B Gaimoz

M Chatenet

I Coulibaly

A Koné

A Maman

Zakou

G Bergametti
email: gilles.bergametti@lisa.ipsl.fr

J.-L Rajot

B Marticorena

A Féron

C Gaimoz

B Chatenet

M Coulibaly

I Koné

A Zakou

Rain, Wind and Dust Connections in the Sahel

  L'archive ouverte pluridisciplinaire

Introduction

Between 1000 and 4000 Tg of mineral dust are injected yearly by wind erosion into the atmosphere (e.g., Boucher et al., 2013;[START_REF] Huneeus | Global dust model intercomparison in AeroCom phase I[END_REF], making dust as one of the most emitted particulate species. As a consequence, the dust cycle has significant impacts on the Earth's environment and is now recognized as a key actor in the Earth System Science (e.g., [START_REF] Shao | Dust cycle: an emerging core theme in Earth System Science[END_REF]. In dust source regions, mainly arid and semi-arid areas, the movement of windblown sediments modulates the geomorphology of landscapes (e.g., [START_REF] Greeley | Wind as a geological process on Earth, Mars, Venus and Titan[END_REF][START_REF] Livingstone | Aeolian geomorphology: an introduction[END_REF] and can also lead to an impoverishment of naturally vegetated areas and cultivated soils (e.g., [START_REF] Li | Quantitative effects of vegetation cover on wind erosion and soil nutrient loss in a desert grassland of southern New Mexico, USA[END_REF]2008;[START_REF] Sterk | Causes, consequences and control of wind erosion in Sahelian Africa: a review[END_REF][START_REF] Sterk | Wind-blown nutrient transport and soil productivity changes in Southwest Niger[END_REF]. During their transport in the atmosphere, the finest component of dust (particles smaller than about 20 µm in diameter) can interact with solar and terrestrial radiation, affecting the Earth radiation budget (e.g., [START_REF] Miller | Impact of dust radiative forcing upon climate[END_REF][START_REF] Sokolik | Outstanding problems in quantifying the radiative impacts of mineral dust[END_REF]. Mineral dust could also act in the formation of clouds, especially as ice nuclei (e.g., DeMott et al., 2003aDeMott et al., , 2003b;;[START_REF] Sassen | Characterization of convective systems and their association with African easterly waves[END_REF] or modifying their microphysical and optical properties (e.g., [START_REF] Knopf | Heterogeneous nucleation of ice on surrogates of mineral dust[END_REF][START_REF] Min | Evidence of mineral dust altering cloud microphysics and precipitation[END_REF][START_REF] Weinzierl | The Saharan aerosol long-range transport and aerosol-cloud-interaction experiment: Overview and selected highlights[END_REF]. In deposition areas, dust provides terrestrial and oceanic ecosystems with key nutrients or micronutrients such as phosphorus or iron (e.g., [START_REF] Bergametti | Source, transport and deposition of atmospheric phosphorus over the Northwestern Mediterranean[END_REF][START_REF] Jickells | Global iron connections between desert dust, ocean biogeochemistry, and climate[END_REF]2014;[START_REF] Mahowald | Global distribution of atmospheric phosphorus sources, concentrations and deposition rates, and anthropogenic impacts[END_REF]Okin et al., 2004).

The main processes controlling the dust cycle on Earth are very sensitive to meteorological parameters such as surface wind speed and precipitation. Thus, it is suspected that climate change could significantly modify the atmospheric dust content in the future, especially by changing the intensity and location of the dust emissions. The semi-arid regions that are climatic transitional zones should be particularly affected. In these regions, the expected changes should concern not only the meteorological parameters that directly drive dust emission but also those controlling the vegetation cover such as precipitation and evapotranspiration. In addition, the fringes of the arid regions are inhabited, with a population density growing rapidly (e.g., [START_REF] Garenne | La pression de la population dans les pays sahéliens francophones: Analyse des estimations et projections de population 1950-2100[END_REF]UNDP, 2015). Therefore, it can be expected that land use activities may intensify in the future to provide the food necessary to support this expanding population (e.g., [START_REF] Van Vliet | Scientific documentation of crop land changes in the Sahel: A half empty box of knowledge to support policy[END_REF]. As a consequence, surface cover and its temporal dynamics should be strongly modified by transforming naturally vegetated surfaces into crops and/or by changing the pasture pressure exerted on the grazing lands.

Among the semi-arid regions, the Sahelian belt is suspected to be one of the areas where the most significant changes in dust emission could occur in the future. Unfortunately, Global Climate Models (GCM) show very large uncertainties in the projected precipitation trend for this region and do not agree on the amplitude of the change in temperature (e.g., [START_REF] Douville | On the tropical origin of uncertainties in the global land precipitation response to global warming[END_REF][START_REF] Monerie | Model uncertainties in climate change impacts on Sahel precipitation in ensembles of CMIP5 and CMIP6 simulations[END_REF]. Regional climate models (RCM) do not provide a much more reliable assessment, mainly because the Sahelian climate is strongly influenced by interactions between large, meso and small scales processes that even RCM cannot reproduce satisfyingly (e.g., [START_REF] Dosio | Climate change projections for CORDEX-Africa with COSMO-CLM regional climate model and differences with the driving global climate models[END_REF][START_REF] Dosio | What can we know about future precipitation in Africa? robustness, significance and added value of projections from a large ensemble of regional climate models[END_REF]. However, recently, the results of a large ensemble of RCMs converge to suggest that, in the future, the precipitation frequency may decrease while the precipitation intensity increases over the Sahel with possible differences between Western and Central Sahel [START_REF] Dosio | A tale of two futures: contrasting scenarios of future precipitation for West Africa from an ensemble of regional climate models[END_REF].

In the Sahel, dust emission is mainly linked to two main meteorological phenomena depending on the season. During the dry season (~November to April), the Sahel is subject to the Harmattan regime, i.e., the continental northeast trade wind blowing over the North Africa. The surface wind direction up to about 3 km height is northeasterly and brings hot and dry Saharan air masses into the Sahel. At this period of the year, the strongest surface wind speed occurs between 8:00-12:00 UTC as the result of the morning breakdown of the Nocturnal Low Level Jet (NLLJ), a jet stream whose maximum speed is generally located at ~400 m above ground level (agl) (e.g., [START_REF] Lothon | Observation of the diurnal cycle in the low troposphere of West Africa[END_REF]. A wind speed maximum generally develops after sunset in a layer decoupled from the surface as the consequence of the stable stratification induced by the radiative cooling. In the morning, from sunrise to about midday, the surface heating increases the turbulence that induces a downward mixing of momentum from the NLLJ. By midday, the turbulence reaches its maximum reducing the vertical gradient of momentum and finally progressively dissipating the jet. This leads to surface wind speed generally not higher than 10 m s -1 but sufficiently strong to initiate a moderate aeolian erosion (e.g., [START_REF] Rajot | AMMA dust experiment: An overview of measurements performed during the dry season special observation period (SOP0) at the Banizoumbou (Niger) supersite[END_REF].. This morning wind speed enhancement is also observed during the rainy season. However, the wind direction is opposite due to the monsoon flow that blows in the lower atmospheric layer at that time and the associated wind speed is weaker than during the dry season (Figure 1) and the transition period from dry to wet season also called the moistening period. Such phenomena affect not only the Sahel but a large part of Africa, as shown by the pioneer work performed in Sudan by [START_REF] Sutton | The Climate of Khartoum[END_REF], further generalized by [START_REF] Tetzlaff | Nordafrikanischer Passat im Winter[END_REF] and also reported latter by various authors (e.g., [START_REF] Fiedler | Climatology of nocturnal low-level jets over North Africa and implications for modeling mineral dust emission[END_REF][START_REF] Knippertz | Dust emissions in the west African heat trough: The role of the diurnal cycle and of extratropical disturbances[END_REF][START_REF] Lothon | Observation of the diurnal cycle in the low troposphere of West Africa[END_REF]. Thus, during the dry season, the Sahelian climate can be viewed as stationary in the sense defined by Abu [START_REF] Abu Bakr | A boundary-layer model for the determination of hourly surface wind characteristics in a representative tropical African region[END_REF] from observations in Sudan, i.e., the day-to-day variations of the key meteorological parameters are very small and the average diurnal cycle shows a similar behavior all across the region. In terms of dust concentration, it must be noted that the highest monthly and daily mean PM10 concentrations are recorded between February and April. They are mainly due to frequent synoptic transport events of Saharan dust in the Harmattan flow [START_REF] Kaly | Variability of mineral dust concentrations over West Africa monitored by the Sahelian Dust Transect[END_REF]Klose et al., 2010;[START_REF] Marticorena | Temporal variability of mineral dust concentrations over West Africa: Analyses of a pluriannual monitoring from the AMMA Sahelian Dust Transect[END_REF].

