Atmospheric Boundary Layer in the Atlantic: the desert dust impact

Atmospheric Boundary Layer in the Atlantic: the desert dust impact Ioanna Tsikoudi1,2, Eleni Marinou1, Maria Tombrou2, Eleni Giannakaki2, Emmanouil Proestakis1, Konstantinos Rizos1, Ville Vakkari3,4, and Vassilis Amiridis1 1National Observatory of Athens, IAASARS, Greece 2Department of Physics, National and Kapodistrian University of Athens, Greece 3Finnish Meteorological Institute, Finland 4Atmospheric Chemistry Research Group, Chemical Resource Beneficiation, North-West University, Potchefstroom, South Africa Correspondence: Ioanna Tsikoudi ([email protected]) Abstract. We investigate the dynamics of the atmospheric Boundary Layer (BL) over the Atlantic Ocean, with a focus on the region surrounding Cabo Verde during the Joint Aeolus Tropical Atlantic Campaign (JATAC) and the ASKOS experiment, using a combination of ground-based PollyXT and Doppler lidars, satellite lidar data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), radiosondes, and the model outputs of the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The comparison of CALIPSO lidar results with5 ECMWF/IFS reanalysis for 2012-2022, revealed strong correlations for BL top over open ocean regions but weaker relation over dust-affected areas closer to the African continent. In these regions, space lidar indicated lower BL tops during daytime than those estimated by ECMWF/IFS. Observations in Cabo Verde highlight distinctive Marine Atmospheric Boundary Layer (MABL) characteristics, such as limited diurnal evolution, but also show the potential for BL heights to reach up to 1 km, driven by factors like strong winds that increase mechanical turbulence. Additionally, the challenges in estimating the BL height using10 lidar-derived aerosol mixing height versus profiling of meteorological parameters acquired from radiosondes are illustrated, examining cases with strong and weaker inversions that affect the vertical mixing and the penetration of dust particles within the BL. The findings underline the need for further improvements in the ECMWF/IFS reanalysis model towards capturing the complex interactions between marine and dust-laden air masses over the Atlantic, which are essential for constraining the dynamic processes in BL and aerosol-cloud interactions.15 1 Introduction The atmospheric Boundary Layer (BL) is characterized by complex interactions between surface-driven forces and meteorological conditions, which determine its height, structure, and the degree of turbulent mixing within (Stull, 1988). BL dynamics vary considerably across different environments, presenting challenges for weather modeling and prediction, especially in transitional zones like those between deserts and oceans (Seibert et al., 2000; Li et al., 2017).20 Monitoring the BL top reliably is a challenge, particularly in heterogeneous environments where traditional observation methods may fall short. Lidar systems have proven valuable for continuous profiling of aerosol and atmospheric structures, as their high vertical resolution enables detailed monitoring of BL height (Wiegner et al., 2006; Baars et al., 2008). Yet, automatic 1 https://doi.org/10.5194/egusphere-2025-1105 Preprint. Discussion started: 14 March 2025 c Author(s) 2025. CC BY 4.0 License. identification of the BL top from lidar data is challenging in complex areas, because BL structures can be influenced by surface type, time of day, and atmospheric stability (Tsikoudi et al., 2022). Up to now, lidar-based BL retrievals showed very25 good performance on relatively predictable areas with known BL patterns, such as open land surfaces or stable atmospheric conditions (Tsaknakis et al., 2011; Seidel et al., 2012). Expanding lidar BL retrievals to more complex environments, is an ongoing challenge especially when it comes to oceanic and coastal BLs where ground-based observation sites are limited. Over the open Atlantic, the Marine Atmospheric Boundary Layer (MABL) is typically shallow and influenced by the relatively constant sea surface temperature, while boundary layers in coastal and island regions experience terrestrial-marine30 interactions that increase their variability (Garratt, 1994; Wood, 2012). Few studies over years have addressed the detection and analysis of MABL using lidar data, largely due to practical and observational challenges over the ocean (e.g. Atlas et al. 1986; Flamant et al. 1997; Pena et al. 2015). Given these constraints, satellite observations, such as those provided by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, have become essential for studying lower troposphere characteristics over remote regions, offering a means to improve understanding of these complex systems.35 The general circulation over