Search

International audience; The paradigm of Sahelian desertification, whose roots lie in the colonial period, increased in popularity following the droughts of the 1970s and 1980s. This "desertification narrative" was shaped in the international arena by organizations working in the fields of international cooperation, human rights, regional development, economic regulation and environmental questions. This narrative has been deployed to have real-world implications of how risks and responses in the Sahel are understood and prioritised, with particularly tangible implications for civil society and international donor agencies. It is indeed widely used in technical writings, general public media and environmental protection projects, regardless of the fact that the majority of literature in environmental science does not support its underlying rationales. It depicts rural populations as victims and culprits (or villains) partially responsible for the desertification, which in turn justifies external intervention in the Sahelian countries. The desertification narrative has an impact on research and development funding by overemphasizing the role of international development aid to combat desertification, thus favoring research on the subject of Sahelian desertification. Furthermore, we argue that the Sahelian desertification narrative contributes to the political control of rural populations, the latter being stigmatized because of their often-considered excessive use of environmental resources.

Heatwaves pose a serious threat to human health worldwide but remain poorly documented over Africa. This study uses mainly the ERA5 dataset to investigate their large-scale drivers over the Sahel region during boreal spring, with a focus on the role of tropical modes of variability including the Madden–Julian Oscillation (MJO) and the equatorial Rossby and Kelvin waves. Heatwaves were defined from daily minimum and maximum temperatures using a methodology that retains only intraseasonal scale events of large spatial extent. The results show that tropical modes have a large influence on the occurrence of Sahelian heatwaves, and, to a lesser extent, on their intensity. Depending on their convective phase, they can either increase or inhibit heatwave occurrence, with the MJO being the most important of the investigated drivers. A certain sensitivity to the geographic location and the diurnal cycle is observed, with nighttime heatwaves more impacted by the modes over the eastern Sahel and daytime heatwaves more affected over the western Sahel. The examination of the physical mechanisms shows that the modulation is made possible through the perturbation of regional circulation. Tropical modes thus exert a control on moisture and the subsequent longwave radiation, as well as on the advection of hot air. A detailed case study of a major event, which took place in April 2003, further supports these findings. Given the potential predictability offered by tropical modes at the intraseasonal scale, this study has key implications for heatwave risk management in the Sahel.

Due to associated hydrological risks, there is an urgent need to provide plausible quantified changes in future extreme rainfall rates. Convection-permitting (CP) climate simulations represent a major advance in capturing extreme rainfall and its sensitivities to atmospheric changes under global warming. However, they are computationally costly, limiting uncertainty evaluation in ensembles and covered time periods. This is in contrast to the Climate Model Intercomparison Project (CMIP) 5 and 6 ensembles, which cannot capture relevant convective processes, but provide a range of plausible projections for atmospheric drivers of rainfall change. Here, we quantify the sensitivity of extreme rainfall within West African storms to changes in atmospheric rainfall drivers, using both observations and a CP projection representing a decade under the Representative Concentration Pathway 8.5 around 2100. We illustrate how these physical relationships can then be used to reconstruct better-informed extreme rainfall changes from CMIP, including for time periods not covered by the CP model. We find reconstructed hourly extreme rainfall over the Sahel increases across all CMIP models, with a plausible range of 37-75% for 2070-2100 (mean 55%, and 18-30% for 2030-2060). This is considerably higher than the +0-60% (mean +30%) we obtain from a traditional extreme rainfall metric based on raw daily CMIP rainfall, suggesting such analyses can underestimate extreme rainfall intensification. We conclude that process-based rainfall scaling is a useful approach for creating time-evolving rainfall projections in line with CP model behaviour, reconstructing important information for medium-term decision making. This approach also better enables the communication of uncertainties in extreme rainfall projections that reflect our current state of knowledge on its response to global warming, away from the limitations of coarse-scale climate models alone.

Over the recent decades, extreme precipitation events (EPEs) have become more frequent over the Sahel. Their properties, however, have so far received little attention. In this study the spatial distribution, intensity, seasonality, and interannual variability of EPEs are examined, using both a reference dataset based on a high-density rain gauge network over Burkina Faso and 24 precipitation gridded datasets. The gridded datasets are evaluated in depth over Burkina Faso while their commonalities are used to document the EPE properties over the Sahel. EPEs are defined as the occurrence of daily accumulated precipitation exceeding the all-day 99th percentile over a 1° × 1° pixel. Over Burkina Faso, this percentile ranges between 21 and 33 mm day−1. The reference dataset show that EPEs occur in phase with the West African monsoon annual cycle, more frequently during the monsoon core season and during wet years. These results are consistent among the gridded datasets over Burkina Faso but also over the wider Sahel. The gridded datasets exhibit a wide diversity of skills when compared to the Burkinabe reference. The Global Precipitation Climatology Centre Full Data Daily version 1 (GPCC-FDDv1) and the Global Satellite Mapping of Precipitation Gauge Reanalysis version 6.0 (GSMaP-gauge-RNL v6.0) are the only products that properly reproduce all of the EPE features examined in this work. The datasets using a combination of microwave and infrared measurements are prone to overestimate the EPE intensity, while infrared-only products generally underestimate it. Their calibrated versions perform better than their uncalibrated (near-real-time) versions. This study finally emphasizes that the lack of rain gauge data availability over the whole Sahel strongly impedes our ability to gain insights in EPE properties.

The summer Guinean Coast (GC) rainfall (GCR) displays a strong variability on different timescales that are driven by Sea Surface Temperature (SST) variations and amplified by land–atmosphere processes. However, the relationships between the GCR and SST modes of variability in the pre-monsoon (March–May, MAM), post-monsoon (October–November, ON) and Harmattan (December–February, DJF) seasons are not well known nor understood. Using observational dataset covering the twentieth century, we extend the conclusion obtained in previous studies that mainly analyzed the summer period (June–September, JJAS) by considering changes in SST-rainfall linkages throughout the year. We show that, in boreal winter, SST interannual variability in the tropical basins are anticorrelated with the GCR. The South Atlantic Ocean Dipole (SAOD) and the Atlantic Niño (ATL3) appear, however, as major drivers of the pre-monsoon and monsoon GCR. In MAM, both modes are in opposite phases with the GCR. Below normal SST in the tropical South Atlantic in MAM leads to a surface divergence south of the equator, and the resulting southerlies bring moist air into coastal Guinea, increasing rainfall. During JJAS, ATL3 and SAOD are in phase with the GCR. During ON, the eastern Mediterranean Sea anomalous warming strengthens the Saharan Heat Low, whose extension in the tropical North Atlantic enhances the low-level westerly Jet. This jet transports moisture into GC. The stationarity of the correlations between the GCR and SST indices has also been assessed, and the strongest and most stationary links are obtained during the monsoon season.

