In June and July 2016 the Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa (DACCIWA) project organised a major international field campaign in southern West Africa (SWA) including measurements from three inland ground supersites, urban sites in Cotonou and Abidjan, radiosondes, and three research aircraft. A significant range of different weather situations were encountered during this period, including the monsoon onset. The purpose of this paper is to characterise the large-scale setting for the campaign as well as synoptic and mesoscale weather systems affecting the study region in the light of existing conceptual ideas, mainly using objective and subjective identification algorithms based on (re-)analysis and satellite products. In addition, it is shown how the described synoptic variations influence the atmospheric composition over SWA through advection of mineral dust, biomass burning and urban pollution plumes.The boreal summer of 2016 was characterised by Pacific La Niña, Atlantic El Niño and warm eastern Mediterranean conditions, whose competing influences on precipitation led to an overall average rainy season. During the relatively dusty pre-onset Phase 1 (1–21 June 2016), three westward-propagating coherent cyclonic vortices between 4 and 13° N modulated winds and rainfall in the Guinea coastal area. The monsoon onset occurred in connection with a marked extratropical trough and cold surge over northern Africa, leading to a breakdown of the Saharan heat low and African easterly jet and a suppression of rainfall. During this period, quasi-stationary low-level vortices associated with the trough transformed into more tropical, propagating disturbances resembling an African easterly wave (AEW). To the east of this system, moist southerlies penetrated deep into the continent. The post-onset Phase 2 (22 June–20 July 2016) was characterised by a significant increase in low-level cloudiness, unusually dry conditions and strong northeastward dispersion of urban pollution plumes in SWA as well as rainfall modulation by westward-propagating AEWs in the Sahel. Around 12–14 July 2016 an interesting and so-far undocumented cyclonic–anticyclonic vortex couplet crossed SWA. The anticyclonic centre had its origin in the Southern Hemisphere and transported unusually dry air filled with aged aerosol into the region. During Phase 3 (21–26 July 2016), a similar vortex couplet slightly farther north created enhanced westerly moisture transports into SWA and extraordinarily wet conditions, accompanied by a deep penetration of the biomass burning plume from central Africa. Finally, a return to more undisturbed monsoon conditions took place during Phase 4 (27–31 July 2016). The in-depth synoptic analysis reveals that several significant weather systems during the DACCIWA campaign cannot be attributed unequivocally to any of the tropical waves and disturbances described in the literature and thus deserve further study.

Extreme-temperature anomalies such as heat and cold waves may have strong impacts on human activities and health. The heat waves in western Europe in 2003 and in Russia in 2010, or the cold wave in southeastern Europe in 2012, generated a considerable amount of economic loss and resulted in the death of several thousands of people. Providing an operational system to monitor extreme-temperature anomalies in Europe is thus of prime importance to help decision makers and emergency services to be responsive to an unfolding extreme event. In this study, the development and the validation of a monitoring system of extreme-temperature anomalies are presented. The first part of the study describes the methodology based on the persistence of events exceeding a percentile threshold. The method is applied to three different observational datasets, in order to assess the robustness and highlight uncertainties in the observations. The climatology of extreme events from the last 21 years is then analysed to highlight the spatial and temporal variability of the hazard, and discrepancies amongst the observational datasets are discussed. In the last part of the study, the products derived from this study are presented and discussed with respect to previous studies. The results highlight the accuracy of the developed index and the statistical robustness of the distribution used to calculate the return periods.

The Saharan heat low (SHL) plays a pivotal role in the West African monsoon system in spring and summer. The recent trend in SHL activity has been analysed using two sets of numerical weather prediction (NWP) model reanalyses and Atmospheric Models Intercomparison Project simulations from 15 climate models performed in the framework of the 5th Coupled Models Intercomparison Project (CMIP5) exercise. A local increase of temperature in the Sahara during the 90s is found in the two sets of NWP models temperature. This increase is stronger within the SHL region than over the surrounding areas. Using different temporal filters (under 25 days, 25–100 days and above 300 days), we show that this is accompanied by a slight but widespread increase of temperature, and a change in the filtered signal under 25 days during the transition period of the 90s. We also show that SHL pulsations occurring at different time scales impact the West Africa climate on a variety of spatial scales, from the regional scale (for the high band pass) to the synoptic scale (for the low band pass signal). Despite a large variability in the temporal trends for 15 climate models from the CMIP5 project, the warming trend in the 90s is observed in the models ensemble mean. Nevertheless, large discrepancies are found between the NWP models reanalyses and the climate model simulations regarding the spatial and temporal evolutions of the SHL as well as its impact on West African climate at the different time scales. These comparisons also reveal that climate models represent the West African monsoon interactions with SHL pulsations quite differently. We provide recommendations to use some of them depending on the time scales of the processes at play (synoptic, seasonal, interannual) and based on key SHL metrics (location, mean intensity, global trend, interaction with the West African monsoon dynamics).

