Orals: Thu, 7 May, 14:00–18:00 | Room E2
Many natural ecosystems are subject to fine scale variability in biogeophysical and biogeochemical properties, consisting of a mosaic of patches with individual characteristics in e.g. vegetation, hydrology, or microclimate. Carbon cycle fingerprints between patch types may exhibit strong differences, and reactions to current variability in external forcing as well as to future climate change may substantially differ across spatial gradients of often just a few meters or less. Capturing a representative carbon budget for such landscapes is highly challenging, since footprints of common observation techniques are either rather small with limited representativeness (e.g. flux chambers), or rather large and therefore aggregating signals across multiple patch types (e.g. eddy covariance).
This study is based on a 2025 field campaign at Stordalen Mire in Northern Sweden, a highly structured wetland consisting of a patchwork of fens, bogs, palsas and open water areas. Observational platforms included 2 eddy covariance towers with different instrument heights but nested footprints, stationary (fixed collars) and mobile chamber flux measurements within the tower footprints, a floating mobile auto-chamber system for distributed observations across different lakes and lake zones, and a drone equipped with in-situ greenhouse gas analyzers and meteorological sensors for landscape-integrating surveys using grid, curtain and profile flights. Since all platforms focused their observations on the same wetland section (about 500x500m), our dataset allows to merge detailed process information for individual ecosystem patches (e.g. from flux chamber data) with the landscape-scale integrative products (e.g. by eddy towers or drone).
We present results from different scaling approaches for deriving ecosystem-scale CO2 and CH4 budgets and variability, including e.g. data-driven upscaling, decomposition of eddy-covariance observations into patch-level fluxes, and local scale inversion of drone observations, each focusing on different subsets of the observational database. Through combining all data streams we aim at reducing uncertainties in wetland-scale carbon budgets as well as in the assessment of flux representativeness for the larger region. Comparing upscaled fluxes reveals strengths and weaknesses of individual data streams for constraining net carbon budgets and identifying functional controls, and delivers guidelines towards optimum upscaling strategies.
How to cite: Göckede, M., Backer Kanakkassery, S., Bolek, A., Eves, N., Ivanova, K., Oxley, L., Pratt, E., Schlutow, M., Triches, N., Vogt, J., Wahl, E., Yazbeck, T., and Heimann, M.: Integrated observations and atmospheric modeling to bridge the scaling gap from local to landscape, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5481, https://doi.org/10.5194/egusphere-egu26-5481, 2026.
Low-level airborne eddy covariance measurements enable the characterization of how surface heterogeneity in Arctic permafrost regions influences the spatial variability of greenhouse gas exchange. This study uses the Polar-5 aircraft to collect high-frequency (20 Hz) data on wind, CO₂, and CH₄ over the Mackenzie Delta, Canada, in 2013. The aircraft operated at approximately 40–60 m above ground level (AGL), enabling detailed observation of near-surface greenhouse gas flux. Flight legs were partitioned into three regions based on surface-type classifications, elevation, and degree of surface heterogeneity. Using wavelet analyses, the scale-dependent variances and covariances (fluxes) are quantified across horizontal scales ranging from microscale (10 m – 2 km) to mesoscale (2-10 km). The results demonstrate that scalar variances exhibit clear scale dependence, linked to surface types, elevation, and the level of heterogeneity. Specifically, CH₄ and CO₂ concentrations and fluxes exhibit enhanced small-scale variability over highly heterogeneous terrain, whereas wetland- and lake-dominated regions are characterized by stronger mesoscale variability. By partitioning the domain into three regions, we highlight how the underlying state of permafrost and surface classification jointly affect greenhouse gas flux. Our findings provide a process-based framework that connects heterogeneity level, variance scaling, and the detectability of airborne fluxes in Arctic permafrost landscapes, thereby enhancing the interpretation of aircraft eddy covariance measurements for regional greenhouse gas budgets, compared to flux tower measurements.
How to cite: Lin, G., Sachs, T., Helbig, M., Hogan, P., and Lotz, C.: Characterizing Scale-Dependent Variance and Flux Patterns Across Heterogeneous Permafrost Landscapes Using Airborne Measurements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12312, https://doi.org/10.5194/egusphere-egu26-12312, 2026.
How to cite: Tomelleri, E., Candotti, A., Callesen, T., and Montagnani, L.: Disentangling the Effects of Forest Structural Heterogeneity on Observed Ecosystem Carbon and Water Fluxes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17305, https://doi.org/10.5194/egusphere-egu26-17305, 2026.
Forests and clouds are central to Earth’s carbon and water cycles, yet they are rarely studied as a coupled system. Recent observations reveal concurrent shifts in forest CO₂ uptake and cloud regimes across tropical, temperate, and boreal biomes, signaling changes in forest–atmosphere coupling with profound implications for cloud cycling and climate feedbacks. While rising CO₂ may enhance forest assimilation, declining trends in low cloud cover alters radiative fluxes and amplifies warming, potentially modifying forest photosynthesis, turbulence, and biogenic volatile organic compound emissions. In turn, these processes influence clear/cloud boundary layer dynamics by controlling the partitioning of canopy turbulent fluxes, influence boundary-layer dynamics and cloud formation. Yet current Earth system models largely overlook these cross-scale interactions.
To advance our understanding on the forest-cloud coupling, we focus on the Amazon basin as a proof-of-concept where we integrate field observations from the CloudRoots-Amazon22 campaign with new multi-layer canopy large-eddy simulations that explicitly resolve interactions between the forest canopy and the clear/cloudy boundary layer. The CloudRoots-Amazon22 experiment, conducted at the ATTO and Campina supersites during the August 2022 dry season, investigated the sub-diurnal evolution of the common clear-to-cloudy transition in the Amazon.
High-frequency observations reveal that stomatal conductance responds to variations in cloud optical thickness, demonstrating that canopy–cloud radiative perturbations regulate sub-diurnal canopy carbon and water exchange. Turbulent fluxes and vertical transport adjust within minutes to cloud passages, highlighting rapid land–atmosphere coupling. Collocated surface fluxes, profiles of thermodynamic variables, and CO₂ concentrations, further establish causal links between biophysical canopy processes and cloud dynamical development.
Building on these insights, we present an integrated framework that combines high-frequency observations with turbulence-resolving simulations embedded in global storm-resolving models to quantify shifts in cloud–forest coupling under climate change. This coupled approach advances our understanding of how cloud-radiative perturbations, turbulent transport, and photosynthesis co-evolve, bridging leaf-level processes and cloud-scale dynamics, and provides a pathway to constrain key uncertainties in Earth system models.
How to cite: Vila-Guerau de Arellano, J., Moonen, R., deFeiter, V., deBoer, H., Hartogensis, O., Röckmann, T., and Gonzalez-Armas, R.: Cloud–Forest Coupling: New insights integrating Amazon Observations and Explicit Canopy-Cloud Simulations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1708, https://doi.org/10.5194/egusphere-egu26-1708, 2026.
The effects of desert afforestation, such as those used for climate change mitigation, during extreme heat events remain an important yet unresolved question. The well-studied, semi-arid Yatir pine forest, located at the edge of the Negev Desert, provides a unique lens through which we study land surface-atmosphere interactions.
Due to high incoming solar radiation and low albedo, the Yatir Forest's net radiation is higher than in any other eco-region. The massive radiation load is balanced by large sensible heat flux, which can influence the forest microclimate and create a thermal contrast with the surrounding shrubland. These processes, in turn, can affect near-surface atmospheric conditions and boundary-layer dynamics.
Here, we combine in-situ measurements with high-resolution ICON-LAM simulations to offer new insights into the role of local afforestation in shaping surface weather and boundary-layer dynamics during extreme heat events. The in-situ observations not only describe the forest’s physical and physiological properties but also provide essential inputs for the model, enabling an integrated framework that captures known forest-scale processes and demonstrates their upscaling effects across the region.
Our simulations of a heat wave event from May 20 to May 24, 2019, reveal midday sensible heat flux increases of up to 300 W m⁻² within the forest, resulting in surface (skin) cooling of up to 15 °C, while simultaneously producing warming of up to 2 °C in 2-m air temperature. These contrasts generate pronounced modifications in wind patterns and a distinct forest-induced circulation. Remarkably, this circulation produces strong local instability even under synoptic conditions dominated by harsh subsidence. Our findings underscore the complex and sometimes counterintuitive role of semi-arid afforestation during extreme heat events, with important implications for land-management strategies under different atmospheric forcing regimes.
How to cite: Menachem, Y., Magaritz-Ronen, L., Rotenberg, E., Hochman, L., Raveh-Rubin, S., and Yakir, D.: The Complex Role of Semi-Arid Afforestation-Atmosphere Interactions In Shaping Local Weather, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10326, https://doi.org/10.5194/egusphere-egu26-10326, 2026.
Semi-arid landscapes dominate much of Kenya, yet their contribution to regional carbon cycling remains poorly constrained, particularly regarding how peak ecosystem photosynthetic capacity responds to highly variable wet-season rainfall. Here, we synthesize eddy covariance observations from four contrasting Kenyan dryland ecosystems, including natural savannas—a managed savanna grassland at Kapiti and a wooded savanna at Choke—and croplands—a smallholder system at Maktau and a commercial farm at Ausquest. We examine how rainfall, canopy development, and atmospheric demand jointly regulate maximum net ecosystem CO₂ uptake (NEEₘₐₓ) during the wet season, when most annual carbon assimilation occurs and interannual variability in precipitation pulses is pronounced.
Site-specific relationships between rainfall and NEEₘₐₓ were derived, and responses to temperature and vapour pressure deficit (T–VPD) were analysed under light-saturated conditions to disentangle water supply effects from atmospheric constraints on photosynthesis. Across all sites, rainfall primarily acted as a trigger for peak carbon uptake, with NEEₘₐₓ increasing rapidly following rainfall onset but saturating once sufficient soil moisture supported canopy development. In natural savanna ecosystems, increasing rainfall consistently led to higher maximum leaf area index (LAIₘₐₓ) and enhanced NEEₘₐₓ, while differences between grassland and wooded savanna reflected contrasts in vegetation structure and rooting depth. In contrast, croplands exhibited a muted rainfall–NEEₘₐₓ response, with peak uptake largely governed by cropping cycles, crop type, and management practices rather than total rainfall amounts.
Under high-light conditions, temperature and VPD imposed a common upper bound on NEEₘₐₓ across all ecosystems, defining a narrow envelope of maximum photosynthetic capacity. These results demonstrate that peak carbon uptake in East African drylands emerges from interacting controls of rainfall timing, canopy development, vegetation structure, and atmospheric demand and is modulated by management and land use. Our findings provide critical constraints for land–atmosphere coupling in understudied dryland regions and have important implications for modelling carbon cycle responses under increasing rainfall variability and land-use change.
How to cite: Merbold, L., Odongo, V., Räsänen, M., Omondi, J., Tuure, J., Fava, F., Pellikka, P., Vesala, T., Heiskanen, J., Rinne, J., Jackowicz-Korczynski, M., Wooster, M., Dowling, T., Mauder, M., Ceriani, R., and Leitner, S.: When Rain Meets Heat: Drivers of Peak Carbon Uptake in East African Drylands, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14605, https://doi.org/10.5194/egusphere-egu26-14605, 2026.
Effective greenhouse gas (GHG) emission policies rely on accurate and actual GHG emission data. Uncertainties in inventories arise from limited knowledge of actual activity data, the technology actually used and local ecosystem features that altogether need to be considered when estimating GHG emissions from a specific area. Independent monitoring and verification are expected to increase credibility of inventory reports and scenario estimations, ideally at the same spatial and temporal level of integration as the desired GHG inventory.
One key challenge to verify distributed anthropogenic GHG emissions with measured net GHG fluxes is that conventional GHG flux observation techniques are limited to process, facility or ecosystem scales and do rarely integrate over a representative fraction of the gross anthropogenic GHG fluxes in a region or country. We developed and built an observation system based on tall tower eddy covariance as one of the pillars of a future measurement based Danish national GHG observation system and explore its effectiveness to observe the integrated GHG exchange in a representative agricultural landscape.
