This session is intended to give a forum to discuss recent developments and achievements in local to regional measurement concepts and technology. There will be a special emphasis on measurements which seek to improve our understanding of complex atmospheric processes – especially those characterizing interactions in the climate system – through obtaining comprehensive data sets. The focus is on measurements of atmospheric dynamics and thermodynamics, energy and water cycle components, and on the interaction of the atmosphere with the underlying surface.
The session will also include consideration of novel measurement approaches and networks under development for future operational use, e.g., within the frame of the Eumetnet observations program and various COST actions, and the performance of new measurement techniques. Manufacturers of hydro-meteorological instruments and system solutions are thus explicitly invited to present news on sensor development, sensor performance and system integration.
Techniques may cover in-situ and remote sensing measurements from various platforms. Special attention will be given to the creation of a new generation of reliable unmanned instrument networks across Europe that provide calibrated and controlled data on the boundary layer structure in near-real time. This also includes metrological aspects of sensor characterization. Contributions are also welcome that make use of advanced data sets for satellite data validation. We also invite contributions making use of machine learning techniques for quality control or product generation of atmospheric measurement data.
The LOw Frequency ARray (LOFAR) radio telescope is a phased array of thousands of VHF dipoles centered in the Netherlands but spread throughout Europe. While originally mostly designed to observe astronomical phenomena, it is perfectly suited to image terrestrial lightning. Our group has been using LOFAR to image lightning in full 3D and time with nanosecond and sub-meter precision, which has revealed a myriad of new lightning phenomena that gives us new insight into both lightning plasma physics as well as Dutch thunderstorm structure. For example, almost every single lightning flash we image starts with a downward-growing negative leader (plasma channel). This is opposite lightning observed elsewhere, where most lightning starts with an upward growing negative leader. The conclusion is that Dutch thunderstorms are “bottom-heavy” relative to more traditionally studied thunderstorms. That is, where most thunderstorms have a main positive charge layer at higher altitude than the negative layer; the main positive layer in Dutch thunderstorms is below the negative layer. We have also studied small sparks at the top of very intense thunderstorms. These imply that, while most are too weak, the strongest Dutch storms have strong very localized turbulence at their tops when they interact with the ceiling of the troposphere. This local intense turbulence produces small complex charge pockets at higher altitude than the normal large charge layers. In this talk we will discuss recent results from imaging lightning with LOFAR, including extremely high precision images of lightning initiation, the discovery of small sparks that occur at the top of thunderstorms and before lightning initiation, as well as the realization that Dutch thunderstorms have upside-down charge polarity relative to thunderstorms in other places.
How to cite: Hare, B., Cummer, S., Dwyer, J., Liu, N., Lourens, M., Scholten, O., Sterpka, C., Turekova, P., and Wu, B.: Recent developments in Imaging Lightning with LOFAR, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-118, https://doi.org/10.5194/ems2026-118, 2026.
Accurate identification of aerosol type and cloud phase is essential for understanding atmospheric processes, radiative forcing, and aerosol–cloud interactions, especially during long-range transport events such as Saharan dust intrusions and transatlantic wildfire smoke. Recent advances in automatic lidar–ceilometers (ALCs) equipped with depolarization capability, such as the Vaisala CL61, enable continuous and unattended monitoring of aerosol type and cloud phase at high temporal and vertical resolution. However, single-wavelength configurations limit the exploitation of multi-parameter aerosol classification methods developed for advanced multi-wavelength lidars.
At the Royal Meteorological Institute of Belgium (RMI), we developed CONIOPOL (CONIOlogy + POLarization), an algorithm that exploits backscatter and depolarization profiles from the Vaisala CL61. By combining attenuated backscatter, linear depolarization ratio (LDR), and cloud-base height retrievals, CONIOPOL discriminates between clouds, precipitation, and aerosols, and classifies cloud phase, precipitation type, and major aerosol subtypes in near real time. Despite the spectral limitation, the algorithm demonstrates strong temporal and vertical coherence with CAMS forecasts, effectively capturing key aerosol transport events and seasonal variability over Belgium.
This presentation highlights CONIOPOL’s performance through high-impact case studies, long-term statistical analyses, and direct comparisons with CAMS forecasts and surface air quality observations. We focus on the detection of distinct aerosol types—including dust and smoke—and their vertical and seasonal distributions. Beyond operational applications, CONIOPOL enables the construction of consistent aerosol and cloud climatologies from continuous ALC observations, bridging gaps between satellite, in situ, and advanced lidar measurements. These results underscore the potential of depolarization-capable ceilometers to support long-term aerosol monitoring, improve understanding of aerosol–cloud interactions, and enhance air-quality climatologies.
How to cite: Laffineur, Q., Mangold, A., and Delcloo, A.: CONIOPOL: A novel operational approach for real-time aerosol/cloud identification using CL61 depolarization measurements, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-66, https://doi.org/10.5194/ems2026-66, 2026.
Continuous, high-resolution observations of thermodynamic and aerosol properties in the lower and free troposphere are essential for improving numerical weather predictions, climate monitoring, and satellite product validation. In particular, remote-sensing observational systems capable of resolving atmospheric structure and its temporal evolution are increasingly required to support high-resolution forecasting models and operational meteorological services.
Multi-wavelength Raman lidar technology provides dense vertically resolved measurements of temperature, water vapor, and aerosol optical properties, offering comprehensive insight into atmospheric dynamics and thermodynamics. In addition to thermodynamic profiling, lidar systems enable aerosol characterization, cloud detection, and boundary-layer monitoring, contributing to applications in meteorology and climate studies.
We present the operational performance of our multi-wavelength Raman lidar systems, designed for continuous and unattended 24-hour tropospheric profiling. The systems combine rotational Raman channels for temperature retrieval, rotational or vibrational Raman channels for water vapor mixing ratio measurements, and elastic and depolarization channels for aerosol backscatter and extinction profiling. Sustained daytime and nighttime operation is achieved through optimized optical filtering, effective solar background suppression, automated calibration procedures, and real-time data processing.
Continuous measurement case studies demonstrate the capability to resolve diurnal boundary-layer development, moisture variability, and aerosol layer evolution with high temporal and spatial resolution. Day-to-night performance, retrieval uncertainty, and product stability are assessed, while comparisons with collocated radiosonde observations confirm the accuracy and consistency of the thermodynamic profiles throughout the troposphere.
These results demonstrate the suitability of multi-wavelength Raman lidar systems for integration into operational atmospheric monitoring networks and emerging unmanned observational infrastructures. The provision of calibrated and quality-controlled thermodynamic and aerosol products supports applications in model validation, data assimilation, satellite evaluation, and long-term atmospheric studies.
How to cite: Soupiona, O., Dellis, S., Tsaknakis, G., and Georgoussis, G.: Operational Capability of Multi-Wavelength Raman Lidar systems for Continuous Thermodynamic and aerosol Profiling in the Troposphere, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-88, https://doi.org/10.5194/ems2026-88, 2026.
The demand for precise and user-friendly instruments for measuring fluxes between the earth's surface and the atmosphere is increasing. The LI-720 CO2/H2O flux sensor addresses this need by offering performance comparable to traditional high-end Eddy Covariance (EC) systems, but with reduced costs, maintenance and power consumption as well as the ability to measure additional biometeorological variables. The LI-720 represents a radically simplified form of eddy covariance with integrated ultrasonic anemometer for measurement of wind speed in 3 dimensions (U, V, W), photosynthetically active radiation (PAR), air temperature (Tair), relative humidity (RH), barometric pressure (Pa), evapotranspiration (ET) and carbon dioxide flux (FCO2).
The LI-720 is integrated into the Carbon Node, a system that combines the LI-720 sensor with a power and IoT communication box, resulting in a wireless, lightweight instrument. This setup is more akin to a meteorological sensor and delivers flux data directly to the LI-COR Cloud. LI-COR cloud supports real-time data access and automated data processing including quality control, gapfilling as well as footprint analysis, reducing the need for manual analysis.
Distributed environmental monitoring in natural and agricultural ecosystems can aid in reducing biases in site- selection and improve estimates of large-scale environmental phenomena including surface-atmosphere fluxes of trace gases, energy, and momentum. The Carbon Node's design allows for scalable operations, enabling the deployment of multiple nodes across ecosystems. Field data from the LENS project in Nebraska demonstrates the system's capability to capture spatially distributed fluxes measurements under various conditions and highlights the system's potential for continuous monitoring of spatial flux variability, providing a foundation for future scaling and network analyses.
How to cite: Kittler, F., Kathilankal, J. C., Baker, T., Thomas, T., and Hupp, J.: Innovative LI-720 CO2/H2O Flux Monitoring and Carbon Node Integration, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-266, https://doi.org/10.5194/ems2026-266, 2026.