Intense rains appear near the Gulf of Guinea in March-April while the Inter-Tropical Convergence Zone (ITCZ) is located between 5° and 10° N. Then, the ITCZ moves to ~ 20°N in August when the monsoon is fully developed (e.g., N'Tchayi [START_REF] Mbourou | Impact of desert dust on the biogeochemistry of phosphorus in terrestrial ecosystems[END_REF].

It starts its retreat southward, generally after mid-September. Obviously, intense air masses conflicts can occur along the Inter-Tropical Front as the result of the contrast between the low-level moist southwesterly monsoon flow and the mid-tropospheric dry northeasterly Harmattan air mass. Indeed, during the moistening and monsoon periods, the surface heating manuscript accepted to Journal of Geophysical Research-Atmospheres during daytime can be sufficient to promote the growth of the boundary layer leading to an inversion of the flow in the lower layers. This favors the wind convergence in the humid lower layers, reinforcing the vertical wind shear and the atmospheric instability and finally allowing the formation of convective cells. When such individual convective cells joint together in a more or less organized structure, they form a Mesoscale Convective System (MCS). Such an organization is favored when the vertical mixing extends across the free troposphere and is accompanied by a disturbance of the mid-tropospheric African Easterly waves (e.g., [START_REF] Diedhiou | Easterly wave regimes and associated convection over West Africa and tropical Atlantic: Results from the NCEP/NCAR and ECMWF reanalyses[END_REF]Mekonen and Rossow, 2018;Semunegus et al., 2017;[START_REF] Vizy | Mesoscale convective systems and nocturnal rainfall over the west African Sahel: Role of the inter-tropical front[END_REF].

Up to 95% of the rainfall over the Sahel is associated with MCSs (e.g., d'Amato & Lebel, 1998;[START_REF] Dhonneur | Les amas nuageux mobiles principale composante de la météorologie du Sahel[END_REF][START_REF] Laing | Contribution of mesoscale convective complexes to rainfall in Sahelian Africa: estimates from geostationary infrared and passive microwave data[END_REF][START_REF] Laurent | How important is the contribution of the mesoscale convective complexes to the Sahelian rainfall?[END_REF][START_REF] Mohr | Interannual, monthly, and regional variability in the wet season diurnal cycle of precipitation in sub-Saharan Africa[END_REF]. However, in the region of Niamey (Niger), [START_REF] Mathon | Mesoscale convective system rainfall in the Sahel[END_REF] distinguished the so-called Organized Convective Systems among the MCSs they have studied. These are large, well-organized and fast-moving MCSs such as squall lines. This type of MCSs accounts for only 12% of the total number of MCSs, but they contribute to about 90 % of the rainfall.

The cooling caused by phase changes in precipitation falling through the unsaturated Sahelian dry troposphere enhances the formation of a downdraft that is colder and denser than the surrounding air. At the surface, a cold pool is thus formed and propagates in the form of a density current. The winds associated with this cold pool are often gusty (e.g., [START_REF] Roberts | Haboobs: Convectively generated dust storms in West Africa[END_REF]Tetzlaff & Peters, 1988a[START_REF] Tetzlaff | The structure of West African squall lines and their environmental moisture budget[END_REF][START_REF] Vizy | Mesoscale convective systems and nocturnal rainfall over the west African Sahel: Role of the inter-tropical front[END_REF]. MCSs are most of the time mature and more or less well organized in the evening and during early night (e.g., [START_REF] Mathon | Mesoscale convective system rainfall in the Sahel[END_REF][START_REF] Vizy | Mesoscale convective systems and nocturnal rainfall over the west African Sahel: Role of the inter-tropical front[END_REF]. Their lifetime ranges from a few hours to about two days, allowing travel paths ranging from 200 to 2000 km (e.g., [START_REF] Devynck | Study of some Sahelian disturbances during WAMEX[END_REF][START_REF] Roca | Robust observational quantification of the contribution of mesoscale convective systems to rainfall in the tropics[END_REF].

In areas where soils are easily erodible, the strong vertical wind shear associated with gust fronts of MCSs promotes the uplift of huge amounts of dust ahead these fronts leading to the famous and impressive walls of dust called "haboobs" that can extend vertically up to 5000 m agl (e.g., [START_REF] Williams | Comment on "Atmospheric controls on the annual cycle of North African dust" by S. Engelstaedter and R. Washington[END_REF][START_REF] Williams | The electrification of dust-lofting gust fronts ('haboobs') in the Sahel[END_REF]. As a consequence, during the Sahelian wet season, there is a strong interconnection between precipitation, high wind speed and dust emission.

The respective contributions of the breakdown of the NLLJ and MCSs to dust emission have been examined quantitatively using the Dust Uplift Potential (DUP), a proxy used to quantify the capability of wind to produce wind erosion and dust emission [START_REF] Fryberger | Dune forms and wind regime in A Study of Global Sand Seas[END_REF][START_REF] Marsham | The importance of the representation of deep convection for modeled dust-generating winds over West Africa during summer[END_REF]. [START_REF] Bergametti | Dust uplift potential in the central Sahel: An analysis based on 10 years of meteorological measurements at high temporal resolution[END_REF] showed that the passing of MCSs is responsible for most of the DUP in the Central Sahel. Similar conclusions were drawn for the Central Sahara for which at least half of dust emission in summer has been estimated to be due to MCSs [START_REF] Allen | Dust detection from ground-based observations in the summer global dust maximum: Results from Fennec 2011 and 2012 and implications for modeling and field observations[END_REF][START_REF] Marsham | Meteorology and dust in the central Sahara: Observations from Fennec supersite-1 manuscript accepted to Journal of Geophysical Research-Atmospheres during the June 2011 Intensive Observation Period[END_REF].

The spatial resolution of large-scale meteorological models is generally suitable to simulate synoptic events but they cannot resolve correctly mesoscale updrafts and downdrafts that are responsible for most of the highest dust emissions in many areas (e.g., [START_REF] Bukowski | Convective distribution of dust over the Arabian Peninsula: the impact of model resolution[END_REF][START_REF] Pantillon | Modeling haboob dust storms in large-scale weather and climate models[END_REF]. In particular, these models are unable to simulate the dust events associated with MCSs, mainly because their parameterization of the convection does not represent correctly the density currents and their propagation (e.g., [START_REF] Garcia-Carreras | The impact of convective cold pool outflows on model biases in the Sahara[END_REF][START_REF] Largeron | Can we use surface wind fields from meteorological reanalyses for Sahelian dust emission simulations[END_REF][START_REF] Marsham | The importance of the representation of deep convection for modeled dust-generating winds over West Africa during summer[END_REF].

Few observational studies of these events for the Sahel are available even if the intensive observation periods of the AMMA (African Monsoon Multidisciplinary Analyses) program have allowed thorough investigation of selected convective events using radar data, airborne manuscript accepted to Journal of Geophysical Research-Atmospheres measurements and/or surface observations, satellite tracking, etc. (Bou [START_REF] Karam | Dry cyclogenesis and dust mobilization in the Inter Tropical Discontinuity of the West African Monsoon: A case study[END_REF][START_REF] Chong | The 11 August 2006 squall-line system as observed from MIT Doppler radar during the AMMA SOP[END_REF][START_REF] Dione | Phenomenology of Sahelian convection observed in Niamey during the early manuscript accepted to Journal of Geophysical Research-Atmospheres monsoon[END_REF]Flamand et al., 2009;[START_REF] Lothon | Life cycle of a mesoscale circular gust front observed by a C-band Doppler radar in West Africa[END_REF][START_REF] Mcgraw-Herdeg | Dusty gust fronts and their contributions to long-lived convection in West Africa[END_REF][START_REF] Provod | A characterization of cold pools in the West African Sahel[END_REF][START_REF] Rickenbach | Radar-observed squall line propagation and the diurnal cycle of convection in Niamey, Niger during the 2006 African Monsoon and Multidisciplinary Analyses Intensive Observing Period[END_REF][START_REF] Tetzlaff | Nordafrikanischer Passat im Winter[END_REF]Peters, 1988a, 1988b;[START_REF] Vizy | Mesoscale convective systems and nocturnal rainfall over the west African Sahel: Role of the inter-tropical front[END_REF]. Most of these detailed observations concern MCSs passing in the region of Niamey during summer 2006 and the number of documented cases remains relatively small, not exceeding a few dozens. Moreover, very few of these studies (e.g., Bou [START_REF] Karam | Dust emissions over the Sahel associatedwith the West African monsoon intertropical manuscript accepted to Journal of Geophysical Research-Atmospheres discontinuity region: A representative case-study[END_REF][START_REF] Crumeyrolle | Increase of the aerosol hygroscopicity by aqueous mixing in a mesoscale convective system: A case study from the AMMA campaign[END_REF] examined the impact of such events on the atmospheric dust content, most of them being dedicated to the study of the genesis and meteorological characteristics of the convective systems.