We measured CO2, CH4, N2O and CO exchanges from a telecommunication mas (Hove, in a Danish agricultural landscape, West of Copenhagen (N 55.716, E12.238) for 15 months. We placed substantial efforts on estimating the origin of the measured fluxes and used this information to improve comparability of observed GHG exchanges with regional IPCC GHG emission inventories comparable.
The presentation focusses on 1. necessary processing steps for estimation of annual net GHG exchange budgets (spectral correction, data quality filtering and gap filling). 2. a novel “flux-landscape approach” to define a common reference area with inventories, and 3. an overview over the results of the comparison between observed GHG exchange and local IPCC inventory.
From these results we conclude that such comparisons strongly depend on the distinction of gross fluxes that are relevant for GHG accounting and reporting from other, biotic fluxes that are currently not climate policy relevant. This is particularly challenging for CO2, where we observe a strong net uptake, while the inventory is dominated by gross emissions.
We acknowledge funding by DFF (Independent Research Fund Denmark, ref. 1127-00308B) and sponsoring by CIBICOM A/S Ballerup Denmark.
How to cite: Ibrom, A., Kissas, K., Gorlenko, A., Wang, Z., Wiesner, S., and Scheutz, C.: On controlling regional greenhouse gas emission inventories with landscape scale flux observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16149, https://doi.org/10.5194/egusphere-egu26-16149, 2026.
Prescribed burns, primarily aimed at preempting uncontrolled fires, present a valuable opportunity for obtaining field measurements on fire and smoke-plume behavior at micro- and sub-microscales. However, this potential remains underutilized for comprehensive data collection with broad spatio-temporal coverage across the burn unit, in part due to underexplored instrumentation strategies and a lack of synchronous, multidisciplinary observations. During a grassland prescribed burn experiment in a valley region, situated in Trinity County, California, the diverse and extensive instrumentation deployed around the 10-acre burn unit enabled the integration of fire-induced wind patterns with fireline evolution history, air-quality measurements, and fuel characteristics. Small uncrewed aircraft system (sUAS)–based infrared imagery tracked fireline progression and spread rate, together with sUAS-based RGB video that additionally helped quantify flame height via computer-vision techniques. Moreover, high-resolution (cm-scale), sUAS-based measurements of pre- and post-burn multispectral imagery and LiDAR point cloud helped quantify burn severity and post-fire residual fuels in combination with ground-based sampling of fuel characteristics (load, height, moisture). In addition, an autonomous, nano-sized, WeatherHive sUAS swarm sampled high‑resolution temperature, relative humidity, and wind data inside the smoke plumes along “lawnmower” trajectories. An Optical Particle Sizer and a DustTrak II measured high-frequency particle size distributions and mass concentrations near the surface, and were collocated with eddy-covariance (EC) instruments along the burn-unit edges, which measured in-situ turbulence and energy flux statistics. Strong fire-induced horizontal wind convergence at the burn-unit edges was captured by the EC sensors amid variable ambient winds. Within the plume, the WeatherHive swarm recorded temperature excursions up to 8°C with upward redirection of near-surface horizontal flow into strong buoyant updrafts. The dynamic local wind direction and fireline proximity strongly modulated the observed near-surface aerosol mass and number concentrations, which were dominated by fine particulate matter (PM2.5), with background conditions recovered about 2.5 hours post-burn. Additionally, data were leveraged to evaluate a physics-based computational module utilizing the popular Reynold-Averaged Navier Stokes or RANS turbulence model. These integrated datasets provide deeper insight into coupled fire-behavior processes, while also illuminating improved measurement strategies for future experiments, including prolonged pre-burn deployment to characterize terrain-induced ambient flow and calculated sensor placement to capture the burn area flux footprint more effectively. Thus, they contribute to a growing observational database useful in advancing predictive models describing fire and smoke behavior, thereby increasing the reliance on prescribed burns for fire management.
How to cite: Desai, A. and the iFireNet Prescribed Burn Research Team: Coupled fire-atmosphere behavior observations from a grassland prescribed burn in a Northern California valley, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8626, https://doi.org/10.5194/egusphere-egu26-8626, 2026.
For many people, beaches are a place they long for and emblematic for summer vacation vibes, even though environmental conditions may be actually physiologically stressful. In order to reduce radiation load, and thereby also exposure to UV radiation, the use of parasols for shading is thus common practise. The parasol, depending on the optical properties of the used fabric, attenuates part of the solar (shortwave) radiation, however at the expense of additional longwave radiation radiated in the downward direction in proportion to the surface temperature of the parasol. Here we ask the question whether sitting under a parasol may actually increase thermal discomfort as the reduction in transmitted shortwave radiation may be compensated by an increase in downward longwave radiation. To this end we have developed a model which allows simulating human thermal comfort in the open (without parasol) compared to below a parasol on a beach. Human thermal comfort is quantified with the Universal Thermal Comfort Index (UTCI). Environmental model inputs are air temperature and relative humidity, mean horizontal wind speed and incident short- and longwave radiation at some reference height above the ground surface. The attenuation of shortwave radiation by the parasol, the upward longwave radiation flux from the sand and the downward longwave radiation flux from the parasol are calculated by solving the radiative and energy balance of the parasol and the sand surface. The radiation calculations below the parasol take the modification of upper and lower hemispheric view factors into account and separately solve for the temperature of the sunlit and shaded sand surface. Our calculations show that the UTCI is generally lower under the parasol (and thus human thermal comfort higher), but differences are often small. Moreover, under certain combinations of conditions, sitting under a parasol feels hotter and we discuss which conditions favour this outcome. Finally, we demonstrate our findings for summertime conditions at some of the globally most well-know beach destinations.
How to cite: Wohlfahrt, G. and Hammerle, A.: The thermal cost of sitting under a parasol: a biometeorological essay, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8096, https://doi.org/10.5194/egusphere-egu26-8096, 2026.
Urban areas are major sources of anthropogenic CO2 emissions, contributing substantially to the global carbon budget. Accurate quantification of urban emissions remains challenging due to uncertainties in measurements and modelling approaches. Eddy covariance (EC) provides direct continuous measurements of net urban CO2 fluxes; however, flux estimates in heterogeneous urban environments can be systematically biased by unresolved micro-scale anthropogenic sources. This study investigates the efficiency of the Identification of Micro-scale Anthropogenic Sources (IMAS) algorithm (Kotthaus and Grimmond, 2012) to detect short-duration, high-frequency micro-scale signals on EC observations. IMAS removes statistically identified micro-scale events from high-frequency data prior to flux computation, enabling retention of standard 30-min averaging periods. Micro-scale event detection is based on statistical metrics computed at 1-min resolution for CO2, H2O and sonic temperature, combining kurtosis, median-based variability, and skewness-sensitive mid-range deviation referenced to a 30-min median.
We applied the IMAS algorithm to two years of continuous EC measurement data, which were collected at the Hardau tall-tower site in the city of Zurich, Switzerland, as part of the ICOS Cities project. Fluxes were measured on a mast on top of a high-rise building at 112 m a.g.l, sampling a heterogeneous footprint influenced by various sources such as residential heating, traffic, railway infrastructure and industrial activities. A local heating unit is located at a horizontal distance of 145 m south-east of the tower, which is used intermittently to support residential heating during cold periods and could potentially affect our tower measurements. Standard EC fluxes and quality control flags were computed using EddyPro software before (L1) and after (L2) the application of the IMAS algorithm. Flux differences between L1 and L2 show a strong dependence on wind direction, with the largest reductions in L2 occuring for sector spanning 120–160°, centered on the direction of a nearby local heating unit (~141°) within the urban footprint. During winter, standard EC processing (L1) overestimates CO2 fluxes by 3.96 ± 0.43 µmol m-2 s-1 (mean ± standard error of the mean) for wind originating from this sector, corresponding to a relative reduction of ~17 % after the IMAS-based removal of micro-scale events. Smaller but consistent mean reductions are also observed for H2O fluxes (0.039 ± 0.005 mmol m-2 s-1, ~12 %) and sensible heat fluxes (4.82 ± 0.75 W m-2, ~38 %). In contrast, IMAS-induced flux changes during summer were minimal. These results demonstrate that unresolved micro-scale emissions can propagate directly into urban CO2 flux calculations, highlighting the need for source-aware, high-frequency preprocessing to complement standard EC quality control in urban carbon flux monitoring.
How to cite: Binoy, A., Sigmund, A., Stagakis, S., and Bigi, A.: Improving Urban Eddy-Covariance CO2 Flux Estimates Through Removal of Anomalies in High-Frequency Data Using the IMAS Algorithm, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6602, https://doi.org/10.5194/egusphere-egu26-6602, 2026.
Eddy-covariance measurements allow us to directly monitor the vertical turbulent CO2 flux at a specific point in the urban atmosphere. Under some assumptions such as stationarity and sufficient turbulence, this flux corresponds to the net emissions in a variable footprint area. Combined with a footprint model and a biospheric CO2 flux model, this method has a high potential for validating and optimizing urban emission inventories. However, the reliability of EC measurements depends on a careful site selection, data processing and quality control. Often, sensor heights below z=50 m a.g.l. are chosen to mitigate issues associated with horizontal heterogeneity, storage flux, and horizontal and vertical advection. The storage flux describes the temporal change of the CO2 amount in the control volume between the surface and sensor height. Tall-tower sites (z>50 m a.g.l.) would be beneficial to capture emissions from a larger part of the city but require careful consideration of these issues. While a few studies have reported plausible EC measurements for urban tall-tower sites, little is known about the impact of the storage flux and advection terms.
In the ICOS-Cities project, tall-tower EC systems and networks of mid-cost and low-cost CO2 concentration sensors were installed in three cities. Here, we aim to better quantify the storage flux and identify periods with horizontal advection by leveraging data from the sensor networks in Zurich, Switzerland, and Munich, Germany, and thus improve the reliability of the observed net CO2 emissions. The low-cost sensors were deployed in the urban canopy layer while the mid-cost sensors were mostly located at the rooftop level and collocated with wind and temperature sensors. We estimate the storage flux by dividing the control volume into three to four layers and averaging data from different sensors in the same layer. The storage flux is then added to the turbulent flux to estimate net surface emissions. To filter out periods in which this estimate is biased by horizontal advection, we consider horizontal CO2 gradients determined using mid-cost sensors at rooftop sites. This approach is compared to the often-used filtering with a friction velocity threshold.
As expected, the storage flux is most important on days with a pronounced diurnal cycle in atmospheric stability. It reduces the net CO2 emission estimates in the morning hours after sunrise and generally increases these estimates at night. From 1.5 to 5 h after sunrise, this effect amounts on average to -7.3 and -8.0 µmol m-2 s-1 in Zurich and Munich, respectively, while in the first 3.5 hours after sunset, it amounts to +4.7 and +3.0 µmol m-2 s-1 (46% and 24% of the turbulent flux) in Zurich and Munich, respectively. On days with a small diurnal cycle in stability, the storage flux plays a smaller role, especially in winter. We will also present insights in the frequency of horizontal advection and favorable conditions for it. Finally, we will discuss the plausibility of median diurnal cycles of the derived net CO2 emissions, considering the directional dependence on land cover and associated sources and sinks.
How to cite: Sigmund, A., Brunner, D., Chen, J., Hilland, R., Christen, A., Feigenwinter, C., Vogt, R., Emmenegger, L., Kalberer, M., and Stagakis, S.: Leveraging CO2 sensor networks to address challenges in urban eddy-covariance measurements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8997, https://doi.org/10.5194/egusphere-egu26-8997, 2026.