North Africa experienced a severe heatwave in April 2010 with daily maximum temperatures ( $$T_{max}$$ ) frequently exceeding $$40\,^{\circ }\mathrm{C}$$ and daily minimum temperatures ( $$T_{min}$$ ) over $$27\,^{\circ }\mathrm{C}$$ for more than five consecutive days in extended Saharan and Sahelian areas. Observations show that areas and periods affected by the heatwave correspond to strong positive anomalies of surface incoming longwave fluxes ( $$LW_{in}$$ ) and negative anomalies of incoming shortwave fluxes ( $$SW_{in}$$ ). The latter are explained by clouds in the Sahara, and by both clouds and dust loadings in the Sahel. However, the strong positive anomalies of $$LW_{in}$$ are hardly related to cloud or aerosol radiative effects. An analysis based on climate-model simulations (CNRM-AM) complemented by a specially-designed conceptual soil-atmospheric surface layer model (SARAWI) shows that this positive anomaly of $$LW_{in}$$ is mainly due to a water vapor greenhouse effect. SARAWI, which represents the two processes driving temperatures, namely turbulence and longwave radiative transfer between the soil and the atmospheric surface layer, points to the crucial impact of synoptic low-level advection of water vapor on $$T_{min}$$ . By increasing the atmospheric infrared emissivity, the advected water vapor dramatically increases the nocturnal radiative warming of the soil surface, then in turn reducing the nocturnal cooling of the atmospheric surface layer, which remains warm throughout the night. Over Western Sahel, this advection is related to an early northward incursion of the monsoon flow. Over Sahara, the anomalously high precipitable water is due to a tropical plume event. Both observations and simulations support this major influence of the low-level water vapor radiative effect on $$T_{min}$$ during this spring heatwave.

Observed rainfall data of the National Meteorological Service of Guinea (NMS) exhibit that synoptic station usually records the largest rainfall amount in Guinea. Only few studies have been done on this rainfall peak observed in Conakry. This work better analyses the atmospheric dynamics leading to rainfall particularity. Using NMS data from 1981 to 2010, the monthly contribution and mean seasonal cycle of each station has been done. These findings of the study show that between July and August (rainfall season peak), the coastline particularly Conakry records the largest amount of rainfall. Using Era Interim data for the common period (1981-2010), we also investigate the rainfall dynamics in the lower level (1000 hPa - 850 hPa) from precipitable water, divergence, and moisture flow transport. There is a west and southwest moisture flow transport explained by a strong moisture convergence in the coastal region (Lower-Guinea). Furthermore, values of precipitable water in the same region are found, in agreement with the high moisture flow transport gradient. These incoming flow (west and south-west) undergo a return by blocking’s Kakoulima range (foehn effect) and Fouta Djallon massif to initiate convection clouds on the Guinean coast. These processes enhance a convergence of moisture associated with orographic origin convection. This has an important effect by increasing the rainfall amount in Conakry.

Le Livre des Problemes d’Aristote d’Evrart de Conty figure parmi les textes qui ont ete (re)decouverts depuis une vingtaine d’annees. Dans cette contribution, nous retracons tout d’abord brievement...

International audience; Due to associated hydrological risks, there is an urgent need to provide plausible quantified changes in future extreme rainfall rates. Convection-permitting (CP) climate simulations represent a major advance in capturing extreme rainfall and its sensitivities to atmospheric changes under global warming. However, they are computationally costly, limiting uncertainty evaluation in ensembles and covered time periods. This is in contrast to the Climate Model Intercomparison Project (CMIP) 5 and 6 ensembles, which cannot capture relevant convective processes, but provide a range of plausible projections for atmospheric drivers of rainfall change. Here, we quantify the sensitivity of extreme rainfall within West African storms to changes in atmospheric rainfall drivers, using both observations and a CP projection representing a decade under the Representative Concentration Pathway 8.5 around 2100. We illustrate how these physical relationships can then be used to reconstruct better-informed extreme rainfall changes from CMIP, including for time periods not covered by the CP model. We find reconstructed hourly extreme rainfall over the Sahel increases across all CMIP models, with a plausible range of 37%–75% for 2070–2100 (mean 55%, and 18%–30% for 2030–2060). This is considerably higher than the +0–60% (mean +30%) we obtain from a traditional extreme rainfall metric based on raw daily CMIP rainfall, suggesting such analyses can underestimate extreme rainfall intensification. We conclude that process-based rainfall scaling is a useful approach for creating time-evolving rainfall projections in line with CP model behaviour, reconstructing important information for medium-term decision making. This approach also better enables the communication of uncertainties in extreme rainfall projections that reflect our current state of knowledge on its response to global warming, away from the limitations of coarse-scale climate models alone.

International audience;  Observational data sets are used to statistically document processes involved in spring time heat waves in the Sahel  Nighttime heat waves are linked to an increase in precipitable water as well as a frequent high aerosol load.  Daytime heat waves are generally associated with cleaner skies. The more intense events show in addition a higher amount of precipitable water.

A coherent synoptic sequence, mostly over North Africa, is identified whereby an upper-level midlatitude trough (in November–March) excites several days of quasi-stationary near-surface warming across the Sahara, leading to rainfall events over northern Congo (NC), and perturbed weather more widely. Ahead of NC rainfall events, composite sequences first identify troughs for several days near Iberia, followed by relatively quick transfer to the Central Mediterranean (CMed). Iberia and CMed daily trough-strength indices reveal that both lead to warming and NC rainfall. Iberia trough linkages develop through West Africa and take longer to reach NC, while CMed linkages reach NC faster (2–3 days), with impact extent focused mostly south and east of CMed. Building up to the rainfall events, initial warming over the central Sahara migrates southeastward close to NC, ultimately with typical magnitude of about 1–2°C at 10–15°N. Such anomalies are statistically predictive for NC daily rainfall and associated nearby atmospheric features: anomalous low-level southerly wind and increased moisture; anomalous low-level westerly wind and vertical easterly shear to 600 hPa; increased mid-level moisture (600 hPa), which along with low-level moisture, connects northward into midlatitudes. A secondary route identified by which Iberia troughs can impact NC rainfall is through direct atmospheric teleconnection with precipitation to the west of NC, and subsequent migration of that convection eastward into NC. The eastern side of NC generally shows a small lag on western parts, and links more strongly to CMed troughs. Taken together, the lagged synoptic expression of Iberia and CMed troughs is widespread over several days, including much of North Africa (to equatorial latitudes), southwestern Asia, eastern Africa and the western Indian Ocean. Overall, these results can contribute to situational awareness for weather forecasters across the zones influenced by the troughs, while also providing a framework for climate timescale analyses.