In the present paper, we investigate specifically the links between wind speed, precipitation and dust concentration during the Sahelian wet season by using measurements of surface meteorological parameters and dust concentration for more than 1000 rainy events over a 10year period from two Sahelian stations. The Banizoumbou station is in a field that has been fallow for more than 25 years, set among traditional fallow/fields. It is located about 2.5 km from the village of Banizoumbou (60 km east of Niamey). The Cinzana station, located about 40 km east-southeast of Segou, is inside the Institut d'Economie Rurale (IER), 1.5 km away from the main buildings of the Station de Recherche Agronomique de Cinzana (SRAC). In this area, the vegetation cover is mainly composed of shrubs and trees.

Meteorological measurements are performed at 6.5 m agl in Banizoumbou and at 2.3 m agl in Cinzana. A Windsonic 2-D anemometer (Gill ® Instruments Ltd.) provides the wind speed and direction averaged over a 5-minute time step. Within each 5-minute period, the 1-second windspeed (sampled every 10 seconds) and hereafter called the "wind gust", was also recorded in [START_REF] Li | Quantitative effects of vegetation cover on wind erosion and soil nutrient loss in a desert grassland of southern New Mexico, USA[END_REF], 2008, 2009, 2010, 2011and 2013in Banizoumbou and from 2007to 2012 (included) (included) in Cinzana. Both in Banizoumbou and Cinzana, the wind gusts are well linearly correlated (r 2 >0.9) with the 5-minute averaged wind speed with a slope of 1.51 and 1.76, respectively (Figure S1). This suggests that the wind speed averaged over 5 minutes can be considered as a good proxy for wind gust. It can also be noted that wind gust can reach values as high as 35 m s -1 and 22 m s -1 in Banizoumbou and Cinzana, respectively.

Rainfall is monitored using an ARG100 aerodynamic tipping bucket rain gauge (Campbell ® Scientific Instruments). It provides a contact closure at each tipping (i.e., for each 0.2 mm of rainfall) and the number of tips is cumulated over a 5-minute time step. Temperature and relative humidity are measured using a 50Y or HMP50 sensor (Vaisala ® ). Data acquisition is performed using a CR200X Campbell ® Scientific Instruments data logger. The energy is provided by solar panels.

In this paper, we used the 5-minute data for the period 2006-2015. The annual recovery rates for meteorological measurements are given in Table S1. They were always greater than 90%. However, data are lacking for more or less long periods during the rainy season of certain years and thus, these years (2008( , 2012( , 2014( for Banizoumbou and 2007( , 2011( , 2013 for Cinzana) have been used when discussing the general characteristics of the rainy events but were excluded to study seasonal or interannual patterns.

Atmospheric concentration of PM10 is measured at 6.5 m agl at both stations using a Tapered Element Oscillating Microbalance (TEOM 1400A from Thermo Scientific ® ) equipped with a PM10 inlet. This instrument allows measurement of particulate concentration ranging from a few micrograms to a few grams per cubic meter. The main element in the instrument is an oscillating element on top of which is located a filter. The particles collected on the filter increase the mass of the oscillating element and thus decrease its oscillation frequency. To maintain a constant confidence level in the particulate concentration measurements, the filters are changed two or three times a month. More details on the PM10 measurements can be found in [START_REF] Marticorena | Temporal variability of mineral dust concentrations over West Africa: Analyses of a pluriannual monitoring from the AMMA Sahelian Dust Transect[END_REF][START_REF] Kaly | Variability of mineral dust concentrations over West Africa monitored by the Sahelian Dust Transect[END_REF]. The annual recovery rates for PM10 measurements (>67% excepted in 2013 in Banizoumbou) are given in Table S1.

manuscript accepted to Journal of Geophysical Research-Atmospheres

Data Selection

The aim of this paper being to investigate the link between rainy events, wind speed and PM10 concentration, we selected all the measurements performed within the time period ranging from 90 minutes before and 90 minutes after the onset of a rainy event.

The onset and the end of a rainy event are defined as the 5-minute intervals during which occur the first and last bucket tippings of a rainy event, respectively. We also define a rainy event as a precipitation event having a cumulative rainfall strictly greater than 0.2 mm. Records of precipitation not exceeding 0.2 mm are, for the most part, due to dew, especially those occurring in the morning during the rainy season. Two consecutive rainy events must be separated by a period of time longer than 3 hours. This means that periods of less than 3 hours without recording precipitation can occur inside a rainy event and that a precipitation occurring more than 3 hours after the end of a rainy event is considered as a new rainy event.

We define the duration of a rainy event as the delay between the first tipping of the precipitation sensor and the last one, i.e., the tipping not followed by another tipping during the following 3 hours.

Using these criteria, 589 rainy events were identified in Cinzana over the 10 years (449 when 2007, 2011 and 2013 were excluded). In Banizoumbou, 431 rainy events were recorded over the same period (304 when 2008, 2012 and 2014 were excluded). Moreover, PM10 concentration was available for 343 (in Banizoumbou) and 277 (in Cinzana) of these rainy events. In the following, the onset of the rainy event will be used as a reference time, because it is the most easily determined and also because dust concentration can be significantly different before and after the rain starts.

DUP

We use the DUP as an indicator the efficiency of wind to generate dust. As mentioned before, DUP is derived from a quantitative expression of the horizontal flux of windblown sediment initially proposed by [START_REF] Kawamura | Study of sand movement by wind[END_REF], tested by [START_REF] White | Soil transport by winds on Mars[END_REF] and adapted by [START_REF] Marsham | The importance of the representation of deep convection for modeled dust-generating winds over West Africa during summer[END_REF]:

𝐷𝑈𝑃 = 𝑢 1 + 𝑢 𝑢 1 - 𝑢 𝑢 for 𝑢 > 𝑢
and 0 otherwise;

where 𝑢 the wind speed at a given height and 𝑢 the threshold wind velocity (TWV), i.e. the minimum wind speed required to initiate wind erosion and dust emission. In its original formulation, [START_REF] Kawamura | Study of sand movement by wind[END_REF]' formula was expressed in wind friction velocity, 𝑢 * , instead of wind velocity. As mentioned by [START_REF] Marsham | The importance of the representation of deep convection for modeled dust-generating winds over West Africa during summer[END_REF], the use of 𝑢 instead of 𝑢 * neglects the effects of atmospheric stability on dust lifting. In this paper, we used constant TWVs similar to those used for the same sites by [START_REF] Bergametti | Dust uplift potential in the central Sahel: An analysis based on 10 years of meteorological measurements at high temporal resolution[END_REF] (i.e., 7 m s -1 for Banizoumbou and 5.5 m s -1 for Cinzana). Using constant TWVs over time and space (and thus a constant roughness length) allows to isolate the role of the meteorology from that of the land surface in dust emission.

Results

General Characteristics of the Rainy Events in the Central Sahel

Figure 2 illustrates the general characteristics of the rainy events recorded in Banizoumbou and Cinzana. The mean rainfall is 581(+/-51) mm in Cinzana and 440(+/-100) mm in Banizoumbou. The average annual number of rainy events is 64 and 43 in Cinzana and Banizoumbou, respectively. The seasonality of precipitation is well-marked with most of the rainy events (69.7% and 71.8% in Cinzana and Banizoumbou, respectively) and the largest part of the rainfall (73.1% and 84,6% in Cinzana and Banizoumbou, respectively) occurring in July, August and September. However, the period corresponding to the pre-monsoon is not negligible, especially in Cinzana for which April, May and June contribute for more than 20% to both the rainfall and the annual number of rainy events. The seasonal pattern of the rainfall is only slightly different between the two stations: the rainy period is a little longer in Cinzana than in Banizoumbou, especially because the first rains occur a little sooner.