the tropical Atlantic is dominated by the Inter-Tropical Convergence Zone (ITCZ) and affected by the presence of the Saharan Air Layer (SAL). The SAL is a typically warm and dry air layer that frequently occurs at large scales in the tropical North Atlantic Ocean and can reside up to 5 km in altitude, often accompanied by dust aerosols (Carlson and Prospero, 1972; Dunion and Velden, 2004; Wu, 2007). The ITCZ, migrates seasonally between the northern and southern tropics, influencing rainfall and convective activity, creating conditions conducive to both the formation of clouds40 and the aerosol convection over the Atlantic (Zhou et al., 2020). In tandem, the SAL, comprising of hot, dry air laden with desert dust from the Sahara, moves westward across the Atlantic Ocean, especially in summer, driven by the prevailing trade winds (Prospero and Mayol-Bracero, 2013) and has consequences on the surface radiation budget (Evan et al., 2009; Yu et al., 2006). These circulation patterns are key in transporting dust from Africa to the Atlantic, affecting the radiative balance and potentially impacting cloud formation, atmospheric stability, and therefore BL behavior in the region (Sun and Zhao, 2020).45 A typical characteristic of the eastern sides of the Atlantic, is that the air subsiding into the subtropical north-east Atlantic is warmer and drier than the air that has been in contact with the relatively cold ocean surface influenced by upwelling, and a strong inversion forms at the interface of the two air masses (Hanson, 1991). As such, transported desert dust from Africa introduce another layer of complexity in tropospheric dynamics and clouds activity by altering radiation budget, atmospheric stability, and moisture distribution (e.g. Marinou et al. 2021; Ansmann et al. 2017; Marsham et al. 2008). This dual effect50 of dust—scattering and absorbing solar radiation while in the same time serving as cloud condensation and ice nucleation nuclei (CCN/IN)—leads to competing influences on the BL (e.g radiative cooling can suppress turbulent mixing, yet CCN activation can lead to increased cloud cover and associated feedback on surface radiation). These processes have been observed to influence the vertical structure and stability of the BL, but their overall impact on BL dynamics is still not fully understood. Accurately representing BL-aerosol interactions in climate and chemical transport models is crucial because these pro-55 cesses affect surface conditions and large-scale atmospheric circulation (Menut et al., 2009; Pérez et al., 2006; Tombrou et al., 2015, 2007). Gaps in observational data over complex environments, such as the dust-laden, desert-ocean transition zone in the Atlantic, limit the model’s ability to accurately capture BL evolution and aerosol influences (Rémy et al., 2019, 2021; 2 https://doi.org/10.5194/egusphere-2025-1105 Preprint. Discussion started: 14 March 2025 c Author(s) 2025. CC BY 4.0 License. Kallos et al., 2007). The need for observational data to validate and refine these models is high, especially given the impacts on cloud formation, energy distribution, and surface-air interactions. Addressing these gaps through both ground-based exper-60 imental campaigns such as Joint Aeolus Tropical Atlantic Campaign (JATAC) and satellite sensors such as space Lidars can significantly enhance understanding and modeling of BL processes in regions of critical climatic importance. In addition to investigating BL-aerosol interactions, this study aims to improve BL top detection methods in diverse and complex environments. By addressing challenges inherent to automated BL detection, particularly in areas affected by aerosols and variable atmospheric conditions, this work contributes to the development of more robust methods for BL identification.65 The structure of this paper is as follows: Section 2 provides an overview of the datasets and methods used, including ground-based lidar, space lidar, radiosonde data, and model outputs. Section 3 examines the BL characteristics across different environments, beginning with the Atlantic Ocean (Area 1) and the ocean-desert transition zone (Area 2), before focusing on Cabo Verde, where dust interactions with the BL are investigated. Finally, Section 4 presents the main conclusions of this study. 2 Framework for Data Sources and Analysis70 This study utilizes data from the ASKOS Campaign (Marinou et al., 2023), which is the ground-based component of the JATAC organised by the European Space Agency (ESA). ASKOS took place at the Ocean Science Centre Mindelo (OSCM), at the island of São Vicente, Cabo Verde, during 2021-2022. 