–8.5 in the far future, with a value of about 6 °C. Many countries may transition from an unrestricted to a high-risk status. Climate change could notably reduce the number of Afcon host countries under the SSP5–8.5 scenario. This study provides valuable insights for Afcon hosting and climate change integration, contributing to resilience and sustainability in urban environments hosting such events

Where should sports events be held under global warming? A case study of the African Cup of Nations

Africa is a global hotspot for climate change, affecting various sectors, including sports. Against this backdrop, major international sports events such as the African Cup of Nations (Afcon) could become more complex under global warming. This study examines projected changes in the wet-bulb globe temperature (WBGT) index used as a proxy to determine suitable Afcon host countries under climate change conditions. Using eleven CMIP6 simulations from NASA\u27s NEX-GDDP-CMIP6, downscaled to a 25 km resolution, the analysis covers three shared socioeconomic pathways (SSP1–2.6, SSP2–4.5, and SSP5–8.5) climate change scenarios for the near future (2031–2060) and far future (2071–2100), relative to 1985–2014. The model ensemble mean reproduced the spatial distribution of the WBGT index and related variables well with the reference datasets over Africa but with some biases. Projections indicate a significant WBGT increase across Africa under all scenarios and periods, especially under SSP5–8.5 in the far future, with a value of about 6 °C. Many countries may transition from an unrestricted to a high-risk status. Climate change could notably reduce the number of Afcon host countries under the SSP5–8.5 scenario. This study provides valuable insights for Afcon hosting and climate change integration, contributing to resilience and sustainability in urban environments hosting such events

Atmospheric circulation patterns that trigger heavy rainfall in West Africa

Classification of atmospheric circulation patterns (CP) is a common tool for downscaling rainfall, but it is rarely used for West Africa. In this study, a two-step classification procedure is proposed for this region, which is applied from 1989 to 2010 for the Sudan-Sahel zone (Central Burkina Faso) with a focus on heavy rainfall. The approach is based on a classification of large-scale atmospheric CPs (e.g., Saharan Heat Low) of the West African Monsoon using a fuzzy rule-based method to describe the seasonal rainfall variability. The wettest CPs are further classified using meso-scale monsoon patterns to better describe the daily rainfall variability during the monsoon period. A comprehensive predictor screening for the seasonal classification indicates that the best performing predictor variables (e.g., surface pressure, meridional moisture fluxes) are closely related to the main processes of the West African Monsoon. In the second classification step, the stream function at 700 hPa for identifying troughs and ridges of tropical waves shows the highest performance, providing an added value to the overall performance of the classification. Thus, the new approach can better distinguish between dry and wet CPs during the rainy season. Moreover, CPs are identified that are of high relevance for daily heavy rainfall in the study area. The two wettest CPs caused roughly half of the extremes on about 6.5% of days. Both wettest patterns are characterized by an intensified Saharan Heat Low and a cyclonic rotation near the study area, indicating a tropical wave trough. Since the classification can be used to condition other statistical approaches used in climate sciences and other disciplines, the presented classification approach opens many different applications for the West African Monsoon region

Classification of atmospheric circulation patterns that trigger rainfall extremes in the Sudan-Sahel region

A better understanding of the rainfall variability and extremes in tropical regions is crucial for the development of improved statistical and numerical approaches used for climate research and weather prediction. In this study, we present a novel fuzzy rule-based method for classifying atmospheric circulation patterns relevant to heavy rainfall in the Sudan-Sahel region over West Africa. In the first step, we determine large-scale atmospheric patterns to describe important seasonal features of the West African Monsoon like the movement of Saharan Heat Low over the African continent. In the second step, meso-scale monsoon patterns are classified to better describe rainfall variability and extremes during the monsoon period. In addition to a comprehensive predictor screening using more than 30 variables at different atmospheric levels, a detailed sensitivity analysis is performed, which aims to improve the transferability of the classification approach to an independent dataset. Furthermore, crucial aspects of the methodological development of fully automatic classification approaches are addressed. Using mean sea level pressure and stream function fields (700hPa) as final predictor variables, we identified 23 circulation patterns as robust solution to represent key atmospheric processes and rainfall variability in the study region. The two wettest patterns are distinguished by an enhanced Saharan Heat Low and cyclonic rotation near the study region, suggesting the presence of a tropical wave trough and triggering about 50% of the rainfall extremes on 6.5% of the days. The identified atmospheric circulation patterns are currently used to develop a variety of improved statistical approaches for this challenging region, such as pattern-dependent bias correction, geostatistical interpolation, and simulation

Atmospheric circulation patterns that trigger heavy rainfall in West Africa

Classification of atmospheric circulation patterns (CP) is a common tool for downscaling rainfall, but it is rarely used for West Africa. In this study, a two-step classification procedure is proposed for this region, which is applied from 1989 to 2010 for the Sudan-Sahel zone (Central Burkina Faso) with a focus on heavy rainfall. The approach is based on a classification of large-scale atmospheric CPs (e.g., Saharan Heat Low) of the West African Monsoon using a fuzzy rule-based method to describe the seasonal rainfall variability. The wettest CPs are further classified using meso-scale monsoon patterns to better describe the daily rainfall variability during the monsoon period. A comprehensive predictor screening for the seasonal classification indicates that the best performing predictor variables (e.g., surface pressure, meridional moisture fluxes) are closely related to the main processes of the West African Monsoon. In the second classification step, the stream function at 700 hPa for identifying troughs and ridges of tropical waves shows the highest performance, providing an added value to the overall performance of the classification. Thus, the new approach can better distinguish between dry and wet CPs during the rainy season. Moreover, CPs are identified that are of high relevance for daily heavy rainfall in the study area. The two wettest CPs caused roughly half of the extremes on about 6.5% of days. Both wettest patterns are characterized by an intensified Saharan Heat Low and a cyclonic rotation near the study area, indicating a tropical wave trough. Since the classification can be used to condition other statistical approaches used in climate sciences and other disciplines, the presented classification approach opens many different applications for the West African Monsoon region