Moreover, there is a continuous decrease in the amount of precipitation per rainy event from

June to November in Cinzana and from July to October in Banizoumbou. The patterns of the monthly rainfall are consistent with those determined by [START_REF] Nicholson | On the question of the "recovery" of the rains in the West African Sahel[END_REF] for the corresponding Sahelian latitude bands and those reported by [START_REF] Frappart | Rainfall regime across the Sahel band in the Gourma region, Mali[END_REF] for various Sahelian stations.

The average time interval separating two consecutive rainy events progressively decreases from the onset of the monsoon (5 to 8 days in May) to the core of the monsoon period, where it reaches its minimum of 1 to 3 days (Table 1). When the monsoon begins its retreat, this interval increases again up to 6 to 10 days in October. The highest standard deviations observed for the average time interval separating two consecutive rainy events in May and to a less degree in June are, for the main part, due to some dry spells that can reach up to 20 consecutive days certain years. [START_REF] Mathon | Life cycle of Sahelian mesoscale convective cloud systems[END_REF].

As shown by the brightness temperatures derived from the observations performed by the Meteosat Second Generation satellite (Figure 3), the convective system that crossed Cinzana on 18 May 2006 was a squall line, i.e., a narrow band of active convective cells extending over more than 500 kilometers in the northeast/southwest direction. The temperature at some cloud tops was as low as 213 K suggesting that very deep convection has developped.

Figure 4 reports the meteorological data and PM10 concentration recorded at the surface during this convective event. About 15 minutes before the rain started, a sharp drop in temperature corresponding to the onset of the cold air outflow was recorded. It was accompanied by an increase of the Water Vapor Mixing Ratio (WVMR). This increase in WVMR is characteristics of the pre-monsoon period (May-June) because during the rest of the rainy season, WVMR decreases when the temperature drops as reported by [START_REF] Provod | A characterization of cold pools in the West African Sahel[END_REF]. Almost simultaneously with the drop in temperature, a sharp increase of the wind speed (from 1.3 m s -1 to 9.9 m s -1 ) occurred in less than 10 minutes. This was the consequence of the gust front associated with the propagation of the leading edge of the outflow. This increase in wind speed was more or less concomittant with a change in wind direction. From 07:00 until 12:00 (not shown) the wind direction was stable and clearly south/southwest (i.e., the direction of the monsoon flow). Then the wind direction oscillated between southwest and northeast to finally settle east a little before than the drop in temperature occurred. For this event, the duration of precipitation was relatively short (~15 minutes) and the rainfall was low (a total of 1.6 mm with a maximum intensity of 12 mm h -1 during the first five minutes).

An increase of more than 2 orders of magnitude of the PM10 concentration was observed as soon as the wind speed increased to reach concentration as high as 13500 µg m -3 . However, the concentration of PM10 declined quite rapidly once the rain started although high wind speed persisted. (red), rainfall (blue) and water vapor mixing ratio (green).

General Characteristics of MCSs in the Central Sahel

The following results, based on the surface observations performed for more than 1000 rainy events, allow statistical characterization of such events. When examining the data, we observed that the time at which the onset of the cold air and that at which the gust front occurs are not always coincident as also reported by Engerer et al. (2008), [START_REF] Goff | The vertical structure of thunderstorm outflows[END_REF] or [START_REF] Provod | A characterization of cold pools in the West African Sahel[END_REF] among others. For that reason, we defined the changes in temperature, wind speed and direction during the same time period surrounding a rainy event (+/-90 minutes) but not necessarily exactly at the same time inside this period.

Surface Wind Direction

A change in wind direction is almost systematically oberved during the 90 minutes preceding a rainy event (Figure 5) but most frequently during the last 15-30 minutes before the rain starts. The rotation of the main surface flow is from southwest to east shifting mostly through the south. This rotation of the wind direction results from downbursts when the cumulonimbus approaches. This leads to an inversion of the direction of the flow at the surface and in the lowest layers of the troposphere (e.g., [START_REF] Iwashita | Transition of meteorological variables while downburst occurrence by a high density ground surface observation network[END_REF]. This change in the surface wind direction is short lived, rarely persisting more than 90 minutes after the rain has started.

Figure 5. Wind direction 90 minutes before and after and at the onset of a rainy event (t), in Banizoumbou (428 rainy events; no data on wind direction were available for three rainy events) and Cinzana (589 rainy events).

Wind Speed and DUP

Wind erosion and dust emission both depend on excess wind speed, raised by some power (excess wind speed is the wind speed minus the threshold wind speed). Thus, the factors controling the temporal dynamics of wind speed from minute to season also control the temporal variability of the dust emissions.

The time separating the maximum wind speed from the onset of the rain is a crucial parameter for dust emission. Indeed, once the rain has started, the soil moisture progressively increases and finally inhibits almost totally the wind erosion making high wind speed inefficient for dust emission (e.g., [START_REF] Bergametti | How long does precipitation inhibit wind erosion in the Sahel[END_REF]. Furthermore, wet removal of dust particles by precipitation will limit their lifetime, and consequently their long range transport.

In Cinzana, in 58% of cases, the maximum wind speed was recorded in the hour preceding the onset of the rainy event. In 33% of cases, the maximum wind speed was recorded in the 15 minutes prior to the start of the rain (Figure 6a). For Banizoumbou, in 63% of cases the maximum wind speed was observed in the hour preceding the onset of rain, 51% in the 30 minutes and 37% in the 15 minutes preceding the onset of rain. These results are consistent with the earlier observations performed by [START_REF] Byers | Structure and dynamics of the thunderstorm[END_REF] who reported that, in convective systems, the first gust is the strongest or those by [START_REF] Goff | The vertical structure of thunderstorm outflows[END_REF] who indicated that gust fronts might be observed up to 45 minutes before the rain starts. In our data set, the maximum wind Dust emission does not only depend on the magnitude of the highest wind speed but also on the duration of above-threshold wind speed. The frequency of wind speed that exceeds TWV is nearly equal before and after the rain even (Figure 6b). However, when looking at their distribution during the rainy season, we observe that wind speed exceeds the TWV during the 3-hour time period surrounding the onset of rain 25% of the time during the pre-monsoon period. In contrast TWV is exceeded only 10% of the same time interval during the core of the monsoon.

We investigated the changes of the distribution of wind speed over a time period of 3-hour distributed evenly around the onset of the rainy event (i.e., -90 minutes/+90 minutes encadring the onset of the rain) during the rainy season. The wind speed distribution is computed for consecutive fractions of the annual rainfall (0-20%, 20-40%, 40-60%, etc…)

for both Banizoumbou and Cinzana. We favored this approach rather using fixed dates since the date of the monsoon onset varies from year to year (e.g., [START_REF] Sultan | The west african monsoon dynamics. Part II: the "preonset" and "onset" of the summer monsoon[END_REF]. The first 20% of the annual rainfall generally corresponds to rainy events occurring in the pre-manuscript accepted to Journal of Geophysical Research-Atmospheres monsoon period while the 80% of the annual rainfall is reached most of the time at the end of the core season, i.e., at the end of August.

Figure 7 shows that the distribution of wind speed during rainy events gradually changes throughout the rainy season. A higher frequency of the highest wind speed classes is observed during the pre-monsoon phase than during the core of the rainy season. The period corresponding to the first 20% of the rainfall represents 63.8% of the number of wind speed ≥ 12 m s -1 and 69% of the number of wind speed ≥ 10 m s -1 observed during the whole rainy season in Banizoumbou and in Cinzana, respectively. This prevalence during the premonsoon period of the highest wind speed associated with the rainy events is reinforced when considering that only 39% and 30% of rainy events are recorded before July 21 in Banizoumbou and Cinzana respectively (Figure 2).

Our results clearly show that the intensity of the gust fronts and their efficiency in terms of dust emission potential decrease from the onset to the core of the monsoon. Following [START_REF] Provod | A characterization of cold pools in the West African Sahel[END_REF], we hypothezise that during the pre-monsoon phase (and to a lesser degree during its retreat), the mid-tropospheric level is drier than during the core of the monsoon which favors the evaporation of hydrometeors and thus reinforces the intensity of the cold pools and associated gusty winds. Cinzana (2007, 2011, 2013 excluded).