Accurate quantitative precipitation estimation (QPE) remains a major challenge in many data-scarce regions, particularly across low- and middle-income countries where conventional rain gauge and radar networks are sparse or absent. Commercial Microwave Links (CMLs), widely deployed for telecommunication purposes, provide an opportunistic measurement technique that enables high-temporal-resolution rainfall observations (1–15 minutes) with large spatial coverage, especially in densely populated areas.
Recent studies in regions including Sri Lanka, Burkina Faso, Zambia, Nigeria, Ghana, and Cameroon have demonstrated that CML-based rainfall retrieval can complement and, in some cases, outperform satellite-based products such as IMERG in terms of accuracy and spatial representativeness. These results highlight the strong potential of CMLs to enhance QPE, particularly in regions where traditional observation infrastructure is limited.
Despite this demonstrated potential, large-scale operational use of CML data is still constrained by technical, legal, and organizational barriers. To address these challenges, the Global Microwave Data Collection Initiative (GMDI), developed within the framework of the COST Action OpenSense, aims to establish a scalable and sustainable system for global collection and use of CML data for rainfall observation.
In this contribution, we present first results from pilot implementations in Europe and Africa of the GMDI core system, the Data Collection, Archiving, and Processing (CAP) system. The CAP system enables near-real-time acquisition, storage, and processing of large volumes of CML data and supports their integration with complementary meteorological datasets. Furthermore, we discuss key challenges related to data quality and standardization, as well as the development of long-term data-sharing frameworks with mobile network operators.
By improving access to high-resolution rainfall observations, particularly in the Global South, GMDI has the potential to significantly enhance QPE capabilities. This will facilitate the integration of CML and satellite-based rainfall estimates, ultimately strengthening flood early warning systems, water resource management, and climate adaptation strategies worldwide.
How to cite: Christisn, C., Fencl, M., Bareš, V., Overeem, A., Uijlenhoet, R., Nebuloi, R., Winterrath, T., Ostrometzky, J., Messer, H., van de Beek, R., Øydvin, E., Van Weverberg, K., and Gosset, M.: Standardized collection and processing of rainfall data from telecommunication networks: First Results from the Global Microwave Data Collection Initiative (GMDI), EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-554, https://doi.org/10.5194/ems2026-554, 2026.
In 2025 Wx Labs introduced an all-sky imaging and sensing platform intended to help fill a gap in routine meteorological observing. While operational networks measure core meteorological variables well, they rarely observe the visual sky state itself. Yet cloud amount, cloud evolution and overhead conditions matter for nowcasting, radiation studies, aviation, solar applications and local decision-making. With recent advances in low-power machine learning, camera-based observations are becoming more realistic as routine measurements. By developing scalable all-sky hardware designed specifically for meteorological applications, Wx Labs is addressing this observing opportunity.
Development over the past year has moved the device beyond a prototype camera system and towards a deployable observation node: optics and camera software have significantly improved image quality, particularly at the horizon; a sloped lid and dedicated internal heater have strengthened weather resilience and icing; custom, swappable electronics and over-the-air software updates have improved longevity and maintainability; and detailed logging with CF-compliant variables have improved interoperability. From initial engagement with the NMHS community, development has also begun on a low-power all-sky camera variant that can operate on 0.2 W to support off-grid national observing stations.
Testing and deployments have been undertaken across multiple environments, including Antarctica, a climatic chamber down to -50 °C, the Alps during TEAMx, and several UK campaigns. Applications have included academic researchers, UAS operators and solar farms. The talk will discuss these deployments and the applications they support, including cloud monitoring, local nowcasting, radiative studies, and augmentation of existing observing networks. Rather than treating sky cameras as ancillary devices, this talk argues that they can become a meaningful new observation layer in meteorology when paired with reliable engineering, usable metadata, and machine learning for automatic interpretation. The main challenge is no longer whether all-sky observations are interesting, but how to make them robust, standardised and interoperable enough to support routine scientific and operational use.
How to cite: Pickering, B.: Seeing the Sky: Progress Toward Routine All-Sky Camera Networks, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-697, https://doi.org/10.5194/ems2026-697, 2026.
The Finnish operational weather radar network has 12 C-band polarimetric radars covering the country. Altough primarily scanning at low elevation angles, the operational scanning schedule for the weather radars contains a vertical ‘birdbath scan’ which is repeated every 15 minutes. The ‘birdbath’ scan is designed for calibrating differential reflectivity (ZDR) and the antenna rotates 360 degrees in azimuth while remaining vertically-pointing. All pulses within the scanning time (< 30 s for a full rotation) are then averaged and processed as normal to provide one vertical profile with the three Doppler moments (Z, v, and spectral width) and the polarimetric variables ZDR and cross-correlation coefficient rho_hv. ZDR at vertical is not useful for meterological purposes but the remaining variables can be utilised in the same manner as for a vertically-pointing Doppler (cloud radar (Frech et al., 2026). It should be noted that the spectral width is broadened due to the rotation. Rho_hv is an excellent indicator of the melting level and can be employed in the same way as LDR or slanted-LDR is used within the Cloudnet processing scheme, and hence the collection of vertical ‘birdbath’ scans can be concatenated to provide very similar output to vertically-pointing Doppler cloud radars and used for satellite and model evaluation in the same way.
Although the effective temporal resolution is rather coarse, this data has the advantage of no Doppler aliasing and minimal attenuation, even in heavy rain. The sensitivity appears sufficient to capture the majority of ice clouds (although maybe missing some liquid layers) including ice clouds above strong precipitation which would be missed by Doppler cloud radars operating at Ka- or W-band. After adjusting for the frequency difference (for both Z and v), these observations have exceptional potential to complement the satellite cal/val and model evaluation activities being performed by cloud radar networks.
Frech, M., S. Kneifel, P. Ockenfuss, and M. Gergely, 2026: Exploring the Untapped Potential of Operational Weather Radars for Vertical Profiling of Precipitation and Clouds. Bull. Amer. Meteor. Soc., 107, E127–E141, https://doi.org/10.1175/BAMS-D-24-0113.1.
How to cite: O'Connor, E., Ritvanen, J., Tukiainen, S., Siipola, T., and von Lerber, A.: Vicarious use of calibration scans from the operational FMI weather radar network, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-635, https://doi.org/10.5194/ems2026-635, 2026.
High-quality water vapor measurements from the ground to space are essential for assessing Earth's radiative balance. Water vapor contributes substantially to the uncertainty of the outgoing longwave radiation, emphasizing the need for accurate and reliable measurements. The current generation of commercially available operational radiosondes exhibits rapidly degrading reliability above the tropopause, leaving a critical observational gap. The Cryogenic Frost Point Hygrometer (CFH), a widely used instrument for water vapor profile measurements relies on the R23 coolant, which was banned under the Montreal Protocol.
The Swiss H2O Hub addresses this challenge using two balloon-borne instruments and a newly developed cryogenic water vapor radiometer. These observations are complemented by the MeteoSwiss RALMO Lidar system. ALBATROSS is a compact mid-IR laser spectrometer that measures the water vapor absorption spectrum in an open-path multipass cell, providing SI-traceable water vapor data. The second balloon-borne instrument is the Peltier Cooled Frost Point Hygrometer (PCFH) that replaces the R23 coolant with a Peltier cooler and measures the frost point temperature via a thermocouple calibrated at METAS (SI-traceable). Stratospheric and mesospheric water vapor is measured with two passive radiometers: the already established MIAWARA instrument at the Zimmerwald Observatory near Bern and a newly developed cryogenic instrument operated at the laboratory building.
In total, we conducted 29 balloon soundings with various payload configurations and performed detailed instrument intercomparisons for the troposphere and the lower stratosphere. Both balloon instruments achieve breakthrough requirements for the stratosphere and reach threshold requirements for the troposphere.
These combined observations enabled the detection of increased water vapor volume-mixing ratios in the lower stratosphere and mesosphere above Switzerland. Both the passive radiometers and the balloon soundings revealed enhanced water vapor levels in the years following the eruption.
How to cite: Stober, G., Brunamonti, S., Wienhold, F. G., Poltera, Y., Romanens, G., Artho, V., Peter, T., Murk, A., Weitnauer, A., Emmenegger, L., Tuzson, B., Bell, A., Matthey, R., Filinis, A., Martucci, G., and Haefele, A.: Swiss H2O Hub: Water vapor measurements from ground to the thermosphere, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-648, https://doi.org/10.5194/ems2026-648, 2026.
The Meteosat Third Generation (MTG) Flexible Combined Imager (FCI) offers enhanced capabilities for monitoring atmospheric processes. Its higher spatial and temporal resolution, together with new spectral channels and advances in deep learning, enables opportunities to re-explore its potential for retrieving temperature and humidity profiles. Vertically resolved inversion of temperature and humidity is inherently ill-posed and becomes more challenging with imagers due to their limited infrared spectral resolution. Operational algorithms rely on numerical weather prediction background fields to guide the retrieval, reducing the independence and added value. Additionally, expanding data volumes also make optimal iterative inversion approaches computationally slow, limiting real-time applications. This study aims to investigate whether spatially aware deep learning models can extract frequent, spatially detailed, and forecast-independent profiles of tropospheric temperature and specific humidity that could complement traditional retrievals, be used for higher-level products or be more frequently assimilated in numerical weather prediction systems.
