102 research outputs found
An investigation of the impacts of intra-seasonal rainfall variability on the maize growing season in Limpopo Province, South Africa from 1990-2014
Get PDFRain fed maize is an important staple food crop for rural communities in Southern Africa as it plays a major role in ensuring food security and improving livelihoods. Rainfall consistency and intensity is an essential requirement for successful maize growing seasons. The variability of intra-seasonal rainfall characteristics such as onset, cessation and wet and dry spells threatens maize yields in Southern Africa. Previous studies have focused on the impacts of seasonal rainfall totals on maize yields. The aim of this study is to investigate the impacts of intra-seasonal rainfall variability on the maize growing season of Limpopo Province, South Africa from 1990 to 2014. A Self-Organizing Map (SOM) is used to identify and distinguish synoptic states and patterns that are conducive for growing maize in the province from those that are not. The SOM is trained using daily mean Geopotential height reanalysis data, composites for rainfall and moisture are then analysed to understand surface responses. CHIRPS daily rainfall data is used to analyse the variability of rainfall characteristics. The relationship between these rainfall characteristics and maize yield is evaluated to assess the impacts of variability on maize yields. The SOM shows that summer maize growing season is characterised by low pressure systems over the mainland which act as tropical sources of moisture and the formation of cloud-bands associated with Tropical Temperate Troughs. There is a trend in late rainfall onset and earlier cessation leading to a shift and shortening of the rainy season. The shifted and shortened rainy seasons are characterised by dry spells and high intensity rainfall events and are potentially more suitable for planting the shorter season maize cultivars. Regardless of these agrometeorological conditions being detrimental to yields, district level and provincially averaged maize yields show an overall increasing trend. This is a result of improved farming methods such as planting drought resistant short season yellow maize cultivars which can withstand dry spells
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Beyond El Niño: unsung climate modes drive African floods
Get PDFThe El Niño Southern Oscillation (ENSO) dominates the conversation about predictability of climate extremes and early warning and preparedness for floods and droughts, but in Africa other modes of climate variability are also known to influence rainfall anomalies. In this study, we compare the role of ENSO in driving flood hazard over sub-Saharan Africa with modes of climate variability in the Indian and Atlantic Oceans. This is achieved by applying flood frequency approaches to a hydrological reanalysis dataset and streamflow observations for different phases of the ENSO, Indian Ocean Dipole and Tropical South Atlantic climate modes. Our results highlight that Indian and Atlantic Ocean modes of climate variability are equally as important as ENSO for driving changes in the frequency of impactful floods across Africa. We propose that in many parts of Africa a larger consideration of these unsung climate modes could provide improved seasonal predictions of associated flood hazard and better inform adaptation to the changing climate
Future changes in extreme rainfall events and circulation patterns over southern Africa
No full textIncludes bibliographical referencesChanges in precipitation extremes are projected by many global climate models as a response to greenhouse gas increases, and such changes will have significant environmental and social impacts. These impacts are a function of exposure and vulnerability. Hence there is critical need to understand the nature of weather and climate extremes. Results from an ensemble of regional climate models from the Coordinated Regional Downscaling Experiment (CORDEX) project are used to investigate projected changes in extreme precipitation characteristics over southern Africa for the middle (2036-2065) and late century (2069-2098) under the representative concentration pathway 4.5 (RCP4.5) and 8.5 (RCP8.5). Two approaches are followed to identify and analyze extreme precipitation events. First, indices for extreme events, which capture moderate extreme events, are calculated on the basis of model data and are compared with indices from two observational gridded datasets at annual basis. The second approach is based on extreme value theory. Here, the Generalized Extreme Value distribution (GEV) is fitted to annual maxima precipitation by a L-moments method. The 20-year return values are analyzed for present and future climate conditions. The physical drivers of the projected change are evaluated by examining the models ability to simulate circulation patterns over the regions with the aid of Self-Organizing Maps (SOM)
Future changes in extreme events in Mozambique as simulated using the PRECIS regional climate modeling system
No full textFuture climate change is generally believed to lead to an increase in climate variability and inthe frequency and intensity of extreme events. Mozambique is well known for its occurrenceof severe weather and extreme climate events such as floods, tropical cyclones and droughts.Such events have serious impacts on the livelihoods of most people who often rely on subsistence agriculture.This dissertation explores possible changes in extremes in temperature and precipitation over Mozambique, based on high-resolution (25 km) simulations of the regional climate model system PRECIS (HadRM3P), forced by the ECHAM4 global mode
Spatial variability of cold waves over Southern Africa and their potential physical mechanisms