Atmospheric CO₂ measurements provide essential constraints for carbon-budget estimates and atmospheric modelling. Virtual tall tower (VTT) methods are a promising, but yet underexamined approach for upscaling ecosystem-level CO₂ concentrations measured at eddy covariance (EC) sites (typically 2–50 m above ground) to atmospheric measurements representative of tall towers (TT; ~100 m and higher). Implementing VTT approaches at existing EC stations could therefore expand the currently sparse network of TT observations. In this study, we evaluate the applicability of a VTT approach using collocated EC–TT measurements. We use 2024 data from the combined ecosystem-atmosphere station Svartberget site in northern Sweden (SE-Svb, SVB), part of the ICOS (Integrated Carbon Observation System) network, with brief examples from one or more other sites. A key advantage of the ICOS Svartberget station is that ecosystem EC and atmospheric TT measurements are available at the same location, with EC observations at 35 m and TT measurements at 35 m and 150 m. The 35 m TT measurements are an important asset for post-hoc calibration correction of the concentrations measured by the EC system, since state-of-the-art EC stations typically do not meet the high calibration requirements of a TT measurement. We implemented the VTT method proposed by Haszpra et al. (2015) and tested the gradient functions of Patton et al. (2003) and Wang et al. (2007) to define a base-run configuration. We then performed a sensitivity analysis of key variables in the VTT formulation. Model performance was evaluated using bias, root mean square error (RMSE), and correlation, by comparing VTT-estimated CO₂ concentrations at the TT top height (150 m) against measured TT concentrations. For 2024, approximately 30% of valid hourly data points met the well-mixed criteria required for VTT application. When treating EC calibration and VTT calculations as separate steps, EC calibration exerted the largest influence on estimated CO₂ at TT height, highlighting calibration as a critical prerequisite for reliable mixed-layer concentration estimates. Sensitivity analysis further showed that, when accounting for both numerical perturbations and measurement uncertainty, the planetary boundary layer height was the most influential variable, producing the largest changes in performance statistics relative to the target TT concentrations. Taken together, these results suggest that VTT approaches could increase the coverage of TT-representative atmospheric CO₂ estimates. Improving planetary boundary layer height (PBLH) estimates should further increase VTT accuracy. Further steps, VTT performance should be tested across additional sites and time periods to assess robustness under different conditions.
How to cite: Marcon-Henge, L., Graf, A., and Peichl, M.: Performance of a Virtual Tall Tower (VTT) approach for estimating CO2 concentrations in the mixed layer from eddy covariance measurements near the surface, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17469, https://doi.org/10.5194/egusphere-egu26-17469, 2026.
One fundamental assumption of surface layer flow theory is homogeneity over a horizontal plane, a hypothesis systematically challenged for many atmospheric flows. For example, variability in terrain elevation, presence of heterogeneous roughness sub-layers and mesoscale motions can alter the spatio-temporal flow evolution even over small distances (≈1 km). In this scenario, the experimental investigation of air-land interactions requires simultaneous data acquisitions at multiple sites, against which the hypothesis of flow homogeneity can be assessed. The Appalachian Mountains (in the Southeastern United States) represent a compelling environment to resolve complex flows over small distances due to their irregular terrain (800-1500 m elevation above sea level) and presence of moderately tall deciduous forests (~20 m) and open fields constituting an uneven roughness sub-layer. In this work, three nearby instrument sites (within 2 km of each another) are investigated as part of the Lidar Experiments for Assessing Flow over Forests (LEAFF) campaign located in and around a deciduous forest in mountainous Virginia (U.S.). Ten months of wind statistics are resolved both within the canopy by a well instrumented flux tower, and above it via four remote sensing Doppler Lidar (up to 300 m above ground, i.e. ≈15 times the forest height), thereby resolving the turbulent flow developing over a roughness sublayer with high statistical accuracy. The goal of the present analysis is twofold. First, to quantify the monthly variability of wind statistics induced by the annual cycles of leaf senescence and synoptic winds. Second, to quantify the heterogeneity of the wind statistics between different but closely spaced sites across different months. A year’s worth of data showed that the wind statistics are predominantly affected by synoptic forcing, while the leaf senescence cycle plays a marginal role in shaping mean wind and turbulence within the surface . Additionally, site-to-site heterogeneity is found to change following a monthly time scale, a result emphasizing the importance of selecting a sufficiently long observational period to correctly address site heterogeneity under different background flow conditions. The present study provides a compelling observational dataset to validate numerical weather prediction tools accounting for the presence of a forest sub-layer, as well as improving our understanding of the physical mechanisms inducing flow heterogeneities over complex terrains.
How to cite: Puccioni, M., Wharton, S., De Wekker, S., Arthur, R., Li, T., Liu, Y., Feng, S., Pressel, K., Rai, R., Berg, L., and Fast, J.: A four-Doppler Lidar study to quantify spatio-temporal heterogeneity of wind statistics over a deciduous forest during the LEAFF campaign, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13713, https://doi.org/10.5194/egusphere-egu26-13713, 2026.
Understory, so within-canopy, eddy-covariance (EC) measurements of energy, water, or CO2 fluxes offer more detailed insights into ecosystem exchange dynamics. Deriving these fluxes from EC systems requires several processing steps, where some of them are only valid for the inertial sublayer (i.e., above the canopy). Here we show that several of these steps are not appropriate for understory EC systems, particularly coordinate rotation, frequency-response correction, and some quality-control procedures. Using a multi-year dataset from a mountain forest site in Austria (At-Mmg), we identify some pitfalls and present precautionary measures.
An underlying assumption of the EC method is that the coordinate system is aligned with the mean flow, which in real-world conditions is not necessarily level or parallel to the surface, requiring coordinate rotations in the post processing of the wind measurements. For complex flow conditions, sectorwise planar fit is a commonly used rotation approach and is often preferred over classical double rotation. We demonstrate advantages of the less commonly used continuous planar fit, which yields more satisfactory results and substantially influences the statistics. Furthermore, the use of seasonal windows is preferable to account for seasonality in the flow structure.
High-frequency response corrections for trace gases (e.g., water vapor, CO₂) require a valid reference spectrum to compensate for instrument-related attenuation. Within the canopy, theoretical reference spectra tailored to the inertial sublayer are not applicable due to altered spectral behavior caused by vegetation elements interacting with the flow. This can introduce additional processes, such as spectral short-cutting, which strongly deviates from expected inertial sublayer behavior and is evident in our dataset. We also show that reference spectra based on temperature measurements are not reliable for trace gases at our site. We therefore explore an experimental, site-specific reference obtained by extrapolating the mid-frequency portion of the CO₂ spectrum to inform corrections.
Quality-control procedures also require revision. Standard turbulence tests assess flux–variance relationships against models to evaluate well-developed turbulence, but these relationships are valid only for the inertial sublayer. Applying them uncritically can misclassify understory data quality. Moreover, some form of low-turbulence filtering is needed. Understory EC systems enable quantification of canopy decoupling, which is becoming an attractive alternative to classical friction-velocity filtering. However, we emphasize that canopy-scale decoupling should not be used to disqualify understory fluxes: for understory measurements, the relevant coupling is between the measurement height and the forest floor, not with the entire canopy.
How to cite: Platter, A., Hammerle, A., and Wohlfahrt, G.: Pitfalls and precautions for understory eddy-covariance processing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7041, https://doi.org/10.5194/egusphere-egu26-7041, 2026.
The persistent lack of energy balance closure in single-tower eddy-covariance measurements remains a major source of uncertainty in surface–atmosphere exchange studies. In most eddy-covariance studies, turbulent fluxes (sensible and latent heat) underestimate available energy (net radiation minus ground heat flux), potentially affecting evapotranspiration estimates used in irrigation management, and propagating uncertainties into land-surface model evaluation and flux upscaling. One important contributor to this imbalance can be the choice of data processing steps, particularly corrections for high-frequency spectral losses, which are known to significantly influence eddy-covariance flux estimates. However, their impact on energy balance closure has not yet been sufficiently quantified for long-term cropland observations.
Here, we investigate how different high-frequency spectral correction methods affect turbulent fluxes and energy balance closure at a managed cropland site in Reinshof, central Germany. Three years of eddy-covariance data collected over rotating crops (winter wheat, winter barley, and sugar beet) during 2022–2024 were processed using EddyPro, applying both analytical (Moncrieff et al., 1997; Massman, 2000; Horst, 1997) and in situ (Ibrom et al., 2007; Fratini et al., 2012) spectral correction methods.
Results show that the choice of spectral correction methods led to differences of up to 3.5% in annual energy balance closure estimates for years using open-path gas analyzers and up to 9.4% for years using closed-path gas analyzers. The in situ correction by Fratini et al. (2012) consistently resulted in the highest energy balance closure across all years, whereas differences among analytical corrections were minor, with a maximum difference of 0.8% in 2023. These effects were driven exclusively by changes in latent heat flux, which increased by 5-15% for open-path systems and by 38% for closed-path systems at the annual scale after spectral correction.
Overall, this study demonstrates that the choice of high-frequency spectral correction methods critically affects energy balance closure estimates in long-term eddy-covariance measurements, with effects varying in magnitude between open- and closed-path systems.
How to cite: Gehrmann, M., Knohl, A., Tunsch, E., and Markwitz, C.: Comparison of high-frequency spectral correction methods for eddy-covariance fluxes over a central German cropland: effects on energy balance closure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7040, https://doi.org/10.5194/egusphere-egu26-7040, 2026.
The disagreement between observed and theoretically expected thermal energy balances in a soil–air system at the ground surface, known as the surface energy imbalance (SEI), has been observed for over 80 years. This intriguing puzzle is marked by a systematic diurnal variation of the SEI across different surface types, beyond observational uncertainties. Guided by total energy conservation, the generalized thermal energy balance equation indicates that the traditional thermal energy balance equation based on the first law of thermodynamics would result in stability-dependent biases. Specifically, it would overestimate the thermal energy increases under convective conditions, underestimate them under stable conditions, and agree with the generalized thermal energy balance under neutral conditions. Considering the diurnal variation of the atmospheric stability within the atmospheric surface layer, these systematic biases align precisely with what field observations reveal in the SEI conundrum. In other words, the observed SEI suggests that a non-isothermal atmosphere is governed by total energy conservation. Furthermore, the limitation of the traditional thermal energy balance equation may also help explain several actively researched issues in the atmospheric boundary layer community, such as the dissimilarity between vertical temperature and humidity profiles under convective conditions and the difficulty of simulating the stable atmospheric boundary layer, including morning and evening transitions.
Turbulence kinetic energy dissipation is estimated using 4-k Hz hot-film observations at four observation heights ranging from 0.5 to 4 m. Its dependence on the atmospheric stability and wind speed is consistent with the development of turbulence driven by both thermal and mechanical forcing. These observations further demonstrate the important contribution of thermal energy transfer to kinetic energy changes, as revealed by the generalized thermal energy balance equation. Overall, this investigation provides additional evidence for the importance of interactions between kinetic and thermal energy variations in explaining the observed surface energy imbalance.
Acknowledgements: The research is supported by the U.S. National Science Foundation, AGS-2231229.
How to cite: Sun, J., Gary Granger, G., Oncley, S., Roden, C., Hoch, S., and Tong, C.: Revisiting the Surface Energy Imbalance with Observed Kinetic Energy Dissipation Guided by the Generalized Thermal Energy Balance, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13286, https://doi.org/10.5194/egusphere-egu26-13286, 2026.
Vertical wind velocity (w) and gas density (c) are two key variables for estimating trace gas fluxes using the eddy covariance (EC) technique. For many decades within the EC community, the Webb, Pearman and Leuning (WPL) theory proposed by Webb et al. (1980) has been widely accepted as a “density effect correction” for flux calculations. However, we found that Webb et al. (1980) derived their equations correctly by calculating the unmeasurable mean vertical velocity (
How to cite: Wang, H., Ma, Y., and Chi, J.: The essence of the Webb, Pearman and Leuning (WPL) correction: w- correction, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10099, https://doi.org/10.5194/egusphere-egu26-10099, 2026.