We developed and evaluated a deep learning framework to retrieve temperature and humidity profiles from FCI measured radiances. The model is based on a U-Net encoder–decoder architecture that exploits spatial context from 128x128 pixel image patches and integrates all 16 FCI spectral channels with ancillary surface and time variables. The network was trained on 14 months of collocated FCI observations as input and profiles of temperature and humidity across 15 pressure levels from CERRA reanalysis as target. Results were validated against temporally independent radiosonde measurements.
When evaluating retrievals and CERRA profiles against radiosondes, temperature retrievals remain within 1 K standard deviations (STDs) of CERRA, while derived relative humidity STDs remain below 5% of CERRA's over the whole profile. Performance degrades under cloudy conditions and at night, but the model preserves physically consistent vertical structures. Compared to above cloud retrievals, we measured a maximum STD increase of 0.3 K temperature and 7% relative humidity below clouds, despite limited direct radiative information. The retrieved profiles substantially improve upon a 30-year climatology baseline from ERA5 against radiosondes.
A permutation feature importance analysis reveals the spectral sensitivities learned by the model. The split window and CO2 infrared channels at 12.3 and 13.3µm have the strongest importance on both temperature and humidity profiles, as they measure both thermodynamic information combined from the cloud top, troposphere and surface. The water vapour channels around 6.3 and 7.3 µm, as expected, also show large importance for mid- and upper-tropospheric humidity. Visible and near-infrared channels despite not being used in traditional radiative transfer, show some sensitivities, with the 0.8 and 0.9µm bands contributing most to lower-tropospheric humidity during daytime.
The results demonstrate that deep learning models can extract potentially useful tropospheric profiles of temperature and humidity by combining radiance measurements with image-based context and learned climatological structures.
How to cite: Salgueiro, A. and Meyer, A.: Tropospheric temperature and humidity retrievals from Meteosat Third Generation Imager (MTG-FCI) based on deep neural networks, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-398, https://doi.org/10.5194/ems2026-398, 2026.
The Royal Netherlands Meteorological Institute (KNMI) operates the national surface observation network for weather, climate, and aviation applications. Ensuring long term consistency and traceability of these observations requires systematic lifecycle management of the underlying instrumentation. This presentation provides insight into the scientific and methodological aspects of such a transition, using the replacement of KNMI’s present weather and visibility sensors as a case study.
Since approximately 2000, visibility and present weather within the KNMI network have been measured using the Vaisala FD12P Present Weather Sensor (PWS). As this instrument has reached end of life and is no longer supported by the manufacturer, KNMI initiated a replacement process that resulted in the selection of the Vaisala FD70 PWS.
To evaluate the performance of the new sensor and the impact of this transition on the observations, an extensive parallel measurement program was established. From April 2024 to January 2026, FD70 sensors were deployed at multiple stations representing a range of environmental conditions. Their performance was evaluated through comparisons with co-located FD12P instruments, and at the test field in De Bilt: reference transmissometer measurements. In De Bilt, two FD70s were also placed side to side to check for consistency and natural variability.
The analysis reveals good agreement between the new FD70 present weather sensor and the transmissometer reference for the lower visibility range (up to ~2 km). However, systematic differences in visibility were observed between the FD12P and FD70, particularly at high visibility ranges. To maintain the long term records, these differences need to investigated and (if needed) corrected for. We found that differences could be attributed to changes in instrument calibration and deterioration, sensor contamination, and insect interferences. Local variations in visibility, caused by patchy fog, introduced additional differences between the two sensors. After extensive automatic and manual filtering, FD70 data can be converted to the FD12P reference (and vice versa), enabling consistent long‑term records.
Present weather identification also shows clear improvement. The FD70’s increased sensitivity compared to the FD12P leads to more reported precipitation events and better detection of small hydrometeors, enabling more reliable distinctions between phenomena such as fog and drizzle. These findings align with independent observations from rain gauges and the KNMI validation team.
These findings highlight the challenges associated with maintaining homogeneous long term visibility and present weather records during sensor transitions. The implications extend to, for example, (aviation) meteorology, fog climatology, and air quality studies.
How to cite: Jongen-Boekee, J., Ruijter, J., Strickland, J., Wauben, W., van Wijngaarden, F., and Bloemink, H.: Replacing KNMIs Present Weather Sensors: insights in systematic sensor renewal, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-362, https://doi.org/10.5194/ems2026-362, 2026.
Evaporation is typically the largest flux of the water balance on a yearly basis in the mid latitudes, often larger than discharge. Yet, it is the most difficult component to measure directly. For this reason, hydrological models often include evaporation as a fraction of potential evaporation or as a residual term. Especially above heterogeneous terrain, determining evaporation is complex and its accuracy highly dependent on e.g. measurement scale, wind speed and direction (footprint), and type of vegetation.
Multiple measurement techniques are available to estimate evaporation (like eddy covariance, scintillometry, or flux variance method). More recently new, lower cost eddy covariance sensors by LiCor (Lincoln, NE, USA) have been introduced to the market, i.e. the LI-710 and LI-720. Some recent intercomparison studies have shown the relevance and downsides of lower cost eddy covariance systems compared to conventional systems. However, these studies did not include other techniques besides eddy covariance techniques, to estimate evaporation. All measurement techniques have their particular uncertainties due to differences in measuring principle, footprint, sensor accuracy, etc. This can lead to large (~35% at mid-day) differences in the obtained evaporation estimates. In this study we aim to quantify the differences in evaporation estimates by comparing several measuring techniques during a summer season over a homogeneous and a heterogeneous terrain in the Netherlands: Cabauw (homogeneous well-watered grass) and Herenboeren Wenumseveld (heterogeneous agricultural site). The measurement techniques included in the intercomparison are: a conventional eddy covariance system, a dual wavelength scintillometer system (optical and microwave), the flux variance method, and the novel LI-710 and LI-720 sensors.
First results, based on a measurement campaign for the summer of 2025, show that the difference in determined evaporation expressed as the latent heat flux between the different sensor techniques is highly variable (up to 250 W/m2), especially above heterogeneous terrain, peaking around mid-day. Above homogeneous terrain, the different sensors are much more in agreement (up to 100 W/m2). During the summer of 2026, the measurement campaign will be repeated to gain more insights in the sensor uncertainty range by adding a LI-720 sensor and by performing a tilt experiment with the LI-710. The latter is meant to test sensor sensitivity for wind direction and turbulence variations, since that has not been done in previous studies with these specific lower cost sensors. This will result in a better understanding of the uncertainties associated with evaporation measurements, which can be especially valuable with regards to water and energy balance closure and for catchment modelling.
How to cite: Bos-Burgering, L., Callejas-Rodelas, J. Á., Hartogensis, O., Maas, D., de Bruijn, C., Ronda, R., Uijlenhoet, R., and Coenders, M.: Quantifying the uncertainty of evaporation estimates with different sensors above homogeneous and heterogeneous terrain, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-137, https://doi.org/10.5194/ems2026-137, 2026.
The potential wind[1] is the wind speed one would measure under ideal WMO conditions, i.e. on a 10-metre mast with only short grass and no hills or obstacles in the surroundings. The potential wind is computed using exposure correction factors (ECFs), which are determined from the wind-speed measurements themselves and depend on the wind direction. Climatology studies should be based on data that are representative of an area wider than the vicinity of the wind mast, so the data should exclude local effects (e.g. from trees or buildings) and sensor changesor measurement site re-locations. If the "disturbance" of the measurement is not extreme, ECFs can be used to correct the measurements (homogenisation). ECFs and potential wind are therefore used for meteorological measurement site inspection, atmospheric model validation, aviation applications and construction regulations for buildings and water works.
Essentially, there are two methods to compute ECFs: (1) the Gustiness method, based on the hourly maximum 3-second mean speed (gust) divided by the hourly mean speed and (2) the Sigma method based on 10-minute standard deviation divided by 10-minute mean wind speed. The latter method was proved to be superior in 2009, but because 10-minute wind measurements were not stored before 2003, KNMI kept using the Gustiness method. Now that KNMI has a substantial (and still growing) dataset, the Sigma method can be applied.
We developed, fine-tuned, tested and verified an algorithm that can automatically provide 10-minute ECF and potential wind speed updates based on the Sigma method. These near-real time updates are of interest to a broader range of users, including forecasters.
