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In recent years, there has been increasing interest in the joint modelling of compound extreme events such as high temperatures and low rainfall. The increase in the frequency of occurrence of these events in many regions has necessitated the development of models for estimating the concurrent probabilities of such compound extreme events. The current study discusses an application of copula models in predicting the concurrent probabilities of compound low rainfall and high-temperature events using data from the Lowveld region of the Limpopo province in South Africa. The second stage discussed two indicators for monitoring compound high temperature and low rainfall events. Empirical results from the study show that elevations ranging from 100–350 m, 350–700 m and 700–1200 m exhibit varying probabilities of experiencing drought, with mild droughts having approximately 64%, 66%, and 65% chances, moderate droughts around 36%, 39%, and 38%, and severe droughts at approximately 16%, 19%, and 18%, respectively. Furthermore, the logistic regression models incorporating the southern oscillation index as a covariate yielded comparable results of copula-based models. The methodology discussed in this paper is robust and can be applied to similar datasets in any regional setting globally. These findings could be useful to disaster management decision makers, helping them formulate effective mitigation strategies and emergency response plans. [ABSTRACT FROM AUTHOR]

In recent decades, southern Africa has experienced a shift towards hotter and drier climate conditions, affecting vital sectors like agriculture, health, water, and energy. Scientific research has shown that the combination of high temperatures and unreliable rainfall can have detrimental effects on agricultural production. Thus, this study focused on assessing climate variability, with implications on rangelands in the Limpopo Province of South Africa over 38 years. Historical climate data from 15 stations, including rainfall and minimum and maximum temperatures from 1980 to 2018, were analysed. To achieve the main objective, various statistics including mean, standard deviation, and coefficient of variation (CV) were computed for all variables across four seasons. The results highlighted significant variability in rainfall, with Musina (71.2%) and Tshiombo (88.3%) stations displaying the highest variability during the September-to-April season. Both minimum and maximum temperatures displayed low variability. The Mann–Kendall test revealed both increasing and decreasing trends in minimum temperatures and rainfall across different stations. Notably, there was a significant increase in maximum temperatures. This study provides valuable climate information for decision makers, aiding in the planning and management of agricultural activities, particularly in understanding how climate variations affect forage availability in rangelands. [ABSTRACT FROM AUTHOR]

High temperature generally causes large‐scale crop yield reduction, and such negative effects are known to depend on the concurrent precipitation. However, the compounding precipitation effect in regulating crop yield response to global warming remains under‐examined. This research aims to evaluate the role of concurrent changes in precipitation in modulating global maize yield response to temperature under 1.5 and 2.0 K temperature rise for RCP 4.5 and 8.5 scenarios, respectively. Empirical linear function is adopted to calculate the function parameters and impact of precipitation modulation based on global census data on maize yield and climate in the baseline period of 1980–2010. The sensitivity of maize yield to temperature is then estimated under condition that with and without removal of precipitation impact. The maize yield sensitivity to temperature is negative in most rain‐fed growing areas in the baseline period of 1980–2010, and the global sensitivity is −9.39%/K if the precipitation impact is considered or −6.92%/K if the precipitation impact is removed. Globally, approximately 30% of the observed strength of relationship between maize yield and temperature is induced by the compounding precipitation effect. Under 1.5 and 2.0 K warming scenarios, global maize yield is projected to decrease by −10.16% to −11.91% and −15.01% to −17.14%, respectively. The world maize yield differences between 1.5 and 2.0 K scenarios will be −4.85% and −5.23% without the compounding precipitation effect and range from −3.52% to −3.89% with the compounding precipitation effect, to which the contribution of compounding precipitation increases to 35%. The modulating impacts of precipitation are the strongest in high latitude countries, while weak effects are found in Argentina, China, India, and South Africa. The research can help us understand the important but uncertain issue that how much the maize yield response to global warming is contributed by the compounding precipitation effect. [ABSTRACT FROM AUTHOR]

The temporal and spatial distribution of the frequency of breaking highest and lowest daily maximum and minimum temperature records over the period of 1951–2019 has been investigated for South Africa. Temperature records are station specific and defined as either larger or smaller than any previous values in a time series of specific year‐days. Daily maximum and minimum temperatures from homogenized time series of 25 weather stations in South Africa were analysed. Aspects considered to influence the frequency of record‐breaking events were the warming trend and variance. The study found that the record‐breaking frequencies of the highest daily maximum (high Tmax) and some high daily minimum temperature (high Tmin) records were higher than the theoretically expected number in a stationary climate. This was particularly apparent near the end of the analysis period. The ratio of highest maximum to lowest minimum temperature records was almost an equal 1:1 ratio near the start of the analysis period and increased to a about 4:1 in the last decade of the period. Focusing on the last decade, that is, 2010–2019 the study found that there is a different spatial pattern between the occurrence of high Tmax and high Tmin records. For high Tmax records the highest number were mostly recorded by stations over the central parts of the country (e.g., Kimberley, Glen College and Bloemfontein). In contrast, the highest number of high Tmin records were less confined spatially. Even when considering the general warming due to climate change, many more high temperature records are broken than expected in certain regions and on average. We deduce that the higher than expected numbers of high Tmax and high Tmin records in the latter part of the analysis period were mainly due to the variability in the warming trend with acceleration in the last decade. [ABSTRACT FROM AUTHOR]

The only previous study on the macrobiota of South African boulder shores showed this assemblage to be more diverse than on nearby rocky platforms, but the drivers of that difference remain unresolved. We recorded water and air temperatures under intertidal boulders and on adjacent exposed rocky platforms, at both the upper- and lower-shore level, at Kommetjie, South Africa, over 2-week tidal cycles, repeating this during summer and winter. The macrobiota in each location was also sampled during diurnal low tides. The most-extreme temperatures, and greatest ranges, occurred during summer on upper-shore open rock (13.9–37.7 °C, range difference of 23.8 °C), while under upper-shore boulders the maximum temperature was lower at 28.9 °C and the range spanned only 15.5 °C. In winter, maximum temperatures and ranges were lower at all locations. Maximum temperatures did not coincide with spring tides, but occurred several days later, when low tides happened during the heat of the day. Closer analysis of daily fluctuations revealed influence of weather on temperatures attained and showed that durations of elevated temperatures were much shorter in the lower shore. The upper shore exhibited low biodiversity, supporting only 9 species, with 8 found only under boulders during diurnal low tide; the lower shore was more diverse, with 11 species on open rock and 29 under boulders. Biomass and abundance were also higher under boulders at both levels, especially on the upper shore. More-benign under-boulder conditions thus facilitate more abundant and diverse biota sheltering there than occurs on adjacent exposed rocks, particularly on the upper shore. [ABSTRACT FROM AUTHOR]