More frequent and intensified high-temperature extremes are acceptable indicators of global warming, which pose serious socio-economic impacts. In the present research, the Climate Prediction Center daily minimum and maximum temperature are used to characterize high temperatures into intensity of hot days (TXx), hot nights (TNx), and frequency indices based on the 90th percentile of hot days (TX90p) and hot nights (TN90p) as defined by the Expert Team on Climate Change Detection and Indices from 1981 to 2020 over Africa. The regression approach based on iterative reweighted least squares and correlation analyses are used to estimate the trends in extreme high-temperature events and their relationship with various meteorological variables. Furthermore, the Pruned exact linear time algorithm is used to assess if the maximum temperature experienced an abrupt change. Results show that many parts of Africa experienced more frequent and intensified hot days and nights in the current period (1998–2020) compared to the recent past (1981–1997), suggesting a clear shift in climate. Thus, we used the climatological mean differences between meteorological parameters before and after the breakpoint to assess the relationship between atmospheric conditions and extreme high-temperature events. As a result, we found that the current period observed an increase in the geopotential height at 500 hPa and reduced total cloud cover, as well as an increase in upward longwave radiation resulting in an upsurge in the frequency of hot days over many African sub-regions. The present study's findings provide useful information for future planning and development of early warning systems to cope with risks associated with hot extremes.
All Science Journal Classification (ASJC) codes
- Atmospheric Science