[1] See also: https://www.knmi.nl/kennis-en-datacentrum/project/potential-wind
How to cite: Helfer, K. C., Stepek, A., and Wijnant, I. L.: Towards an automated method for near-real-time exposure correction of wind measurements, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-154, https://doi.org/10.5194/ems2026-154, 2026.
EUMETNET's observation Programme E-Profile processes and disseminates atmospheric vertical profiles of wind, aerosols and clouds in near real-time, focusing on operational meteorology. In the current phase of the Programme (2024-2028), E-Profile is expanding its profiling capabilities with the setup of a ground-based microwave radiometer (MWR) network dedicated to humidity and temperature profiling. The observations are mostly focusing on the atmospheric boundary layer (ABL), with the goal of achieving a high temporal resolution coupled with low data latency periods. The data are useful for fore- and nowcasting applications and offer a good complement to satellite observations in the context of data assimilation.
E-Profile will provides three groups of data products, quasi continuously and with temporal resolution in the range of seconds or minutes: 1) calibrated brightness temperatures measured at different frequencies (mostly in the K- and V-band) and at different elevation angles; 2) liquid water path, water vapor, and temperature profiles retrieved from the brightness temperatures using the TROPoe retrieval framework based upon optimal estimation; 3) atmospheric stability and Forecast Indices (FI), which can be of particular interest for forecasters, typically in rapidly evolving convective situations.
E-Profile operates a pilot network of 20 instruments from 7 European countries and 3 different manufacturers and has started the near real-time data distribution of the quality controlled brightness temperatures (L1) since the start of 2026. Following the emergence of fast forward operators, these measurements can now directly be assimilated in NWP models. The retrievals of thermodynamic profiles are currently running in real-time on the European Weather Cloud and their validation is ongoing before the data can be distributed in real-time. For the validation study, we have selected three instruments from two different manufacturers located at two reference stations in Europe and performed extensive intercomparisons against radiosonde measurements during the year 2024 and 2025. In this contribution, we show the results of the validation and present the current state of the E-Profile MWR network, including the tools setup for real-time monitoring of data quality.
How to cite: Sauvageat, E., Rüfenacht, R., Turner, D., Turp, M., Cimini, D., Marke, T., Pospichal, B., and Haefele, A.: The E-Profile temperature and humidity network: towards operational real-time thermodynamic profiling at the European scale , EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-510, https://doi.org/10.5194/ems2026-510, 2026.
Improving convective-scale forecasts requires more detailed and continuous observational data of thermodynamic profiles and wind profiles in the atmospheric boundary layer (ABL) than currently available. To meet these data requirements, DWD is establishing a network of various surface remote sensing systems targeted on ABL-profiling for routine network operation. This involves integrating 13 Doppler lidars for observing wind profiles and 13 broadband differential absorption lidars (DIALs) for observing water vapor profiles into the network at selected surface stations across Germany until end of 2027.
This contribution reports the results from the assessment of the DIAL, the DA10 from Vaisala, for water vapor profiling network performance and its ability to improve the boundary-layer moisture in a limited-area numerical weather prediction system. The Vaisala DA10 instrument is designed to provide operational water vapor profile observations in the ABL, without the need for calibration. We operate two DA10 units at the Observatory Lindenberg to evaluate all aspects of instrument reliability, operational sustainability, data quality, and on the potential benefit for the NWP using assimilation experiments. Our methods include comparisons with radiosounding observations (4 per day) over at least one year of continuous observations, as well as observation-minus-background statistics between the DA10s and the regional model system ICON-D2 to identify observation errors and to evaluate the model performance with respect to boundary-layer moisture, e.g., under convection. Furthermore, we present first results from assimilating the DA10 water vapor profiles into the kilometer-scale ensemble data assimilation system (KENDA).
Summarizing, this presentation provides an overview of the DA10 network's operational viability for monitoring water vapour profiles 24/7 and for providing additional information for convective-scale data assimilation.
How to cite: Knist, C., Lehmann, V., Heuser, J., Löffler, M., Pruschke, J., and Schomburg, A.: Assessment of a Broadband Differential Absorption Lidar for use in measurement networks and data assimilation, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-223, https://doi.org/10.5194/ems2026-223, 2026.
Following recent severe weather events Deutscher Wetterdienst (DWD) expands its operational network by adding vertical profile measurements of wind and humidity. The underlying aim is to spatially and temporally refine the observation base. As a consequence, short-term forecasts and warning capabilities are expected to improve, in particular in case of extreme precipitation events.
In this context, a network of Doppler lidar systems will be installed at 13 automatic weather stations across Germany until 2027. Doppler lidar systems are capable of estimating the three-dimensional wind vector in near real-time within the atmospheric boundary layer and (under favourable conditions) up to a height of 12 km above ground level. Routinely this is achieved by measuring radial wind speed for 4 to 24 equidistantly distributed rays, typically at an elevation angle of 75°.
Over a period of one year, up to six of those systems (WindCube 100S, Vaisala) were operated side-by-side on our test site in Hamburg, Germany. This contribution reports on extensive tests, including tests on positioning accuracy. Given that an error of just 0.15° in elevation corresponds to an under- or overestimation of horizontal wind speed by 1%, positioning accuracy is crucial in an operational set-up. Dedicated test scans known as "flip-tests" are suitable for estimating the magnitude of a potential elevation error, even in a remote set-up. Another potential reason for under- or overestimating radial wind speed lies in the deviation of the beam path from the zenith direction (tilt error). Methods for detecting and quantifying tilt errors based on Doppler lidar measurement data are presented.
How to cite: Kabus, S.: Expanding the DWD network by Doppler lidar systems: ensuring high accuracy during operation , EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-516, https://doi.org/10.5194/ems2026-516, 2026.
High-resolution forecasting systems and emerging AI-based weather models are placing increasing demands on atmospheric observations, particularly for vertically resolved measurements in data-sparse regions and across the boundary layer–upper troposphere/lower stratosphere (UT/LS) interface. Current observing networks, however, remain limited in their ability to provide persistent, co-located thermodynamic and kinematic measurements with sufficient temporal and vertical resolution.
Here we present a new in-situ observing approach based on long-duration stratospheric balloons. These platforms provide repeated high-resolution vertical profiles (surface to ~14 km) together with multi-day Lagrangian float trajectories in the upper troposphere. This dual capability enables simultaneous sampling of boundary layer structure, free-tropospheric thermodynamics, and upper-level wind evolution, offering a uniquely comprehensive dataset for process studies, model evaluation, and data assimilation.
System performance is demonstrated through coordinated measurement campaigns, including validation against independent aircraft observations and characterization of vertical resolution (10–100 m in the boundary layer, with ~100 levels per profile). The platform provides persistent sampling across the full diurnal cycle and extends coverage into oceanic and other data-sparse regions, addressing key observational gaps for next-generation NWP and AI-based forecasting systems.
To assess the value of these observations, we conduct Observing System Experiments (OSEs) within an ensemble data assimilation framework coupled to an AI-based forecast model (AIFS-ENS). We separately assimilate (1) vertical thermodynamic profiles, (2) Lagrangian wind observations, and (3) the combined dataset. Results show that vertical profiles primarily improve thermodynamic structure and boundary layer representation, while Lagrangian measurements provide strong constraints on upper-level winds and jet positioning. The combined dataset yields complementary benefits.
These results highlight the potential of long-duration balloon systems as a new class of atmospheric observing networks, capable of delivering calibrated, high-resolution measurements for model development, satellite validation, and operational assimilation. They also demonstrate a practical pathway for integrating advanced observational platforms with AI-based prediction systems, supporting the development of observation-adaptive forecasting.
How to cite: Tian, X. and Tindle, A.: Long Duration Stratospheric Balloon Drift and Soundings and Weather Forecasting Impacts in NWP and AIWP, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-330, https://doi.org/10.5194/ems2026-330, 2026.
Spatially and temporally continuous observations of atmospheric boundary layer (ABL) dynamics and thermodynamics are key for many areas of atmospheric research. State-of-the-art observational approaches are either limited by vertical resolution (satellites), spatial coverage (ground-based profilers) or spatial and temporal coverage (radiosondes). The VITAL II campaign (Vertical Profiling of the Troposphere: Innovation, Optimization and Application) as part of HErZ (Hans Ertel Center for Weather Research), a cooperation on fundamental weather and climate research between the German Meteorological Service (DWD) and German universities, addresses this observational gap.
VITAL II will take place from June 1 – August 31, 2026 in the Cologne Bay region between the west German cities of Cologne, Bonn and Aachen employing and installing seven profiling sites over a wide variety of land surface types. At the profiling sites, ground-based remote sensing systems such as water vapor lidar, Doppler lidar and microwave radiometers will be operated which yield high potential to reliably profile ABL temperature, humidity, winds and turbulence in a nearly continuous manner. Uncrewed aircraft systems (UAS) will additionally be operated at selected sites during an intensive observation period, complemented by a large number of radiosonde ascents.