No full textDespite significant evidence of global warming, cold waves still happen occasionally and are of great concern in regions such as Southern Africa as they are associated with negative impacts such as loss of lives, destruction of infrastructure, loss of crops and livestock and high peak demand of electricity consumption. In this study, we examine the cold wave characteristics over the southern African region for the extended austral winter (May to September) over the 1979–2021 period, using minimum temperature from the European Centre for Medium-Range Weather Forecasts and Berkeley Earth Surface Temperature reanalysis products. Cold waves are calculated using the excess cold factor. Principal component analysis was performed on the cold waves to extract their dominant modes. Linear regression, Spearman rank correlation as well as lagged correlations were employed to find the links between the cold wave characteristics and different climate drives. Results from the study reveal that the lowest nighttime temperatures are found in interior South Africa and Lesotho. There is a decreasing trend in terms of the number of cold wave events over southern Africa, especially north of latitude 15˚S. Local and remote seasonal sea surface temperatures (SST) have the potential to change the likelihood of cold wave characteristics over Southern Africa. Also, seasonal mean circulation results contain seasonal mean ridge/trough structures, which suggests the role of these synoptic features and cold fronts in modulating cold waves over Southern Africa. A future study is needed to analyze the impact of these climate drivers at daily and intraseasonal timescales. There is moderate to high lead correlation between El Ninõ Southern Oscillation (ENSO) and some of the cold wave characteristics, hence ENSO, SST surrounding Southern Africa are good indicators for predicting cold waves over the region. Findings from this study can be useful in improving weather and climate forecasting over the region. Also, these results can support local authorities and communities at risk in developing early actions for tackling cold waves
La Niña, Climate change, high exposure and vulnerability combined led to devastating floods in parts of Southern Africa
No full textCite as Pinto, I. et al., (2026): La Niña, Climate change, high exposure and vulnerability combined led to devastating floods in parts of Southern Africa (WWA scientific report No. 81) World Weather Attributio
What Can We Know About Recent Past Precipitation Over Africa? : Daily Characteristics of African Precipitation From a Large Ensemble of Observational Products for Model Evaluation
No full textAbstract We assess the daily characteristics of recent past precipitation over Africa by means of a large ensemble of observational products, including reanalysis, gauge‐based, and satellite‐based products. The spatial distribution of seasonal mean precipitation varies considerably amongst products especially over areas where gauge networks are sparse. Large uncertainties in the annual precipitation cycle are visible in particular over the Ethiopian Highlands, the eastern Sahel, the coasts of the Gulf of Guinea, and the Horn of Africa. Interannual variability shows large differences especially amongst reanalysis data sets whereas satellite and gauge‐based products usually show more consistent results
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Chapter 6 - Future changes in precipitation distributions over Africa
No full textThe African continent is home to approximately 1.4 billion people, about 18% of the world's population. Monsoon precipitation is critical to African societies, contributing a large proportion of the average annual precipitation. Variations in monsoon precipitation have major impacts on, for example, agriculture, freshwater supply and sanitation, and hydropower generation. Unusually low precipitation can also lead to large and prolonged droughts across Africa, increasing mortality. Future changes in monsoon precipitation, therefore, have important societal implications. In this chapter, we summarize the impact of climate change on future changes in precipitation over Africa and for the end of the 21st century. Climate models show that precipitation is projected to increase over most of the African continent (the central Sahel, east and central Africa), while precipitation is projected to decrease over the western Sahel and south-eastern Africa. We document the impact of climate change on extreme precipitation events. We also explain the uncertainty in simulated changes in precipitation and discuss ways to improve the reliability of projections.</p
An evaluation of CORDEX regional climate models in simulating precipitation over Southern Africa
Get PDFThis article evaluates the ability of the Coordinated Regional Downscaling Experiment
(CORDEX) regional climate models (RCMs) in simulating monthly rainfall variation during
the austral summer half year (October to March) over southern Africa, the timing of the
rainy season and the relative frequencies of rainfall events of varying intensities. The phasing
and amplitude of monthly rainfall evolution and the spatial progression of the wet season
onset are well simulated by the models. Notwithstanding some systematic biases in a few
models, the simulated onset and end of the rainy season and their interannual variability
are highly correlated with those computed from the reference data. The strongest agreements
between the reference and modelled precipitation patterns are found north of about 20∘S in the
vicinity of the Inter Tropical Convergence Zone. A majority of the RCMs adequately capture
the reference precipitation probability density functions, with a few showing a bias towards
excessive light rainfall events.The CORDEX-Africa programme was supported
by the Global Change System for Analysis, Research, and
Training (START) through the Climate Systems Analysis Group
of the University of Cape Town. Support from the World Climate Research Program (WCRP), the Climate and Development
Knowledge Network (CDKN), the International Centre
for Theoretical Physics (ICTP), the Swedish Meteorological
and Hydrological Institute (SMHI) and the European Union
Seventh Framework Programme.http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1530-261Xhb2016Geography, Geoinformatics and Meteorolog
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