Preprints
https://doi.org/10.5194/nhess-2023-144
https://doi.org/10.5194/nhess-2023-144
10 Aug 2023
 | 10 Aug 2023
Status: this preprint is currently under review for the journal NHESS.

Subseasonal-to-seasonal forecasts of Heat waves in West African cities

Cedric Gacial Ngoungue Langue, Christophe Lavaysse, and Cyrille Flamant

Abstract. Heat waves are one of the most dangerous climatic hazards for human and ecosystem health worldwide. Accurate forecasts of these dramatic events are useful for policy makers and climate services to anticipate risks and develop appropriate responses. Sub-seasonal to seasonal forecasts are of great importance for actions to mitigate the human and health consequences of extreme heat. In this perspective, the present study addresses the predictability of heat waves at sub-seasonal to seasonal time scale in West African cities over the period 2001–2020. Two types of heat waves were analyzed: dry and wet heat waves using 2-meter temperature (T2m) and wet bulb temperature (Tw) respectively. Two models that are part of the S2S forecasting project, namely the European Centre for Medium-Range Weather Forecasts (ECMWF) and the UK Met Office models, were evaluated using two state-of-the-art reanalysis products, namely the fifth generation ECMWF reanalysis (ERA5) and the Modern-Era Retrospective analysis for Research and Application. The skill of the models to detect hot extreme events is evaluated using the Brier score. The models show significant skills in detecting hot days both for short- and long-term forecasts (2- and 5-week lead times, respectively). The predictability of heat waves in the forecast models is assessed by calculating categorical metrics such as the hit-rate, the Gilbert score and the false alarm ratio (FAR). The forecast models show significant skills in predicting heat wave days compared to a baseline climatology, mainly for short-term forecasts (two weeks lead time) in three climatic regions in West Africa, but the hit-rate values remain below 50 % on average. We find that nighttime heat waves are more predictable than daytime heat waves. On average, the False Alarm Ratio (FAR) is excessively high and tends to increase with the lead time. Only approximately 15 % to 30 % of the predicted heat wave days are actually observed for Week 5 and Week 2, respectively. This suggests that the models overestimate the duration of the heat waves with respect to ERA5. The skill of the models in forecasting dry and wet heat waves are very close. Although the models demonstrate skills on heat wave detection compared to a baseline climatology, they fail in predicting the intensity of heat waves.

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Cedric Gacial Ngoungue Langue, Christophe Lavaysse, and Cyrille Flamant

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2023-144', Anonymous Referee #1, 15 Sep 2023
  • RC2: 'Comment on nhess-2023-144', Anonymous Referee #2, 22 Sep 2023
Cedric Gacial Ngoungue Langue, Christophe Lavaysse, and Cyrille Flamant
Cedric Gacial Ngoungue Langue, Christophe Lavaysse, and Cyrille Flamant

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Short summary
The present study addresses the predictability of heat waves (HWs) at sub-seasonal to seasonal time scales in West African cities over the period 2001–2020. Two models namely the European Centre for Medium-Range Weather Forecasts and the UK Met Office models, were evaluated using two reanalyses. The forecast models show significant skills in predicting HWs days compared to a baseline climatology upon two weeks lead time. We find that nighttime HWs are more predictable than daytime HWs.
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