The Sahel has experienced an increase in the frequency and intensity of extreme rainfall events over the recent decades. These trends are expected to continue in the future. However the properties of these events have so far received little attention. In the present study, we define a heavy precipitating event (HPE) as the occurrence of daily-mean precipitation exceeding a given percentile (e.g., 99th and higher) over a 1°x1° pixel and examine their spatial distribution, intensity, seasonality and interannual variability. We take advantage of an original reference dataset based on a rather high-density rain-gauge network over Burkina Faso (142 stations) to evaluate 22 precipitation gridded datasets often used in the literature, based on rain-gauge-only measurements, satellite measurements, or both. Our reference dataset documents the HPEs over Burkina Faso. The 99th percentile identifies events greater than 26 mm d-1 with a ~2.5 mm confidence interval depending on the number of stations within a 1°x1° pixel. The HPEs occur in phase with the West African monsoon annual cycle, more frequently during the monsoon core season and during wet years. The evaluation of the gridded rainfall products reveals that only two of the datasets, namely the rain-gauge-only based products GPCC-DDv1 and REGENv1, are able to properly reproduce all of the HPE features examined in the present work. A subset of the remaining rainfall products also provide satisfying skills over Burkina Faso, but generally only for a few HPE features examined here. In particular, we notice a general better performance for rainfall products that include rain-gauge data in the calibration process, while estimates using microwave sensor measurements are prone to overestimate the HPE intensity. The agreement among the 22 datasets is also assessed over the entire Sahel region. While the meridional gradient in HPE properties is well captured by the good performance subset, the zonal direction exhibit larger inter-products spread. This advocates for the need to continue similar evaluation with the available rain-gauge network available in West Africa, both to enhance the HPE documentation and understanding at the scale of the region and to help improve the rainfall dataset quality.

Extreme rainfall is expected to increase under climate change, carrying potential socioeconomic risks. However, the magnitude of increase is uncertain. Over recent decades, extreme storms over the West African Sahel have increased in frequency, with increased vertical wind shear shown to be a cause. Drier midlevels, stronger cold pools, and increased storm organization have also been observed. Global models do not capture the potential effects of lower- to midtropospheric wind shear or cold pools on storm organization since they parameterize convection. Here we use the first convection-permitting simulations of African climate change to understand how changes in thermodynamics and storm dynamics affect future extreme Sahelian rainfall. The model, which simulates warming associated with representative concentration pathway 8.5 (RCP8.5) until the end of the twenty-first century, projects a 28% increase of the extreme rain rate of MCSs. The Sahel moisture change on average follows Clausius–Clapeyron scaling, but has regional heterogeneity. Rain rates scale with the product of time-of-storm total column water (TCW) and in-storm vertical velocity. Additionally, prestorm wind shear and convective available potential energy both modulate in-storm vertical velocity. Although wind shear affects cloud-top temperatures within our model, it has no direct correlation with precipitation rates. In our model, projected future increase in TCW is the primary explanation for increased rain rates. Finally, although colder cold pools are modeled in the future climate, we see no significant change in near-surface winds, highlighting avenues for future research on convection-permitting modeling of storm dynamics.

Tropical savannas comprise mixed woodland grassland ecosystems in which trees and grasses compete for water resources thereby maintaining the spatial structuring of this ecosystem. A global change in rainfall climatology may impact the structure of tropical savanna ecosystems by favouring woody plants, relative to herbaceous vegetation. Here we analysed satellite data and observed a relatively higher increase in woody vegetation (5%) as compared to the increase in annual maximum leaf area index (LAImax, an indicator of the total green vegetation production) (3%) in arid and semi-arid savannas over recent decades. We further observed a declining sensitivity of LAImax to annual rainfall over 56% of the tropical savannas, spatially overlapping with areas of increased woody cover and altered rainfall climatology. This suggests a climate-induced shift in the coexistence of woody and herbaceous vegetation in savanna ecosystems, possibly caused by altered hydrological conditions with significance for land cover and associated biophysical effects such as surface albedo and evapotranspiration., Changing rainfall patterns may drive changes in the structure of tropical savanna. Here Zhang et al. use satellite data from global tropical savannas, and find evidence to suggest that altered rainfall may be favouring woody plants over herbaceous plants in these ecosystems.

The magnitude and sign of soil moisture–precipitation coupling (SMPC) is investigated using a probability-based approach and 10 years of daily microwave satellite data across North Africa at a 1∘ horizontal scale. Specifically, the co-existence and co-variability of spatial (i.e. using soil moisture gradients) and temporal (i.e. using soil moisture anomaly) soil moisture effects on afternoon rainfall is explored. The analysis shows that in the semi-arid environment of the Sahel, the negative spatial and the negative temporal coupling relationships do not only co-exist, but are also dependent on one another. Hence, if afternoon rain falls over temporally drier soils, it is likely to be surrounded by a wetter environment. Two regions are identified as SMPC “hot spots”. These are the south-western part of the domain (7–15∘ N, 10∘ W–7∘ E), with the most robust negative SMPC signal, and the South Sudanese region (5–13∘ N, 24–34∘ E). The sign and significance of the coupling in the latter region is found to be largely modulated by the presence of wetlands and is susceptible to the number of long-lived propagating convective systems. The presence of wetlands and an irrigated land area is found to account for about 30 % of strong and significant spatial SMPC in the North African domain. This study provides the first insight into regional variability of SMPC in North Africa, and supports the potential relevance of mechanisms associated with enhanced sensible heat flux and mesoscale variability in surface soil moisture for deep convection development.

