Sonic anemometry is an established approach for turbulence measurement due to the absence of inertia in the sensor transfer function. On the other hand, the sound transducers and their mounting rods cause perturbations of the free flow, which can only be partially corrected, particularly regarding turbulence. The perturbations depend i.a. on the angle of attack to the measuring paths and the position of the mounting rods with respect to the flow direction. Therefore, the optimal sensor array geometry has been a subject of discussions for decades – and still is.

The concept of Multi-Path (MP) anemometry offers a way to realize different geometric approaches with one sensor head, enabling turbulence measurements by directly measured vertical wind components and/or vertical wind components derived from tilted paths. Depending on the free flow conditions, the optimal geometry can be dynamically selected.

For MP-sonics each sound transducer communicates with more than one partner, thus setting up more than one measuring path, in total nine measuring paths instead of three paths with only six transducers. On one hand the redundancy allows to analyze only subsets of data output, consequently the performance of conventional sonics can be simulated. On the other hand the MP concept allows multiple approaches to calculate turbulence parameters.

The benefits of the Multi-Path approach, especially in view of the heat flux, will be demonstrated by comparing results of field measurements with corresponding data from simulated conventional sonics.

How to cite: Burgemeister, F., Kirtzel, H.-J., and Peters, G.: Improvement of turbulence estimation by Multi-Path sonic anemometry, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12817, https://doi.org/10.5194/egusphere-egu26-12817, 2026.

EGU26-12817

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The atmospheric boundary layer (ABL) is primarily characterised by its diurnal variability, which is crucial in exchanging heat, momentum, moisture, and chemical components between the surface and the free atmosphere. Despite its significance, studies on the evolution of the ABL height with sufficiently high temporal precision are quite few in the tropical region. Our study paves the way to utilise radar data to explore high temporal variability, which is not feasible with the limited availability of conventional radiosonde profiles. This study employs very high frequency (VHF) radar to examine the diurnal and seasonal variability in ABLH using a novel method known as the Normalised Standard Deviation Method (NSDM) spanning over seven years from 2018 to 2024 at a tropical coastal station, Cochin (10.04° N, 76.33° E) in India. This method identifies the intensity of turbulence within the ABL using the profiles of signal-to-noise ratio, wind variability and spectral width. To guarantee accurate profiling, clear-sky and partly clear-sky days were chosen, thereby removing contamination due to rain. Depending on data availability, the dataset includes both continuous profiles of varying durations (24- h or less) and time specific snapshots at selected synoptic hours (06:00, 09:00 and 12:00 UTC), covering over 800 days of observations. Radar-based measurements clearly demonstrate ABLH changes during the day, showing significant temporal variability, as it is influenced by factors such as topography, solar radiation, surface roughness and other surface forcings. Although no discernible seasonal shift is observed in the timing of maximum ABLH, pronounced differences occur in its magnitude. Spectral width values are low at night, indicating weak turbulence within the stable boundary layer and show increased values during the day as convection develops. The seasonal dependence is distinct: boundary layer development is deepest during the pre-monsoon season, with mean peak values of 1.6 ± 0.6 km, followed by winter (1.45 ± 0.2 km), post-monsoon (1.3 ± 0.4 km) and monsoon with the shallowest ABLH (1.2 ± 0.1 km) during clear sky conditions. The study further makes a comparison of the ABLHs derived from reanalysis data such as MERRA2, IMDAA and ERA5. This comparison is aimed at validating the reliability and consistency of the observed values in different atmospheric conditions. Additionally, surface density shows a strong and consistent inverse relationship with ABLH, making it a useful proxy when profile observations are unavailable. Further, the application of machine learning (ML) methods demonstrates that non-linear models outperform linear methods in predicting ABLH. Our results emphasise the robustness of radar-based ABLH estimates, establishing their suitability for regional-scale investigations of boundary layer processes. Given their relatively high temporal resolution, radar observations serve as a reliable benchmark for validating model outputs and reanalysis products. A key strength of this study is its ability to capture vertical reflectivity and turbulence structures, significantly improving its usefulness for convection studies. However, challenges persist under overcast or rainy conditions, which require further investigation.

Keywords: VHF Radar; Radiosonde; ABLH; Diurnal variability; Seasonal evolution

How to cite: Christy, A. A. and Manguttathil Gopalakrishnan, M.: Tracking ABL height with VHF radar: Diurnal and seasonal variability with its link to convection, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1100, https://doi.org/10.5194/egusphere-egu26-1100, 2026.

EGU26-1100

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This work concerns the estimation of the turbulence kinetic energy dissipation rate from time series recorded by a fixed-point sensor or from lidar data. For such estimates, it is usually assumed that the wind velocity spectrum follows Kolmogorov scaling at small scales. To convert the measured time series into space-dependent data, the Taylor frozen-eddy hypothesis is typically employed, in which the mean wind velocity is assumed to advect turbulence structures past the sensor without distortion. This assumption works well for strong winds and when the turbulence intensity (defined as the ratio of the root-mean-square of the wind velocity fluctuations to the mean wind speed) is small.

However, the Taylor hypothesis is not always fulfilled, for example in the convective regime with weak winds, or in the neutral or stable boundary layer when the wind becomes weaker but decaying turbulent motions are still present. As the turbulence intensity increases, it can no longer be assumed that turbulence structures, “frozen” in time, are simply advected past the sensor. Instead, the sweeping of small eddies by larger ones becomes an important mechanism, considerably affecting the frequency spectra. In this case, no simple relationship between frequency and wavenumber exists. In addition, the measured time series are subject to effective spectral cut-offs due to the finite sampling frequency of the sensor. This acts as a low-pass filter, which may also affect the resolved large-scale motions.

In this work, we consider an iterative method for estimating the turbulence kinetic energy dissipation rate, originally proposed by Wacławczyk et al. (Atmos. Measur. Tech., 10, 2017) and Akinlabi et al. (J. Atmos. Sci., 76, 2019), and extend it to account for the effects of random sweeping and the finite frequency of the sensor. The iterative method has several advantages over standard spectral estimates. In spectral methods (or methods based on structure functions), a fitting range in which Kolmogorov scaling holds must be defined a priori. In contrast, the iterative method requires only the calculation of the time derivative of the time series, its standard deviation, and a correcting factor that accounts for the shape of the unresolved part of the spectrum. In the proposed improved iterative method, the assumed spectral form incorporates modifications due to both random sweeping and low-pass filtering by the sensor.

How to cite: Kujawska, A., Wacławczyk, M., and Malinowski, S.: An Iterative Method for Estimating Turbulence Kinetic Energy Dissipation Rate Considering Random Sweeping and Sensor Low-Pass Filtering Effects  , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3474, https://doi.org/10.5194/egusphere-egu26-3474, 2026.