During VITAL II, first data from the Meteosat Third Generation Sounder (MTG-S1) satellite instrument IRS (Infrared Sounder) will be employed for providing continuous 3D observations of temperature and humidity with a temporal resolution of ~30 min. However, IRS deficits will remain in observing the ABL, especially in cloudy conditions. VITAL II will leverage the use of these novel, hyperspectral IRS observations by combining them with the VITAL II surface-based in-situ and remote sensing observations. Novel machine learning algorithms which synthesize MTG-S1 data with surface-based observations will be applied to and assessed by the multitude of additional VITAL II profiling observations. The objective is to significantly enhance the observed information content in the ABL. Next to the extensive profiling, VITAL II will install a dense near-surface observation network on the meso-beta-scale (20–200km = regional scale). Up to 50 surface stations of the updated autonomous cold pool logger (APOLLO 2.0) will be installed within Cologne Bay.
Altogether, the observational setup will be used for enhancing the understanding of the evolution of the stable and convective ABL over an urban – rural transition zone, as well as on convective cold pools. For the latter, the main focus is on merging dense spatial, near surface data with vertical temperature and humidity patterns. The profiling observations will be used for data assimilation studies with the DWD numerical weather prediction model ICON and for evaluating and improving ICON land surface and ABL turbulence parameterization schemes.
This contribution will present in detail the VITAL II concept and first measurements highlighting the importance of sensor synergy for ABL coverage.
How to cite: Löhnert, U., Ahlgrimm, M., Ament, F., Beyrich, F., Büchau, Y., Esters, L., Marke, T., Obermann-Hellhund, A., Oertel, A., Platis, A., Pospichal, B., Pschera, A., Rapmund, A., Schween, J., Sakradzija, M., Toporov, M., and Wieser, A.: VITAL II: Enhancing regional atmospheric boundary layer observations through the synergy of novel state-of-the-art sensors , EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-771, https://doi.org/10.5194/ems2026-771, 2026.
The Land-Atmosphere Feedback Initiative (LAFI, https://www.lafi-dfg.de), funded by the German Research Foundation (DFG), is an interdisciplinary consortium of researchers from atmospheric, agricultural, soil, hydrological, and neuroinformatic sciences dedicated to an improved understanding and quantification of land-atmosphere feedback processes, employing an innovative combination of advanced research methods. These processes are being investigated via unique synergistic observations and model simulations from the micro-gamma (» 2 m) to the meso-gamma (» 2 km) spatial scales, and across diurnal to seasonal time scales.
The four main objectives of LAFI are:
- To analyze the relationships between surface fluxes and their driving variables using Machine-Learning tools in order to identify possible ways to overcome the limitations of Monin-Obukhov Similarity Theory,
- To better understand the partitioning and variability of surface fluxes above heterogeneous land surfaces in view of improving the experimental energy balance closure,
- To partition evapotranspiration (ET) by quantifying E and T from within crop stands during the vegetation period using observational and modeling approaches
- To quantify entrainment by identifying and describing the key processes in the convective boundary layer with the aim to unravel relevant relationships for an improved parameterization of entrainment fluxes in models.
The backbone of the LAFI research are the operational measurements at the GEWEX Land-Atmosphere Feedback Observatory (GLAFO, https://lafo.uni-hohenheim.de/en) at the University of Hohenheim in Stuttgart, Germany. The site represents a mixed farmland area in the Southern part of Germany. Within LAFI, the observatory program at Hohenheim was augmented by a number of innovative measurement techniques, most of which were operated continuously over the full growing season from the end of March to the end of October, 2025. Additionally, specific measurements were carried out during five intensive observation periods, each covering 3-5 days between April and August, 2025. The micrometeorological measurements focused on two stands covered with winter wheat and maize.
The following key techniques were applied:
- scanning lidar systems for 3D water-vapor, temperature, and wind measurements,
- Fiber-Optic Distributed Sensors (FODS) for simultaneous high-resolution horizontal and vertical temperature measurements in the soil, vegetation, and atmosphere,
- Uncrewed Aerial Vehicles (UAVs) for multispectral and microwave high-spatial resolution observations of the land surface,
- in-situ sensors for observing (partitioning) ET, including lysimeter, and eddy-covariance in combination with isotope measurements of water-vapor in the soil, roots, canopy, and atmosphere,
- in-situ networks of sensors for the profiling of other soil, canopy air space and plant variables such as matric potential, sap flow, leaf gas exchange (CO2, H2O) and stomatal control,
- scintillometers to link the local EC-based fluxes with the entrainment fluxes derived from the lidar synergy,
- Cosmic-Ray Neutron Sensing (CRNS) to capture integrated field scale soil moisture dynamics.
With this contribution we will outline the LAFI measurement setup and strategy, characterize the data availability over the measurement period and show first examples of a synergetic analysis and interpretation of the measurements.
How to cite: Wulfmeyer, V. and Beyrich, F. and the LAFI GOP Team: Sensor Synergy to Study Land-Atmosphere Interaction: A Field Experiment at the Hohenheim Land-Atmosphere Feedback Observatory (LAFO) Covering the 2025 Growing Season, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-778, https://doi.org/10.5194/ems2026-778, 2026.
The wind blows and waves form in response. This general process forms the basis for the widespread use of Monin-Obukhov similarity theory (MOST) in the parameterisation of turbulent exchange between the atmospheric boundary layer (ABL) and the ocean. There are a multitude of conditions under which the assumptions required for the application of MOST fail, however. While the wind forcing in the ABL is highly localised, the local wave field can be strongly impacted by non-local wind forcing. During low wind conditions, waves excited non-locally have the capacity to force motions within the ABL. This wave-forcing on the ABL presents conditions under which the application of MOST fails, particularly within the first ten meters. The deviations from MOST in this case are, however, rarely documented in great detail.
A novel and comprehensive field campaign was designed to both qualify and quantify the flux-gradient relationship in the atmospheric boundary layer during low-wind large-swell conditions. We present here the preliminary results from this field campaign at Belle-Île-en-mer. The dataset includes measurements of mean wind and temperature profiles, high frequency momentum and heat fluxes, and global ABL and wave conditions.
Above the sea surface, the mean wind profile (wind speed and wind direction) was remotely sensed at 3~km offshore at a very fine vertical resolution thanks to two scanning LiDARs and the temperature profile was measured by a flying drone. Fluxes at the surface were recorded at high frequency by equipment mounted on a dedicated trimaran. Global ABL conditions were monitored using a profiling LiDAR, a microwave-radiometer and atmospheric soundings. We provide a first look into the measured flux-gradient relationships and highlight cases during which deviations from MOST are observed.
How to cite: Everard, K., Conan, B., Keravec, P., Bourras, D., Bouin, M.-N., Goret, M., Julien, F., Baudru, S., Perret, L., Piquet, T., and Van Eijk, A.: Observations of the flux-gradient relationship at the air-sea interface: preliminary results, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-175, https://doi.org/10.5194/ems2026-175, 2026.
For decades, carefully-selected and quality-controlled measurements of atmospheric turbulence and fluxes across a variety of environments – including open ocean, flat farmland, and complex mountainous terrain – has facilitated verification of classical theories of atmospheric turbulence upon which numerical weather model parameterizations, air quality studies and monitoring, and myriad other applications are based. However, measurements of coastal atmospheric boundary layer (ABL) turbulence are limited, in part due to the challenges in securing long-term measurements in addition to the inherent complexities in such environments. Specifically, coastal regions – spanning several tens of kilometers on either side of the coastline – are characterized by strong gradients in surface thermal and roughness properties and can feature complex topography, which modify the ABL beyond the canonical homogeneous theory. Consequently, the applicability of traditional theories and behavior of atmospheric turbulence within coastal environments remains an enigma.
Here, we examine coastal turbulence data obtained at a novel coastal observing site, the Naval Research Laboratory Coastal Environmental Observation Station (NRL-CEOBS), located within the Monterey Bay region of Central California. We address challenges in quality controlling high-frequency turbulent data, and present preliminary eddy-covariance data collected across January to March 2024 collected from a flux tower outfitted with a sonic anemometer and gas, humidity, and temperature sensors located within 0.25 km of the coast. Computed velocity and temperature variance spectra and flux cospectra are compared with classical datasets (e.g., Kaimal et al 1972). Preliminary results reveal that the existence of a true inertial subrange hinges on the direction of the prevailing flow and therefore flux footprint. Additionally, turbulence isotropy is diagnosed using the Reynolds Stress tensor. The data reveal highly anisotropic turbulence is diagnosed more frequently during onshore-oriented flow compared to offshore flow. The proportion of isotropic data increases when decreasing the flux averaging time period, which removes large, energy-producing scales of motion from consideration. We also corroborate the flux tower measurements with upper boundary layer measurements obtained using profiling and scanning LiDAR modes, to elucidate environmental flow attributes which correlate with the near-surface turbulence behavior.