Figure 8, which reports the DUP summed over 20-day period, confirms that the contribution of the pre-monsoon period to the wind erosion and dust emission potential is dominant.

Indeed, most of the DUP occurring before the 10 minutes after the commencement of rain (rain + 10 minutes) is recorded before July 19 both in Banizoumbou (71%) and Cinzana (83%) despite only 38% and 35% of rainy events occurred before this date in Banizoumbou manuscript accepted to Journal of Geophysical Research-Atmospheres and Cinzana, respectively (Figures 8c and8d). Moreover, most of the DUP (67% and 74% in Banizoumbou and Cinzana, respectively) whatever the date, is produced before or in the 10 minutes following the start of the rain, i.e., a period during which the potential of wind speed for wind erosion and dust emission is not yet fully inhibited by rain (Figures 8a and8b).

We conclude that the maximum wind speed intensity and frequency are associated with rainy events during the pre-monsoon period. This high wind speed mainly occurs during the dry phase of the convective event, i.e., before the rain starts. This clearly suggests that most of the high wind speed associated with such rainy events are the most efficient dust producers since they generally occur before the rain inhibits the erodability of the surface. Moreover, the prevalence of the highest wind speed in May/June has large consequences in terms of dust emission since this period of the year is that during which the soil surface is the less protected by the vegetative residues from the previous year (e.g., Abdourhamane Touré et al., 2011;[START_REF] Bergametti | The respective roles of wind speed and green vegetation in controlling Sahelian dust emission during the wet season[END_REF][START_REF] Pierre | Modeling vegetation and wind erosion from a millet field and from a rangeland: Two Sahelian case studies[END_REF]. Thus, it can be concluded that meteorological conditions and surface characteristics converge to favor the genesis of intense wind erosion and dust emission events during the pre-monsoon period and the beginning of the monsoon.

Cold Pools and Wind Speed

Cold pools are one of the main components of the convective systems: as cooler air accumulates near the surface, the surface pressure increases hydrostatically leading to gusty winds in response to the changing surface pressure field (e.g., [START_REF] Provod | A characterization of cold pools in the West African Sahel[END_REF][START_REF] Purdom | Some uses of high-resolution GOES imagery in the mesoscale forecasting of convection and its behavior[END_REF][START_REF] Wilson | Initiation of convective storms at radar-observed boundary-layer convergence lines[END_REF]. Thus, we investigated the links between the cold pool intensity and the surface wind speed.

We use the decrease in surface air temperature as an indicator of the intensity of a cold pool. Thus, for each rainy event we computed the associated decrease in temperature (hereafter T)

as the difference between the maximum temperature observed during the 30 minutes preceding the onset of the rain and the minimum temperature observed during the 30 minutes following the onset of the rain. Indeed, depending on the event, the maximum and minimum manuscript accepted to Journal of Geophysical Research-Atmospheres temperature can occur at different times with regards to the start of the rain [START_REF] Provod | A characterization of cold pools in the West African Sahel[END_REF]. We also computed the change in wind speed (hereafter U) as the difference between the maximum and the minimum wind speed observed in t + 60 minutes and t -60 minutes, t being the time of the onset of the rain. We selected a slightly longer time window than for temperature to account for the 10 to 15% of high wind speed occuring between 30-60 minutes before or after the rain starts (Figure 6). Lastly, we also retained the maximum wind speed averaged over a time period of 5 minutes for each rainy event and occuring inside this time interval as an other useful parameter.

The range of T measured at both stations is very large. The highest observed decreases in surface temperature are 19.4°C and 19.8°C in Banizoumbou and Cinzana, respectively.

Temperature decreases higher than 5°C are recorded for 48% (207 rainy events) and 47%

(275 rainy events) of the rainy events in Banizoumbou and Cinzana, respectively. On the other hand, a significant number of rainy events appears not to be associated with intense cold pools since 26% (112 rainy events) and 25% (147 rainy events) in Banizoumbou and

Cinzana respectively, have a T < 2°C (Figure 10). There is a strong linear relationship (<0.01) between T and U, as well as between T and the maximum wind speed (Figure 11). This is consistent with the assumption that gust fronts have the dynamic characteristics of a density current (e.g., [START_REF] Knippertz | High-resolution simulations of convective cold pools over the northwestern Sahara[END_REF][START_REF] Wakimoto | The life cycle of thunderstorm gust fronts as viewed with Doppler radar and rawinsonde data[END_REF] and should move faster when the temperature drop is larger.

Figure 11. Relationships between T, the maximum wind speed (red) and U (green) for Banizoumbou (432 rainy events) and Cinzana (586 rainy events).

The relation between U (or the maximum wind speed) with T looks like a mixing line that may reflect the spectrum of structures between the convective and stratiform extremes [START_REF] Mapes | Cloud clusters and superclusters over the oceanic warm pool[END_REF][START_REF] Houze | Stratiform precipitation in regions of convection: a meteorological paradox[END_REF]. This relation is consistent with the observations performed by [START_REF] Taylor | Frequency of extreme Sahelian storms tripled since 1982 in satellite observations[END_REF] that underlined that colder MCSs are associated with increases in propagation speed. Thus, we tried to characterize the properties of the two "endmembers" defined as: 1-the rainy events having a T ≥ 10°C (49 events in Banizoumbou and 67 in Cinzana) and 2-those having a T≤ 1°C (73 events in Banizoumbou and 90 in Cinzana).

These two groups exhibit very different characteristics (Figure 12). Both in Banizoumbou and Cinzana, the rainy events corresponding to T ≥ 10°C are associated with high wind speed and dominant wind directions from E-NE. Most of them have high rainfall, and occur during the pre-monsoon period. They are more frequent in the late afternoon and early night in Banizoumbou but occur a little earlier in Cinzana. This diurnal cycle is quite similar to that observed for the occurrence of haboobs in Khartoum (Sudan) by [START_REF] Sutton | Haboobs[END_REF] with a peak from 18:00-20:00 local time and a quiet period from 04:00-12:00 local time. Zhang et al.

(2016) and [START_REF] Vizy | Mesoscale convective systems and nocturnal rainfall over the west African Sahel: Role of the inter-tropical front[END_REF] also reported that MCS activity and rainfall frequencies peak in the evening (18:00-02:00) over most of the Sahel.

The rainy events having a T ≤ 1°C have almost opposite characteristics (low wind speed, low rainfall and occur mainly at night during the core of the monsoon). Regarding the wind directions, there is also a strong distinction between the two groups: for example, in Banizoumbou, the wind directions associated with T≥ 10°C are for 91.8% between 22°5 and 180° (and mainly between 67.5° and 157.5°) while for T≤ 1°C 69.9% of wind directions are between 180° and 360° with most of them between 180° and 247.5°. Table 2 summarizes the differences highlighted for the two groups in Cinzana and Banizoumbou.

We also observe for both stations that the percentage of cases for which at least one 5-minute wind speed exceeds the TWV is almost 100% for the events having T ≥ 10°C while it is less than 20% for those having T ≤ 1°C. The greater the decrease in temperature is, the greater the probability to have wind speed exceeding the TWV (Figure 13). [START_REF] Houze | Stratiform precipitation in regions of convection: a meteorological paradox[END_REF]2004) suggests that, in the tropics, the cumulonimbus contain an evolving pattern of newer and older precipitation, the younger part of the cumulonimbus being associated with violent updrafts while in the older part the vertical air motions are generally weaker, leading to precipitation viewed as stratiform. The very different characteristics of the two groups suggest that events with large T correspond to the convective phase of the rainy events while those having T ≤ 1°C could correspond to the final stratiform stage of the MCSs. Thus, we suspect that for the cases of rainy events exhibiting a T ≤1°C only the region of the stratiform precipitation was recorded suggesting that the active part of some MCSs does not always cross exactly the location of the station. 16:00-22:00 04:00-07:00 15:00-18:00 03:00-07:00 Rainfall (mm) >10 <2 >10 <2

Figure 13. Percentages of rainy events for which at least one 5-minute wind speed (during the period +/-90 minutes surrounding the onset of the rain event) exceeds the TWV depending on the T class.