EGU26-3474

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Fog is a type of cloud that forms in direct contact with the Earth’s surface. It is composed of extremely small water droplets or ice particles suspended in the air, similar to those found in clouds. For atmospheric conditions to be classified as fog, horizontal visibility must be reduced to less than 1 kilometer due to the presence of these fine particles, which scatter and absorb light and significantly limit what can be seen near the ground. Fog also plays an important role in the Earth system because it influences the surface radiation budget, in daytime causing cooling and in nighttime causing warming. Fog is a significant phenomenon that impacts the safety of terrestrial, maritime, and especially aviation transportation.

This study investigates variations in fog microphysics and the correlations with horizontal visibility. The analysis is performed on datasets gathered during in situ continuous measurements conducted in wintertime 2025-2026 in Bucharest using the Fog Monitor FM-120 from Droplet Envea Group. A weather station from Luft (WS600-UMB) monitored meteorological parameters: temperature, pressure, humidity, wind direction and wind speed.

The measurements were taken at the National Institute for Aerospace Research (INCAS) in Bucharest (coordinates: 44.4672° N, 26.0814° E), that is located in a Bucharest area with high traffic likely providing plenty of condensation nuclei. We present very recent observational evidence on the fog droplet signature in real time, linking temporal droplet size distribution changes and visibility evolution. We focused on assessing the microphysical parameters of fog, including number concentration (N), effective diameter (ED), liquid water content (LWC), and mean volume diameter (MVD), across a dimensional spectrum from 2 to 50 µm. The observational datasets were then used to test some visibility parameterizations, with the goal of determining a specific parameterization, linking visibility to the fog microphysics, best suited for the Bucharest area.

The results add to the past studies aiming to contribute to a better understanding of fog characteristics and visibility parameterization using regional characteristics, ultimately aiding in improving safety measures in various transport sectors.

How to cite: Vlad, A., Antonescu, B., Iorga, G., and Vâjâiac, N. S.: Urban Fog Microphysics and Visibility Parameterization Based on Winter 2025–2026 In Situ Measurements in Bucharest, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6554, https://doi.org/10.5194/egusphere-egu26-6554, 2026.

EGU26-6554

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The atmospheric boundary layer height (ABLH) is a key parameter for understanding turbulent exchange processes, air‑quality dynamics, and land–atmosphere interactions. Radiosonde profiles are traditionally used as a reference for determining the ABLH, but their sparse temporal coverage limits their value for continuous monitoring. Ground‑based remote‑sensing instruments, such as ceilometers and Doppler lidars, offer high‑frequency observations throughout the day, but the derivation of the ABLH from these systems depends strongly on the chosen retrieval method. In this study, we evaluate multiple commonly used algorithms for ABLH estimation, like gradient-based and variance-based methods using a threshold, all applied to co‑located ceilometer and Doppler lidar measurements. The resulting ABLH estimates are systematically compared against radiosonde-derived heights to assess performance under varying meteorological conditions.

Our analysis reveals substantial discrepancies between methods, both within and across instrument types. Ceilometer-based retrievals tend to diverge most strongly during conditions with weak aerosol gradients, at night and during the afternoon transition, while Doppler lidar methods show larger spread during periods with low signal due to weak winds. No single method consistently reproduces radiosonde-derived heights across all stability regimes. Instead, each approach captures different structural aspects of the boundary layer, suggesting that the ABLH is not a single, easily definable quantity, but rather a multifaceted feature of the lower atmosphere.

These findings raise an important question for the boundary layer community: Is the derivation of a robust ABLH from ground-based remote sensing fundamentally limited by the information content of individual instruments and methods, and do we ultimately require a synergistic, multi-sensor, multi-method product to obtain a physically meaningful estimate? This contribution will explore these challenges in detail and discuss pathways towards an integrated ABLH retrieval framework.

How to cite: Baumgarten, K., Päschke, E., and Beyrich, F.: Evaluating the atmospheric boundary layer height from ceilometer and Doppler lidar: Divergent retrievals across methods and the question of what they truly represent, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6622, https://doi.org/10.5194/egusphere-egu26-6622, 2026.

EGU26-6622

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Wintertime fog over the Indo-Gangetic Plains (IGP) exhibits large variability in frequency, duration, and intensity, with significant implications for transportation, air quality, and human health. This study examines the interannual variability of fog hours, fog days, duration, and intensity over Lucknow (26.85° N, 80.95° E), a rapidly urbanizing city in the central IGP, using half-hourly METAR visibility observations and associated meteorological parameters during 2016–2023. Rapid urban expansion and increasing anthropogenic emissions in Lucknow have the potential to modify near-surface thermodynamic conditions, moisture availability, and boundary-layer stability, thereby influencing fog formation and persistence.

The results show that January experiences the highest occurrence in fog hours and days, followed by December and February. Fog hours and fog days increased until 2017, after which fog hours declined by approximately 19%, while fog days increased by about 12% up to 2023. Analysis of the data reveals an increase in shallow and moderate fog events, whereas dense and very dense fog hours exhibit a significant decreasing trend. In contrast, fog days show an increasing tendency across most intensity categories, except for moderate fog days. The results reveal a significant increasing trend in shallow and moderate intensity, whereas a significant decreasing trend in dense and very dense fog hour events, and a similar increasing trend has been noticed in fog intensity days, except in moderate intensity. The study reveals that there is a significant decline in persistence and intensity of fog amidst rising event frequency. These findings indicate a transition toward more frequent but shorter-duration and less intense fog events, suggesting a weakening of long-duration fog persistence and severity over the study period, likely linked to evolving urban and boundary-layer processes in the IGP.

Keywords: Winter fog, Interannual variability, METAR Visibility, Urbanisation

How to cite: Prathima, D. and Satyanarayana, A. N. V.: Interannual Variability of Wintertime Fog over a Rapidly Urbanising City in the Indo-Gangetic Plains, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7187, https://doi.org/10.5194/egusphere-egu26-7187, 2026.

EGU26-7187

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Doppler wind lidar has recently seen rapidly increasing utilization as an observational instrument capable of continuously retrieving high-resolution vertical profiles of wind. However, the accuracy of the retrieved wind vectors can vary depending on the scanning strategy and data processing configurations. In this study, algebraic algorithms for retrieving wind vectors from line-of-sight velocities observed by a vertically profiling lidar are presented. The performance of each algorithm is evaluated through comparisons with wind vectors derived from GPS-tracked radiosonde observations. In addition, the utility of wind lidar observations is verified by comparison with wind profiler measurements for cases characterized by pronounced local variability.