A unified probability density function (PDF) parameterization for subgrid moist convection and turbulence is developed using a Lagrangian stochastic modeling (LSM) approach. The model solves the transport equations of the joint PDF of turbulent velocity and passive scalars by tracking an ensemble of stochastic particles governed by coupled stochastic differential equations (SDEs). Building on previously developed SDEs for particle velocity and temperature, the LSM is extended to represent inhomogeneous stratified turbulence and its entrainment process. Furthermore, using Lagrangian particle tracking data obtained from large-eddy simulations (LES) of boundary layer and moist convection cases, the SDEs are refined and their parameters are optimized to reproduce the Lagrangian statistics diagnosed from the LES. In the proposed model, turbulence statistics and turbulent fluxes are obtained directly from particle ensembles, providing a full representation of the turbulence PDF without invoking traditional closure assumptions for turbulent transport. The proposed model is evaluated against LES results for convective and stable atmospheric boundary layer (ABL) cases, including shallow convection cases. In convective regimes, the LSM realistically captures entrainment processes and reproduces mean thermodynamic profiles and turbulent fluxes that closely agree with LES results. The simulated joint PDFs exhibit pronounced non-Gaussian features and PDF separation in the entrainment zone. In stable ABL simulations, the LSM predicts realistic turbulence intensities and mean profiles, with near-Gaussian PDFs consistent with LES results. In the shallow convection case, the model simulates realistic vertical structures and variability of convection in the cloud layer. These results demonstrate that the proposed LSM framework provides a physically consistent and flexible approach for simulating both moist convection and turbulence with a full representation of the subgrid-scale PDF.
How to cite: Shin, J.: Unified PDF Parameterization of Subgrid Moist Convection and Turbulence Using a Lagrangian Stochastic Approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18158, https://doi.org/10.5194/egusphere-egu26-18158, 2026.
This research focuses on improving the near-surface performance of an Implicit Large
Eddy Simulation (ILES) model. The ILES model uses the Semi-implicit semi-Lagrangian
numerical method for simulating the atmospheric boundary layer. Moreover, the model
is called an “implicit” model because it includes no explicit scheme to represent
subgrid-scale fluxes but makes use of the numerical dissipation. One of the problems
we’ve met so far is that, for example, in the neutral boundary layer case, some
simulations indicate the weakness of this model in resolving the eddies near the bottom
boundary, which can be reflected by, for example, failure to reproduce a log wind profile
for the neutral case. We hope that this type of issue can be solved by spreading the
eRect of surface flux convergence into several model layers using a surface model. The
purpose of this surface model is to minimize the inability of our ILES model to resolve
the near-surface eddies.
How to cite: Tong, Y., Thuburn, J., and Efstathiou, G.: A Surface Layer Scheme for an Implicit Large Eddy Simulation Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23263, https://doi.org/10.5194/egusphere-egu26-23263, 2026.
Posters on site: Thu, 7 May, 10:45–12:30 | Hall X5
Between 17th -18th December 2023, Tuticorin district and adjoining regions in Southern India experienced an exceptional extreme precipitation event, receiving approximately 950 millimetres of rainfall within 24 hours, leading to severe inundation and extensive losses to agriculture and infrastructure. The fact that the amount of rainfall received on a single day exceeded the average annual rainfall over Tuticorin makes this event particularly noteworthy. This study investigates the hydrological and meteorological drivers responsible for this rare extreme event using high resolution reanalysis datasets and India Meteorological Department 0.25° gridded precipitation data. The influence of Integrated water Vapour Transport (IVT), along with other dynamic factors such as atmospheric instability and total column water vapour on the extreme precipitation is assessed using a factor combination methodology based on conditional probability. Additionally, to reveal the moisture sources for this event, the backward trajectory of moisture particles was traced using HYbrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Results reveal that all three factors exceeded their 99th percentile thresholds, with their peaks occurring one day prior to the rainfall maximum, indicating a strong preconditioning of the atmosphere for extreme convection. HYSPLIT results confirmed sustained moisture influx from the Bay of Bengal and equatorial Indian Ocean up to seven days before the event. A comparative evaluation across El Niño years (1991, 1997, 2005, 2015, and 2023) showed that only the 2023 event exhibited concurrent extremes in all parameters. These findings underscore the compound nature of the 2023 Tuticorin flood and highlight the need for integrated moisture diagnostics in predicting future extreme rainfall events over peninsular India.
How to cite: Ghodichore, N. and Rajendran, V.: Multivariate driver analysis and moisture attribution of the December 2023 Tuticorin floods, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-696, https://doi.org/10.5194/egusphere-egu26-696, 2026.
In mid-latitudes, and over polar regions, a vast majority of precipitations are linked to the production of ice crystals in clouds. Cloud microphysical processes of complex mountain regions, where mixed-phase clouds (MPC) are consistently present, are therefore better represented if the number of ice crystals are correctly estimated. However, observations have shown that measured ice crystal number concentration (ICNC) can exceed the concentration of ice nucleating particles by orders of magnitude. Moreover, model simulations that rely mainly on primary ice production mechanisms usually underestimate ICNC when compared with observations. Blowing snow particles (BSP) are believed to be one of the causes affecting this discrepancy, but their influence on ICNC in MPS remains poorly understood. Our research uses the numerical model CRYOWRF, which includes blowing snow prognostic equations coupled with the advanced land surface snow model SNOWPACK, to analyze how BSP influence the highly nonlinear cloud microphysics and ICNCs. Numerical results are then validated with observation data from the Cloud and Aerosol Characterization Experiment (CLAVE) 2014 campaign at Jungfraujoch. Results show that, when high wind velocities trigger blowing snow transport, due to the strong updraft typical of mountain regions, BSP reach high levels in the atmosphere thus affecting precipitation and snow redistribution.
How to cite: Viaro, S.: Transport of blowing snow particles through turbulent motions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5092, https://doi.org/10.5194/egusphere-egu26-5092, 2026.
Dynamic sub grid-scale turbulence closures require explicit spatial filtering to separate resolved and sub filter-scale contributions. In unstructured-grid atmospheric models such as ICON, constructing consistent filtering operators is nontrivial due to the triangular mesh and the staggered placement of prognostic variables on cells and edges. This work presents the implementation of a spatial filtering framework for the ICON nonhydrostatic dynamical core, designed as methodological infrastructure for scale-aware turbulence modeling.
A coarse-graining filter based on neighbor averaging has been developed on the ICON triangular grid. Cell-centered variables are filtered using edge-connected neighboring cells, while edge-centered variables are treated consistently using the adjacent cell-edge connectivity. The filter may be applied iteratively to achieve a prescribed effective filter width and is compatible with ICON’s block-based data layout on an unstructured mesh.
The filtering operators are integrated into the diffusion module as a diagnostic operation applied after explicit diffusion and halo synchronization, ensuring consistency across MPI subdomain boundaries. Ongoing work focuses on extending this framework toward a dynamic Smagorinsky-type closure using a test-filter formulation.
How to cite: Baksi, A.: Spatial filtering framework for scale-aware turbulence modeling on the ICON unstructured grid., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10777, https://doi.org/10.5194/egusphere-egu26-10777, 2026.
Uncertainty in vertical mixing is a major source of error in simulations of long-lived trace gases such as CO2 in atmospheric chemical transport models. We perform a set of sensitivity experiments with the GEOS-Chem model by applying different scaling factors to the vertical eddy diffusivity (Kz), thereby varying the strength of vertical mixing. Model results are evaluated using aircraft observations from the ASIA-AQ campaign conducted over Asia, a major anthropogenic CO2 source region where simulations are particularly sensitive to the representation of vertical mixing. The observations cover a wide range of boundary-layer and free-tropospheric conditions. Model–observation agreement is quantified using a suite of statistical metrics. Simulations with weaker vertical mixing consistently show better agreement with aircraft observations across regions than the default model configuration. The improved agreement reflects a better representation of the observed vertical and temporal variability. This study suggests that vertical mixing in GEOS-Chem may be overestimated over Asia and provides a basis for improving the model representation of vertical transport.
How to cite: Kim, M., Park, R. J., Jung, J., Oh, S., and Jeong, J. I.: Impact of Vertical Mixing on CO2 Simulations during the ASIA-AQ campaign, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16151, https://doi.org/10.5194/egusphere-egu26-16151, 2026.
Data-driven parameterisations offer a promising route to improving the representation of unresolved processes in geophysical models. In this work, the two-timescale Lorenz 96 system is used as a controlled testbed to systematically compare deterministic, stochastic, and memory-aware machine-learning closures. A range of architectures are implemented, including multilayer perceptrons, convolutional networks, recurrent models, and conditional generative approaches, and are evaluated in both offline and online settings using weather-style forecast metrics and long-term climatological diagnostics. The results show that models incorporating physically motivated inductive biases, such as stochasticity, spatial structure, or temporal memory, outperform simpler deterministic and memoryless closures. In particular, stochastic generative models and recurrent networks better reproduce regime behaviour, spatio-temporal correlations, and long-term statistics, highlighting the importance of representing intrinsic variability and non-Markovian effects. Ongoing and future work will extend this framework to more realistic dynamical systems, including quasi-geostrophic and primitive-equation models, with a focus on enforcing physical consistency, incorporating explicit memory effects, and developing hydrid physics-machine learning closures.
How to cite: Ridao, M.: Data-Driven Parameterisations for the Multiscale Lorenz 96 System , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20490, https://doi.org/10.5194/egusphere-egu26-20490, 2026.
Starting from the spatially filtered equations in the large-eddy simulation (LES) regime,
commonly used turbulence closures assume a local equilibrium between turbulence
production and dissipation, with the closure parameters representing the continuous
cascade of energy from the resolved to the subgrid scales. However, away from grid
resolutions that adequately resolve the inertial subrange of turbulence, this equilibrium
assumption breaks down. Moreover, at such resolutions, the dominant turbulent eddies
are only partially resolved, and the appropriate values of the closure parameters are
generally unknown.
In this study, we explore a dynamic closure for a prognostic turbulent kinetic energy
(TKE) scheme in a quasi-steady convective boundary layer (CBL) case, spanning
resolutions from LES toward the grey zone. The dynamic approach optimises the
closure parameters using information from the resolved small-scale turbulence,
exploiting the assumed similarity between resolved and unresolved scales. Preliminary
results show that the dynamically derived length scales exhibit the desired scale
dependency across resolutions, leading to improved agreement with LES.
How to cite: Efstathiou, G. and Clark, P.: Towards dynamic closures for higher-order turbulence schemes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22783, https://doi.org/10.5194/egusphere-egu26-22783, 2026.
Despite its omnipresence in atmospheric models, the Penman-Monteith (PM) equation often fails to represent the latent heat (LE) flux accurately. Deviations of several tens of % between modelled and observed LE flux are not an exception. The original PM equation assumed a constant stomatal resistance in time, but most current atmospheric models implement a varying resistance that depends on atmospheric conditions such as radiation, temperature and vapor pressure, while more recent models account for plant physiological stomata control.
In this study, we present a diagnosis of LE fluxes modelled based on the Penman-Monteith equation combined with a fixed, an environmentally driven and a plant physiology driven stomatal conductance model versus observed LE fluxes by Eddy-Covariance. The analysis covers a decade of observations for a grass and three years for a forest site in the Netherlands. We identify atmospheric conditions where the model and observations most strongly disagree and evaluate the contribution of varying stomatal resistance models in reproducing flux observations. We demonstrate that implementing models that account for varying stomatal conductance in response to atmospheric and soil conditions does not help to improve LE model estimates for these two datasets. We investigate the role of aerodynamic versus stomatal conductance in controlling LE flux as well as the effects of diurnal effects of radiation, VPD and stomatal conductance response and how they differ between the grass and forest sites. The aim is to provide suggestions for conceptual improvements that can help resolve some of the shortcomings in the PM-based LE flux estimation.
How to cite: ten Veldhuis, M.-C., Jongen-Boekee, J., and van de Wiel, B.: Diagnosing LE , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9186, https://doi.org/10.5194/egusphere-egu26-9186, 2026.