Mid‐level clouds, located between 2 and 9 km height, are ubiquitous in the tropical belt. However, few studies have documented their characteristics and tried to identify the associated thermodynamic properties, particularly in West Africa. This region is characterized by a strong seasonality with precipitation occurring in the Sahel from June to September (monsoon season). This period also coincides with the annual maximum of the cloud cover. Here, we document the macro‐ and microphysical properties of mid‐level clouds, the environment in which such clouds occur, as well as their radiative properties across West Africa. To do so, we combined high‐resolution observations from two ground‐based sites (including lidar and cloud radar) in contrasted environments: one in the Sahel (Niamey, AMMA campaign, 2006) and the other in the Sahara (Bordj Badji Mokhtar, Fennec campaign, June 2011) along with the merged CloudSat‐CALIPSO satellite products. The results show that mid‐level clouds are found throughout the year with a predominance around the monsoon season early in the morning. They also are preferentially observed in the southern and western parts of West Africa. They are usually thin (most of them are less than 1000 m deep) and as observed in Niamey, mainly composed of liquid water. A clustering method applied to Niamey data allows us to distinguish three different types of cloud: one with low bases, one with high bases and another with large thicknesses. The two first cloud families are capped by an inversion. The last family is associated with a large vertical moisture transport and likely has the highest radiative effect at the Earth's surface among the three cloud types.

In the Sahel very high temperatures prevail in spring, but little is known about heat waves in this region at that time of year. This study documents Sahelian heat waves with a new methodology that allows selecting heat waves at specific spatiotemporal scales and can be used in other parts of the world. It is applied separately to daily maximum and minimum temperatures, as they lead to the identification of distinct events. Synoptic–intraseasonal Sahelian heat waves are characterized from March to July over the period 1950–2012 with the Berkeley Earth Surface Temperature (BEST) gridded dataset. Morphological and temperature-related characteristics of the selected heat waves are presented. From March to July, the further into the season, the shorter and the less frequent the heat waves become. From 1950 to 2012, these synoptic–intraseasonal heat waves do not tend to be more frequent; however, they become warmer, and this trend follows the Sahelian climatic trend. Compared to other commonly used indices, the present index tends to select heat waves with more uniform intensities. This comparison of indices also underlined the importance of the heat index definition on the estimated climatic heat wave trends in a changing climate. Finally, heat waves were identified with data from three meteorological reanalyses: ERA-Interim, MERRA, and NCEP-2. The spreads in temperature variabilities, seasonal cycles, and trends among reanalyses lead to differences in the characteristics, interannual variability, and climatic trends of heat waves, with fewer departures from BEST for ERA-Interim.

In most state-of-the-art climate models, systematic errors persist in the representation of the rainfall seasonality, near surface air temperature, and surface energy budget over West Africa, even during the dry season. Most biases are related to an incorrect latitudinal position of the monsoon structures. To disentangle the role of the large-scale dynamics from that of the physical processes in these biases, simulations are performed with the LMDZ general circulation model in which the horizontal winds are nudged toward reanalysis. Wind nudging greatly improves the position of the ITCZ as well as the representation of the components of the surface energy budget directly impacted by the water budget and hence facilitates a more systematic analysis of remaining biases associated with the physics in the model. The great potential of wind nudging to compare the energetics of the atmospheric column in climate models at grid cell scale with station observations, even for coarse grid models, is then shown. Despite the improved water advec-tion and rainfall seasonality in the nudged simulations, errors consisting in a cold bias during the dry season over Sahel, an underestimated seasonal variation of surface albedo, and an overestimation of the solar incoming flux remain. The origin of these remaining biases is further investigated by conducting a series of dedicated sensitivity experiments. Results highlight the key role of the soil thermal inertia, the turbulent mixing efficiency, the surface albedo, and the aerosols and clouds radiative effects in the representation of meteorological 2m-variables and surface energy budget.

Key words Non photosynthetic vegetation, Sahel, STI, dust interannual variability, MODIS. North Africa is the largest dust source on Earth. However, the drivers of dust emission interannual variability in this region are still debated. Early studies outlined the role of previous-season rainfall and vegetation growth, while some recent studies emphasize the role of wind variability. Here we use a newly developed estimation of dry-season nonphotosynthetic vegetation cover in the Sahel to address this question [1]. This estimation is based on data from the Moderate Resolution Imaging Spectroradiometer (MODIS) shortwave infrared bands and covers the 2002-2015 period. Firstly, we showed that the annual vegetation growth anomalies caused by variability of rainfall in June-September (rainy season) translate into anomalies of dry vegetation cover that persist throughout the dry season until May, i.e. until the very end of it. Secondly, we showed that these vegetation anomalies explain 43% (50%) of the year-to-year variance in Sahelian-mean dry-season aerosol optical depth (AOD) as derived from MODIS Deep Blue (or AERONET Sun photometers). Similar explained variance is found with 10 m wind speed and dust uplift potential from the ECMWF. Wind and dry-season vegetation anomalies are not correlated and are further combined in a linear two-variable model. This model is compared to the independent dust concentration data from the Sahelian Dust Transect. The central Sahel proves more important than the western Sahel for dry-season AOD variability, but no relationship to Land Use was found. Dry-season vegetation, for which we now have large-scale observations, is being implemented in models. Figure: (a) Dry-season STI and corresponding dry-vegetation cover in % from MODIS. Letters mark the AERONET stations. The red lines are the 600 mm and 100 mm isohyets. (b) Map of correlation of dry-season STI (October-June) with previous growing-season NDVI (July-September). (c) Map of correlation between dry-season STI and Sahelian AOD.

This study analyses the role of breeze circulations induced by a surface sensible heat flux heterogeneity on deep convection initiation. Large-eddy simulations are used to disentangle the processes at play in a typical case of daytime triggering of deep convection over a semi arid land. We show that the presence of a realistic surface sensible heat flux heterogeneity leads to an earlier triggering of convection and induces a strong determinism in the triggering location at the beta meso-scale (i.e 50 km). The transition to deep convection consists of three consecutive stages, each one corresponding to a specific mode of interaction between (i) the boundary-layer thermals (small-scale), (ii) the breeze circulation (meso-scale) and (iii) the background wind (synoptic scale). These stages are both interpreted thermodynamically and morphologically. All along the transition phase, the boundary-layer growth acts to slow down the background wind, which strengthens the breeze circulation. The breeze evolves towards a circular shape which optimizes moisture convergence and cloud formation just prior to triggering. The presence of wind shear leads with a more asymmetric shape of the breeze in the afternoon, associated with a preferential triggering on the down-shear side of the breeze circulation.