Differences in wind speed depending on the selected azimuth angles within a single scan cycle violate the assumption of a homogeneous wind field required for height-resolved wind vector retrieval. From another perspective, this suggests the presence of atmospheric turbulence that disrupts the homogeneity of the flow. Using u, v, and w wind components retrieved at approximately 2.3-s intervals, turbulence intensity, momentum flux, and turbulent kinetic energy are estimated and compared with results obtained from a 20-Hz three-dimensional ultrasonic anemometers installed on a 300-m meteorological tower using the eddy correlation method. The two sets of results show very good agreement.

These findings demonstrate that Doppler wind lidar can effectively capture the vertical structure of the atmospheric boundary layer and provide critical hazardous-weather information essential for urban air mobility (UAM) operations. Furthermore, the results highlight the need to reconsider quality control procedures for spectral data, as enforced symmetry checks and corrections may remove genuine turbulent components. Further systematic investigation is required to better understand the impacts of spectral quality control procedures on both the representation and retrieval of atmospheric turbulence.

How to cite: Kwon, B. H., Yu, A., and Jung, Y.: Boundary-Layer Wind and Turbulence Retrieval from Doppler Wind Lidar for UAM Applications , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8642, https://doi.org/10.5194/egusphere-egu26-8642, 2026.

EGU26-8642

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Urban Air Mobility (UAM) is emerging as a next-generation transportation system that not only alleviates traffic congestion in high-density urban areas but also supports emergency medical response, time-critical logistics and supply delivery, and urban and regional tourism. UAM vehicles operate at low altitudes within the atmospheric boundary layer, where airflow and turbulence are strongly modified by topography, buildings, and other urban structures. In such environments, localized meteorological phenomena, such as gusts, vertical wind shear, and turbulence, frequently develop and pose significant challenges to flight stability and operational safety.

Conventional meteorological observation networks and mesoscale numerical weather prediction models lack the spatial and temporal resolution required to resolve these microscale urban flow features. Consequently, short-term forecasting of boundary-layer winds and turbulence in complex urban environments remains highly uncertain. To support safe UAM operations, a new observation framework providing high-resolution, three-dimensional meteorological information is needed. High-frequency, multi-point surface and remote-sensing observations can capture spatiotemporal variability of meteorological conditions and provide essential inputs for data assimilation in numerical prediction models as well as for training and constraining artificial-intelligence-based forecast systems designed to generate high-fidelity, short-term meteorological fields for UAM operations.

We propose a multi-point meteorological observation network designed to characterize wind and turbulence fields within UAM corridors. The network is configured to resolve the spatiotemporal variability of winds and turbulence in the boundary layer with high fidelity. The resulting dataset can enhance the understanding of urban low-altitude meteorology and provide a foundational dataset for high-resolution forecasting and operational decision-support for safe and efficient UAM operations.

This work was funded by the Korea Meteorological Administration Research and Development Program under Grant (RS-2024-00404042).

How to cite: Park, Y., Han, S., Seo, S., Shin, J., Kim, J.-J., and Choi, W.: Establishing High-Resolution Meteorological Monitoring for Safe Urban Air Mobility Operations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8896, https://doi.org/10.5194/egusphere-egu26-8896, 2026.

EGU26-8896

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Nocturnal valley winds (NVWs) strongly modulate atmospheric stability, turbulence, and scalar transport in complex terrain. However,  their sensitivity to synoptic forcing and their representation in numerical models remain uncertain and extremely site dependent. 

In this work, we analyse an 11-month observational dataset, including several stations deployed at distinct, pre-selected locations along the Aure valley (near central French Pyrenees). These data provide complementary surface wind, radiation and turbulence observations. The valley is oriented north–south , opened to the north onto the Lannemezan Plateau, and its regional synoptic climatology is mainly dominated by westerlies (largely perpendicular to the valley axis).

From the observations, representative NVW cases are selected using a detection algorithm based on local and synoptic filters applied at each station, allowing the selection of events under contrasting large-scale conditions. NVWs are found even under moderate synoptic forcing (700 hPa winds higher than 12 m s⁻¹), consistent with the role of orographic shielding. Particular attention is given to moderate westerly situations (perpendicular to the valley main axis) in which the synoptic flow and the NVW coexist, enabling detailed analysis of their interaction in both wind speed and direction. For each selected case, night-time radiosoundings provide information on low-level jet height, inversion depth, and atmospheric stability, while high-resolution WRF simulations are analysed in detail to study the occurrence, phase, jet structure, and along-valley heterogeneity. 

The combined observational–modeling approach highlights the ability of NVWs to persist even under non-negligible synoptic forcing and provides insight into their vertical structure and spatial variability in complex terrain.

How to cite: Ortiz-Corral, P., Carbone, J., Román-Cascón, C., Sun, J., Lohou, F., Lothon, M., Sastre, M., Jiménez Rincón, J. A., and Yagüe, C.: Nocturnal Valley Winds in the Aure Valley (France): Analysis of Case Studies using Radiosoundings and High-Resolution WRF simulations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6866, https://doi.org/10.5194/egusphere-egu26-6866, 2026.

EGU26-6866

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The frequency and impacts of heatwaves have significantly increased in recent decades (1975–2020), with Spain experiencing a marked rise in the occurrence of these extreme events (Núñez-Mora, 2021). In coastal environments, sea breezes —driven by temperature gradients between land and sea surfaces— can play a crucial role in mitigating extreme temperatures. This study examines the impact of coastal breezes on thermal comfort during a heatwave period in the southwest of the Iberian Peninsula.

Coastal areas have undergone intense urban development, and approximately 60% of the Spanish population currently resides in these regions (de Andrés et al., 2017). Consequently, urban heat exposure is modulated by meteorological processes operating across multiple spatial (from meters to hundreds of meters) and temporal scales. Within cities, air temperature and humidity exhibit local variations over hundreds of meters, while wind speed and shortwave/longwave radiation show important microscale heterogeneity influenced by urban settlement.

In this work, we employ the Weather Research and Forecasting (WRF) model coupled with the urban parameterization WRF-Comfort (Martilli et al., 2024) to investigate the impact of coastal breezes on thermal comfort. A comprehensive set of numerical experiments is designed to assess the sensitivity of sea-breeze simulations to key model inputs, including large-scale atmospheric forcing, urban datasets with different levels of morphological detail, and alternative sea surface temperature forcings. Model results are evaluated through systematic evaluation with observational data from surface meteorological stations, radiosoundings launched at strategic coastal locations during sea-breeze conditions, and oceanic measurements from a buoy in the Gulf of Cádiz.

This integrated modelling–observational framework enables investigation of the thermoregulatory effects of coastal breezes and their influence on the vertical structure of the coastal urban boundary layer. The study highlights the importance of accurately representing large-scale forcing, urban characteristics, and air–sea interactions to improve coastal breeze simulation and its role in modulating thermal comfort. The results contribute to a better understanding of mesoscale interactions between urban environments and regional climate processes during extreme heat events, with implications for assessing and mitigating heat stress in coastal cities.