2.1 Datasets For this analysis, we use the comprehensive ASKOS dataset that, among others, includes active remote sensing observations75 and radiosonde datasets that are crucial for understanding atmospheric dynamics in the region. More specifically, radiosonde profiles, ground-based PollyXT lidar and Wind Doppler lidar measurements as well the LIVAS (LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies) Climate Data Record (CDR) (Amiridis et al., 2015) using CALIPSO are examined. Additionally, the measurements-derived BL is compared to the ERA5 Re-Analysis dataset from Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF), at 0.25° × 0.25° resolution.80 2.1.1 Groundbased Lidar The ground-based PollyXT Raman Lidar (Engelmann et al., 2016), consists of a compact, pulsed Nd:YAG laser, emitting at 355, 532, and 1064 nm at a 20 Hz repetition rate, with the laser beam pointed into the atmosphere at an off-zenith angle of 5°. The backscattered signal is collected by a Newtonian telescope with a 0.9m focal length, acquiring profiles with a vertical resolution of 7.5 m, and a temporal resolution of 30 s. The system was operated by TROPOS during the ASKOS Campaign,85 providing data coverage for the entire campaign. Figure 1 presents PollyXT measurements, conducted during the ASKOS Campaign. Specifically, the attenuated backscatter coefficient of the 1064 nm channel (Att BSC, Fig. 1-left) is examined to derive the BL top, and the volume linear depolarization ratio (VLDR, Fig. 1-right) is investigated to infer the aerosol shape. 3 https://doi.org/10.5194/egusphere-2025-1105 Preprint. Discussion started: 14 March 2025 c Author(s) 2025. CC BY 4.0 License. On that day, the closest CALIPSO trajectory point was at 4:07 UTC, located approximately 240 km east of the Mindelo site. The white points in the attenuated backscatter indicate the presence of clouds and were not included in the BL analysis.90 Figure 1. Ground-based PollyXT Lidar at Mindelo (16.87°N, 24.99°W), Cabo Verde, on the 10th of September, 2021, depicting the attenuated backscatter coefficient (Att Bsc) at 1064 nm (left), and volume linear depolarization ratio (VLDR) at 532 nm (right). Additionally, complementary data from a Halo Photonics Stream Line scanning Doppler lidar were used to examine the horizontal wind speed and direction, as well as the vertical wind component. This lidar is a 1.5 µm pulsed Doppler lidar with a heterodyne detector (Pearson et al., 2009). The Doppler lidar has a range resolution of 48 m and measures the attenuated aerosol backscatter and Doppler velocity along the beam direction. Horizontal wind profiles were retrieved from a velocity azimuth display (VAD) scan with 12 azimuthal angles at 60° elevation angle every 15 minutes. Otherwise, the Doppler lidar95 operated in vertical stare mode, retrieving vertical wind profile time series. The Doppler lidar data was post-processed according to Vakkari et al. (2019) and a signal-to-noise ratio (SNR) threshold of 0.005 was applied to the vertically-pointing measurements. Turbulent kinetic energy (TKE) dissipation rate profiles were calculated from the vertically-pointing data using the method by O’Connor et al. (2010). Instrumental noise was calculated from signal-to-noise ratio according to Pearson et al. (2009) and subtracted from the vertical wind variance time series before100 the TKE dissipation rate calculation. To estimate mixed layer height (MLH) from the TKE dissipation rate profiles a threshold of 10−4m2s−3was applied, similar to previous studies (e.g. Vakkari et al., 2015). 2.1.2 Space lidar: CALIPSO–CALIOP Towards investigating the dynamics of the BL over the Atlantic Ocean, observations of the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP; Hunt et al. 2009), the primary instrument on board the joint National Aeronautics and Space105 4 https://doi.org/10.5194/egusphere-2025-1105 Preprint. Discussion started: 14 March 2025 c Author(s) 2025. CC BY 4.0 License. Administration (NASA) and Centre National D’Études Spatiales (CNES) Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission (Winker et al., 2010), are extensively used. More specifically, CALIOP provided as integrated component of the Afternoon-Train constellation of polar-orbit sun-synchronous satellites (Stephens et al., 2018), profiles of aerosols and clouds along the CALIPSO orbit-path between June 2006 and August 2023. In the framework of the study, CALIOP Level 2 (L2) Version 4 (V4) aerosol profiles (APro) of backscatter coefficient at 532 nm and particulate110 depolarization ratio at 532 nm are used, provided at uniform 5 km horizontal resolution and 60 m vertical resolution for the altitudinal range between -0.5 and 20.2 km above mean sea level (a.m.s.l.) are used, for the domain encompassing the broader North Atlantic Ocean - Western Saharan Desert and for September 2021. Prior implementation of CALIOP optical products, rigorous