How to cite: Hlywiak, J., Schmidt, J., Flagg, D. D., and Turney, F.: Demystifying the behavior of Coastal Atmospheric Surface Layer Turbulence, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-179, https://doi.org/10.5194/ems2026-179, 2026.
Offshore wind energy is a rapidly expanding sector and a key element of the transition toward sustainable energy systems. Accurate characterization of site conditions, such as wind speed, atmospheric stability, and metocean conditions, is essential for the planning, design, and operation of offshore wind farms.
While traditional meteorological masts can provide detailed measurements of these parameters, their installation and maintenance are costly. Consequently, floating lidar systems (FLS) have become the preferred alternative for offshore wind resource assessment, providing wind measurements together with selected meteorological and oceanographic parameters.
Mounting a microwave radiometer (MWR) on a floating platform would complement these measurements by providing continuous vertical profiles of temperature and humidity, enabling in-situ characterization of atmospheric stability. Atmospheric stability strongly influences boundary-layer structure, wind shear, and wake development and is therefore important for offshore wind resource assessment and modeling.
This study investigates the feasibility of such a concept by assessing the influence of platform motion on MWR measurements, which are used to derive stability parameter, such as the bulk Richardson number. Measurements from a motion-table-mounted, moving, uncompensated MWR are compared with those from a stationary system of the same type in an onshore experiment.
The results quantify the impact of platform motion on retrieved profiles and evaluate whether motion compensation is required for reliable deployment of MWR systems on floating platforms. The analysis includes controlled sinusoidal motion patterns (roll, pitch, and combined pitch \& roll) at three intensity levels, as well as realistic motion derived from floating platform measurements. The findings of this work contribute to the assessment of the feasibility of integrating MWR systems into floating platforms for offshore wind applications.
How to cite: Watson, W., Czekala, H., and Gottschall, J.: Effects of Platform Motion on Microwave Radiometer Measurements, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-228, https://doi.org/10.5194/ems2026-228, 2026.
Three-dimensional turbulent processes substantially contribute to the exchange of energy and momentum in the mountain boundary layer (MoBL). These processes are usually not properly represented in current numerical weather prediction models, since turbulence parameterizations are not adapted to complex terrain. To better understand the three-dimensional structure of turbulence in the MoBL and to inform future parameterization development, in-situ observational data from MoBLs is necessary. The optimal dataset would consist of 3D wind and standard atmospheric state variables measured at distributed locations simultaneously. The novel method of using a fleet of drones (i.e., Uncrewed Aerial Systems, UAS) can provide an approximation to this goal.
The drones of the SWUF-3D fleet allow for three-dimensional wind measurements and are equipped with fast temperature sensors and a capacitive humidity sensor. They can be programmed to hover at certain positions for a duration of approximately 20 minutes. Three measurement campaigns were conducted at Nafingalm, an Alpine pasture near Innsbruck, in the framework of the TEAMx research programme. The most recent campaign, carried out in summer 2025, encompassed a maximum of 30 UAS hovering between 50 and 240 m above ground level (AGL). Depending on the chosen pattern in which the drones are organized, different analyses can be performed. Turbulent fluxes and turbulence kinetic energy (TKE) can be compared between different drones for any pattern. Arranging the drones in a box-like pattern allows for computing gradients between UAS in all three spatial directions. All of the turbulence quantities to be analyzed require at least one of the three wind components. Deriving absolute vertical velocity accurately is particularly challenging. An essential parameter for vertical wind calculation is the rotor thrust of the multicopter. Thrust is directly proportional to air density.
Analysis showed that approximating the temperature by the international standard atmosphere to derive the density at the measurement site nearly 2000 m above mean sea level can lead to substantial errors in absolute vertical wind. In highly three-dimensional flow such as in an Alpine valley, an accurate estimate for the absolute vertical velocity is important to understand orographic flow deflection. Therefore, if UAS are used to obtain the 3D wind vector, an integrated sensor suite for temperature, humidity and pressure is essential and thermodynamic measurements need to be thoroughly quality-checked for all variables. Regarding TKE, preliminary results show that the drones reasonably capture the diurnal evolution when compared to a ground-based sonic anemometer located 5 m AGL. TKE and turbulent momentum fluxes at the different drone positions indicate spatial heterogeneity for given points in time. This contribution will focus on the technique of measuring turbulence with a drone fleet as well as the analysis of different turbulence quantities and their distribution across the valley.
How to cite: Alexa, A., Wildmann, N., Gohm, A., Wiech, A., and Lappin, F.: Using the SWUF-3D drone fleet to determine turbulence characteristics in a small Alpine valley during TEAMx, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-714, https://doi.org/10.5194/ems2026-714, 2026.
Accurate modelling of turbulent sensible heat fluxes (QH) within cities is essential for understanding energy exchange between the urban surface and the atmosphere, with implications for several fields, including climate modelling, weather prediction, and urban environmental management. In this study, six Large-Aperture Scintillometers (LAS) operating over different neighbourhoods of Berlin within the urbisphere-Berlin campaign (Fenner et al., 2024) are used to derive QH. Following Saunders et al. (2024), the LAS source areas are determined by combining multiple footprints along each path using the optical path-weighting function, with iteratively derived surface roughness parameters (z0, zd, zf) obtained using the Kanda et al. (2013) method combined with a detailed building-vegetation digital surface model. Geospatial data resolution is adjusted with varying atmospheric stability conditions to ensure adequate domain representation. The LAS-derived QH uses observed refractive index structure parameter (Cn2), with meteorological variables, roughness parameters and Monin-Obukhov Similarity Theory.
The six LAS paths span both inner and outer city areas of Berlin, enabling analysis of the spatial and temporal variability of QH for different building density and vegetation, as well as land use (e.g. inner city, residential). Results are presented across season and synoptic conditions, highlighting the influence of land cover and boundary layer dynamics on QH. Source-area land cover composition shows a clear urban gradient, with vegetation decreasing from ≈ 50-55% in outer-city paths to ≈ 35-50% in inner-city paths, while building fractions increase from ≈ 15-17% to ≈ 20-32%, alongside consistently high paved surface contributions (≈ 28-35%). LAS observed QH compared to eddy-covariance measurements show strong consistency. QH from high resolution (O(100 m)) numerical weather prediction modelling, undertaken with the Met Office Unified model during selected days, are compared to the LAS QH using the footprint characteristic to assess simulation capability.
How to cite: Southgate-Ash, C., Glazer, R., Christen, A., Fenner, D., Saunders, B., Tsirantonakis, D., and Grimmond, S.: Spatio-temporal variability of sensible heat fluxes: Large-Aperture Scintillometry observations during urbisphere-Berlin, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-241, https://doi.org/10.5194/ems2026-241, 2026.
Climate change already affects most of the world’s urban population. Developing resilient urban environments requires improving both weather and climate modelling. Heterogeneity exists from street (100 m) to neighbourhood (1 km) to city (10 km) scales due to urban form and function. Hectometric-scale numerical weather prediction (NWP) may be starting to resolve neighbourhood-scale heterogeneity but how can observation networks be designed to capture spatial variation in urban climates (horizontally and vertically) to evaluate these model predictions robustly?
To address these challenges, we combine city-scale field observations, resident interviews, high-resolution numerical (Large Eddy Simulation, NWP) and wind-tunnel modelling. Three research projects (ASSURE, urbisphere, and UrbanAIR) have collaborated to design and maintain an urban observation network in the UK. The focus is on Bristol as it is compact, has representative land-use, is close to the coast, and lies in relatively low-lying complex terrain. Bristol City authorities had previously used Met Office climate simulations at 2.2 km resolution to plan for urban heat vulnerability. Both partners were engaged in our design of a network of over 40 lamp-post mounted automatic weather stations that has run since spring 2024. A network of ground-based remote sensing (Doppler wind lidars, automatic lidar ceilometers) was deployed at six sites across the city to observe boundary layer development in response to the urban surface and orography. Other observations included indoor climate, radiation, vegetation, and tracer gas dispersion experiments. The core Bristol field campaign ran from spring 2024-2025 but a sub-set of measurements is ongoing. This follows other year-long urbisphere campaigns in Berlin, Paris, Freiburg, and Heraklion.
This talk provides an overview of the observation network in the Bristol project and the data-set obtained. Key findings will be presented where field and modelling approaches were combined to design the deployment, e.g., a Virtual Doppler Lidar approach using LES, lessons learned from a testbed of a high-resolution NWP ensemble.
How to cite: Barlow, J., Grimmond, S., Birkmann, J., Carpentieri, M., Christen, A., Chysoulakis, N., Coceal, O., Lean, H., Matthews, J., Placidi, M., Robins, A., Shallcross, D., Smith, S. T., van Reeuwijk, M., and Xie, Z.-T.: Across-Scale boundary layer processeS in complex URban Environments: the ASSURE/urbisphere/UrbanAIR observation network in Bristol, UK., EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-665, https://doi.org/10.5194/ems2026-665, 2026.