How to cite: Román-Cascón, C., Carbone, J., Luján-Amoraga, E., Ortiz-Corral, P., Martilli, A., Sánchez, B., Sastre, M., Bolado-Penagos, M., Álvarez, Ó., and Yagüe, C.: Observational and modelling study of coastal breezes and thermal comfort under heatwave conditions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9908, https://doi.org/10.5194/egusphere-egu26-9908, 2026.

EGU26-9908

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Vegetation plays a key role in the interchange of water, energy, and carbon fluxes between the land surface and the atmosphere. This study aims to determine the relationship between these fluxes and meteorological conditions, soil moisture, and vegetation dynamics in La Herrería forest area (Madrid, Spain). Observations over two years are available (2018 and 2019) at two nearby mountainous ecosystems with contrasting surface characteristics. The first site (HER) is a grassland with scattered shrubs and trees, while the second site (PORT) exhibits a higher tree density and the soil has a higher sand content, favouring faster water drainage. Turbulent and meteorological variables were measured using eddy-covariance towers, while satellite data was used to estimate the vegetation activity from the normalized difference vegetation index (NDVI). A joint meteorological and turbulent analysis shows that the interannual variability measured at the weather stations is greater than the differences obtained when comparing both locations for the main variables. Both ecosystems show a remarkably similar response to atmospheric forcing, with strong linear correlation for different atmospheric and turbulent parameters. In contrast, vegetation dynamics differ between both sites, showing the impact of soil type on plant growth and demonstrating how precipitation and its distribution modulate vegetation growth and, therefore, CO₂ exchanges with the atmosphere. These results underline the importance of combining in situ flux measurements and remote sensing to better understand how soil and vegetation characteristics modulate land-atmosphere interactions in Mediterranean mountainous environments. 

How to cite: Canino, R., Yagüe, C., and Cicuéndez, V. M.: Characterization of heat, water and CO2 fluxes in La Herrería Forest environment (Madrid, Spain), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13644, https://doi.org/10.5194/egusphere-egu26-13644, 2026.

EGU26-13644

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During the summer of 2025 (23 June–13 July), an intensive meteorological and turbulence observation campaign was conducted in central Madrid within the framework of the AIRTEC2-CM and MULTIURBAN-II projects. Measurements combined data from a permanent meteorological station and a portable high-frequency eddy-covariance system (IRGASON) from the GuMNet network, both installed on a rooftop at 27 m above ground level. Standard meteorological variables, radiative fluxes, and key turbulence parameters, including friction velocity, turbulent kinetic energy, and sensible heat flux, were recorded.

The observational period was dominated by persistent anticyclonic conditions over the Iberian Peninsula, leading to strong atmospheric stability, weak synoptic forcing, and positive geopotential height anomalies at 500 hPa. These conditions favoured the development of thermally driven mesoscale circulations, particularly nocturnal breezes, which interacted with the urban boundary layer and modulated turbulence and mixing processes. Diurnal cycles of meteorological and turbulent variables are analysed with particular emphasis on the evening transition and the nocturnal stable boundary layer.

Several episodes characterized by very stable conditions and elevated NO₂ concentrations (exceeding 100 μg m⁻³) were observed. The onset of nocturnal breezes was associated with enhanced turbulent mixing and a rapid decrease in pollutant concentrations. High-resolution simulations with the WRF mesoscale model are also presented to evaluate its ability to reproduce the observed thermally driven circulations and their impact on the nocturnal urban boundary layer. Overall, the results highlight the key role of mesoscale thermally driven flows in regulating turbulence, mixing, and scalar transport in urban environments under weak synoptic forcing.

How to cite: Yagüe, C., Carbone, J., Sastre, M., Ortiz-Corral, P., Román-Cascón, C., Cicuéndez, V., Martilli, A., Sánchez, B., Santiago, J. L., Inclán, R. M., Sun, J., Viana, S., and Borge, R.: Thermally driven mesoscale circulations and their impact on the urban boundary layer and turbulence in Madrid, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13938, https://doi.org/10.5194/egusphere-egu26-13938, 2026.

EGU26-13938

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Fog and low stratus are a widespread phenomena worldwide, influencing the climate system and human activities. They reflect sunlight, reducing incoming solar radiation, yet also trap Earth’s thermal emission, leading to complex interactions that are not yet fully understood. Fog additionally supplies moisture to ecosystems. In terms of their impacts on human activities, fog reduces visibility, disrupting traffic systems, and, when combined with urban air pollution, can adversely affect human health. Although recent satellite-based research has advanced our understanding of fog and low clouds, accurate observations are still needed in order to describe fog life-cycle phases. Ground-based observations of fog life-cycle processes are essential for constraining the physical parametrization of fog formation and dissipation in weather and climate models.­

To fill these gaps, the Karlsruhe Institute of Technology (KIT), as part of ACTRIS (Aerosol, Clouds and Trace Gases Research Infrastructure), has recently developed a mobile facility: KLOCX (Karlsruhe Low Cloud Exploratory Platform). KLOCX combines in-situ and remote sensing instrumentation, delivering high-resolution vertical and temporal data on fog and low-cloud processes. Here, we analyze KLOCX observations from the TEAMx campaign in Austria’s Inn Valley, spanning the full fog season (winter 2024 – spring 2025). The study aims to identify how life cycle-phases differ among fog types and which mechanisms drive those differences. Our methodology comprised three stages: (1) fog event identification, (2) fog-types classification, and (3) life cycle-phases analysis. Thirty-five fog events were detected and classified by their main physical mechanism prior to fog onset, observing predominantly radiation fog (30 cases), followed by cloud-base lowering fog (3), and precipitation fog (2). These events served as the basis for applying an automated life-cycle algorithm that detected the start and end times of each phase using visibility trends and predefined thresholds. Our results show that the average durations of formation, maturity and dissipation phases vary across fog types. These findings improve our understanding of how complex topography interacts with local atmospheric conditions, which is essential for better models and forecasting accuracy.

How to cite: Keim-Vera, K., Vüllers, J., Pauli, E., Andersen, H., and Cermak, J.: Life-cycle analysis of fog types in the Inn Valley, Austria, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12985, https://doi.org/10.5194/egusphere-egu26-12985, 2026.

