Characteristics and thermodynamics of Sahelian heatwaves analysed using various thermal indices

Abstract

Prolonged periods of extreme heat also known as heatwaves are a growing concern in a changing climate. Over the Sahel, a hot and semi-arid region in West Africa, they are still relatively poorly understood and managed. In this research, five multivariate thermal indices derived from the ERA5 database were used to characterize Sahelian heatwaves for statistical analysis and as a sampling basis to investigate their underlying thermodynamic causes. Results show that on average most locations in the Sahel suffer from one or two heatwaves a year lasting 3–5 days but with severe magnitude. The eastern Sahel is more at risk than the west, experiencing more frequent and longer lasting events. Despite similar statistics of intensity, duration and frequency across the heatwave indices, for a given diurnal phase, there is surprisingly low agreement in the timing of events. Furthermore daytime and nighttime heatwaves have little synchronicity. In terms of associated thermodynamic processes, heat advection and the greenhouse effect of moisture are identified as the main causes of Sahelian heatwaves. The processes are nevertheless sensitive to the indices, consequence of the distinctness of their respective samples. Therefore attention should be given to the choice of either index in operational monitoring and forecasting of heatwaves. This will allow to effectively target different exposed socio-economic groups and resultantly enhance the efficiency of early warning systems.

Prediction skill of Sahelian heatwaves out to subseasonal lead times and importance of atmospheric tropical modes of variability

“…The literature indicates that Sahelian heatwaves are relatively short-lived as compared to other regions, but are extremely severe in magnitude (e.g. Oueslati et al 2017;Guigma et al 2020a). Moreover, over the recent decades and in agreement with the global trend, they have been more frequent, more intense (especially at night) and longer lasting (Fontaine et al 2013;Ringard et al 2016;Moron et al 2016;Oueslati et al 2017;Barbier et al 2018).…”

“…The present research analyses heatwave prediction skill for forecasts initialised in two seasons, as in Guigma et al (2020a): the February to March season (FM hereafter) and the pre-monsoon April to June season (AMJ hereafter), which marks the peak of heat in the region.…”

“…BEST data consist of daily Tmax and Tmin (no moisture data is available) at a native resolution of 1° × 1°, regridded to 0.5° × 0.5° to match the hindcast grid. Guigma et al (2020a) showed that in the Sahel, heatwaves defined using different thermal indices over the same diurnal period, or the daytime versus nighttime heatwaves of a same index are not synchronous, and often result from different underlying thermodynamic processes. Their predictability could therefore also differ, and to account for this eventuality, two distinct measures of heat are used in this paper: Temperature (T) and the heat index (HI).…”

“…Using the method of Guigma et al (2020a), heatwaves in the ERA5 dataset are defined for each thermal index and at each grid-cell, as spells of at least three consecutive days where the daily index value exceeds both the 75th percentile of its total distribution over all days, and the 90th percentile of its (1) HI = −42.37 + 2.04T + 10.14RH − 0.22T.RH − 6.83×10 −3 T 2 − 5.48 × 10 −2 RH 2 + 1.22 × 10 −3 T 2 .RH + 8.52 × 10 −4 T.RH 2 − 1.99 × 10 −6 T 2 .RH calendar day distribution computed over a 31-day centred window. Binary data of heatwave occurrence (coded 1) or non-occurrence (coded 0) are thus obtained.…”

“… b show the spatial distribution and the length of the event across the country. Both daytime and nighttime were affected (which is unusual in the Sahel;Guigma et al 2020a) over the whole country. It should be noted that the event was less marked in HI-day and HI-night than in T-day and T-night (not shown).…”