quality assurance procedures are applied (Marinou et al., 2017; Proestakis et al., 2024), following also the quality controls adopted towards the generalization of the official CALIPSO Level 3 (L3) products (Winker et al., 2013; Tackett et al.,115 2018). Towards this objective, the most aggressive quality control procedure applied in the framework of the study is the cloudfree condition, removing the entire L2 profiles when detected atmospheric layers (Vaughan et al., 2009) along the CALIPSO orbit-path are classified as clouds in the feature-type classification algorithm (Liu et al., 2009; Zeng et al., 2019). Figure 2 provides an indicative example of the considered CALIOP observations and products, and more specifically the Feature Type (Fig.2 top left) product and the profiles of particulate depolarization ratio at 532 nm (Fig.2 top right), total backscatter coeffi-120 cient at 532 nm (Fig.2 bottom left), and quality-assured total backscatter coefficient at 532 nm (Fig.2 bottom right), along the CALIPSO overpass on the 10th of September 2021. Figure 2. CALIPSO nighttime overpass in the ESA-ASKOS campaign region of interest in the proximity of Cabo Verde on the 10th of September, 2021, depicting the Feature Type (top left), particulate depolarization ratio at 532 nm (top right), total backscatter coefficient at 532 nm (bottom left), and the quality-assured total backscatter coefficient at 532 nm (bottom right). 5 https://doi.org/10.5194/egusphere-2025-1105 Preprint. Discussion started: 14 March 2025 c Author(s) 2025. CC BY 4.0 License. 2.1.3 Radiosondes and models Radiosonde profiles were analyzed to examine the dynamic structure of the lower troposphere and to evaluate the remote sensing measurements conducted during the ASKOS Campaign. The GRAW DFM-09 radiosondes were launched to provide125 real-time, high-resolution measurements of temperature, humidity, and wind, which are essential for identifying the BL key characteristics, such as height, stability, and thermodynamic properties. The sensors were equipped with a GPS receiver and transmit data via a radiofrequency link to the ground station. The measurements-derived BL height was compared to values obtained from the ERA5 Reanalysis dataset, produced by the ECMWF/IFS. The ERA5 data, available at a horizontal resolution of 0.25° × 0.25° with 137 vertical levels (Vogelezang and130 Holtslag, 1996), offers a consistent representation of atmospheric conditions. The BL height in ERA5 is determined according to ECMWF (2017), Chapter 3, incorporating thermodynamic criteria. Additionally, Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) is employed to analyse the backward trajectories of air masses arriving at the site of the ASKOS Campaign, Mindelo, Cabo Verde. This model estimates the tracking of air parcels over time, providing valuable information about the origins of the air parcels and their potential interactions with135 dust and other atmospheric constituents (Rolph et al., 2017). By identifying these pathways, a clearer understanding of the sources and transport mechanisms of the the atmospheric conditions at Cabo Verde can be established. 2.2 Boundary Layer top retrieval Methods To retrieve the BL heights from the lidar measurements, the Wavelet Covariance Transform (WCT) and the Gradient Method are applied (Brooks, 2003; Li et al., 2021) on the cloud-free backscatter coefficient profiles of the CALIOP (Fig. 2-bottom right)140 and ground-based PollyXT lidar (Fig. 1, left) for the channels of 532 and 1064 nm respectively. For the radiosonde data, layer detection is achieved with the gradient method. In some cases, detecting the BL top relies on visual inspection to accurately locate the inversion cap, especially in cases where automated methods might miss subtle features. Figure 3 shows profiles of the backscatter coefficient at 1064 nm from ground-based PollyXT (left), of the Relative Humidity (RH) from radiosonde (middle) and backscatter coefficient at 532 nm from CALIPSO satellite lidar (right) from the 23rd of September 2022, around145 19:30 UTC. The grey lines represent the result of the method applied for detecting BL top, namely WCT method for PollyXT Lidar and Gradient method for the rest two. A local maximum of the wavelet profile for WCT method, and a local minimum of the gradient for the gradient method, represent steep reduction in the investigated signal (red dashed lines). Several significant challenges arise when studying the BL with lidars (both ground-based and satellite), particularly in complex environments. For a satellite-based lidar like CALIOP, the signal can become highly attenuated as it approaches150 the Earth’s surface, due to the existence of clouds above the BL. This can compromise the reliability of detecting lower tropospheric features and lead to inaccurate identification of the BL top. To mitigate this, only cloud-free profiles were selected to ensure data quality, though this restriction reduces the dataset and introduces observational limitations. Additionally, in marine environments, cumulus clouds frequently form at the BL top, which can serve as a useful, albeit indirect, marker for BL height for ground-based lidars that can detect the cloud base. Moreover, if a thin cumulus cloud is present above the BL155 6 https://doi.org/10.5194/egusphere-2025-1105 Preprint. Discussion started: 14 March 2025 c Author(s) 2025. CC BY 4.0 License. Figure 3. 