EGU26-12985

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In the coastal Atacama Desert, fog and dew represent the main atmospheric water inputs to the surface water balance in a context of near-total absence of precipitation. Both processes originate from the advection of the marine boundary layer (MBL) over the coastal topography, strongly influencing the spatial distribution of xeric, highly adapted ecosystems. Despite advances in understanding MBL advection under fog conditions, the physical differentiation between fog and dew remains unclear due to instrumental limitations, hindering their independent quantification and the assessment of their hydrological role. This study focuses on the thermodynamic characterization of the MBL under fog and dew events in the coastal Atacama Desert and is structured around three main objectives: (1) reclassification of atmospheric water harvesting events, (2) analysis of MBL stability, and (3) assessment of moisture tendency evolution. The analysis is based on a topographic transect of meteorological stations facing the ocean, distributed between 48 and 1354 m a.s.l., using 10-minute observations collected during 2024. Event reclassification integrates visibility measurements and the Fog Low Cloud (FLC) product from the GOES satellite, enabling discrimination between fog and dew beyond the signal provided by standard fog and dew collectors (SFC and SDC). Preliminary results indicate that standard collectors fail to adequately distinguish fog from dew events, as the inclusion of visibility and satellite information increases the annual proportion of dew events from 0.5% to 3.4%, while fog events remain close to 3.4%. Analysis of vertical profiles of potential temperature (θ) and specific humidity (q) shows that fog events are associated with a thermally and moisture well-mixed MBL, whereas dew formation occurs under a stratified (stable) MBL. In particular, the vertical gradient of θ reveals distinct stability thresholds differentiating fog (∂θ/∂z < 0.0020 K m⁻¹) from dew (0.0020 K m⁻¹ < ∂θ/∂z < 0.0031 K m⁻¹) events, while vertical profiles of q do not show significant differences between event types. Finally, the analysis of moisture tendency (∂q/∂t) reveals small but significant differences between fog and dew events, with sharper moisture decreases during dew conditions, indicating stronger atmosphere–surface water exchange at dawn. This study contributes to disentangling the atmospheric processes controlling fog and dew occurrence in the driest place on Earth.

How to cite: Munoz, F., Lobos, F., Acevedo, S., and Del Río, C.: Thermodynamic characterization of the boundary layer under fog and dew events in the coastal hyper-arid climate of the Atacama Desert, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15106, https://doi.org/10.5194/egusphere-egu26-15106, 2026.

EGU26-15106

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Rapid urbanization is a critical factor altering the atmospheric boundary layer environment of metropolitan areas, particularly in the lower atmosphere, where low-altitude aviation and emerging urban air mobility (UAM) operations are expected to occur. Airports located near urban areas are directly influenced by continuous urban expansion, necessitating an assessment of how urbanization-induced changes in temperature and wind affect aircraft operating environments.

This study examines the long-term effects of urbanization on near-surface temperature and wind characteristics in the vicinity of Gimpo International Airport, which is located adjacent to Seoul, South Korea. Using approximately 30 years of observational records and reanalysis datasets, this study aims to examine how urbanization-related changes in the local meteorological environment are associated with conditions relevant to aircraft operations around the airport.

The results indicate that all sites exhibit strong seasonal variability, and there is a persistent long-term increase in annual mean temperatures. This warming trend is most pronounced at the Gimpo site, where urbanization has progressed most rapidly. Regarding wind characteristics, a gradual weakening of near-surface wind speeds was identified in highly urbanized areas. This trend is attributed to increased surface roughness associated with higher building density.

Overall, the combined long-term observational and reanalysis data confirms the co-occurrence of increasing temperature and weakening near-surface wind tendencies in areas surrounding the airport. Furthermore, persistent near-surface warming may influence surface heating and mixing processes in urban-adjacent regions, potentially contributing to long-term changes in the low-level wind environment. From this perspective, the findings of this study provide a fundamental basis for understanding long-term changes in near-airport low-level environments influenced by urbanization.

How to cite: Choi, Y., Kwon, D.-Y., Seo, J., and Won, W.-S.: Urbanization-Induced Changes in Low-Level Temperature and Wind near Gimpo International Airport, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15819, https://doi.org/10.5194/egusphere-egu26-15819, 2026.

EGU26-15819

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General aviation (GA) and emerging urban air mobility (UAM) operations are primarily conducted at low altitudes within the atmospheric boundary layer (ABL), where aircraft are directly exposed to turbulence generated by complex terrain. Despite its operational importance, the physical mechanisms linking boundary-layer flow structures to observed aircraft vibration and response characteristics remain insufficiently understood. This limitation is particularly critical in terrain-influenced ABL environments, where flow variability is dominant and conventional turbulence metrics, such as the eddy dissipation rate (EDR), may provide limited insight into aircraft response characteristics.

In this study, aircraft vibration responses observed during low-altitude flights within the ABL over Jeju Island are analyzed using high-frequency (100 Hz) three-axis acceleration data collected from a Cessna aircraft operating at altitudes of 1,000–2,000 ft AGL. Flight segments near mountainous terrain exhibit relatively enhanced aircraft vibration responses compared to surrounding regions. Root-mean-square (RMS) acceleration and power spectral density (PSD) analyses are employed to examine the directional dependence and anisotropic characteristics of aircraft responses under low-altitude turbulent conditions.

To interpret the observed aircraft responses from an ABL physics perspective, numerical simulations are conducted using a high-resolution atmospheric flow model capable of resolving terrain-induced boundary-layer flow structures. These simulations are intended to analyze the spatial and temporal relationships between terrain-modified ABL flow variability and the locations and times at which enhanced aircraft vibration responses are observed.

Rather than treating aircraft acceleration as a direct measure of atmospheric turbulence intensity, this study interprets it as a manifestation of aircraft response to localized ABL flow variability shaped by complex terrain. Through this approach, the study explores the potential of terrain-resolving numerical simulations as an interpretative tool for linking boundary-layer flow structures with low-altitude aircraft responses. The findings of this work are expected to provide meaningful implications for low-altitude flight safety assessment, UAM corridor design, and the applied extension of ABL research. 

How to cite: Kwon, D., Choi, Y., Seo, J., and Won, W.-S.: Aircraft Vibration Responses to Terrain-Induced Boundary-Layer Flow Variability during Low-Altitude Flights, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16036, https://doi.org/10.5194/egusphere-egu26-16036, 2026.

EGU26-16036

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Atmospheric aerosols in the Amazon forest exhibit strong temporal variability driven by seasonally changing sources and boundary-layer processes [1]. In central Amazonia, wet-season conditions are typically dominated by biogenic emissions and secondary organic aerosol (SOA) formation, whereas dry-season conditions are strongly influenced by biomass-burning emissions and long-range transport events [2]. This variability makes the region a natural laboratory for investigating aerosol–boundary layer interactions and vertical exchange processes.

The occurrence of convection, turbulence, and boundary-layer dynamics promotes the vertical motion of particles and trace gases [3]. These processes govern the exchange of particles between atmospheric layers, allowing surface-emitted aerosols to reach the free troposphere through deep convection, while SOA formed at higher levels may be reintroduced into the boundary layer through subsidence and downdrafts. Convective downdrafts associated with precipitation have also been shown to increase ground-level ozone concentration, contributing to new particle formation and growth [4].