An early warning system for drought events can provide valuable information for decision makers dealing with water resources management and international aid. However, predicting such extreme events is still a big challenge. In this study, we compare two approaches for drought predictions based on forecasted precipitation derived from the Ensemble extended forecast model (ENS) of the ECMWF, and on forecasted monthly occurrence anomalies of weather regimes (MOAWRs), also derived from the ECMWF model. Results show that the MOAWRs approach outperforms the one based on forecasted precipitation in winter in the north-eastern parts of the European continent, where more than 65 % of droughts are detected 1 month in advance. The approach based on forecasted precipitation achieves better performance in predicting drought events in central and eastern Europe in both spring and summer, when the local atmospheric forcing could be the key driver of the precipitation. Sensitivity tests also reveal the challenges in predicting small-scale droughts and drought onsets at longer lead times. Finally, the results show that the ENS model of the ECMWF successfully represents most of the observed linkages between large-scale atmospheric patterns, depicted by the weather regimes and drought events over Europe.

Heat and cold waves may have considerable human and economic impacts in Europe. Recent events, like the heat waves observed in France in 2003 and Russia in 2010, illustrated the major consequences to be expected. Reliable Early Warning Systems for extreme temperatures would, therefore, be of high value for decision makers. However, they require a clear definition and robust forecasts of these events. This study analyzes the predictability of heat and cold waves over Europe, defined as at least three consecutive days of \({\text {T}}_{\text {min}}\) and \({\text {T}}_{\text {max}}\) above the quantile Q90 (under Q10), using the extended ensemble system of ECMWF. The results show significant predictability for events within a 2-week lead time, but with a strong decrease of the predictability during the first week of forecasts (from 80 to 40% of observed events correctly forecasted). The scores show a higher predictive skill for the cold waves (in winter) than for the heat waves (in summer). The uncertainties and the sensitivities of the predictability are discussed on the basis of tests conducted with different spatial and temporal resolutions. Results demonstrate the negligible effect of the temporal resolution (very few errors due to bad timing of the forecasts), and a better predictability of large-scale events. The onset and the end of the waves are slightly less predictable with an average of about 35% (30%) of observed heat (cold) waves onsets or ends correctly forecasted with a 5-day lead time. Finally, the forecasted intensities show a correlation of about 0.65 with those observed, revealing the challenge to predict this important characteristic.

Heat waves can be one of the most dangerous climatic hazards affecting the planet, having dramatic impacts on the health of humans and natural ecosystems as well as on anthropogenic activities, infrastructures and economy. Based on climatic conditions in West Africa, the urban centres of the region appear to be vulnerable to heat waves. The goals of this work are firstly to assess the potential uncertainties encountered in heat wave detection and secondly to analyse their recent trend in West Africa cities during the period 1993–2020. This is done using two state-of-the-art reanalysis products, namely the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5) and Modern-Era Retrospective analysis for Research and Applications (MERRA), as well as two local station datasets, namely Dakar–Yoff in Senegal and Aéroport Félix Houphouët-Boigny, Abidjan, in Côte d'Ivoire. An estimate of station data from reanalyses is processed using an interpolation technique: the nearest neighbour to the station with a land sea mask ≥0.5. The interpolated temperatures from local stations in Dakar and Abidjan show slightly better correlation with ERA5 than with MERRA. Three types of uncertainty are discussed: the first type of uncertainty is related to the reanalyses themselves, the second is related to the sensitivity of heat wave frequency and duration to the threshold values used to monitor them, and the last one is linked to the choice of indicators and the methodology used to define heat waves. Three sorts of heat wave have been analysed, namely those occurring during daytime, nighttime, and both daytime and nighttime concomitantly. Four indicators have been used to analyse heat waves based on 2 m temperature, humidity, 10 m wind or a combination of these. We found that humidity plays an important role in nighttime events; concomitant events detected with wet-bulb temperature are more frequent and located over the northern Sahel. Strong and more persistent heat waves are found in the continental (CONT) region. For all indicators, we identified 6 years with a significantly higher frequency of events (1998, 2005, 2010, 2016, 2019 and 2020), possibly due to higher sea surface temperatures in the equatorial Atlantic Ocean corresponding to El Niño events for some years. A significant increase in the frequency, duration and intensity of heat waves in the cities has been observed during the last decade (2012–2020); this is thought to be a consequence of climate change acting on extreme events.