23rd September 2022, around 19:30 UTC: Profiles of atmospheric variables and their corresponding detection methods for determining the boundary layer (BL) top. The blue lines represent the observed signals, while the grey lines correspond to the applied methods for BL top detection. Left: Backscatter coefficient at 1064 nm from the ground-based PollyXT lidar, Middle: Relative Humidity (RH) from radiosonde, and Right: backscatter coefficient at 532 nm from the CALIPSO satellite lidar. The selected BL top is highlighted by the red dashed lines. top and allows partial laser penetration, the WCT may incorrectly identify the cloud’s upper boundary as the BL top instead of the actual BL height. A similar issue occurs in the presence of dust layers, as the WCT detects reductions in the lidar signal caused by these layers. This can lead to misclassification of the dust layer boundaries as the BL top, complicating the accurate identification of the atmospheric structure. These limitations underscore the need for visual inspection to ensure accuracy in identifying the BL top in such settings, as automated methods may struggle to locate the correct layering.160 3 Boundary Layer Characteristics in diverse environments The characteristics of the BL during JATAC Campaign are examined across the contrasting environments depicted in Figure 4: over the Atlantic Ocean (blue rectangle - Area 1), within the ocean-desert transition zone (orange rectangle – Area 2), and at the area of São Vicente in Cabo Verde (red circle). The Sahara Desert and the Atlantic Ocean are characterized by distinct conditions in terms of weather, aerosol concentrations, and therefore atmospheric dynamics. These variations are anticipated165 to influence respectively the structure and evolution of BL in the Areas of Figure 4. The lower troposphere above the Atlantic Ocean is rich in marine aerosols, and presents relatively stable meteorological conditions, typical for open-ocean broad-scale circulations (Croft et al., 2021). In contrast, the lower troposphere over the desert is characterized by high dust aerosol concentrations, intense solar heating, and variable atmospheric stability (Giménez et al., 2010). The border region between ocean and desert introduces an interaction zone where different aerosols co-exist in170 big concentrations, producing unique BL characteristics due to the convergence of these differing air masses. Moreover, the existence of SAL has an impact on the on the surface radiation budget (Evan et al., 2009) and hence on the sea surface temperature (SST). Foltz and McPhaden (2008) found that Saharan dust outflows at the Tropical North Atlantic, were consistently associated with a reduction in solar radiation, with approximately 35% of SST variability attributed to dust outbreaks, while 7 https://doi.org/10.5194/egusphere-2025-1105 Preprint. Discussion started: 14 March 2025 c Author(s) 2025. CC BY 4.0 License. other SST cooling anomalies were linked to wind stress. The dust aerosol effect on SST depends on several factors, such as175 the temperature contrast between the dust layer and SST, the characteristics of the dust layer, concentration and altitude (Luo et al., 2021). Figure 4. Map displaying the study areas for BL analysis: The blue rectangle (Area 1) represents the open-ocean Marine Atmospheric Boundary Layer (MABL) discussed in Section 3.1. The orange rectangle (Area 2) marks a transition zone at the ocean-desert interface, analysed in Section 3.2. The red circle is the ground-based measurements site at the Ocean Science Center Mindelo (OSCM) in Cabo Verde (3.3). 3.1 Analysis of Area 1: The BL in the Atlantic Ocean The Atlantic Ocean is characterized by dynamic weather systems and cyclonic activity, incorporating continuous exchange of heat and moisture between the sea surface and the adjacent air parcel (Schnitker, 1982). In open ocean areas such as Area 1,180 there is no direct interaction of the lower troposphere and the land, allowing for the development of a MABL. The MABL contains higher humidity levels and the airflow is smoother due to reduced friction from the water surface, comparing to land. Wind and temperature profiles in the MABL are mainly influenced by sea surface temperature, oceanic currents and large-scale atmospheric circulation. In this section, we focus on the MABL characteristics within the blue rectangle of Area 1 (Figure 4). 