In this context, this study aims to evaluate particle and ozone fluxes over the central Amazon, quantifying the importance of vertical transport mechanisms for the atmospheric composition within the lower troposphere. A diverse range of ground-based measurements performed at the 325-m Amazon Tall Tower Observatory (ATTO) was employed, combining long-term aerosol observations, sonic anemometer measurements, and a novel robotic lift system [5] that enables continuous vertical profiling of aerosol properties.

Both eddy covariance and flux-gradient techniques were employed to derive vertical fluxes of particles and ozone during clean wet season conditions. The gradient-based analysis reveals coherent vertical flux patterns associated with rainfall intensity, boundary-layer stratification, and diurnal evolution. Deposition aerosol fluxes dominated, with a mean value of −0.28(12) × 10⁶ m⁻² s⁻¹, in agreement with other flux studies conducted in the Amazon region [6]. Furthermore, negative ozone fluxes were also consistently observed during strong precipitation, indicating the downward transport of ozone-rich air from upper levels in these events.

This study sheds light on the magnitude and importance of multiple vertical transport mechanisms, including emission, dry and wet deposition, downdrafts, and the diurnal evolution of the boundary layer, for the variability of aerosol concentrations in the Amazon. Our results provide quantitative constraints on sources, sinks, and transformation pathways of aerosol particles, contributing to an improved understanding of aerosol–turbulence interactions in tropical forest environments and their implications for the local climate.

[1] P. Artaxo, et al. Tellus Series B 24.1 (2022): 24–163.

[2] R. Valiati, et al. Atmos. Chem. Phys. 25.21 (2025): 14923–14944.

[3] L. A. T. Machado, et al. Atmos. Chem. Phys. 21.23 (2021): 18065–18086.

[4] L. A. T. Machado, et al. Nat. Geosci. 17 (2024): 1225–1232.

[5] S. Brill, et al. Atmos. Meas. Tech. 19.1 (2026): 101–118.

[6] L. Ahlm, et al. Atmos. Chem. Phys. 9.24 (2009): 9381–9400.

How to cite: Valiati, R., Dias-Júnior, C., Brill, S., Meller, B., Tsokankunku, A., Pöhlker, C., and Artaxo, P.: Aerosol and ozone vertical distribution and fluxes over the Amazonian boundary layer, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17534, https://doi.org/10.5194/egusphere-egu26-17534, 2026.

EGU26-17534

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Severe wintertime fog frequently affects Delhi National Capital Rregion (NCR), causing extreme visibility reduction and exacerbating air quality and transportation disruptions. Fog formation over the Indo-Gangetic Plain is commonly linked to high aerosol loading, elevated humidity, and favourable synoptic conditions; however, the influence of rapid urban expansion and land-use driven surface processes driven by micro-meteorology remains unexplored. Urban built-up surface possesses distinct radiative and thermal properties compared to surrounding agricultural land, potentially modifying nocturnal cooling, near-surface microclimate and thus vertical structure of fog.

This study investigates the influence of urban expansion over the last three decades on the surface energy balance and its feedback on different stages of urban fog genesis to delineate the aerosol induced effects across the extensive urban built-up landmass of the Delhi–NCR region. High-resolution (9–3–1 km) numerical simulations are conducted using the WRF-ARW/Chem model, employing historical (1992) and latest (2024) urban land-use datasets to isolate the impact of urban expansion and to examine the coupled effects of aerosols, radiation and microphysics. The model reasonably captures the spatial and temporal evolution of observed fog events.

Results show that urban built-up areas in Delhi–NCR have expanded by over 100% in recent decades, primarily replacing irrigated cropland and vegetation, thereby altering surface radiative-thermal properties and intensifying the urban heat island effect resulting in distinct impact and effect of surface cooling after sunset. Consequently, during dense fog events, fog onset over urban areas is delayed and dissipation occurs earlier than over surrounding agricultural regions, leading to reduced liquid water content across the fog life cycle, both spatially and vertically. In contrast, radiative fog event exhibits an increase in LWC during the fog evolution, with a pronounced enhancement in the lower fog layers and a simultaneous reduction in the upper fog layers. This vertical redistribution of LWC is consistently reproduced in urban sensitivity simulations. Furthermore, WRF-Chem simulations reveal stronger LWC increases (>0.5 g kg^-1) during fog initiation and continues to enhance in the upper fog layers throughout the event, while LWC decreases (< -0.4 g kg^-1) in the lower layers during fog development and dissipation.

Overall, the results demonstrate that urban expansion influences fog initiation and dissipation but also its vertical structure and microphysical characteristics through combined thermal and chemical feedback. The results highlight an underexplored pathway linking urbanization and aerosol feedback, surface thermal dynamics, and atmospheric chemistry in fog genesis. 

How to cite: Patel, A., Sheoran, R., Reddy, M. C., Liu, Dr. P., and Gunthe, Dr. S. S.: Urban built-up expansion induced accelerated surface cooling modulates fog genesis over Delhi, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17840, https://doi.org/10.5194/egusphere-egu26-17840, 2026.

EGU26-17840

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Networks of commercial lidars are being deployed in cities to study how urban surfaces affect the planetary boundary layer (PBL). These observations are essential input for numerical models at various scales. Due to the size and complexity of urban modifications of the PBL, dense networks of sensors and models are required. Our study considers the outcomes from an intensive observation campaign within the greater Paris, France area in 2023 and 2024. The results of this campaign are used to develop, compare and integrate model simulations of the urban atmosphere (e.g., UrbanAIR, Urbisphere). 

The wind field, clouds and structures in the atmospheric boundary layer can be routinely extracted from Doppler lidar (DWL) and ceilometer lidar (ALC) observations. The co-location of such instruments allows diurnal mixed/mixing layer development to be assessed together with turbulence statistics. However, because lidar observations are inherently noisy, the derived outcomes require careful evaluation. 

We present a comprehensive dataset that has been prepared for the purpose of model evaluations. We investigate the impact of processing algorithms on the quantification and classifications of atmospheric boundary layer properties. The approach involves aligning the computations with the level-configuration of models. We will highlight prominent patterns in the observations and examine how they relate to the direction and magnitude of flow relative to the surrounding urban and rural environment, as well as discuss the limitations of comparing such observations with numerical models. 

How to cite: Zeeman, M., Looschelders, D., Andrae, U., Menon, A., Theeuwes, N., Wurtz, J., and Christen, A.: Integration of ground-based lidar remote sensing products for model evaluation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20240, https://doi.org/10.5194/egusphere-egu26-20240, 2026.