We extend the Cloud Layers Unified by Binormals (CLUBB) turbulence scheme within the GFDL atmospheric model (AM4) by implementing direct momentum-flux prognosis and a multiscale turbulent length scale, to improve the simulation of nocturnal precipitation and associated Low-Level Jets (LLJs) over the Great Plains (GP). Towards this aim, we set up four AM4-CLUBB configurations: diagnosed momentum flux, prognosed momentum flux, diagnosed momentum flux with a multiscale turbulent lengtshcale, and prognosed momentum flux with a multiscale turbulent lengtshcale. Simulations are evaluated against the AM4 control, the Integrated Multi-satellitE Retrievals for GPM (IMERG), and the Doppler wind radar profiles from the Atmospheric Radiation Measurement (ARM) program. Results show that all AM4-CLUBB configurations improve the precipitation timing from the unrealistic midday peak seen in the AM4 control simulation toward the satellite-observed nocturnal maximum. The configuration that prognoses momentum flux and uses a multi-scale turbulent length scale, best matches the timing and intensity of GP precipitation rate. This configuration is also that which more accurately simulates the ARM-observed nocturnal LLJ wind profiles, while increasing the frequency of counter-gradient momentum fluxes near the LLJ core compared to prognosing momentum fluxes with the original AM4-CLUBB turbulent lengthscale. Momentum budget analysis attributes this increase to a nearly fivefold enhancement in the buoyancy production term when using the multiscale formulation, and leads to stronger nocturnal convective activity, as diagnosed from the greater vertical velocity skewness and plume asymmetry.
How to cite: Gentile, E. S., Larson, V., Zhao, M., Zarzycki, C., and Svensson, G.: Enhancing Great Plains Nocturnal Precipitation and Low-Level Jets in AM4 with an Extended CLUBB Closure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21639, https://doi.org/10.5194/egusphere-egu26-21639, 2026.
Previous commercially available closed-path eddy covariance instrumentation used to quantify fluxes of trace gases relied on large flow rates from large pumps to attain high frequency response. These pumps would require AC mains power as well as environmental protection, limiting suitable locations for deployment. Building on over 20-years of experience manufacturing field-rugged trace gas analyzers, Campbell Scientific has developed a new novel closed-path analyzer to measure methane or nitrous oxide mixing ratios. The new analyzer achieves excellent frequency response (>3Hz bandwidth) with only 1.8 LPM flow rate and typical power consumption of 40W, while maintaining excellent noise performance (<5 ppb and <1 ppb typical noise at 10Hz Allan deviation for methane and nitrous oxide respectively).
How to cite: Conrad, B.: Frequency Response of a Low-Power Trace Gas Analyzer for Eddy-Covariance Flux Measurements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3183, https://doi.org/10.5194/egusphere-egu26-3183, 2026.
We present two major advancements to the wavelet-based, non-stationary flux estimation method of Destouet et al. (2025), enabling accurate calculation of high-resolution (1-minute) ecosystem fluxes and their time-derivatives.
We introduce first a scale-dependent estimation process that explicitly accounts for frequency-dependent eddy correlation times. By assigning different averaging times to each frequency band, we enhances the isolation of turbulent scales, reduces flux estimation errors, and improves the separation of local turbulence from larger scales by eliminating spurious correlations around the 'spectral gap'. This advancement is particularly valuable for wavelet-based flux partitioning, as it preserves high-quality flux estimates while retaining small-scale eddies, such as those hypothesized to transport soil respiration through forest canopies.
Second, our method now enables the computation of flux time-derivatives, allowing analysis of turbulent transport dynamics and ecosystem responses to environmental changes. As a first application, we present how to optimally determine the averaging time required for observed turbulent fluxes to represent underlying ecosystem fluxes. This is achieved by analysing the co-variation of flux time-derivatives with variables such as incoming radiation and carbon storage, which reflect underlying ecosystem dynamics.
These improvements together refine high-resolution flux estimation and unlock new opportunities to investigate ecosystem dynamics from flux towers. They have been implemented in the open-source TurbulenceFlux.jl package, which is readily available for community use.
Reference:
Destouet G, Besic N, Joetzjer E, and Cuntz M (2025) Turbulent transport extraction in time and frequency and the estimation of eddy fluxes at high resolution, Atmospheric Measurement Techniques 18(13):3193–3215, doi:10.5194/amt-18-3193-2025
How to cite: Destouet, G., Joetzjer, E., Besic, N., and Cuntz, M.: Improved wavelet method for accurate high-resolution ecosystem flux estimation and time-derivative analysis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6583, https://doi.org/10.5194/egusphere-egu26-6583, 2026.
Sub-Arctic peatlands are often delicately poised at the carbon source-sink threshold. With peatlands among the most carbon-dense ecosystems on Earth, they are critical players in global climate regulation, with land–atmosphere feedbacks that can disproportionately influence climate change trajectories. However, peatland carbon dynamics, and whether they act as sources or sinks for carbon, are strongly shaped by local conditions underscoring the need for site-specific measurements of turbulent fluxes and meteorology to predict their future role in the carbon cycle. While eddy-covariance is a common and critical in-situ measurement technique, the choice of pre-processing algorithms has the potential to interfere in the clear interpretation of source or sink classification in transitional peatland regimes .
Here, we present two years of eddy-covariance observations from a newly established eddy-covariance tower in a fen peatland in northeastern Finland. Our analysis characterises the carbon dynamics at the site and addresses a key methodological challenge that is often overlooked: the uncertainty introduced by the subjective choices inherent in eddy-covariance data processing. By generating multiple datasets using alternative processing algorithms, we quantify the sensitivity of flux estimates at the peatland to these decisions, where processing methods affect conclusions regarding its source-sink status. The results provide motivation for a framework for more robust interpretation of peatland carbon fluxes.
How to cite: Cranko Page, J., Jensen, R., Koskinen, E., Lämsä, J., López-Blanco, E., Marttila, H., Mastepanov, M., Paavola, R., and Christensen, T. R.: Turbulent Fluxes at a Sub-Arctic Peatland and the Role of Data Processing Choices in Carbon Dynamics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12061, https://doi.org/10.5194/egusphere-egu26-12061, 2026.
This study reports a comparative investigation of two alpine research sites situated in the Aosta Valley (Italian Alps), representing distinct neighbouring ecosystems: a high-altitude grassland and a mature larch forest. Eddy covariance flux measurements have been operational since 2008 at the grassland site (2168 m a.s.l.) and since 2012 at the larch forest site (2100 m a.s.l.). Each station is fully instrumented for flux and meteorological observations using identical instrumentation. The straight-line distance between the two sites is approximately 2.7 km and they experience comparable climatic conditions, thereby enabling direct inter-site comparisons.
The primary aim of this study is to quantify and interpret differences in the carbon dioxide exchange between these ecosystems, with particular attention to the peculiarities of the years showing extreme meteorological conditions.
The two sites represent contrasting stages along a land‑use transition gradient, where the abandoned grasslands — no longer subject to livestock grazing since 2008, when the area was fenced and permanently excluded from grazing — exhibit a progressive encroachment by woody species, ultimately evolving into mature larch stands. This is a widely documented process in the Alpine region: the abandonment of traditional grazing practices and the subsequent natural recolonization of former grasslands by forest species.
To complement this analysis, preliminary results from a third eddy covariance station, installed in 2024 within a transitional ecotone characterized by scattered small larch saplings and shrub species, will also be presented.
Overall, this study demonstrates how multi-year eddy covariance measurements can reveal differences in ecosystem functioning under the same climatic conditions but across distinct vegetation types and successional stages, offering new insights into carbon flux dynamics along alpine land-use gradients.
How to cite: Ferraris, D., Galvagno, M., Oddi, L., Filippa, G., Cremonese, E., Pogliotti, P., Grosso, F., Morra di Cella, U., Koliopoulous, S., Guarnieri, C., Wohlfahrt, G., Leitinger, G., Migliavacca, M., Hammerle, A., and Papale, D.: Tracing Carbon Flux Dynamics and Ecosystem Functioning Along a Land-Use Gradient: Long-Term Eddy Covariance Observations in the western Italian Alps, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6756, https://doi.org/10.5194/egusphere-egu26-6756, 2026.
Restoration of drained peatlands aims to recover the natural carbon sink and storage functions of a mire but also leads to changes in the ecosystems’ biophysical surface properties and, consequently, to their local climate. Impacts of land cover changes on local temperatures are governed by both radiative and non-radiative processes, i.e. changes in albedo and energy partitioning, respectively, with the latter typically as the dominant factor.
There is evidence that the land surface temperature (LST) in degraded peatlands will tend to become similar to that in nearby intact ecosystems1. Therefore, quantifying how the differences in the surface properties between pristine mires and forests contribute to the differences in their LST is relevant to understanding the biophysical effects of peatland restoration. However, data on LST changes following a forest to mire transition are scarce.
We attribute the difference in LST between a boreal mire and forest to the differences in their biophysical surface properties: albedo, energy storage, aerodynamic resistance and bulk surface resistance to evapotranspiration. We use eddy covariance measurements of sensible and latent heat fluxes as well as supporting meteorology. The attribution methodology is the two-resistance mechanism2, but compared to previous studies we also include auto- and cross correlations between the attributed variables using second-order Taylor series expansion3. The attribution is compared between seasons based on vegetation phenology and between weather events based on climatic indicators of warm, cool, wet or dry days.
We hypothesized that contributions to LST difference from the differences in surface resistance would be important because of the very different hydrology and vegetation in the compared ecosystems. However, our results show that the importance of surface resistance was minor compared to aerodynamic resistance which is the dominant factor during spring, summer and autumn. The lower surface roughness of the open mire leads to higher aerodynamic resistance, which has been identified as a strong warming factor also in previous literature comparing forests and open ecosystem such as croplands (e.g. ref.4). During late winter with a continuous snow cover still on the mire, the higher albedo values in the mire explain most of the lower LST there. The interdependencies between the attributed variables emerge as important factors, especially when comparing between different weather conditions.
References
1. Burdun, I. et al. Satellite data archives reveal positive effects of peatland restoration: albedo and temperature begin to resemble those of intact peatlands. Environ. Res. Lett. 20, 084037 (2025).
2. Rigden, A. J. & Li, D. Attribution of surface temperature anomalies induced by land use and land cover changes. Geophys. Res. Lett. 44, 6814–6822 (2017).
3. Chen, C., Wang, L., Myneni, R. B. & Li, D. Attribution of Land-Use/Land-Cover Change Induced Surface Temperature Anomaly: How Accurate Is the First-Order Taylor Series Expansion? J. Geophys. Res. Biogeosciences 125, e2020JG005787 (2020).
4. Chen, C. et al. Biophysical effects of croplands on land surface temperature. Nat. Commun. 15, 10901 (2024).
How to cite: Rinne, E., Tuovinen, J.-P., Linkosalmi, M., and Aurela, M.: Attributing the surface temperature difference between a northern boreal mire and forest to the differences in their surface biophysical properties, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6900, https://doi.org/10.5194/egusphere-egu26-6900, 2026.
Ultrasonic anemometers (UA) are frequently employed to measure wind, air temperature, and turbulent exchange of energy and matter in the atmospheric boundary layer. They are fast-response, linear, accurate, first-principle instruments. Their accuracy is determined by the lengths of the acoustic paths, the direction cosines of the path geometry, and the time of flight of the acoustic signals. A fundamental limitation of UA is the self-shadowing wake effect caused by the ultrasonic transducers and support structures interfering with the flow field, leading to underestimation of the wind measurement along the acoustic paths. To minimize the transducer wake effects, numerous UA designs with different geometry, orientation, and length of the ultrasonic paths have been proposed, but there is no consensus on optimal transducer arrangement. In a widely used non-orthogonal UA design each of the three acoustic paths is tilted 60 degrees from the horizontal plane and equally spaced 120 degrees around the vertical axes. The advantage of the non-orthogonal UA is that the transducers are taken out of the horizontal plane and the three sensing paths intersect forming a small measurement volume preserving the correlation between the components of the wind vector. Alternatively, in a less common orthogonal UA design, the acoustic paths are arranged perpendicular to each other and parallel to the axes of a Cartesian coordinate system, allowing the measurement of the vertical wind component by a single pair of transducers. A disadvantage of the orthogonal UA is the large separation between the wind components and the self-shadowing effects of the transducers in the horizontal plane. To compare the performance of the orthogonal and non-orthogonal UAs we designed a unique integrated twelve-transducer probe, combining both designs in one structure with all six acoustic paths referenced to a common coordinate system. Such an arrangement reduces the uncertainty of the combined wind measurements by eliminating the need for coordinate rotation to align each UA coordinate system to the mean flow field. This study is unique because the two UAs use the same ultrasonic transducers, have equal path length to transducer diameter ratios, utilize the same time-of-flight signal processing algorithm, sample rate and measurement bandwidth. The primary difference between the two UAs is the orientation of the six acoustic paths. We demonstrate the details of the design of the combined probe and present results from a field experiment.