10 years of CALIOP185 data (2012–2022) are examined, using only the profiles recorded in month September. By limiting the data to one month, we aim to achieve more homogeneous conditions to better capture the prevailing environmental characteristics (e.g. relatively consistent sea surface temperatures). Figure 5-left illustrates the conceptual trajectories of the CALIPSO satellite across the study area. The analysis targets cloud-free profiles measured within approximately 40 km around latitude 16.87° N, corresponding to the latitude of ground-based measuring site in Cabo Verde, as represented by the red points in Figure 5-left. A total of 6392190 nighttime and daytime profiles (conceptually indicated in green and purple, respectively) are analyzed across longitudes from 60° W to 25° W. The spatial range of 40 km is suitable for capturing representative MABL characteristics in the study area because the selected profiles are cloud-free and measured over the ocean surface, maintaining generally homogeneous conditions 8 https://doi.org/10.5194/egusphere-2025-1105 Preprint. Discussion started: 14 March 2025 c Author(s) 2025. CC BY 4.0 License. of temperature, and humidity. For each profile, the derivative of the backscatter-coefficient profile at 532 nm is calculated (as in Fig. 3-right) and the minima are constrained at the lower 3 km.195 Figure 5. Left: Conceptual illustration of the trajectories of the CALIPSO satellite across the study area. Right: Comparison of BL top derived from CALIPSO (blue points) and ECMWF (magenta points) for 10 years (2012-2022) in Area 1. The results of the MABL analysis from the space lidar data are compared with BL heights derived from the ECMWF/IFS dataset. To account for longitudinal time differences, each profile’s measurement time is converted to local time based on its longitude. For each lidar profile, a temporally and spatially matched ECMWF point at the same local time is selected for direct comparison. The findings are presented in Figure 5-right. The blue circles display the MABL top heights derived from CALIPSO profiles, averaged hourly in local time. The magenta200 points represent the corresponding hourly-averaged BL top heights from ECMWF. The data points are clustered within the 00:00–04:00 and 12:00–16:00 local time windows, because they correspond to CALIPSO’s nighttime and daytime overpasses in the Atlantic region. The results show very good agreement overall, though lidar-derived BL heights carry greater uncertainty and sensitivity. This is expected, as uncertainties in the lidar profiles, occur not only from time averaging but also from the gradient method used to derive heights from CALIOP profiles, which can be challenging to automate due to low signal to noise205 ratios especially during daytime. In contrast, the model is less sensitive to small-scale variations, as it provides an averaged representation over a relatively large grid (0.25° or 27.83 km around 16°N). The BL top in Area 1 under cloud-free conditions, is found to consistently range between 600 and 800 meters above sea level. Although uncertainties in deriving the BL and time averaging broaden this estimate, these findings align well with expected MABL behavior that typically do not show a significant diurnal evolution.210 3.2 Analysis of Area 2: The BL in the Ocean-Desert Transition Zone Area 2, highlighted by the orange rectangle in Figure 4, spans within longitudes of 35°W-0°: from the eastern Atlantic Ocean to the Western Africa, including the region around Cabo Verde. This area lies at the interface of two significantly different 9 https://doi.org/10.5194/egusphere-2025-1105 Preprint. Discussion started: 14 March 2025 c Author(s) 2025. CC BY 4.0 License. the marine and coastal air masses, impacting aerosol concentrations and BL dynamics. In Figure 11a, the values of VLDR inside the BL are close to 20%, indicating the existence of dust particles in the MABL, mixed with marine particles. The315 radiosonde profiles of virtual potential temperature and relative humidity reveal weaker inversions than those observed in Section 3.3.1, with a notable inversion around 500 m, which may indicate the approximate BL top in this case. This weakened inversion also suggests that the BL may be more susceptible to vertical mixing, facilitating dust intrusion from higher altitudes into the BL. On this particular day, the wind speed profile (magenta line) shows milder conditions, reaching speeds up to 10 m/s (~5 on the Beaufort scale). The