EGU26-20240

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Observations from the Pampa-2016 field campaign over southern Brazilian grasslands documented nights with a distinct nocturnal transition between two stable boundary layer (SBL) regimes a Very Stable Boundary Layer (VSBL) shortly after sunset, followed by a transition to a Weakly Stable Boundary Layer (WSBL) after midnight. This work investigates the physical mechanisms and forcing components required to reproduce such regime shifts using Large-Eddy Simulations (LES) with the PALM model. The simulations are initialized using convective boundary layer (CBL) profiles observed during the campaign and integrated through a complete diurnal cycle to resolve the evening transition. The numerical domain assumes horizontal homogeneity, representing the natural grassland footprint of the 30 m flux tower. The SBL regime transition is analyzed through the relationship between wind speed (V) and turbulence intensity diagnosed from the square root of the turbulence kinetic energy (VTKE). Model performance is evaluated against tower measurements at 3 m and 29 m and 3-hourly radiosoundings. The comparisons focus on turbulence quantities and in the vertical structure of potential temperature, including inversion strength and depth. Finally, the individual terms of the TKE budget are analyzed to assess the relative roles of radiative cooling and shear-driven mixing during the transition from a radiation-dominated VSBL to a turbulence-driven WSBL.

How to cite: Camponogara, L. F., Serra Neto, E. M., Santos, J. L. S. D., Gomes, T. F., Maroneze, R., and Costa, F. D.: Simulation of turbulence recovery in the stable boundary layer over Pampa grasslands using the PALM model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18827, https://doi.org/10.5194/egusphere-egu26-18827, 2026.

EGU26-18827

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In urban environments, wind is a key meteorological factor that strongly affects the lives of urban residents, including the dispersion of air pollutants and heat as well as thermal comfort at pedestrian level. The distribution of building heights is a major determinant of the surrounding wind field patterns. Solar radiation is also known to exert a substantial influence on the wind field through surface heating and shadow induced thermal contrasts. Therefore, as a fundamental study for urban modeling aimed at predicting urban microclimates, this work quantitatively analyzes how building height variation and radiative heat transfer affect the urban wind environment. To simulate the urban wind environment, we use the PALM large eddy simulation model under idealized urban conditions to examine differences in the wind field around buildings associated with changes in the height distribution of high rise buildings. Under conditions without the radiation module, we compare experiments with different high rise building heights to identify differences in wind distribution at pedestrian level. With the radiation module activated for the same building configurations, changes in turbulent kinetic energy driven by radiation are found. In future work, we plan to extend these findings to simulations of real urban environments. The results obtained under such idealized conditions are expected to provide a basic reference for interpreting physical processes and validating model results in simulations of complex real world urban settings.

How to cite: Lee, S.-H., Kim, J., and Yoo, J.: Analysis of wind field and turbulence characteristics according to high-rise building distribution and surface radiation conditions using PALM, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2910, https://doi.org/10.5194/egusphere-egu26-2910, 2026.

EGU26-2910

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This study develops a novel implicit large-eddy simulation (ILES) model with strict energy-conserving properties, named Turpy, for high-resolution analysis of microscale turbulent structures in the atmospheric boundary layer. The model is implemented natively in Python and leverages the machine learning framework Pytorch to enable efficient GPU computation, achieving parallel scalability exceeding 90% at meter-scale spatial resolution. The numerics of Turpy is tailored towards the meter-scale turbulence simulation: first, the model adopts the energy-conserving form of the compressible Euler equations as the governing system, ensuring total energy conservation while naturally representing the conversion between internal and kinetic energy; second, the model employs a finite-volume discretization without introducing explicit scale filtering, and subgrid-scale effects are represented through the numerical dissipation generated by a Low Mach Number Approximate Riemann Solver (LMARS), eliminating the need for additional subgrid-scale turbulence parameterizations. Numerical experiments demonstrate that Turpy can reasonably reproduce the characteristic structures of wind and temperature fields in the boundary layer under different thermal stratification conditions. Furthermore, by incorporating a wind turbine model, Turpy accurately captures the spatial structure and evolution of wind turbine wakes, highlighting its strong capability and application potential in boundary-layer turbulence research and wind energy applications.

How to cite: Zhang, W. and Chen, X.: Turpy: A GPU-Native implicit LES Model for Meter-Scale Boundary Layer Turbulence Based on Energy-Conserving LMARS Dynamics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4621, https://doi.org/10.5194/egusphere-egu26-4621, 2026.

EGU26-4621

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The complex structure of the urban canopy and the high spatial heterogeneity of emission sources significantly influence the turbulent dispersion, mixing, and chemical reactions of atmospheric pollutants. However, due to the limitation of model resolutions and insufficient understanding of these processes, current mesoscale atmospheric chemical models struggle to accurately represent these interactions, contributing to major uncertainties in urban air quality simulations. To address this issue, this study employs high-resolution computational fluid dynamics (CFD) simulations with explicitly resolved buildings and large-eddy simulations (LES) coupled with an urban canopy model to systematically investigate the synergistic effects of spatial heterogeneity in building morphology and emission distributions on pollutant turbulent dispersion and chemical reactions. The research will quantify the impact of subgrid-scale heterogeneity on effective chemical reaction rates and develop parameterization schemes for subgrid-scale pollutant turbulent diffusion coefficients and effective chemical reaction rates, designed for mesoscale models.

How to cite: Wang, Y.: Impact of subgrid-scale spatial heterogeneity in the urban canopy on pollutant turbulent dispersion and chemical reactions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6260, https://doi.org/10.5194/egusphere-egu26-6260, 2026.

EGU26-6260

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Very stable boundary layers (SBLs) exhibit weak, intermittent turbulence with strongly suppressed vertical motions. In these conditions  turbulence is highly anisotropic and varies strongly in space and time. As a result, common scaling approaches and turbulence closures that assume near‑isotropy or rely only on bulk fluxes (e.g., MOST) often fail to represent momentum and scalar transport in very stable regimes. Moreover, many Large Eddy Simulation setups and subgrid models tend to produce overly isotropic small‑scale motions, masking the true scale dependence of anisotropy.

We analyze high-resolution Large Eddy Simulation data from the psNCAR LES code simulating the GABLS1 and modified GABLES 3 case, that correspond to canonical high-Reynolds-number stably stratified boundary layers driven by constant geostrophic winds over a horizontally homogeneous surface, and two different surface cooling rates corresponding to weakly and strongly stratified turbulence. The domain size is 400 m × 400 m × 400 m with a fine grid resolution of approximately 20 cm, enabling detailed capture of turbulent structures. This spatial resolution enables us to determine the scales at which turbulence remains anisotropic, minimizing the influence of subgrid‑scale parameterizations.

How to cite: Wedel, M.-S. and Stiperski, I.: Scale‑Aware Anisotropy in Very Stable Boundary Layers: Insights from Ultra‑High‑Resolution LES, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6798, https://doi.org/10.5194/egusphere-egu26-6798, 2026.