High Wind Speed Events of Rainy Season Occurring Without Rainfall

We observed that strong wind speed not linked to NLLJ occurs during the rainy season despite the absence of recorded precipitation at the stations. However, accounting for the local character of our stations and for the limited size of the MCSs, such high wind speed events could nevertheless be related to the passing of MCSs in the area surrounding the stations. To check if precipitation has occurred in the Banizoumbou area during the selected "dry" high wind speed events, we used rainfall data collected in 2006 and 2007 by the AMMA-Catch/LOP rain gauge network. In an area called the "Niamey square degree" (Figure S2), thirty rain gauge stations of this network recorded the rainfall with a 5-minute time step inside a circle of radius ~ 80 km around Banizoumbou (e.g., [START_REF] Lebel | AMMA-CATCH studies in the Sahelian region of West-Africa: An overview[END_REF].

The method we used consists in selecting the episodes having a wind speed > 7 m s -1 and T  1° C, U > 1 m s -1 . It should be noted that the method to determine T and U was not exactly the same that the one we used previously (i.e., the start of the rain as reference time): for these "dry" episodes, T and U are determined using the time at which the maximum wind speed is recorded as a reference time. There were a total of 70 episodes in Banizoumbou in 2006 and 2007 corresponding to the above criteria, a number slightly lower than that of the rainy episodes during the same period (86).

Using this method discarded the high wind speed linked to the breakdown of the NLLJ, since only a few selected events (10%) occurred during the time interval 07:00-13:00 during which high wind speed linked to NLLJ occur (see Table S2).

Among the 70 "dry" episodes, 45 (i.e., 64%) are associated with rainy events recorded in at least one station of the network. Nineteen of the 24 (79%) dry episodes exhibiting the highest wind speed (> 10 m s -1 ) are associated with rainfall in the Banizoumbou area (Table S2). These 70 "dry" episodes have very similar characteristics to the rainy events with a strong link between wind speed and T (see Figure S3), suggesting that they are for most of them due to the passing of MCS in the Banizoumbou area. It should also be noted that among the 10% (7) of selected events occurring between the 07:00-13:00 time period, only one was not associated with rain in the vicinity of Banizoumbou. This confirms that even for these morning events these high wind speed events were not directly linked to the NLLJ but rather to MCSs.

These results clearly suggest that almost all high wind speed events measured at Banizoumbou during the rainy season were the consequence of the passing of convective events even if precipitation was not recorded at the station.

Wind Speed and PM10 During Rainy Events

The PM10 concentration is an integrative parameter that results from the interaction of wind speed, surface properties (such as roughness, soil type, vegetation cover, soil moisture, etc.) and deposition processes such as wet deposition linked to precipitation. In the Sahelian rainy season, some of the surface parameters evolve with times. Indeed, the soil moisture changes rapidly when it rains, reinforcing the cohesive forces linking the soil grains together and thus increasing the TWV and reducing the frequency and intensity of dust emission (e.g., [START_REF] Bergametti | How long does precipitation inhibit wind erosion in the Sahel[END_REF][START_REF] Pierre | Impact of vegetation and soil moisture seasonal dynamics on dust emissions over the Sahel[END_REF]. Rain also scavenges suspended particles as shown on Figure 4. Thus, to rule out the effect of the rain scavenging, we eliminated the episodes for which the highest wind speed occurred after the beginning of the rain events and those that occurred less than 24 hours after the previous rain event.

Precipitation also allows the growth of seasonal vegetation that increases both the surface cover and the roughness, decreasing the ability of the wind to cause wind erosion and dust emission (e.g., [START_REF] Bergametti | The respective roles of wind speed and green vegetation in controlling Sahelian dust emission during the wet season[END_REF].

Figures 14a and14e show that maximum PM10 concentration and maximum wind speed are correlated in both Banizoumbou and Cinzana. This clearly demonstrates that the measured dust concentration results from local emissions due to the high wind speed associated with MCS. However, the dust concentration is higher during the pre-monsoon period by almost one order of magnitude, consistently with the higher frequency of high wind speed at that time compared to the core of the monsoon season (Figure 6). Similar pattern is observed between PM10 and T (Figures 14c and14d). These figures

show that for similar wind speed, the PM10 concentration is higher in May and June and at the beginning of July compared to end of July, August, September and October. [START_REF] Bergametti | The respective roles of wind speed and green vegetation in controlling Sahelian dust emission during the wet season[END_REF], using NDVI to monitor the growth of the vegetation, suggested that the efficiency of wind for dust emission is strongly affected by the growth of the vegetation which reduces PM10 concentration up to 80% in the core and end of the rainy season. The relation between Umax and dust concentration (Figures 14b and14f) shows an increase of TWV due to vegetation growth. Indeed, the TWV is close to 5-6 m s -1 in both Banizoumbou and Cinzana from May to early July while it exceeds 8-10 m s -1 in August, September and October. Because of the strong link between wind speed and T (Figure 11), we observe in Banizoumbou (Figure 14d) that a minimum  able to initiate wind erosion can be defined (around 5°C) in May, June and early July while even events having T as high 8°C are not associated with dust emission during the August-October timeframe. However, such a pattern is not observed in Cinzana (Figure 14h) for the CMIP5 GCM ensemble simulations. Moreover, the models predict that this meridional gradient will strengthen throughout the 21 st century. This predicted increase in the meridional gradient and the resulting intensification of the MCSs support the idea that dust emissions occurring during the rainy season could be more intense in the future. Unfortunately, most models are unable to resolve properly MCS and therefore fail to simulate these intense Sahelian dust events, and underestimate their impacts on the Earth's climate systems. Banizoumbou (428 rainy events; no data on wind direction were available for three rainy events) and Cinzana (589 rainy events).

Figure 1 .

 1 Figure 1. The diurnal cycle of (a, b) wind speed, (c, d) temperature, (e, f) water vapor mixing ratio at Banizoumbou (Niger) in (a, c, e) January (dry season) and (b, d, f) July (rainy season). Data are averaged over the period 2006-2015. Bars indicate the standard deviation over the ten years.

Figure 2 .

 2 Figure 2. (a, b) Average monthly number of rainy events, (c, d) average monthly rainfall and (e, f) average monthly rainfall per rainy event for (left) Banizoumbou and (right) Cinzana. Data recorded over the period 2006-2015 from which are excluded the years 2008, 2012 and 2014 for Banizoumbou and the years 2007, 2011 and 2013 for Cinzana (see text for explanation). The vertical bars correspond to the interannual standard deviations.

Figure 3 .Figure 4 .

 34 Figure 3. 3-km MSG SEVIRI 10.8 μm channel brightness temperature imagery from 18 May 2006 17:00 UTC over the region surrounding Cinzana (Mali). The convective system is a squall line extending over about 500 kilometers in the northeast/southwest direction. The temperature of some cloud tops was close to -213 K suggesting regions of very deep convection.

  Figure 6. (a) Time of occurrence of the maximum wind speed and (b) of wind speed greater than the TWV in the period ranging from -90 minutes to +90 minutes from the onset of a rainy event for Banizoumbou (black), 431 rainy events and Cinzana (red), 589 rainy events.

Figure 7 .

 7 Figure 7. Distribution of surface wind speed for precipitation classes of 20% of the accumulated rainfall since the first rain of the season. The wind speed distribution is calculated from the average of the wind speed distribution during each rainy event of each precipitation class taking into account all the wind speed values preceding the onset of a rain by 90 minutes and following the onset of the same rain by 90 minutes. Only years with no notable data gaps during the period April-October are considered. There are 7 years for each series. 302 rainy events for Banizoumbou (2008, 2012 and 2014 excluded) and 449 for

Figure 8 .

 8 Figure 8. 20 days cumulated DUP computed as the sum of the DUP during the 90 minutes preceding the rainy event and of the DUP during the first 10 minutes of a rainy event (red):

Figure 9

 9 Figure 9 provides an example of surface temperature change with the passing of a squall line.When comparing with the previous day (17/05/2006) during which no rainy event occurred, the temperature on 18 May in Cinzana was identical to that on 17 May from 12:00 to about 16:30. However, on 18 May, when the rain started, the temperature dropped dramatically.About 30 minutes after the onset of the rain, the temperature was 11°C lower than the previous day at the same hour and the temperature anomaly was still 3.7°C two hours after the rain stopped.

Figure 9 .