How to cite: Bogoev, I. and Strickler, B.: Performance Evaluation of Three-Component Ultrasonic Anemometers with Orthogonal and Non-Orthogonal Transducer Arrays, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3170, https://doi.org/10.5194/egusphere-egu26-3170, 2026.
Land-atmosphere interactions play a key role in the Earth’s climate. The surface temperature is a key parameter in calculating the latent and sensible heat flux and thus important for the closure of the surface energy balance (SEB). Yet vegetated surfaces have different properties compared to bare soil and thus behave differently. Grass-vegetated surfaces are by far the most common type of land cover, covering over 40 % of all land area. Therefore, accurate modelling of soil and grass temperatures is essential for improving numerical weather prediction models.
In current weather models, the surface temperature is often estimated using an empirical skin resistance model, which may lead to significant errors in both the phase and amplitude of the surface temperature, negatively affecting the closure of the SEB. A more refined and physics-based approach is thus needed for accurate modelling of heat transfer processes in the vegetation-soil continuum.
In this research we investigate a new modelling approach for grass-vegetated and topsoil layers, using both analytical and numerical diffusive modelling approaches, building on the work of Van Dijk (2024), where grass was treated as a homogeneous sponge-layer with a uniform thermal diffusivity. The aim is to capture the temperature dynamics within the grass (and soil) layer and compare these with millimetre-resolution observations using distributed temperature sensing (DTS) measurements, as described in Ter Horst (2025).
Results indicate that a purely diffusive model is accurate in describing the temperature dynamics within the soil, but is not fully able to capture the heat transfer within the vegetation layer accurately. Therefore, adjustments are made to the vegetation ‘sponge’-layer, adding a more realistic height-dependent density and a height-dependent (radiative) source term.
First results from a rudimentary analytic model already show promising results for temperature profiles in quasi-steady state, both during night- and daytime. Similar temperature profile shapes to the DTS measurements are achieved, that would not have been possible for a purely diffusive model.
How to cite: Steenge, J., van de Wiel, B., ten Veldhuis, M.-C., Romijn, N., and van der Linden, S.: Earth’s Green Blanket: A study of Heat Transfer through Grass, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11835, https://doi.org/10.5194/egusphere-egu26-11835, 2026.
A high quality of the representation of land-atmosphere (L-A) feedbacks is fundamental for advancing the performance of weather forecasts, seasonal simulations, and climate projections. These feedbacks are due to a highly complex interaction of variables related to the exchange and conservation of momentum, energy, and mass. The Land-Atmosphere Feedback Initiative (LAFI, see https://www.lafi-dfg.de) is the Collaborative Research Unit 5639 funded by the German Research Foundation (DFG). The overarching goal of LAFI is to understand and quantify L-A feedbacks via unique synergistic observations and model simulations from the micro-gamma (» 2 m) to the meso-gamma (» 2 km) scales from diurnal to seasonal time scales.
The fundament to reach this goal is provided by the observation of L-A system processes and feedbacks at the Land-Atmosphere Feedback Observatory (LAFO) of the University of Hohenheim in Stuttgart, Germany. Here, a worldwide-unparalleled synergy of measurements is realized including water stable isotopes, temperature by fiber-optic distributed sensors, and a suite of atmospheric variables with turbulence resolution using scanning lidar systems.
A key research objective of LAFI is to quantify entrainment in the convective boundary layer (CBL), to separate and quantify related processes such as engulfment, and to derive similarity relationships for parameterizing entrainment fluxes. We will present first measurements of entrainment fluxes at LAFO with lidar synergy, which are typically on the order of 100-200 W/m2 around noon with respect to the latent heat. These new measurements allow for quantifying the flux divergences in the CBL that are an essential part of the heat and water-vapor budget equations. Furthermore, we will relate the entrainment flux to surface variables for characterizing feedback metrics such as the relative humidity tendency and the mixing diagram. Finally, we will present an outlook of future work and its collaboration and coordination with the Global Land-Atmosphere System Studies (GLASS) Panel of the Global Energy and Water Exchanges (GEWEX) project.
How to cite: Wulfmeyer, V., Beyrich, F., Jagdhuber, T., Kunstmann, H., Mauder, M., Schymanski, S., Thomas, C., Branch, O., Rajtschan, V., Ingwersen, J., Orlowski, N., Hellwig, F., Seeburger, P., Voigt, C., Fersch, B., Winkelmann, A., von Klitzing, L., Schumacher, M., Behrendt, A., and Lange, D.: How important is the entrainment flux for characterizing land-atmosphere feedback in the convective boundary layer?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20896, https://doi.org/10.5194/egusphere-egu26-20896, 2026.
The surface energy balance (SEB), which defines the partitioning of energy exchange between the Earth’s surface and the atmosphere, is crucial for characterizing the development and evolution of the atmospheric boundary layer. While an accurate assessment of SEB components is essential for numerous applications, eddy-covariance measurements remain affected by significant uncertainties. Specifically, turbulent heat fluxes typically fail to balance the available energy at the surface. Research suggests that this energy balance closure problem stems primarily from advection driven by secondary circulations, which are prevalent over heterogeneous and complex terrain due to differential heating.
This study assesses the relationship between SEB non-closure, surface heterogeneity, and the subsequent development of local and mesoscale thermally driven circulations. The analysis utilizes data from seven flux sites across diverse Alpine environments (both on flat and sloped terrain) - including vineyards, pastures, pre-alpine and continental forests - incorporating at least two years of data per site, with many exceeding four years. The results provide a systematic and robust quantification of SEB non-closure across several typical Alpine contexts, highlighting key similarities and differences between sites based on their topographic features, land cover, and prevailing meteorological conditions.
The present work is part of the INTERFACE project (INvestigating ThE suRFACe Energy balance over mountain areas), which is performed in the framework of the TEAMx research programme.
How to cite: Carpentari, S., Shivani Sankar, M., Vendrame, N., Zardi, D., and Giovannini, L.: Assessment of Surface Energy Balance Closure at eddy-covariance sites in Diverse Alpine Environments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4241, https://doi.org/10.5194/egusphere-egu26-4241, 2026.
Spatial heterogeneity of land use impacts land-atmosphere feedback and therefore the spatial and temporal variability of latent and sensible heat fluxes within the atmospheric boundary layer. This is especially visible during clear sky days without notable advection.
In spring and summer 2025 at the GEWEX Land Atmosphere Feedback Observatory (GLAFO) site of the University of Hohenheim (Stuttgart, Germany) an extensive field campaign was performed by the research group Land Atmosphere Feedback Initiative (LAFI) funded by the German Research Foundation. During five intensive observation periods (IOPs) the GLAFO equipment, which includes two Eddy-Covariance stations, was extended by Lidar measurements of wind, humidity and temperature.
To study the three-dimensional pattern of the heat fluxes over a heterogeneous surface during the day we applied the Weather Research and Forecasting model (WRF). We used WRF in a nested configuration with resolutions of 1250 m, 250 m and 50 m, forced with ECMWF operational data for a clear sky case study on 24 June 2025. In the two inner domains, WRF was applied in Large-Eddy simulation (LES) mode with switched-off turbulence scheme. The simulated evolution of the planetary boundary layer and the influence of the land surface on its development was compared with the temporal and vertical evolution in data from the lidar systems and eddy-covariance stations.
In addition, we focused on the vertical representation of latent and sensible heat fluxes at the different model resolutions and their dependence on the underlying land surface. This will reveal the so-called blending height, namely the height at which the horizontal distributions of the fluxes are no longer dependent on the underlying surface. The derivation of this important variable paves the way to a more physical coupling of the land surface and the atmosphere in the model.
How to cite: Bauer, H.-S., Jach, L., Branch, O., Lange, D., Rajtschan, V., Wulfmeyer, V., and Warrach-Sagi, K.: Spatial variability of the diurnal cycle of heat fluxes in the atmospheric boundary layer over agricultural land and forest of the GLAFO site in Stuttgart (Germany) on a clear sky day, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11416, https://doi.org/10.5194/egusphere-egu26-11416, 2026.
Planetary boundary layer height (PBLh), despite being key to atmospheric modelling parametrizations, remains difficult to consistently define, model, and observe. The Southern Ontario Lidar (SOLID) Mesonet, established by Environment and Climate Change Canada (ECCC) in and around Toronto beginning in 2022, provides an opportunity for high spatial and temporal resolution estimates of the PBLh in diverse atmospheric conditions. We present a Doppler lidar-derived PBLh data product using SOLID Mesonet observations, assessed in comparison to PBLh estimates from ECCC’s Global Environmental Multiscale (GEM) model, ERA5, and nearby radiosonde flights in Buffalo, NY. These comparisons highlight the uncertainties between various methods for PBLh estimation, particularly in stable atmospheric conditions such as overnight and in winter months, and give key insights into the accuracy of PBLh estimates for usage in atmospheric modelling as well as avenues for improvements.
How to cite: Duff, P., Crawford, R., Galarneau, E., Lauer, A., Leroyer, S., Mariani, Z., and Strong, K.: Insights into planetary boundary layer height estimation from the Southern Ontario LIDar (SOLID) Mesonet , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13661, https://doi.org/10.5194/egusphere-egu26-13661, 2026.
Land–atmosphere interactions at the leaf scale play a critical role in regulating surface energy exchange and plant water use under increasing heat and drought, yet quantitative indicators capturing short-term thermal–hydraulic coupling remain limited. This study compared seedlings of Acer pictum subsp. mono, with highly dissected leaves and low boundary-layer resistance, and Hovenia dulcis, with smoother leaves and thicker boundary layers, to test how leaf morphology constrains thermal and hydraulic regulation. Seedlings were exposed to well-watered, control, and severe-drought treatments, creating a clear soil-moisture gradient, while leaf temperature and sap flux were monitored alongside key environmental drivers. This design enabled evaluation of short-term leaf temperature variability (ΔT, 5-min scale) and its coupling with radiation and transpiration across contrasting water conditions.
Across both species, ΔT was most strongly coupled with changes in photosynthetically active radiation(PAR). In A. mono, the PAR increase threshold triggering synchronized ΔT responses declined under severe drought (≈103 μmol m⁻² s⁻¹) relative to well-watered conditions (≈135 μmol m⁻² s⁻¹), whereas H. dulcis showed no significant treatment dependence. Under identical PAR reduction levels, higher sap velocity consistently enhanced leaf temperature declines, indicating transpiration-driven amplification of short-term cooling. At high temperatures (30–35 °C), A. mono maintained strong cooling responses, while H. dulcis exhibited flattened sap–ΔT relationships and increased ΔT amplitude under severe drought (≈5.0 °C). These results demonstrate that short-term leaf cooling emerges from the interaction between radiation forcing and transpiration, with species-specific constraints imposed by leaf morphology and hydraulic limitation. Integrating ΔT, PAR, and sap flux provides a quantitative framework for comparing thermal–hydraulic strategies among species and offers a sensitive tool for early diagnosis of drought vulnerability at the seedling stage.
How to cite: Shin, H. D., Park, S., Baek, J., Yun, A., Lee, T., Lee, M., Kim, K., Hong, J., and Kim, H. S.: Quantifying Water Stress in Acer pictum subsp. mono and Hovenia dulcis Seedlings Using Thermal Imaging and Sap Flux, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17086, https://doi.org/10.5194/egusphere-egu26-17086, 2026.
Arid and hyper-arid regions (deserts) are dynamic ecosystems that respond sensitively to changes in water availability, temperature, and atmospheric CO₂, and can both indicate and influence climate change. Although approximately 27% of the world’s land surface is classified as deserts, these regions are second only to oceans in the scarcity of long-term measurement sites. This results in an inadequate representation of the complex interactions among the pedosphere, hydrosphere, and atmosphere in these regions. This knowledge gap limits understanding of desert-specific air–land processes and, given the close coupling between desert climates and the global system, contributes to uncertainty in climate projections.