EGU26-6798

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Planetary boundary layer (PBL) parameterizations depend on spatially and temporally invariant empirical parameters. These are commonly set by comparing parameterization output with large-eddy simulations (LES) and seeking for the parameter values that minimize the differences. Model errors are caused not only by the oversimplified closure assumptions (structural error), but also by the suboptimal specification of spatially and temporally invariant empirical parameters (parameteric error).

We seek to improve the accuracy of PBL parameterization schemes by making parameters adaptive to atmospheric conditions, and therefore spatially and temporally dependent, using ensemble-based parameter estimation (PE). To achieve this, we utilize an idealized modelling environment implemented with WRF and DART. We conduct Observing System Simulation Experiments (OSSEs), which involve an LES serving as the virtual truth and an ensemble of single-column models (SCM), where the only model error source is the PBL parameterization. Based on previously published parameter identifiability studies, we focus on global parameters influencing the parameterized vertical turbulent mixing. We assimilate vertical profiles from LES using the Ensemble Adjustment Kalman Filter (EAKF), in order to objectively adjust empirical turbulence parameters.

Specifically, we focus on the YSU PBL scheme, which implements a first-order turbulence closure. The empirical parameters in this scheme were originally determined through subjective comparison with a set of dry LES, which represent various wind speed and sensible heat flux regimes. We feed synthetic observations from these LES into the PE algorithm and demonstrate that adjusting turbulence parameters using ensemble-based methods outperforms experiments that estimate the state alone. Moreover, we address the limitations imposed by the EAKF’s linearity assumption. Finally, we discuss how the estimated parameters are affected by environmental conditions.

How to cite: Fritz, M., Serafin, S., and Weissmann, M.: Parameter estimation for the YSU boundary-layer turbulence scheme, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9274, https://doi.org/10.5194/egusphere-egu26-9274, 2026.

EGU26-9274

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Challenges in the numerical simulation of atmospheric flows persist in representing surface roughness effects and near-wall turbulence. While Monin-Obhukov similarity theory (MOST) is extensively used in many numerical solvers due to it's simplicity and efficiency, its limitations are well known, prominently under very stable stratification and over rough surfaces (e.g., [1, 2]). The binding element is the atmospheric surface layer that exhibits strong variability in structure and thickness. Emerging dynamical features, in particular intermittency and laminar-turbulent transitions, present core challenges for advanced surface-flux parameterization. Here, an idealized Atmospheric Boundary Layer (ABL), the so-called Ekman Boundary Layer (EBL) is numerically analyzed to address some of the aforementioned challenges utilizing the dimensionally reduced, stochastic One-Dimensional Turbulence (ODT) model. ODT was applied previously as a stand-alone tool to stratified EBL flows over (almost) smooth and very rough surfaces [3, 4, 5], demonstrating predictive capabilities relevant for developing advanced wall models. Recently, the model has been utilized to obtain homogeneous roughness parameterizations for various types of surfaces in channel flow, demonstrating forward modeling capabilities for the Reynolds shear stress otherwise prescribed, e.g., in widely used Reynolds-averaged Navier-Stokes models [6]. In the contribution, the model's capabilities to capture turbulent-laminar regime transitions are discussed and ongoing work on parameterization for dynamic effects associated with roughness-induced drag is presented.

References

[1] M. Optis, A. Monahan, F. C. Bosveld (2016). Limitations and breakdown of Monin–Obukhov similarity theory for wind profile extrapolation under stable stratification. Wind Energy, 19, 1053–1072. https://doi.org/10.1002/we.1883

[2] J. Kostelecky, C. Ansorge (2025). Surface roughness in stratified turbulent Ekman flow. Boundary-Layer Meteorology, 191, 5. https://doi.org/10.1007/s10546-024-00895-5

[3] A. R. Kerstein, S. Wunsch (2006). Simulation of a Stably Stratified Atmospheric Boundary Layer Using One-Dimensional Turbulence. Boundary-Layer Meteorology, 118, 325-356. https://doi.org/10.1007/s10546-005-9004-x

[4] L. S. Freire, M. Chamecki (2018). A one-dimensional stochastic model of turbulence within and above plant canopies. Agricultural and Forest Meteorology, 250-251, 9-23. https://doi.org/10.1016/j.agrformet.2017.12.211

[5] M. Klein, H. Schmidt (2022). Exploring stratification effects in stable Ekman boundary layers using a stochastic one-dimensional turbulence model. Advances in Science and Research, 19, 117-136. https://doi.org/10.5194/asr-19-117-2022

[6] J. A. Medina Méndez, M. Klein, J. W. R. Peeters, H. Schmidt (2026). International Journal of Heat and Fluid Flow, 117, 110113. https://doi.org/10.1016/j.ijheatfluidflow.2025.110113

How to cite: Shampa, M. N., Klein, M., Medina Méndez, J. A., and Schmidt, H.: Modeling transitional boundary layers over smooth and rough sufaces with a map-based stochastic modeling approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12837, https://doi.org/10.5194/egusphere-egu26-12837, 2026.

EGU26-12837

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As a part of the Agricultural Meteorology research unit at Met Éireann, atmospheric dispersion modelling (ADM) is used to investigate and provide forecast for emergency and risk awareness networks. ADM is performed computationally to create mathematical simulations of the transport and dispersion of particles in the atmosphere. At present, Met Éireann uses the HYSPLIT  program in order to calculate and model the trajectory and concentrations of airborne pollutants. HYSPLIT allows for a high degree of customization of the pollutant source terms, which enables dispersion modelling estimations of emission from both man-made and natural sources of interest, including but not limited to nuclear release, smoke, small insects and pollen. This can be used to predict future concentrations, depositions and arrival times of particles under specific scenarios.

Met Éireann currently acts in support of the EPA for nuclear dispersion modelling, in the event of an emergency. We provide daily meteorological forecast data to the EPA and, as a part of the Response and Assistance Network (RANET), can provide additional modelling during an event if requested. We participated with the EPA during the ConvEx-3 exercise in 2025, simulating a nuclear emergency in Romania, to test our communication and dispersion modelling capabilities. Our communications during the event were responsive and modelling results across multiple programs agreed. The experience of the exercise will be used in the development of ensemble dispersion modelling pipelines for future events.

Met Éireann also runs an operational daily forecast of Bluetongue virus, which is based on dispersion modelling the possible transport of the insect that act as the vector. This is provided to relevant agricultural stakeholders, particularly in close collaboration with UCD and DAFM. As climate change continues, a range of pests and possible disease vectors that were either previously unknown to Ireland or inactive at certain times of the year could potentially harm native species of plants & animals. This may necessitate further research and expansion of the current dispersion work on forecasting possible pest or disease vector risks.

How to cite: McKeague, S., Finkele, K., and Varghese, S.: Investigating nuclear events and vector borne disease risk through atmospheric dispersion modelling with HYSPLIT, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7513, https://doi.org/10.5194/egusphere-egu26-7513, 2026.

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EGU26-7513

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