 9 Figure 9. Decrease in temperature due to a squall line that crossed Cinzana on 18/05/2006 compared to the previous day (17/05/2006) during which no precipitation occurred; (red) temperature on 18 May 2006 ; (green) temperature on 17 May 2006; (blue) rainfall on 18 May 2006.

Figure 10 .

 10 Figure 10. Frequency distribution of the decrease in surface temperature associated with the rainy events observed in Banizombou and Cinzana.

Figure 12 .

 12 Figure 12. Frequency of maximum wind speed, wind direction, rainfall, hour and month of occurrence for the rainy events corresponding to (dark grey) T ≤ 1°C and (red) T ≥ 10°C for (left) Banizoumbou and (right) Cinzana. Wind direction and hour are those observed at the onset of the rainy event.

Figure 14 .

 14 Figure 14. Links between the maximum 5-minute PM10 concentration and Umax and T in (left) semi-log and (right) linear ; for (a-d) Banizoumbou and (e-h) Cinzana for rainy events not preceded by another rainy event in the previous 24 hours and for which Umax is observed before the onset of the rain.5 Dust concentration in dry and wet seasonThe contribution of convective events to dust emissions that occur in the wet season compared to the contribution of the NLLJ in the dry season can be evaluated by looking at

Figure 15 .

 15 Figure 15. (a) Number of 5-minute dust concentration higher than different thresholds for the dry and rainy seasons in Banizoumbou and Cinzana and (b) relative contributions of the dry and rainy seasons to each class of 5-minute dust concentration.

Figure 1 .

 1 Figure 1. The diurnal cycle of (a, b) wind speed, (c, d) temperature, (e, f) water vapor mixing ratio at Banizoumbou (Niger) in (a, c, e) January and (b, d, f) July. Data are averaged over the period 2006-2015. Bars indicate the standard deviation over the ten years.

Figure 2 .

 2 Figure 2. (a, b) Average monthly number of rainy events, (c, d) average monthly rainfall and (e, f) average monthly rainfall per rainy event for (left) Banizoumbou and (right) Cinzana. Averages of data recorded over the period 2006-2015 from which are excluded the years 2008, 2012 and 2014 for Banizoumbou and years 2007, 2011 and 2013 for Cinzana (see text for explanation). The vertical bars correspond to the interannual standard deviations.

Figure 3 .

 3 Figure 3. 3-km MSG SEVIRI 10.8 μm channel brightness temperature imagery from 18 May 2006 17:00 UTC over the region surrounding Cinzana (Mali). The convective system is a squall line extending over about 500 kilometers in the northeast/southwest direction. The temperature of some cloud tops was close to -213 K suggesting regions of very deep convection.

Figure 4 .

 4 Figure 4. The 18 May 2006 convective event as recorded at the surface in Cinzana (Mali). (a) wind direction (purple), PM10 concentration (orange) and wind speed (black); (b) temperature (red), rainfall (blue) and water vapor mixing ratio (green).

Figure 5 .

 5 Figure 5. Wind direction 90 minutes before and after and at the onset of a rainy event (t), in

Figure 6 .

 6 Figure 6. (a) Time of occurrence of the maximum wind speed and (b) of wind speed greaterthan the TWV in the period ranging from -90 minutes to +90 minutes from the onset of a rainy event for Banizoumbou (black), 431 rainy events and Cinzana (red), 589 rainy events.

Figure 7 .

 7 Figure 7. Distribution of surface wind speed for precipitation classes of 20% of the accumulated rainfall since the first rain of the season. The wind speed distribution is calculated from the average of the wind speed distribution during each rainy event of each precipitation class taking into account all the wind speed values preceding the onset of a rain by 90 minutes and following the onset of the same rain by 90 minutes. Only years with no notable data gaps during the period April-October are considered. There are 7 years for each series. 302 rainy events for Banizoumbou (2008, 2012 and 2014 excluded) and 449 forCinzana(2007, 2011, 2013 excluded).

Figure 8 .

 8 Figure 8. 20 days cumulated DUP computed as the sum of the DUP during the 90 minutes preceding the rainy event and of the DUP during the first 10 minutes of a rainy event (red): (a, b) mean DUP during all the whole rainy event (i.e., +/-90 minutes from the start of the rain; green); (c, d) mean number of rainy event (black). Means are computed over 2006-2015 excepted years 2008, 2012 and 2014 for Banizoumbou and years 2007, 2011 and 2013 for Cinzana.

Figure 9 .

 9 Figure 9. Decrease in temperature due to a squall line that crossed Cinzana on 18/05/2006 compared to the previous day (17/05/2006) during which no precipitation occurred; (red) temperature on 18 May 2006 ; (green) temperature on 17 May 2006; (blue) rainfall on 18 May 2006.

Figure 10 .

 10 Figure 10. Frequency distribution of the decrease in surface temperature associated with the rainy events observed in Banizombou and Cinzana.

Figure 11 .

 11 Figure 11. Relationships between T, the maximum wind speed (red) and U (green) for Banizoumbou (432 rainy events) and Cinzana (586 rainy events).

Figure 12 .

 12 Figure 12. Frequency of maximum wind speed, wind direction, rainfall, hour and month of occurrence for the rainy events corresponding to (dark grey) T ≤ 1°C and (red) T ≥ 10°C for (left) Banizoumbou and (right) Cinzana. Wind direction and hour are those observed at the onset of the rainy event.

Figure 13 .

 13 Figure13. Percentages of rainy events for which at least one 5-minute wind speed (during the period +/-90 minutes surrounding the onset of the rain event) exceeds the TWV depending on the T class.

Figure 14 .

 14 Figure 14. Links between the maximum 5-minute PM10 concentration and Umax and T in (left) semi-log and (right) linear; for (a-d) Banizoumbou and (e-h) Cinzana for rainy events.not preceded by another rainy event in the previous 24 hours and for which Umax is observed before the onset of the rain.

Figure 15 .

 15 Figure 15. (a) Number of 5-minute dust concentration higher than different thresholds for the dry and rainy seasons in Banizoumbou and Cinzana and (b) relative contributions of the dry and rainy seasons to each class of 5-minute dust concentration.

Table 1

 1 Average Time Interval Between Two Rainy Events in Banizoumbou and Cinzana. Period

	2006-2015 (Only Periods Without Sampling Gaps Between Two Rainy Events are
	Considered)

3.2.1 A Typical Squall Line: the 18/05/2006 Event in Cinzana

Infrared observations from satellites allow detection of convective clouds assuming that low brightness temperatures are related to convection. The 253 K threshold is generally selected as the highest cloud temperature associated with convection while the 213 K threshold is generally associated with very deep convection (e.g.,

[START_REF] Mapes | Cloud clusters and superclusters over the oceanic warm pool[END_REF] Mathon &

Table 2

 2 Mean Characteristics of Rainy Events Exhibiting a T ≥ 10°C and ≤ 1°C in Banizoumbou

	and Cinzana
		Banizoumbou	Cinzana
		T ≥ 10°C	T ≤ 1°C	T ≥ 10°C	T ≤ 1°C
	Max Wind speed (m s -1 )	14-15	3-4	6-7	2-3

Table Captions Table 1

 Captions1 Average Time Interval Between Two Rainy Events in Banizoumbou and Cinzana.

	Period 2006-2015 (Only Periods Without Sampling Gaps Between Two Rainy Events are
	Considered)

Table 2

 2 Mean Characteristics of Rainy Events Exhibiting a T ≥ 10°C and ≤ 1°C in Banizoumbou and Cinzana

Acknowledgments

Measurements in Banizoumbou and Cinzana are performed in the framework of the French National Observatory Services INDAAF that is supported since 2010 by the Observatoire des Sciences de l'Univers EFLUVE, the INSU/CNRS, and the IRD. The treatment of the data was performed in the framework of the research programs CAVIARS supported by the French National Agency for Research (ANR-12-SENV-0007-01) and DustClim supported by the European Commission under the ERA4CS action-Joint Call on Researching and Advancing Climate Services Development, Grant Agreement no. 690462 -ERA4CS -H2020-SC5-2014-2015/H2020-SC5-2015-one-stage. We also thanks AMMA-Catch for providing the rainfall data of their network. The AMMA-CATCH Environmental Research Observatory (http://www.amma-catch.org) was set up thanks to incentive funding from the French Ministry of Research. The continuity and sustainability of the measures are based on the funding granted without interruption by the IRD since 1990, and by the CNRS-INSU since 2005. The authors would like to thank the Institut d'Economie Rurale (IER) in Mali for hosting one of our stations and in particular Dr. Zoumana Kouyaté, Delegate of the Station de Recherche Agronomique de Cinzana (Mali) for the help in logistics and local management.