This study analyses uncertainties associated with the annual cycle of West African rainfall characteristics in 15 simulations of the Coupled Model Intercomparison Project phase 5 (CMIP5) over the Sahel and Guinean regions. Indices based on daily rainfall such as the frequency and the ntensity of wet days, the consecutive dry days (CDD) and wet days (CWD), the 95th percentile of daily rainfall (R95) and its contribution to the umulative monsoon rainfall (R95PTOT) have been assessed. Over both regions, TRMM, GPCP and CHIRPS observational datasets provide very consistent results on the annual cycle of precipitation but less so on the frequency of wet days. Conversely, higher uncertainties are noted on the intensity of wet days over both study areas, particularly over the Guinean region. Overall, CMIP5 simulations present much higher uncertainties in the representation of the mean precipitation climatology, often provide too early (late) onset dates over the Sahel (the Guinean region) and overestimate rainfall during the early and late monsoon phases. These errors do not compensate at the annual scale nor when considering West Africa as a hole. Results also reveal that over the Guinean region, the difficulty of models to represent the annual structure of the mean precipitation strongly involves biases in the representation of the annual cycle of the frequency of wet days. We found strong uncertainties in the simulation of the CWD and he CDD over both areas. Conversely for R95p and R95PTOT, the ncertainties in CMIP5 models appear somewhat weaker, but the magnitude f R95 is largely underestimated in most models.

International audience; This study focuses on the ability of the global Land Data Assimilation System, LDAS-Monde, to improve the representation of land surface variables (LSVs) over Burkina-Faso through the joint assimilation of satellite derived surface soil moisture (SSM) and leaf area index (LAI) from January 2001 to June 2018. The LDAS-Monde offline system is forced by the latest European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis ERA5 as well as ERA-Interim former reanalysis, leading to reanalyses of LSVs at 0.25 • × 0.25 • and 0.50 • × 0.50 • spatial resolution, respectively. Within LDAS-Monde, SSM and LAI observations from the Copernicus Global Land Service (CGLS) are assimilated with a simplified extended Kalman filter (SEKF) using the CO2-responsive version of the ISBA (Interactions between Soil, Biosphere, and Atmosphere) land surface model (LSM). First, it is shown that ERA5 better represents precipitation and incoming solar radiation than ERA-Interim former reanalysis from ECMWF based on in situ data. Results of four experiments are then compared: Open-loop simulation (i.e., no assimilation) and analysis (i.e., joint assimilation of SSM and LAI) forced by either ERA5 or ERA-Interim. After jointly assimilating SSM and LAI, it is noticed that the assimilation is able to impact soil moisture in the first top soil layers (the first 20 cm), and also in deeper soil layers (from 20 cm to 60 cm and below), as reflected by the structure of the SEKF Jacobians. The added value of using ERA5 reanalysis over ERA-Interim when used in LDAS-Monde is highlighted. The assimilation is able to improve the simulation of both SSM and LAI: The analyses add skill to both configurations, indicating the healthy behavior of LDAS-Monde. For LAI in particular, the southern region of the domain (dominated by a Sudan-Guinean climate) highlights a strong impact of the assimilation compared to the other two sub-regions of Burkina-Faso (dominated by Sahelian and Sudan-Sahelian climates). In the southern part of the domain, differences between the model and the observations are the Remote Sens. 2019, 11, 735 2 of 26 largest, prior to any assimilation. These differences are linked to the model failing to represent the behavior of some specific vegetation species, which are known to put on leaves before the first rains of the season. The LDAS-Monde analysis is very efficient at compensating for this model weakness. Evapotranspiration estimates from the Global Land Evaporation Amsterdam Model (GLEAM) project as well as upscaled carbon uptake from the FLUXCOM project and sun-induced fluorescence from the Global Ozone Monitoring Experiment-2 (GOME-2) are used in the evaluation process, again demonstrating improvements in the representation of evapotranspiration and gross primary production after assimilation.

International audience; The semi-arid Sahelian region is particularly prone to wind erosion due to low and variable annual precipitation producing low vegetation cover with a high interannual variability. Surfaces traditionally devoted to livestock grazing are used as croplands, increasing the proportion of bare surface unprotected from wind erosion. Wind erosion could significantly evolve in the future with climate change and the changes in land use and agropastoral management practices expected from the persistent demographic growth. To estimate the wind erosion and dust emission in the Sahel, we have developed a regional modelling approach in the framework of the CAVIARS ANR project (Climate, Agriculture and Vegetation: Impacts on Aeolian eRosion in the Sahel). The approach is based on existing models that were adapted and coupled to represent the main processes involved in the wind erosion and their dependence to climate parameters and agropastoral practices. Natural vegetation (herbaceous) and cropped vegetation (millet) are respectively modelled with the STEP vegetation model and the SARRA-H agronomic model,both models improved to reproduce the dynamics of dry vegetation. The wind erosion model has been tested and adapted to represent the erosion fluxes over typical Sahelian vegetated surfaces. A specific parameterization have been developed to represent the very strong surface winds associated to the convective activity. Grazing pressure maps were established based on national data and/or agro-pastoral census. The spatial and temporal distribution of the simulated dust emissions computed for the period 2000-2014 will be presented. The parameterization of the wind speed distribution associated with the convective activity allows to better capture the seasonal pattern of local wind erosion. The relative weight of climatic parameters and agropastoral management will be estimated by reference to a simulation with no vegetation and no land use.