Urban processes are poorly represented in NWP and climate models due to heterogeneous surfaces, complex morphology, and multi-scale interactions, leading to errors in surface-atmosphere energy exchange across spatial and temporal scales. Satellite derived urban fluxes also face similar issues from coarse resolution and sub-pixel heterogeneity. Addressing this requires multi-scale, multi-height observations, which are rare and only a few urban sites worldwide provide such comprehensive long-term data. This study investigates urban energy fluxes in Enschede, The Netherlands using a net-radiometer (at micro-scale) with an eddy-covariance (EC, at neighborhood-scale) and a Scintillometer (SC, at city-scale) for one year in 2020. Enschede is a city in Eastern Netherlands and has a temperate oceanic climate, an area dominated by built-up (up to 84%), and predominantly compact, mid-rise local climate zone (LCZ-2). For the year 2020 this study examines annual variability, consistency, and representativeness of turbulent fluxes across scales, evaluates uncertainties from methodological choices, and assesses flux sensitivity to key input parameters.
The results show that turbulent fluxes, sensible (QH) and latent heat flux (QE), generally follow the seasonal and diurnal patterns of net radiation (Q*). Observed EC fluxes at two heights show consistent vertical divergence due to the flow distortion caused by the building on which the EC instruments are installed and consequent roughness sublayer effects. QH estimates from EC tower and Scintillometer show comparable magnitudes, whereas QE derived from Scintillometer is approximately twice that obtained from EC indicating differences in sampled footprint. Our results show that, in urban areas accounting for stability-dependent effective height is critical while processing Scintillometer data, as neglecting this factor introduces substantial errors (up to 150 Wm-2 in QH and 80 Wm-2 for QE under unstable conditions). This issue is particularly important because the associated uncertainty increases with unstable stratification, which often coincides with the overpass times of many satellites. Turbulent fluxes estimated by the Scintillometer depend strongly on two parameters: surface roughness (z0) and displacement height (zd). Our results show that these affect the results in opposite ways with higher z0 increases fluxes, while higher zd decreases them. Different aerodynamic parameterizations used to estimate these parameters often make comparable errors in both, which cancel out and give reasonable flux values. However, this result is site-specific and cannot be relied on in general. In practice, z0 mainly affects friction velocity (u*) and has a smaller impact when measurements are taken well above the surface. In contrast, zd directly influences flux estimates and has a much stronger effect. Therefore, estimating zd accurately is more important than estimating z0. This long-term dataset supports urban process modeling, satellite product validation, and offers guidance on uncertainty and sensitivity for designing and interpreting future urban flux measurements.
How to cite: Joshi, H., Gadde, S., Hartogensis, O., and Timmermans, W.: Multi-Scale Observations of Urban Surface-Atmosphere Energy Exchange: Representativeness, Sensitivity, and Measurement Uncertainty, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-675, https://doi.org/10.5194/ems2026-675, 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.: Performance Evaluation of Three-Component Ultrasonic Anemometers with Orthogonal and Non-Orthogonal Transducer Arrays, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-116, https://doi.org/10.5194/ems2026-116, 2026.
From January 2025 to the end of July 2025, a solid-state meteorological polarimetric radar was tested at Météo France International in Toulouse. During this period, colleagues at Météo France International experimented with various scanning strategies using different pulse characteristics. Overall, the testing campaign was successful. One key advantage was the presence of a magnetron weather radar at the same location, which enabled direct comparison of the data. A portion of this poster focuses on that comparison.
The radar, equipped with a 2.4-meter antenna and a 1.7° beamwidth, utilized two 5 kW C-band solid-state power amplifiers. Over the six month testing period, it captured a wide range of meteorological phenomena, from microphysical processes within stratiform precipitation systems to the development of a mesoscale convective vortex, as well as intense supercell storms accompanied by large hail. Selected cases, such as the supercells observed on 3 May 2025 and the mesoscale convective vortex on 19 May 2025, will be presented and analyzed further in the poster.
Since the two radars were installed in close proximity at a distance of approximately 200 meters, their outputs could be directly compared. For this comparison, two different weather scenarios were selected, a winter case with stratiform precipitation and a summer case involving severe rotating thunderstorms, specifically supercells. Both radars produced broadly similar measurements, with any differences mainly arising from the methods used to calculate certain polarimetric variables, such as the correlation coefficient (RhoHV) and specific differential phase (KDP).
The Meteopress and Météo-France radars differ in their scanning strategies. Météo France used a triple PRF scheme, while Meteopress employed a staggered PRF, which can lead to differences in the quality of Doppler radial velocity measurements. Reflectivity data from the Météo-France was attenuation-corrected, resulting in notable differences between the radars in regions of higher reflectivity, especially behind convective cells where attenuation is strongest. Additionally, differences in censoring and filtering techniques contribute to the variations observed between the two radar datasets.
In our poster, we will present the differences using examples of measured data, together with a more detailed comparison of radar reflectivity or differential reflectivity (ZDR).
How to cite: Najman, F., Stanek, M., Horak, J., and Mickova, Z.: Comparison between Solid State and Magnetron C-band radars in Toulouse, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-617, https://doi.org/10.5194/ems2026-617, 2026.
The company Meteopress has developed two mobile weather radars: an X-band radar (MeteoRover X-class) and a C-band radar (MeteoRover C-class), both of which were tested during 2025 and 2026. The testing included hardware and software aspects and derived weather products (such as hydrometeor classification). During the campaign, IQ data was also recorded for the development of new signal processing methods.
The MeteoRover X-class operates at a frequency of 9.410 GHz and is equipped with a 1.2-meter antenna with a gain of 39 dBi. This configuration allows the radar to be used both for operational warning purposes and for scientific applications, including the testing of new algorithms, while enabling continuous operation for 6 to 10 hours depending on the selected scanning strategy. The MeteoRover C-class operates at a frequency of 5.590 GHz and features a 2.4-meter antenna with a gain of 40 dBi. The beamwidth of both radars is 1.7°, which allows for closely comparable measurements when both systems are configured similarly.
During the summer of 2025, several cases of strong convective storms over the Czech Republic were successfully observed. The measurements included testing various radar configurations, such as different scanning strategies, pulse repetition frequency settings, and pulse lengths. At the same time, we focused on meteorological products calculated at high spatial resolution, ranging from 25 to 100 meters depending on the application. Five scanning strategies were implemented, each designed for a specific measurement objective, such as microphysical characterization or low-level wind shear detection, and adapted to the distance of the observed storms. This included adjustments not only to elevation angles but also to pulse length and other radar parameters. Similar measurement activities are continuing in 2026.
This poster presents not only the current technical design of the mobile radar systems but also examples of the collected data, comparisons between the two radars, and detailed analyses of selected cases using derived products such as hydrometeor classification.
How to cite: Najman, F., Stanek, M., Mickova, Z., and Horak, J.: Analysis of Severe Convective Storms in Central Europe Measured by Mobile Weather Radars, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-623, https://doi.org/10.5194/ems2026-623, 2026.
Cloud radars are powerful tools for investigating cloud formation, radiative processes, and cloud microphysics. In recent years, polarimetric cloud radars have become increasingly common around the world. Since many cloud property retrieval techniques rely on accurately measured reflectivity, ensuring high-quality calibration is essential. The most widely used calibration approach is one based on disdrometer measurements, but this method carries significant uncertainties, particularly due to the vertical variability of rainfall characteristics. To address the limitations and to complement in cloud radar calibration methods, A. Myagkov et al. (2020) introduced a self-consistency calibration technique that makes use of the polarization capabilities of W-band cloud radars. In this study, we assess the suitability of the self-consistency calibration method and identify the modifications required to make the approach more user-friendly and practical for operational applications.For this study, we have used 94 GHz cloud radar data operated at 300 elevation angle during days having rainfall rate less than 20 mm/hr. The methodology of self-consistency method consists of 4 steps. 1) Using Rayleigh Plateau detection method (Unal and van den Brule,2024), retrieve propagational (Kdp) and backscattering (δ) components from differential phase (φ) and, differential attenuation (Adp). 2) Calculate non-attenuated reflectivity Z0. 3) Calculate Kdp and Adp using Z0, δ and the coefficients given in A. Myagkov et al. (2020). 4) Compare the measured and calculated Kdp and Adp, and find the best fit for calibration coefficient. This study shows that a 30° elevation angle and rainfall rate below 20 mm/hr are not the only criteria required for applying the self-consistency method. The values of differential backscatter phase(δ) and Doppler spectrum width also play important roles. In addition to the calibration of reflectivity, the retrieval of the one-way attenuation profile is shown to be another significant output of the self-consistency calibration technique.