This work has also strongly benefited from the administrative support of the representations of IRD in Niger and Mali, thanks to all of them. The authors would like to acknowledge G. S.

Okin and two anonymous reviewers for their comments that helped to improve the quality of this paper.

Data Availability Statement

manuscript accepted to Journal of Geophysical Research-Atmospheres

The wind speed and direction, rainfall and PM10 data are distributed at an hourly time resolution through the INDAAF website (https://indaaf.obs-mip.fr/database/). The data used in this manuscript are available for download for research and educational purposes at the following web link (http://www.lisa.u-pec.fr/fr/donnees) maintained by Laboratoire Interuniversitaire des Systèmes Atmosphériques.


Jens Gustedt

Improve type generic programming ISO/IEC JTC 1/SC 22/WG14 N2890 WG21 P2304

How to create an interface that is simple and safe to use? With a lambda:

12 * h); }; // Can be used in function call or for a function pointer double ( * fp)(double, double, double ( * )(double)) = λ5; Jens Gustedt (INRIA) Improve type generic programming

// freeze ε to δ and have the function parameter dependent

auto const λ5ε = [δ = ε](double x, typeof(x) func(typeof(x))) { double h = δ * x; return (-func(x+2 * h)+8 * func(x+h)-8 * func(x-h)+func(x-2 * h))/(12 * h); };
or so: // also freeze a function, and have the parameter dependent

auto const λ5ε_func = [δ = ε, func = f](typeof(func(0)) x) { auto h = ε * x; return (-func(x+2 * h)+8 * func(x+h)-8 * func(x-h)+func(x-2 * h))/(

  point tangent evaluation for approximation of a derivative:(-func(x+2 * h) + 8 * func(x+h) -8 * func(x-h) + func(x-2 * h))/(12 * h)

January 30, 2022


extend the standard valid code remains valid new feature integrates syntaxtically and semantically fix as much requirements as possible through constraints specific syntax explicit constraints avoid new undefined behavior only, if property is not (or hardly) detectable at translation time or we leave design space to implementations don't mess with ABI no changes no extensions Jens Gustedt (INRIA) Type inference for variables and functions February 1,

typeof(cos(x)) y = cos(x); // error prone: paste and copy With auto this becomes much simpler:

		Variables
	Example: simple function return Example: local variables for macros Semantic
	What is the type of an integer literal? different qualification and pointer derivation	(int, long or long long)
	Policy How to catch the return of a <tgmath.h> function? [[l]l]div(38484848448, 448484844); static auto const string1 = "α"; // valid
	#define dataCondStoreTG(P, E, D) static auto * const string2 = "α"; // valid \ C++ and widely used gcc extensions
	Variables So, which function to use? do { static auto const * string3 = "α"; // invalid \ (div, ldiv, lldiv) auto * _pr_p = (P); \ inference C++ gcc et al C extension current C23
	How do we do it? Functions Use a generic expresssion #define div(X, Y) auto _pr_expected = (E); auto _pr_desired = (D); bool _pr_c; from type decltype as-if auto were replaced by a typeof from lvalue decltype \ _Generix((X)+(Y), \ int: div, do { mtx_lock(&_pr_p->mtx); static typeof((0, "α")) from type typeof const string1 = "α"; \ \ \ \ \ \ long: ldiv, _pr_c = (_pr_p->data == _pr_expected); \ static typeof((0, "α")[0]) * const string2 = "α"; from lvalue typeof \ long long: lldiv) \ if (_pr_c) _pr_p->data = _pr_desired; \ mtx_unlock(&_pr_p->mtx); static typeof(????) const * string3 = "α"; from lvalue \ How do we do it? Existing extensions auto y = cos(x); // type safe and copy safe typeof typeof remove_quals Even works if we don't use <tgmath.h> ((X), (Y)) Which return type? (div_t, ldiv_t, lldiv_t) } while(!_pr_c); \ initializer expression is evaluated exactly once } while (false) from value auto __auto_type
	static char *	const string1 = "α"; // same qual type
	static char *	const string2 = "α"; // same qual type
	static XXX	const * string3 = "α"; // different type
	Jens Gustedt (INRIA)	Type inference for variables and functions	February 1, 2022	4 / 18

#include <tgmath.h> guessType y = cos(x); // error prone: silent conversion With the new typeof extension this can already be done: Jens Gustedt (INRIA) Type inference for variables and functions February 1, 2022 5 / 18 Example: implementation dependent type auto res = div(38484848448, 448484844); auto a = b * res.quot + res.rem;

February 1, 2022

 -----------------sum now visible --------------------*


even if the capture is itself a lambda value // also freeze a function, and have the parameter dependent

auto const λ5ε_func = [δ = ε, func = f](typeof(func(0)) x) { auto h = ε * x; return (-func(x+2 * h)+8 * func(x+h)-8 * func(x-h)+func(x-2 * h))/(12 * h); };
this works if f is a function, function pointer or lambda

  function literal appears close to its use return type is inferred as the same as strcmp function literal is converted to function pointer int ( * )(void const * a, void const * b) that function pointer is passed into qsort Jens Gustedt (INRIA) Basic lambdas for C February 1, 2022 5 / 16 auto strSort = [](size_t n, char const * stringArray[n]) { qsort(stringArray, n, sizeof(stringArray[0]), [](void const * a, void const * b){ typeof(stringArray[0]) const * A = a; typeof(stringArray[0]) const * B = b; return strcmp( * A, * B); }); }; a lambda expression that sorts string pointers the outer lambda has no return => return type is void use of sizeof and typeof makes it type safe (no evaluation!) no function with void * parameters is exported may be used directly in a function call may be converted to a function pointer void ( * )(size_t n, char const * stringArray[n]) Example: value closure value captures are evaluated when the lambda expression is met // freeze ε to δ and have the function parameter dependent auto const λ5ε = [δ = ε](double x, typeof(x) func(typeof(x))) { double h = δ * x; return (-func(x+2 * h)+8 * func(x+h)-8 * func(x-h)+func(x-2 * h))/(12 * h); };

Table of Contents

 of

	Example: simple function literal
	char const * stringArray[NUMEL];
	... Policy qsort(stringArray, NUMEL, sizeof(stringArray[0]),
	[](void const * a, void const * b){
	char const * const * A = a;
	Motivation char const * const * B = b;
	return strcmp( * A, * B);
	});
	Design choices
	Syntax
	Existing extensions
	Jens Gustedt (INRIA)	Basic lambdas for C	February 1, 2022	4 / 16

Table of Contents

 of

		Design choices
	Design choice, expression
	Policy Function definitions versus expressions Interoperability function definition all is fixed at translation time naming is a burden Motivation function use is distant from definition no linker dependency
	nested functions may access all outer variables (no control mechanism) Design choices Not available expression recursion only if function literal via function pointer anonymous Syntax use where defined stdarg no variable argument list allowed
	lambda expression: VM types would be evaluated
	Existing extensions dedicated syntax to control access to outer variables
	Jens Gustedt (INRIA) Jens Gustedt (INRIA)	Basic lambdas for C Basic lambdas for C	February 1, 2022 February 1, 2022	8 / 16 9 / 16

Jens Gustedt (INRIA)

Basic lambdas for C February 1, 2022

February 1, 2022

Basic lambdas for C February 1, 2022


Table of Contents

 of

	Closure Syntax
	Implicit captures and explicit captures
	Current state default identifier captures where ",. . . . . . . . . " is empty or a mixed list of value or shadow captures. Ambiguities Explicit shadow captures introduce new syntax ambiguities with Current state	[&,. . . . . . . . .]
	default shadow captures designated initializers (bounded lookahead)	[=,. . . . . . . . .]
	Proposed options where ",. . . . . . . . . " is empty or a mixed list of value or identifier captures. attributes (unbounded lookahead) Proposed options
	Explicit shadow captures Disambiguation
	Motivation frozen value of an automatic variable Force consecutive [ [ tokens to be the start of an attribute Motivation	[id0,. . . . . . . . .]
	where ",. . . . . . . . . " is empty or a mixed list of all three types of explicit captures.

February 2, 2022