To address this gap, we are establishing a first-of-its-kind megasite in the Negev Desert representing the subtropical desert belt. Israel’s relatively small size, with ~60% of its territory classified as arid or hyper-arid, makes the Negev uniquely accessible for long-term observations. The Mashash Desert Climate Observatory is built on a record of meteorological data collected at the site since 1973 and extensive micrometeorological measurements conducted in recent years.
The new megasite will generate vertically resolved surface-to-atmosphere profiles of wind, temperature, and moisture, along with detailed radiation, heat, CO2, and dust fluxes, enabling direct analysis of air–land coupling from the soil to the top of the troposphere. Co-located measurements of soil moisture, soil heat flux, and soil CO₂ efflux will allow characterization of subsurface controls on surface energy partitioning and carbon exchange. These continuous estimates will highlight the evolution of dynamics at diurnal, seasonal, and annual scales, linking surface radiative forcing to turbulent transport and boundary-layer development. Combined radiative and thermodynamic profiles will further resolve the vertical structure of moisture transport and non-precipitating systems, clarifying how episodic hydrological inputs propagate through the soil–vegetation–atmosphere continuum in desert environments. The observatory will be open to the international research community, and its data architecture is designed to be compatible with global networks (e.g., FLUXNET and NASA archiving standards), while maintaining access to raw data to ensure transparency and scientific integrity.
By providing sustained observations of air–land interactions in an understudied environment, the Mashash Desert Climate Observatory will deliver essential data for improving land-surface and boundary-layer models, support model–observation intercomparisons and remote-sensing validation, and advance understanding of multi-scale desert processes toward initial upscaling to global climate models.
How to cite: Cohen-Zada, A. L., Armon, M., Dente, E., Harnik, N., Hirsch, E., Karnieli, A., Koren, I., Raveh-Rubin, S., Shoshany, M., Weisbrod, N., and Agam, N.: The Mashash Desert Climate Observatory: A New Megasite for Air–Land Exchange Processes in Subtropical Deserts, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3359, https://doi.org/10.5194/egusphere-egu26-3359, 2026.
Direct Air Capture (DAC) technologies designed for atmospheric water harvesting are increasingly being considered as a means of supplying water for green hydrogen production, particularly in arid and semi-arid regions. However, large-scale moisture removal from the atmosphere may affect the thermodynamics of the planetary boundary-layer, yet the magnitude and spatial characteristics of these impacts remain insufficiently characterized. In this study, we implement a physically based DAC parameterization within the ICOsahedral Nonhydrostatic (ICON) model, using Large-Eddy Simulation (LES) to explicitly resolve land–atmosphere exchange processes. DAC operation is represented as an imposed constant moisture extraction flux subtracted from the surface latent heat flux, with configurations spanning a range of flux densities (0–800 W/m) and deployment scales (4–900 units). Simulations reveal systematic near-surface warming and atmospheric drying associated with DAC operation. From the results High flux densities (>= 400 W/m^2) 1) reduce specific humidity of the local lower atmosphere by ~0.2 g/kg, and that of the land surface by 3.5 g/kg relative to the control, 2) decrease relative humidity by ~4 percentage points, 3) and increase virtual potential temperature by ~0.5 K with no significant regional effect. In addition, Large-scale deployments yield spatially distributed but cumulative effects both at the local and regional scale, producing domain-mean warming of ~0.5 K and specific humidity reductions of ~0.1–0.4 g/kg. These perturbations arise from suppressed evaporative cooling and reduced near-surface moisture availability, which may lead to modified local energy partitioning without fundamentally altering boundary-layer stability in the atmospheric boundary layer. For deployment densities above ~400 units, non-physical negative humidity values emerge, indicating that the extraction of moisture exceeds the atmospheric supply—a flux threshold for single unit DAC operation under the atmospheric conditions used here in the study. The results demonstrate that DAC-induced thermodynamic perturbations are non-negligible at both local and regional scales and can influence turbulent mixing, boundary-layer structure. This work provides a quantitative foundation for incorporating DAC into land-surface design, environmental regulation, and future deployment strategy for atmospheric water harvesting systems.
How to cite: Owusu, R., Kollet, S., Poll, S., and Selmert, V.: Influence of Atmospheric Water Harvesting on Coupled Land Surface-Atmosphere Processes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10726, https://doi.org/10.5194/egusphere-egu26-10726, 2026.
Tall-tower eddy covariance (TTEC) systems are increasingly used to monitor land–atmosphere exchanges over complex agricultural and urban landscapes. However, interpreting flux estimates is challenging because the eddy covariance footprint varies significantly with meteorological conditions, which can introduce considerable bias assuming that sources and sinks are not uniformly distributed across the landscape or over the diel cycle. For fluxes with systematic diurnal patterns, such as traffic-related emissions, photosynthesis, or agricultural activities, uneven temporal sampling can prevent capturing a full daily cycle, introducing temporal sampling bias into daily flux estimates. The objective of this study was to evaluate the performance of a multi-level TTEC system in reducing footprint-related sampling bias.
The study site is located in an agricultural landscape west of Copenhagen, Denmark. A 15-month dataset (2023-2024) was collected, representing a heterogeneous landscape dominated by grassland and cropland, with scattered settlements, hedgerows, and forested areas. The TTEC system was installed on a 300 m telecommunication tower and equipped with three measurement levels at 70, 90, and 115 m. These sampling heights were selected a priori based on flux footprint estimates from wind data of a nearby tall tower, ensuring a more uniform footprint at a wider range of atmospheric stability conditions. Each level was equipped with a 3D ultrasonic anemometer (uSonic-3 Class A MP, METEK, Germany). A fast-response gas analyser was connected to the system and configured to sample air from one of the three heights at a time based on criteria related to optimal footprint size and constant flux layer requirements.
The results of the study showed that a greater number of observations were collected at the upper sampling height during daytime whereas nighttime observations were predominantly obtained from the lower level. The intermediate level was primarily used during the transition periods between day and night. The multi-level sampling scheme enabled a substantial reduction in sampling bias by actively controlling the horizontal extent of the flux footprint compared to a single-level TTEC system. Consequently, footprint size and the relative contributions of different land-cover types were more consistent across atmospheric stability regimes. The findings from this study highlight the importance of implementing a multi-level approach, particularly for TTEC systems operating over landscapes with greater heterogeneity than those typically sampled by conventional eddy covariance systems.
Acknowledgements
This project is supported by the Independent Research Fund Denmark (DFF-grant 1127-00308B - Observation System of Greenhouse Gas Sources and Sinks at the Landscape Scale for Verification of the Green Transition of Denmark). The authors wish to thank Cibicom A/S for sponsoring access to Hove telecommunication tower.
How to cite: Kissas, K., Gorlenko, A., Wang, Z., Wiesner, S., Scheutz, C., and Ibrom, A.: A method to reduce sampling bias in multi-level tall-tower eddy covariance systems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14918, https://doi.org/10.5194/egusphere-egu26-14918, 2026.
Forests regulate moisture and heat fluxes in the lower atmosphere, which are inextricably linked to fair weather shallow cumulus formation within the boundary layer. Forest enhanced cloud shading thereby affects the earth’s surface radiation budget, a phenomenon that has been reasonably well studied through modelling and large-scale satellite studies. However, there is a lack of surface-based observational studies linking surface fluxes to cloud formation. By combining flux tower and ceilometer measurements in a mixed Acadian (Atlantic Canadian) forest near Fredericton, New Brunswick, we gain a unique opportunity to study land-cloud coupling using these local, surface-based flux observations. Analysis of 30-minute averaged surface-based tower measurements reveals fair weather summertime shallow cumulus formation over a 3-year period (2023-2025). Shallow cumuli occur on 160 days in total, exhibiting a clear seasonal cycle with a pronounced peak between June and August. We employ machine learning to determine the importance of environmental drivers and surface fluxes on daytime cloud fraction and cloud base height on days with shallow cumuli, with surface moisture exhibiting the strongest influence. Additionally, we show the response of shallow cumulus to extreme surface conditions by examining the period between August and September 2025. Fredericton experienced anomalously dry conditions, receiving only ~15% and ~40% of normal precipitation in August and September, respectively, during which soil moisture falls to 30% typical late-summer values. We find a significant reduction in shallow cumulus formation during the dry conditions, which we hypothesize is caused by the shift of surface flux partitioning from latent to sensible heating, and the concurrent enhancement of daytime lifting condensation level growth.
How to cite: Rudaitis, L., Helbig, M., Zhou, X., Mengering, D., and Heerah, J.: On the Role of Land-Atmosphere Coupling in Boundary Layer Cloud Development Over a Mixed Forest in Eastern Canada , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15855, https://doi.org/10.5194/egusphere-egu26-15855, 2026.
When vegetation intercepts precipitation, the quantity of rainwater reaching the ground is affected, as it passes through the canopy, drips from it, and runs down the stem. Interception also significantly alters the characteristics of rainfall, which is among others reflected in differences in the number, size and velocity of raindrops. Throughfall drop size distribution was monitored and analysed for three vegetation types, including a single pine tree in an urban park, trees in an urban mixed forest, and a maize field in an agricultural area. Velocity-diameter diagrams were compiled for the 33 selected throughfall events and grouped into three distinct clusters based on similarity using a hierarchical clustering approach. Pine throughfall events were grouped in Cluster 1, urban mixed forest events in Cluster 2, while maize events were split between Clusters 1 (with all the pine tree events) and Cluster 3. A detailed analysis of rainfall microstructure characteristics under maize and pine canopies was conducted in relation to the rainfall event conditions and crop growing stage to evaluate why, in some cases, throughfall microstructure under maize is similar to that beneath pine (events assigned to Cluster 1), and, in other cases, it differs (events assigned to Cluster 3). Throughfall events in Cluster 3 were generally larger and more intense, showing a unimodal temporal distribution. In contrast, maize throughfall events in Cluster 1 exhibited a bimodal distribution, with two intensity peaks separated by a rainfall break. Notably, the maize leaf area index (LAI) exceeded a value of 4 during the period when the shift occurred from the events assigned in Cluster 1 to the subsequent events assigned in Cluster 3. As maize leaves mature, they become less flexible and do not bend as much under the weight of rain. Consequently, throughfall consist of more drips (larger drops) than direct rainfall (smaller drops). Further research could include additional types of vegetation, and the results could be supported by measurements over a longer period of time. These values could also be used for direct analyses of rainfall erosivity.
Acknowledgment: This contribution is part of the ongoing research project entitled “Evaluation of the impact of rainfall interception on soil erosion” supported by the Slovenian Research and Innovation Agency (J2-4489) and the Austrian Science Fund (FWF) I 6254-N.
How to cite: Zabret, K., Radulović, L., Szeles, B., Parajka, J., Marjanović, D., Vilhar, U., Pavčič, J., Alivio, M. B., Kuzmanić, T., Lebar, K., Bezak, N., Strauss, P., Blöschl, G., and Šraj, M.: Why Maize Sometimes Behaves Like Pine: Throughfall Microstructure and LAI Influence, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5034, https://doi.org/10.5194/egusphere-egu26-5034, 2026.
Precise estimates of actual evapotranspiration (ETa) are crucial for enhancing our understanding of the water and energy exchanges between land and atmosphere. These estimates are essential for applications and advancements in meteorological, climatological, ecological, and hydrological research. This study compares ET measurements obtained by two commonly used methods: eddy covariance (EC) and lysimeter (LY), based on long-term parallel measurements from 2012 to 2020. The analyses reveal a pronounced seasonal cycle in all measurements, with the highest values observed in summer and the lowest in winter. ET measurements from two lysimeters showed a significant difference of about 30% between areas of vegetation and bare soil. The ET values from the lysimeter method showed good agreement with the EC measurements, with an approximate difference of 7% between the two methods. Additionally, precipitation estimates from the lysimeter method were slightly higher than those from rain gauge measurements. The study identified air temperature as the primary controlling factor of ET, contributing nearly 60%. Net radiation and NDVI also played significant roles, with contributions larger than 10% and approximately 10%, respectively. The main causes of discrepancies between lysimeter and EC measurements were attributed to different measurement scales, varying crop growth stages, and soil moisture conditions. This study quantified ET at two different scales in nine-year period, providing valuable insights into the rational utilization of water resources in the region. The findings underscore the importance of considering measurement scales and environmental conditions when interpreting ET data for water resource management.