direction of the wind is northern (black stars) relatively to the previous case. At the northern320 side of the measurements’ site, there is the neighbouring Santo Antão island that could act as an obstacle to the wind’s flow, shaping local dynamics that affect the vertical mixing. Figure 11. Same as Figure 9 for 23 September 2022. a) The radiosonde launch time at 19:38 UTC on 23 September 2022. b) ECMWF BL height (blue dashed line) at 720 m, WCT maximum (red dashed line) at 500 m. c) Halo Wind Doppler Lidar TKE dissipation rate for the same time period as PollyXT, with the black hexagons representing the MLH. The WCT method (grey line) applied to the averaged ¯ β1064 profile (Fig. 11b) identifies multiple maxima, none of which are particularly dominant. The most pronounced feature below 1.5 km appears at 500 m (red dashed line). This method presents limitations when the lidar signal is influenced by overlying features, such as elevated aerosol layers or thin cirrus clouds325 16 https://doi.org/10.5194/egusphere-2025-1105 Preprint. Discussion started: 14 March 2025 c Author(s) 2025. CC BY 4.0 License. (Brooks, 2003). In such cases it is essential to cross-check the results with independent measurements. According to Wind lidar TKE dissipation rate, turbulent motions extend up to 600 m (Fig. 11c), while the ECMWF BL top for the same time is located at 720 m (blue dashed line). The two ground-based lidars show better agreement, both indicating a BL top around 500–600 m. The weaker inversion observed in the radiosonde profile supports this lower BL height, however, the ECMWF BL top is notably higher (at 720 m), highlighting a larger discrepancy between the model and observations compared to the330 previous case. 4 Conclusions This study highlights the critical importance of understanding the BL in the Atlantic, to better characterize the complex interactions between the ocean and the atmosphere, particularly in the presence of transported Saharan dust. These interactions govern fundamental processes such as evaporation, sea surface temperature variability, and cloud formation, all of which have335 significant implications for climate modelling and marine ecosystem productivity due to dust nutrient deposition. Our findings demonstrate that, based on 10 years (2012-2022) of CALIPSO measurements over the open Atlantic (Area 1), the BL height ranges from 600 m to 800 m for both daytime and nighttime trajectories, with cloud-free profiles considered during September. Furthermore, a strong correlation is observed between the CALIPSO measurements and ECMWF/IFS model outputs for this Area during the decade. However, the variations associated with CALIPSO BL are significantly larger than340 those of the ECMWF/IFS model outputs. CALIPSO’s sensitivity to small-scale features such as aerosols and clouds leads to more variability in the data. In contrast, ECMWF/IFS model outputs are based on global atmospheric simulations that provide a more general, smoothed estimate with less sensitivity to local disturbances. The analysis of Area 2 reveals distinct BL characteristics over the ocean and land, shaped by differences in surface properties, meteorological conditions, and aerosol composition. Over the ocean (35°W–17°W), CALIPSO and ECMWF show strong345 agreement in BL heights, typically ranging from 500 to 800 meters, consistent with findings from Area 1. However, over the examined area of land (17°W–0°), discrepancies emerge, particularly during the daytime, when ECMWF estimates a significantly higher BL top than CALIPSO, likely due to differences in how the model and lidar capture the mixing layer, residual layer, and entrainment zone. The under-representation of aerosols in ECMWF/IFS model (Morcrette et al., 2008; Bozzo et al., 2020; Rémy et al., 2024) may also contribute to these differences. At night over land, CALIPSO generally reports350 higher BL than ECMWF, which is most probably due to the presence of the residual layer that provides an aerosol layer height significantly higher than the thermodynamically defined BL top. In Cabo Verde, collocated data from CALIPSO, PollyXT, Halo Lidar and radiosondes were analyzed for September 2021–2022. Correlations between all measurements and ECMWF with CALIPSO data were assessed. 