The Sahel has experienced strong climate variability in the past decades. Understanding its implications for natural and cultivated ecosystems is pivotal in a context of high population growth and mainly agriculture-based livelihoods. However, efforts to model processes at the land–atmosphere interface are hindered, particularly when the multi-decadal timescale is targeted, as climatic data are scarce, largely incomplete and often unreliable. This study presents the generation of a long-term, high-temporal resolution, multivariate local climatic data set for Niamey, Central Sahel. The continuous series spans the period 1950–2009 at a 30-min timescale and includes ground station-based meteorological variables (precipitation, air temperature, relative and specific humidity, air pressure, wind speed, downwelling long- and short-wave radiation) as well as process-modelled surface fluxes (upwelling long- and short-wave radiation, latent, sensible and soil heat fluxes and surface temperature). A combination of complementary techniques (linear/spline regressions, a multivariate analogue method, artificial neural networks and recursive gap filling) was used to reconstruct missing meteorological data. The complete surface energy budget was then obtained for two dominant land cover types, fallow bush and millet, by applying the meteorological forcing data set to a finely field-calibrated land surface model. Uncertainty in reconstructed data was expressed by means of a stochastic ensemble of plausible historical time series. Climatological statistics were computed at sub-daily to decadal timescales and compared with local, regional and global data sets such as CRU and ERA-Interim. The reconstructed precipitation statistics, ∼1 °C increase in mean annual temperature from 1950 to 2009, and mean diurnal and annual cycles for all variables were in good agreement with previous studies. The new data set, denoted NAD (Niamey Airport-derived set) and publicly available, can be used to investigate the water and energy cycles in Central Sahel, while the methodology can be applied to reconstruct series at other stations. (Resume d'auteur)

In semi-arid areas like the Sahel, vegetation is particularly sensitive to climate variability and can play an important role in surface-atmosphere coupling. After a wet period extending from 1950 to 1970, the Sahel experienced a severe drought in the 1970s and 1980s, followed by a partial recovery of rainfall and a “re-greening” of vegetation beginning in the 1990s. This study explores how the multidecadal variability of Sahelian rainfall and particularly the drought period have affected vegetation phenology and growth since 1960. The STEP model, which is specifically designed to simulate the Sahelian annual vegetation, including the dry season processes, is run over an area extending from 13°N to 18°N and from 20°W to 20°E. Mean values, interannual variability and phenological characteristics of the Sahelian annual grasslands simulated by STEP are in good agreement with MODIS derived production and phenology over the 2001–2014 period, which demonstrates the skill of the model and allows the analysis of vegetation changes and variability over the last 50 years. It was found that droughts in the 1970s and 1980s shortened the mean vegetation cycle and reduced its amplitude and that, despite the rainfall recovery since the 1990s, the current conditions for green and dry vegetation are still below pre-drought conditions. While the decrease in vegetation production has been largely homogeneous during droughts, vegetation recovery has been heterogeneous over the Sahel since 1990, with specific changes near the western coast and at the eastern edge of the West African monsoon area. Since 1970, the Sahel also experienced an increased interannual variability in vegetation mass and phenology. In terms of phenology, region-averaged End and Length of Season are the most variable, while maximum date and Start of Season are the least variable, although the latter displays a high variability locally.

We investigate how the representation of the boundary layer in a climate model impacts the representation of the near-surface wind and dust emission, with a focus on the Sahel/Sahara region. We show that the combination of vertical turbulent diffusion with a representation of the thermal cells of the convective boundary layer by a mass flux scheme leads to realistic representation of the diurnal cycle of wind in spring, with a maximum near-surface wind in the morning. This maximum occurs when the thermal plumes reach the low-level jet that forms during the night at a few hundred meters above surface. The horizontal momentum in the jet is transported downward to the surface by compensating subsidence around thermal plumes in typically less than 1 h. This leads to a rapid increase of wind speed at surface and therefore of dust emissions owing to the strong nonlinearity of emission laws. The numerical experiments are performed with a zoomed and nudged configuration of the LMDZ general circulation model coupled to the emission module of the CHIMERE chemistry transport model, in which winds are relaxed toward that of the ERA-Interim reanalyses. The new set of parameterizations leads to a strong improvement of the representation of the diurnal cycle of wind when compared to a previous version of LMDZ as well as to the reanalyses used for nudging themselves. It also generates dust emissions in better agreement with current estimates, but the aerosol optical thickness is still significantly underestimated.

The Sahel is prone to intense soil erosion, and the dust emission flux is very sensitive to the surface wind speed. In this study, we use high-frequency observations acquired across the Sahel to assess the ability of three global reanalyses (ERA-interim, NCEP-CFSR and MERRA) to capture the observed surface wind events that are critical to wind erosion. ERA-Interim is shown to perform best. However, all three reanalyses present a too flat annual cycle, with important season-dependent biases: they overestimate the surface wind during dry season nights and underestimate it during spring and monsoon season days. More importantly, the strongest wind speeds, observed in the morning and during deep convective events, are systematically underestimated. As analyzed wind fields are one of the main inputs of many dust emission models, their too low fraction of high wind speeds will lead to major errors in dust emission simulations.

A case of daytime development of deep convection over tropical semi-arid land is used to evaluate the representation of convection in global and regional models. The case is based on observations collected during the African Monsoon Multidisciplinary Analysis (AMMA) field campaign and includes two distinct transition phases, from clear sky to shallow cumulus and from cumulus to deep convection. Different types of models, run with identical initial and boundary conditions, are intercompared: a reference large-eddy simulation (LES), single-column model (SCM) version of four different Earth system models that participated in the Coupled Model Intercomparison Project 5 exercise, the SCM version of the European Centre for Medium-range Weather Forecasts operational forecast model, the SCM version of a mesoscale model and a bulk model. Surface fluxes and radiative heating are prescribed preventing any atmosphere–surface and cloud–radiation coupling in order to simplify the analyses so that it focuses only on convective processes. New physics packages are also evaluated within this framework. As the LES correctly reproduces the observed growth of the boundary layer, the gradual development of shallow clouds, the initiation of deep convection and the development of cold pools, it provides a basis to evaluate in detail the representation of the diurnal cycle of convection by the other models and to test the hypotheses underlying convective parametrizations. Most SCMs have difficulty in representing the timing of convective initiation and rain intensity, although substantial modifications to boundary-layer and deep-convection parametrizations lead to improvements. The SCMs also fail to represent the mid-level troposphere moistening during the shallow convection phase, which we analyse further. Nevertheless, beyond differences in timing of deep convection, the SCM models reproduce the sensitivity to initial and boundary conditions simulated in the LES regarding boundary-layer characteristics, and often the timing of convection triggering.