How to cite: Xu, Z.: Evapotranspiration measurements in the north China plain: insights from multi-years of lysimeter and eddy covariance system, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8519, https://doi.org/10.5194/egusphere-egu26-8519, 2026.
Anthropogenic heat (AH) is an important urban forcing factor, with its impacts span local, regional, and larger-scale atmospheric processes. However, its multiscale effects are difficult to quantify using conventional global and regional models. Here we address this challenge by applying a global variable-resolution atmospheric model, the integrated Atmospheric Model Across Scales (iAMAS), which explicitly links urban-scale processes with regional and large-scale atmospheric feedbacks within a single modeling framework. The model employs grid spacing that transitions from 50 km globally to 3 km over the East China with 3 km to resolve the anthropogenic heat effect over urban areas. Two AH parameterizations are implemented in this study: a spatially uniform AH parameterization (UniAH) and a spatially distributed gridded dataset (GrdAH), enabling an investigation of the multiscale atmospheric impacts of different AH parameterizations. At the local boundary-layer scale, both UniAH and GrdAH indicate that AH increases near-surface temperature and planetary boundary layer height, with the strongest responses occurring in winter. Nevertheless, GrdAH reproduces observed 2-m air temperature and 10-m wind speed more accurately than UniAH. At the urban scale, both parameterizations reduce the underestimation of the urban heat island and enhance vertical motion, while producing distinct precipitation responses between urban areas and their surrounding rural regions. At larger scales associated with atmospheric circulation, both UniAH and GrdAH indicate that AH redistributes momentum, partially impeding the upper-level circulation and modifying urban-scale convergence and divergence patterns. The convergent circulation downwind of the city corresponds to enhanced precipitation, demonstrating the coupled interactions across different scales. These results highlight the inherently multiscale nature of AH effects and demonstrate the methodological value of variable-resolution modeling for capturing urban forcing and its associated multiscale atmospheric feedbacks.
How to cite: Yang, Q., Zhao, C., Yang, X., Zhang, Z., Feng, J., Li, G., Xia, Z., Yang, Z., Xu, M., and Gu, J.: Investigating the impacts of anthropogenic heat over East China with a global variable-resolution model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6083, https://doi.org/10.5194/egusphere-egu26-6083, 2026.
Aerosols affect the worldwide plant environment in both beneficial and harmful ways. Despite its potential importance, its direct influence on plant–water interactions is little known. Tomato plants were grown in ambient urban air, filtered air, and severely polluted air following precise exposure procedures. While measuring transpiration rate and stomatal density, leaf hydration kinetics, microscopic leaf wetness creation, and aerosol deposition patterns were also assessed.
The experiment was conducted from August 2025 in three plant-growing chambers at IIT Delhi. Temperature and RH were the same. At plant level, plants were exposed to natural daylight (up to 1500 µmol m⁻² s⁻¹). Leaf dust deposition was monitored. Every other day, elevated chambers were sprayed with dust, while HEPA filters cleaned air in filtered chambers. PM2.5 deposition on leaves ranges from 50 µg/cm² to 600 µg/cm² for HEPA filter-equipped and increased PM conc. chambers, respectively. During the monitoring period, PM2.5 levels at several locations in the area averaged 150-600 µgm⁻³.Net photosynthesis, stomatal conductance, and transpiration rate were measured in real time using LI-COR 6400XT.
The mass accumulated on leaves was 10 to 12 times more in the elevated PM chamber. Fresh leaves from plants grown under reduced, ambient, and elevated chamber conditions were collected, affixed to specimen holders using adhesive Leit tabs, and analysed using environmental scanning electron microscopy. Stomatal density was seen to have risen (~170 per mm²) from the seedling stage. The minimum leaf conductance (gmin) was measured on leaflets. Photosynthetic rate increased from 14 µmol m⁻² s⁻¹ to 21 µmol m⁻² s⁻¹. The gmin is anticipated to rise when dust deposition on leaves increases. The rise in water uptake by plants suggests that phenomena such as hydraulic activation of stomata (HAS) or heat retention by deposited aerosols have intensified water loss, either through cooling themselves from the heat absorbed from excessive dust accumulation or by forming wicks into the leaves from the salts in the aerosols, thereby facilitating the escape of water from leaves into the environment through evaporation. The Fv/Fm ratio, a measure of photosynthetic efficiency, was maximised in the lowered chamber.
The impact of aerosols on plants is contingent upon their composition, species, and environmental conditions, affecting the movement of water via stomata and cuticular transpiration. Research indicates that ambient aerosol deposition in polluted urban environments elevates gmin, transpiration rates and modified stomatal density. Severity of impact increases pollution levels and hygroscopic aerosols due to extended exposure. Aerosol-induced water loss diminishes stomatal regulation, impairs drought resilience and water usage efficiency, and complicates carbon-water flow scaling. The increased transpiration rate leads to greater water consumption by plants, which might contribute to the depletion of groundwater levels in the IGP India. Additional investigation is required to elucidate the processes connecting aerosol deposition and stomatal response, considering their significance for global climate change.
How to cite: Pannu, S., Shrivastava, P., Singh, V., Mina, U., Gupta, C., Singh, B., Jain, P., and kumar, M.: Increased PM levels influence leaf conductance and modify transpiration dynamics, altering groundwater levels in IGP India., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1138, https://doi.org/10.5194/egusphere-egu26-1138, 2026.
Posters virtual: Wed, 6 May, 14:00–18:00 | vPoster spot 5
EGU26-4100 | Posters virtual | VPS4
Improved net ecosystem exchange (NEE) modelling under drought conditions in the Argentine PampasWed, 06 May, 14:00–14:03 (CEST) vPoster spot 5
The terrestrial biosphere is responsible for most CO₂ exchanges between land surfaces and the atmosphere, with ecosystems functioning as either carbon sinks or sources. These exchanges are primarily controlled by photosynthesis and ecosystem respiration, which depend on vegetation traits, environmental drivers, and soil water availability. Under drought conditions, plants tend to reduce stomatal conductance to conserve water, decreasing photosynthetic efficiency and limiting atmospheric CO₂ uptake.
In Argentina, observational studies of ecosystem CO₂ fluxes remain scarce, partly due to the high costs of instrumentation. Models such as the Vegetation Photosynthesis and Respiration Model (VPRM) provide an alternative approach to estimate ecosystem–atmosphere carbon exchange using meteorological forcing and satellite-derived vegetation indices. Recent developments include a modified VPRM formulation that explicitly accounts for water availability effects on respiration (Gourdji et al., 2022), which may improve model skill during drought. Additionally, high-resolution satellite observations have been demonstrated to more accurately represent heterogeneous agricultural landscapes, such as the crop mosaics characteristic of central Argentina.
In this work, we assess the ability of a modified VPRM driven by high-resolution satellite data to reproduce net ecosystem exchange (NEE) under contrasting hydroclimatic conditions. We use eddy-covariance observations from three sites (two grasslands and one under crop rotation cycles) in the Argentine Pampas. For each site, information on vegetation conditions in the vicinity of the flux tower was extracted from MODIS Terra and Sentinel-2 images. Time series of the Enhanced Vegetation Index (EVI) and the Land Surface Water Index (LSWI) were derived. NEE was simulated using both the original and the modified VPRM forced by each satellite data source, evaluating all model–satellite combinations. Drought conditions were characterized using the Standardized Precipitation–Evapotranspiration Index (SPEI) computed from CRU TS v4 gridded data at the nearest grid cells. Based on SPEI thresholds, the observational period was classified into “normal”, “mild drought”, and “moderate-to-severe drought”. Also, model performance statistics were computed for each regime.
Across sites, the configuration combining the modified VPRM with Sentinel-2 inputs (VPRMnew_S2) achieved improved skill (R2 = 0.49, 0.24, 0.65) compared with the original VPRM driven by MODIS imagery (R2 = 0.43, 0.23, 0.52). For the grassland sites, VPRMnew_S2 consistently outperformed the other configurations across all moisture regimes (higher R2, lower RMSE, and near-zero bias). At the cropland site, VPRMnew_S2 showed similar skill to the original model in terms of R2 and RMSE, but substantially reduced bias under water-limited conditions. These findings suggest that high-resolution satellite indices, coupled with drought-sensitive parameterizations, better capture NEE responses to water stress in the Argentine Pampas. Improved modelling of drought impacts on CO₂ exchange is essential to reduce uncertainty in regional carbon budgets and to assess ecosystem vulnerability under increasing drought frequency.
Keywords: Net Ecosystem Exchange, Eddy Covariance, MODIS, Sentinel-2, VPRM (Vegetation Photosynthesis and Respiration Model)
Acknowledgements
This research was financed by the UBACyT 2020–2025 program (N° 20020190100128BA) and by PIP-CONICET (N° 11220200100794CO) grants. Rodrigo Merino is supported by a scholarship granted by CONICET.
How to cite: Gassmann, M., Merino, R., Tonti, N., Covi, M., and Pérez, C.: Improved net ecosystem exchange (NEE) modelling under drought conditions in the Argentine Pampas, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4100, https://doi.org/10.5194/egusphere-egu26-4100, 2026.
EGU26-21667 | Posters virtual | VPS4
A multi-site comparison of spectral and co-spectral approaches for correction of turbulent gas fluxes with ICOS set-upWed, 06 May, 14:03–14:06 (CEST) vPoster spot 5
Correction of high-frequency spectral losses is a major technical challenge of the eddy covariance (EC) technique. If not properly accounted for during post-processing, these losses can result in a systematic underestimation of the measured gas fluxes exchanged between the ecosystem and the atmosphere. To address this issue, several methods have been developed, with experimental approaches relying on the definition of a transfer function and its associated cut-off frequency to describe the EC system as a first order low-pass filter.
One still debated yet fundamental choice is whether to use power spectra or co-spectra to derive the system cut-off frequency. In this study, we present a systematic, multi-site, data-driven comparison of the these two methods. To do so, we used one year of CO2 and H2O data from all of 38 ICOS Class 1 and Class 2 stations (Integrated Carbon Observation System, www.icos-cp.eu), all equipped with a standard setup comprising the LI-7200 enclosed path analyser and the HS-50 sonic anemometer.
We showed that the corrections were limited for both approaches, especially for CO2, ranging from 1 to 1.2, generally higher for H2O, ranging from 1 to 2, and overall consistent across sites. This highlighted the good spectral performance of the enclosed path analyser as well as the effectiveness of the setup standardisation. Nonetheless, the results showed that differences in correction factors between the methods existed. They were analysed for all sites, separately for stable and unstable conditions. They increased with atmospheric stability and attenuation level, and decreased with measurement height above the canopy. In particularly, they were systematically the highest in stable conditions. However, when assessing the impact of the two corrections on cumulative u*-filtered fluxes, we found that rejections of most stable conditions through this standard post-processing filtering led to differences under 3% for CO2 in 89% of sites and under 6% for H2O in 79% of sites.
With this specific experimental setup, we suggest prioritising the co-spectral for two main reasons. First, sensor separation is a dominant part of the high-frequency attenuation and is treated experimentally in the co-spectral method, whereas the spectral approach relies on a fully theoretical formulation. Second, the spectral method requires a robust denoising procedure, which is not needed in the co-spectral approach. Finally, while recognising its crucial importance at a network level, we highlight the complexity of having a fully automatic pipeline for spectral corrections.
How to cite: Faurès, A., Papale, D., Nicolini, G., Sabbatini, S., and Heinesch, B.: A multi-site comparison of spectral and co-spectral approaches for correction of turbulent gas fluxes with ICOS set-up, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21667, https://doi.org/10.5194/egusphere-egu26-21667, 2026.