66% of the PollyXT points, 50% of the ECMWF points and 30% of the Halo points indicate agreement within 20% error when comparing with CALIPSO BL355 height. The weakest correlation is observed between CALIPSO and Halo Lidar, due to methodological differences —CALIPSO primarily detects layering that may include the residual layer, while Halo Lidar estimates the mixing layer height based on TKE 17 https://doi.org/10.5194/egusphere-2025-1105 Preprint. Discussion started: 14 March 2025 c Author(s) 2025. CC BY 4.0 License. dissipation rate. Moreover, systematic differences could arise from variations in measurement techniques, retrieval algorithms, or even inherent model biases in representing BL processes. To further investigate the situation in Cabo Verde, two cases with distinct thermodynamic conditions were examined. The360 first case (12 September 2022) is characterized by stronger inversions and dust aerosols primarily above the capping layer. Temperature and humidity inversions are observed at approximately 1 km; however, PollyXT and Halo Lidar detect the BL top at 650 m and 520 m, respectively, aligning more closely with the marine BL. While the two ground-based lidars show good agreement, the radiosonde profile indicates a higher BL top near 1 km. This discrepancy likely arises because the lidars primarily capture the well-mixed layer, whereas the radiosonde inversion marks a more stable upper boundary, potentially365 corresponding to the entrainment zone or a decoupled residual layer. Such differences are anticipated in complex environments like Cabo Verde, where the interplay of dust, marine aerosols, and variable meteorological conditions introduce challenges to understand the BL dynamics. In the second case (23 September 2022), characterized by a weaker inversion and dust aerosols within the BL, the BL top was found lower, with both ground-based lidars detecting it around 500 m. The key differences in this case are the smoother wind speed and a more northerly wind direction. The northern wind flow may have been influenced370 by the presence of Santo Antão island to the north, impacting local dynamics. Additionally, the slope of the virtual potential temperature profile suggests less unstable conditions, promoting better vertical mixing and enabling dust to enter the BL. The observed differences in BL height can be mainly attributed to the mechanical turbulence driven by strong winds in the first case, highlighting the variability of the atmospheric conditions in this region, that is influenced by a combination of marine and dust aerosols, as well as the complex sea-land interactions in between, that contribute to the diverse atmospheric375 conditions. SST emerges as a key factor, driving BL evolution, fostering an unstable lower troposphere. This study suggests that when these complex conditions favor less instability, desert dust from the SAL is more efficiently penetrating to the BL. This mechanism should be further examined on its importance as a facilitator of dust deposition to the ocean. Experiments such as JATAC bring the observational synergies needed to study complex BL dynamics governing dust transport. Data availability. Visualized datasets of the ASKOS Campaign and additional information are available at https://askos.space.noa.gr/data;380 the ERA5 ECMWF Re-analysis Dataset is available at https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5; the LIVAS CALIPSO data are available upon request. Author contributions. IT and EM conducted the analysis and drafted the manuscript; MT, EG and VA provided methodological guidance and contributed to the interpretation of the data; EM, MT and VA designed the study framework and defined the research objectives; EP, KR and VV contributed to the data curation, processing, visualization and revisions of the results; EM and VA provided funding acquisition and385 project administration; All authors edited and reviewed the original draft, provided critical feedback and helped shape the research, analysis and manuscript. 18 https://doi.org/10.5194/egusphere-2025-1105 Preprint. Discussion started: 14 March 2025 c Author(s) 2025. CC BY 4.0 License. Competing interests. The authors declare that they have no competing interests. Acknowledgements. This research has been supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “3rd Call for H.F.R.I. Research Projects to support Post-Doctoral Researchers” (Project Acronym: REVEAL, Project Number: 07222). We also390 acknowledge the support by the PANGEA4CalVal project (Grant Agreement 101079201) funded by the European Union . Emmanouil Proestakis acknowledges support by the AXA Research Fund for postdoctoral researchers under the project entitled “Earth Observation for Air-Quality – Dust Fine-Mode (EO4AQ-DustFM)”. Funding was also received from Horizon Europe programme under Grant Agreement No 101137680 via project CERTAINTY (Cloud-aERosol inTeractions & their impActs IN The earth sYstem). Finally, the authors would like to acknowledge the project of ASKOS (Grant agreement 4000131861/20/NL/IA) from the European Space Agency.395 19 https://doi.org/10.5194/egusphere-2025-1105 Preprint. Discussion started: 14 March 2025 c Author(s) 2025. CC BY 4.0 License. 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