Lothon, Marie et al., © 2014 Author(s). Due to the major role of the sun in heating the earth's surface, the atmospheric planetary boundary layer over land is inherently marked by a diurnal cycle. The afternoon transition, the period of the day that connects the daytime dry convective boundary layer to the night-time stable boundary layer, still has a number of unanswered scientific questions. This phase of the diurnal cycle is challenging from both modelling and observational perspectives: it is transitory, most of the forcings are small or null and the turbulence regime changes from fully convective, close to homogeneous and isotropic, toward a more heterogeneous and intermittent state. These issues motivated the BLLAST (Boundary-Layer Late Afternoon and Sunset Turbulence) field campaign that was conducted from 14 June to 8 July 2011 in southern France, in an area of complex and heterogeneous terrain. A wide range of instrumented platforms including full-size aircraft, remotely piloted aircraft systems, remote-sensing instruments, radiosoundings, tethered balloons, surface flux stations and various meteorological towers were deployed over different surface types. The boundary layer, from the earth's surface to the free troposphere, was probed during the entire day, with a focus and intense observation periods that were conducted from midday until sunset. The BLLAST field campaign also provided an opportunity to test innovative measurement systems, such as new miniaturized sensors, and a new technique for frequent radiosoundings of the low troposphere. Twelve fair weather days displaying various meteorological conditions were extensively documented during the field experiment. The boundary-layer growth varied from one day to another depending on many contributions including stability, advection, subsidence, the state of the previous day's residual layer, as well as local, meso-or synoptic scale conditions. Ground-based measurements combined with tethered-balloon and airborne observations captured the turbulence decay from the surface throughout the whole boundary layer and documented the evolution of the turbulence characteristic length scales during the transition period. Closely integrated with the field experiment, numerical studies are now underway with a complete hierarchy of models to support the data interpretation and improve the model representations., The BLLAST field experiment was made possible thanks to the contribution of several institutions and supports: INSU-CNRS (Institut National des Sciences de l’Univers, Centre national de la Recherche Scientifique, LEFE-IMAGO program), Météo-France, Observatoire Midi-Pyrénées (University of Toulouse), EUFAR (EUropean Facility for Airborne Research) BLLATE-1&2, COST ES0802 (European Cooperation in the field of Scientific and Technical) and the Spanish MINECO projects CGL2009–08609, CGL2012–37416–C04–03, CGL2012–37416– C04–02 and CGL2011-13477-E

International audience; The diurnal cycle is an important mode of variability in the Tropics that is not correctly predicted by numerical weather prediction models. The African Monsoon Multidisciplinary Analyses program provided for the first time a large dataset to document the diurnal cycle over West Africa. In order to assess the processes and mechanisms that are crucial for the representation of the diurnal cycle, four different regimes that characterize the varying conditions encountered over land along a surface-temperature gradient are selected. A single-column modelling framework is used in order to relate the features of the simulated diurnal cycle to physical processes in these four distinct cases. Particular attention is given to providing realistic initial and boundary conditions at the surface and in the atmosphere, enabling the use of independent data for the evaluation of the simulations. The study focuses on the simulation of the surface energy budget and low-level characteristics and analyzes the balance between cloud/surface/boundary-layer processes at the sub-diurnal time scale. The biases and drawbacks of the simulations are found to change along the temperature gradient but they always involve the representation of clouds. They also explain parts of the bias obtained with the same model when used in a less constrained configuration. Surface-atmosphere-cloud interactions arising at the sub-diurnal time scale are invoked to explain the distinct features of the low-level diurnal cycle observed over West Africa.

Thisstudyaimstoachieveabetterunderstandingoftheinitiationofdeepconvection in the Sahel by using the African Monsoon Multidisciplinary Analyses (AMMA) dataset. Based on the Massachusetts Institute of Technology (MIT) radar, wind profiler,satellitedata,surfacefluxandmeteorologicalstations,wehavecharacterised the atmospheric convection which occurred over Niamey during the onset period of the monsoon. From 6 to 31 July, radar reflectivity fields combined with brightness temperatures were used to classify the type of convection observed each day within a 50km radius of the MIT radar location. Four types of convection have been identified: fair weather (FW) with a clear sky throughout the entire day, shallow convection (SH), afternoon locally initiated deep convection (LC), and propagating deep convection (PC). Subsequently, the mechanisms responsible for the initiation of local deep convection were investigated. Neither early morning convective available potential energy nor the convective triggering potential allowed the onset of local deep convection to be predicted correctly. In effect, they were both favourable to deep convection most of the time, while convective inhibition was typically quite large. Our results show that the daytime growth of the atmospheric boundary layer needed to be sufficient for local deep convection to occur during that period. Convergence lines, which grew within the morning clear-air roll organisation, were found to be precursors of local deep convection. Classes FW, SH and LC ultimately behaved quite similarly, with notable convergence in the lower troposphere, but FW showed smaller boundarylayer growth, and FW and SH classes revealed a significant divergence above the boundary layer. Most cases of LC generated a circular gust front. These density currents almost always generated new convective cells. Copyright c � 2013 Royal

International audience; African dust emission and transport exhibits variability on diurnal to decadal timescales and is known to influence processes such as Amazon productivity, Atlantic climate modes, regional atmospheric composition and radiative balance and precipitation in the Sahel. To elucidate the role of African dust in the climate system, it is necessary to understand the factors governing its emission and transport. However, African dust is correlated with seemingly disparate atmospheric phenomena, including the El Niño/Southern Oscillation, the North Atlantic Oscillation, the meridional position of the intertropical convergence zone, Sahelian rainfall8 and surface temperatures over the Sahara Desert, all of which obfuscate the connection between dust and climate. Here we show that the surface wind field responsible for most of the variability in North African dust emission reflects the topography of the Sahara, owing to orographic acceleration of the surface flow. As such, the correlations between dust and various climate phenomena probably arise from the projection of the winds associated with these phenomena onto an orographically controlled pattern of wind variability. A 161-year time series of dust from 1851 to 2011, created by projecting this wind field pattern onto surface winds from a historical reanalysis, suggests that the highest concentrations of dust occurred from the 1910s to the 1940s and the 1970s to the 1980s, and that there have been three periods of persistent anomalously low dust concentrations—in the 1860s, 1950s and 2000s. Projections of the wind pattern onto climate models give a statistically significant downward trend in African dust emission and transport as greenhouse gas concentrations increase over the twenty-first century, potentially associated with a slow-down of the tropical circulation. Such a dust feedback, which is not represented in climate models, may be of benefit to human and ecosystem health in West Africa via improved air quality and increased rainfall6. This feedback may also enhance warming of the tropical North Atlantic, which would make the basin more suitable for hurricane formation and growth.

