Heatwave Variability and Structure in South Africa during Summer Drought

Mbokodo, Innocent L.; Bopape, Mary-Jane M.; Ndarana, Thando; Mbatha, Sifiso M. S.; Muofhe, Tshimbiluni P.; Singo, Mukovhe V.; Xulu, Nkosinathi G.; Mohomi, Tumelo; Ayisi, Kingsley Kwabena; Chikoore, Hector

doi:10.3390/cli11020038

Cited by 12 publications

(5 citation statements)

References 72 publications

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“…Furthermore, mean maximum temperatures are generally increasing in the Limpopo Province, although variations exist among different areas. These findings are corroborated by previous studies [30,50,78]. The temperature variations can be attributed to factors such as elevation, as mountainous regions experience lower temperatures compared to other areas in the Lowveld.…”

Section: Discussionsupporting

confidence: 90%

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Analysis of Climate Variability and Its Implications on Rangelands in the Limpopo Province

Maluleke,

Moeletsi,

Tsubo

2023

Climate

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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.

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Section: Discussionsupporting

confidence: 90%

“…Maximum temperatures displayed a low CV during all the seasons considered in all the stations. The highest mean maximum temperatures are observed in the DJF season [30]. Furthermore, mean maximum temperatures are generally increasing in the Limpopo Province, although variations exist among different areas.…”

Section: Discussionmentioning

confidence: 92%

Analysis of Climate Variability and Its Implications on Rangelands in the Limpopo Province

Maluleke,

Moeletsi,

Tsubo

2023

Climate

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“…This result implies that when there are anomalously positive 850‐hPa geopotential heights over South Africa, there are anomalously hot conditions over most parts of South Africa. In fact, when there is a high‐pressure system extending from Angola into the interior of South Africa, it is usually dry and hot over most parts of the country (e.g., Mbokodo et al, 2023). The opposite is true for the CCA maps in Figure 8, showing that during the same year (2016), there are anomalously negative predictor's spatial loadings over Angola stretching into South Africa for weeks 1–4 lead times and the temporal scores are also negative.…”

Section: Resultsmentioning

confidence: 99%

Probabilistic skill of statistically downscaled ECMWF S2S forecasts of maximum and minimum temperatures for weeks 1–4 over South Africa

Phakula,

Landman,

Engelbrecht

2024

Meteorological Applications

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The probabilistic forecast skill level of statistically downscaled European Centre for Medium‐Range Weather Forecasts (ECMWF) subseasonal‐to‐seasonal (S2S) forecasts is determined in predicting maximum and minimum temperatures for weeks 1–4 lead times during 20‐year December–January–February (DJF) seasons from 2001 to 2020 over South Africa. Skilful S2S forecasts are vital in assisting decision‐makers in the development of contingency planning for any eventualities that may arise because of weather and climate phenomena. Extreme high‐ and low‐temperature events over a prolonged period can lead to hyperthermia and hypothermia, respectively, and can lead to loss of life. The results from the relative operating characteristic (ROC) and reliability diagrams indicate that the ECMWF S2S model has skill in predicting maximum temperature up to week 3 ahead, particularly over the central and eastern parts of South Africa. The ROC scores indicate that the model has skill in predicting minimum temperature up to week 4 ahead for the above‐normal category, particularly over the central and eastern parts of South Africa. Reliability diagrams indicate that the model has a tendency of overestimating the below‐normal category when predicting both maximum and minimum temperatures for weeks 1–4 lead times over South Africa. Furthermore, canonical correlation analysis (CCA) pattern analysis suggests that when there are anomalously positive and negative predicted 850‐hPa geopotential heights located over South Africa, there are anomalously hot and cold conditions during the DJF seasons over most parts of South Africa, respectively. These results suggests that statistical downscaling of model forecasts can improve forecast skill. Moreover, the results suggest that there is potential for S2S predictions in South Africa, and as such, S2S prediction system for maximum and minimum temperatures can be developed.

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“…The amplified energy conversion in turn leads to enhanced high‐frequency temperature variance (EAPE HF ), which manifests itself at the surface as a broadening of the probability density of temperature. This broadening, combined with a general shift of probabilities toward warmer temperatures due to El Niño's impact on seasonal‐mean temperatures, contributes to enhancing the frequency of warm extremes (Mbokodo et al., 2023), especially over Eastern South Africa.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Tropical Pacific Influence on Summertime South African High‐Frequency Temperature Variability and Heat Waves

Martineau

Behera

Nonaka

et al. 2023

Geophysical Research Letters

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Day-to-day weather variability affecting Southern Africa is driven by a wide range of weather systems such as mid-latitude cyclones, cut-off lows, and tropical-temperate troughs (Lennard, 2019). The activity of many of these transient phenomena, as measured by their amplitude, duration, and/or frequency, exhibits notable year-to-year variations. For instance, cut-off lows (Favre et al., 2012;Singleton & Reason, 2007), tropical temperate troughs (Ratna et al., 2013), and cold fronts associated with mid-latitude cyclones (Picas & Grab, 2021) have been found to be more frequent during the cold phase of El Niño-Southern Oscillation (ENSO), that is, La Niña. As such, the likelihood of experiencing weather extremes associated with these systems may be predictable given ENSO's long-range predictability (Tang et al., 2018). Mulenga et al. (2003) suggested that ENSO, in the context of dry summers, impacts weather systems over Southern Africa through modulations of large-scale seasonal features of the atmospheric circulation. More specifically, the enhanced upper-level westerly winds over southwestern South Africa as part of El Niño's teleconnection could modulate baroclinic wave activity by steering frontal systems more toward southwestern South Africa, and less toward southeastern South Africa. The enhanced westerlies have been identified in the signature of El Niño in the zonal-mean circulation (L'Heureux & Thompson, 2006) and are accompanied, as expected from thermal wind balance, by dipolar temperature anomalies which reinforce the climatological equatorward gradient of temperature just south of South Africa. The associated enhancement of lower-tropospheric baroclinicity may contribute to the development of baroclinic eddies, but the detailed dynamical mechanisms and whether it has an impact on Southern African weather remain unknown.The primary goal of this work is thus to elucidate the dynamical processes regulating year-to-year variations in high-frequency atmospheric temperature variability that are associated with the aforementioned weather systems and to understand the role played by ENSO in these variations. Focus is placed on Austral summertime, when El Niño events are typically amplified (Rasmusson & Carpenter, 1982), have a greater impact on the Southern Hemisphere (SH) extratropics (L'Heureux & Thompson, 2006), and when weather variability has important socioeconomic impacts on agriculture and human health (e.g., Sazib et al., 2020).

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Heatwave Variability and Structure in South Africa during Summer Drought

Cited by 12 publications

References 72 publications

Analysis of Climate Variability and Its Implications on Rangelands in the Limpopo Province

Analysis of Climate Variability and Its Implications on Rangelands in the Limpopo Province

Probabilistic skill of statistically downscaled ECMWF S2S forecasts of maximum and minimum temperatures for weeks 1–4 over South Africa

Tropical Pacific Influence on Summertime South African High‐Frequency Temperature Variability and Heat Waves

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