This study evaluates the ability of three operational models, AROME, ARPEGE and ECMWF, to predict the boundary-layer turbulent processes and mesoscale variability observed during the Boundary Layer Late-Afternoon and Sunset Turbulence (BLLAST) field campaign. AROME is a 2.5 km limited area non-hydrostatic model operated over France, ARPEGE a global model with a 10 km grid-size over France and ECMWF a global model with a 16 km grid-size. We analyze the representation of the vertical profiles of temperature and humidity and the time evolution of near surface atmospheric variables as well as the radiative and turbulent fluxes for a total of 12 24h-long Intensive Observing Periods. Special attention is paid to the evolution of the turbulent kinetic energy that was sampled by a combination of independent instruments. For the first time, this variable, which is a central variable in the turbulence scheme used in AROME and ARPEGE, is evaluated with observations. In general, the 24h-forecasts succeed in reproducing the variability from one day to the other in term of cloud cover, temperature, boundary-layer depth. However, they exhibit some systematic biases, in particular a cold bias within the daytime boundary layer for all models. An overestimation of the sensible heat flux is noted for two points in ARPEGE, partly related to an inaccurate simplification of surface characteristics and over-predominance of forests. AROME shows a moist bias within the daytime boundary layer, consistently with overestimated latent heat fluxes. ECMWF presents a dry bias at 2 m above surface and also overestimates the sensible heat flux. The high-resolution model AROME better resolves the vertical structures, in particular the strong daytime inversion and the evening thin stable boundary layer. This model is also capable to capture the peculiar observed features, such as the orographically-driven subsidence and a well-defined maximum in water vapor mixing ratio in the upper part of the residual layer that arises during the evening due to mesoscale advection. The mesoscale variability is analyzed and the order of magnitude is also well reproduced in AROME. AROME provides a good simulation of the diurnal variability of the turbulent kinetic energy while ARPEGE shows a right order of magnitude.

This study focuses on the occurrence and type of clouds observed in West Africa, a subject that has been neither much documented nor quantified. It takes advantage of data collected above Niamey, Niger, in 2006 with the Atmospheric Radiation Measurement (ARM) Mobile Facility. A survey of cloud characteristics inferred from ground measurements is presented with a focus on their seasonal evolution and diurnal cycle. Four types of clouds are distinguished: high-level clouds, deep convective clouds, shallow convective clouds, and midlevel clouds. A frequent occurrence of the latter clouds located at the top of the Saharan air layer is highlighted. High-level clouds are ubiquitous throughout the period whereas shallow convective clouds are mainly noticeable during the core of the monsoon. The diurnal cycle of each cloud category and its seasonal evolution are investigated. CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are used to demonstrate that these four cloud types (in addition to stratocumulus clouds over the ocean) are not a particularity of the Niamey region and that midlevel clouds are present over the Sahara during most of the monsoon season. Moreover, using complementary datasets, the radiative impact of each type of clouds at the surface level has been quantified in the short- and longwave domains. Midlevel clouds and anvil clouds have the largest impact, respectively, in longwave (about 15 W m−2) and shortwave (about 150 W m−2) radiation. Furthermore, midlevel clouds exert a strong radiative forcing during the spring at a time when the other cloud types are less numerous.

A modelling case study designed from observations from the African Monsoon Multidisciplinary Analysis (AMMA) is presented and discussed. It aims at investigating the issue of initiation of convection in a semi-arid environment. This case corresponds to the development of local daytime convection mainly controlled by boundary layer characteristics rather than by atmospheric synoptic scales. A high-resolution three-dimensional simulation is presented and extensively evaluated against the numerous observations available for 10 July 2006 from the AMMA campaign. The simulation, run over a domain of100 × 100 km, is able to represent main boundary layer structures and processes leading to deep convection initiation as well as the formation of density currents. Sensitivity tests point to the key role of the sensible heat flux, the humidity of low to mid levels, the lapse rate at low levels and of a mesoscale ascent to initiate deep convection in those semi-arid conditions, while evaporation of precipitation is shown to play a minor role. This study thus provides a case to investigate the ability of parametrizations to handle the initiation of convection in a semi-arid environment. Copyright c � 2011 Royal Meteorological

International audience; The major advances achieved during African monsoon multidisciplinary analysis in our physical understanding of the West African monsoon (WAM) system are reviewed. Recent research provides an advanced understanding of key WAM features. The Saharan heat low, the interactions of the monsoon flow with the surface and the reversed flow on top of it, all play a more important role than previously assumed, and interact according to the phase of the diurnal cycle of convection. Recent studies also emphasise the significance of upstream conditions in Central and East Africa, as well as strong interactions between midlatitudes and the WAM.

A method to analyze the daily cycle of evapotranspiration over land is presented. It quantifies the influence of external forcings, such as radiation and advection, and of internal feedbacks induced by boundary layer, surface layer, and land surface processes on evapotranspiration. It consists of a budget equation for evapotranspiration that is derived by combining a time derivative of the Penman–Monteith equation with a mixed-layer model for the convective boundary layer. Measurements and model results for days at two contrasting locations are analyzed using the method: midlatitudes (Cabauw, Netherlands) and semiarid (Niamey, Niger). The analysis shows that the time evolution of evapotranspiration is a complex interplay of forcings and feedbacks. Although evapotranspiration is initiated by radiation, it is significantly regulated by the atmospheric boundary layer and the land surface throughout the day. In both cases boundary layer feedbacks enhance the evapotranspiration up to 20 W m−2 h−1. However, in the case of Niamey this is offset by the land surface feedbacks since the soil drying reaches −30 W m−2 h−1. Remarkably, surface layer feedbacks are of negligible importance in a fully coupled system. Analysis of the boundary layer feedbacks hints at the existence of two regimes in this feedback depending on atmospheric temperature, with a gradual transition region in between the two. In the low-temperature regime specific humidity variations induced by evapotranspiration and dry-air entrainment have a strong impact on the evapotranspiration. In the high-temperature regime the impact of humidity variations is less pronounced and the effects of boundary layer feedbacks are mostly determined by temperature variations.