How to cite: Nandan, R. and Unal, C.: Applicability of self-consistency calibration method on polarimetric cloud radars, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-573, https://doi.org/10.5194/ems2026-573, 2026.
High-frequency fluctuations in microwave-link received power contain valuable information about atmospheric processes along the propagation path. In addition to well-known turbulence-induced scintillations, raindrop motion can generate a distinct high-frequency signature in both the variance and power spectral density (PSD) of the signal. These rain-induced scintillations contain information related to raindrop size and velocity distributions, but they remain largely unexplored.
In this study, we derived a simple mathematical PSD model that combines turbulence and rainfall contributions, bridging previous turbulence- and rainfall-only models. To isolate the rainfall signature from turbulence, we analyzed a dataset collected in Wageningen using a 2.2 km microwave link operating at 26 GHz with a 20 Hz sampling rate. Variance and PSDs were calculated over 30 s windows under dry and rainy conditions, respectively.
We then examined correlations between signal fluctuation metrics and rainfall characteristics (e.g., path-averaged rainfall rate and moments of the raindrop size distribution measured by disdrometers along the path), as well as nearby crosswind. Differences in spectral power dominance across temporal frequencies were identified: rainfall dominates near 10 Hz (the Nyquist frequency), while crosswind dominates around 2 Hz. The 6th moment of the raindrop size distribution exhibits the highest correlation with signal fluctuation metrics, while the raindrop concentration exhibits the lowest.
These findings highlight the potential to retrieve rainfall characteristics and crosswind from microwave-link observations during rainy events. However, challenges remain, including the low signal-to-noise ratio of the data and the lack of colocated wind and turbulence measurements. Future work should focus on improving measurement setups and advancing the simulation of the combined PSD.
How to cite: Wang, P., Droste, A., Schleiss, M., and Uijlenhoet, R.: Spectral Signatures of Rainfall and Crosswind in Microwave-Link Signals, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-735, https://doi.org/10.5194/ems2026-735, 2026.
Mobile Doppler lidar systems provide new opportunities to observe spatially heterogeneous boundary-layer flows, but introduce additional uncertainties related to platform motion, scan geometry, and data quality. In this contribution, we present UWOW (University of Virginia Wind Observatory on Wheels), a mobile Doppler lidar system designed for boundary layer wind profiling, and assess its performance using both field observations and controlled numerical simulations.
UWOW integrates a HALO Photonics StreamLine XR Doppler lidar with a GPS and a VectorNav inertial navigation system (INS) mounted on a mobile trailer. The system performs scanning Doppler lidar measurements while in motion, enabling wind profile retrievals from approximately 100 to 3000 m above ground with ~30 m vertical resolution. Wind speed and direction are derived by combining radial velocity measurements with platform motion and attitude information (heading, pitch, and roll) from the INS through a multi-beam retrieval approach.
We first evaluate UWOW performance using observations collected during the Sundowner Wind Experiment near Santa Barbara, California. These data are used to assess the impact of platform motion, attitude corrections, scan geometry, and signal-to-noise ratio (SNR) on retrieved wind profiles. In particular, we examine how SNR-based filtering can reduce outliers and improve the robustness of the retrieval under real-world conditions.
To further quantify uncertainties, we conduct controlled experiments using output from the Weather Research and Forecasting (WRF) model. Synthetic Doppler lidar observations are generated by sampling WRF wind fields along realistic UWOW trajectories and scan patterns, while prescribing representative platform speeds and attitude variations. Applying the same retrieval algorithms to these synthetic datasets enables direct comparison with the known model wind fields and provides a quantitative assessment of retrieval errors.
This combined observational and modeling framework provides a systematic characterization of UWOW measurement uncertainty and highlights the sensitivity of retrieved winds to platform motion and data filtering choices. The results demonstrate the capability of mobile Doppler lidar systems to resolve boundary layer wind variability in complex terrain, while identifying key factors required for accurate and reliable wind measurements.
How to cite: De Wekker, S. F. J., Desai, J., Duine, G.-J., Carvalho, L., Emmitt, D., and Greco, S.: Characterizing Uncertainty in Boundary-Layer Wind Measurements from UWOW, a Ground-Based Mobile Doppler Lidar, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-559, https://doi.org/10.5194/ems2026-559, 2026.
Over the past decade, the Royal Netherlands Meteorological Institute (KNMI) has undertaken significant effort to integrate emerging surface-based remote sensing technology in its services for operations and research. KNMI deploys several types of ground-based lidar instruments to detect clouds and volcanic ash, and measure vertical profiles of aerosols, wind and water vapor. Real-time information on the vertical structure of the atmosphere is becoming increasingly important input for nowcasting purposes and models supporting KNMI’s forecasting, climate, early warning, maritime, and energy tasks.
Since the late 1990’s KNMI deploys automatic lidar ceilometers (ALC) for continuous (24/7), fully automated observations of cloud base height and cloud cover. These ALCs are integrated in our nationwide automatic weather station network and currently consists of 45 stations, including civil and defense airports and North Sea platforms. ALC backscatter profile data provides aerosol layer information, including the boundary layer and elevated aerosol layers, allowing to monitor Sahara dust, wildfire smoke and volcanic ash. Those different types of aerosols can be differentiated with the Raman lidars at the Cabauw atmospheric research station, part of the Ruisdael Observatory and ACTRIS National Facility. One Raman lidar also measures vertical profiles of the water vapor mixing ratio. The KNMI ALCs are part of the European ALC network within E-PROFILE. Current research focuses on the real-time retrieval of boundary layer height from ALC backscatter data and its transition from research to operations (R2O). The ground-based lidars at Cabauw play a significant role in validation of space-born lidars, such as EarthCARE.
Since end 2010’s KNMI uses Doppler lidars that measure wind. The development of wind farms on the Dutch North Sea provided the opportunity to deploy short-range wind lidars offshore. The current network consists of 7 stations, within 4 wind farms. The measured wind profiles are made available to key users, including the wind farm operators and KNMI forecasters, in near-real time. At Cabauw, a long-range scanning Doppler lidar provides vertical profiles of horizontal wind and vertical velocity in the boundary layer, from which for instance low-level jets, mixing height and gravity waves are detected. It is part of the European DWL network within E-PROFILE. More recently, KNMI deployed a long-range scanning Doppler lidar for research and operational deployment at Amsterdam Schiphol Airport, supporting KNMI’s aviation services. Research includes the development of aircraft wake vortex persistence monitoring or alerting systems for dangerous wind phenomena such as wind shear or gust fronts.
Here we will present an overview of KNMI’s ground-based lidar activities, along with an outlook on future developments and opportunities.
How to cite: Apituley, A., Alves Gouveia, D., de Haij, M., de Jong, M., Knoop, S., Mathijssen, T., and Schaap, T.: Ground-based lidar operational and research activities at KNMI, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-468, https://doi.org/10.5194/ems2026-468, 2026.
The current observational coverage of the atmospheric boundary layer (ABL) remains insufficient to improve high-resolution forecasting, including numerical weather prediction (NWP) and nowcasting, particularly for severe weather events. The existing measurement networks cannot provide, at sufficient spatial and temporal resolution, the vertically resolved kinematic and thermodynamic information needed to resolve the ABL for high-resolution forecasting. In order to address this shortcoming, the German Weather Service, Deutscher Wetterdienst (DWD), is currently expanding its operational network to include ground-based vertical profile measurements. Lidar remote sensing profilers are being installed at thirteen selected weather stations across Germany. These stations will complement DWD’s observation systems, such as radiosondes, radar wind profilers, and AMDAR measurements.
Doppler-lidar systems and differential absorption lidars (DIALs) will allow for the continuous retrieval of wind and humidity across the boundary layer. The DIALs, DA10 atmospheric profilers by Vaisala, will be used to provide vertical humidity profiles up to 4 km above ground level based on broadband differential absorption at two wavelengths in the near-infrared spectrum.
As part of their deployment, the DA10 units undergo extensive characterisation and testing. This includes continuous monitoring of the technical parameters alongside the measured water vapour mixing ratio and attenuated backscatter profiles, enabling the simultaneous assessment of operational reliability and data quality across a wide range of meteorological conditions. In conjunction with this monitoring, systematic intercomparisons were conducted both among the DA10 units themselves and against established reference measurements, primarily radiosondes, further strengthening this assessment. Initial results indicate a good overall agreement between the DIALs’ humidity profiles and the radiosonde measurements, while also highlighting the limitations of these commercially available lidars for systematic measurements of ground-based humidity profiles.
How to cite: Heuser, J., Kabus, S., Khordakova, D., Knist, C., and Lehmann, V.: Introducing ground-based water vapour profiling to the DWD network: Broadband differential absorption lidar measurements, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-527, https://doi.org/10.5194/ems2026-527, 2026.
The surface energy balance (SEB) provides a physically consistent framework for interpreting land–atmosphere interactions based on the fundamental idea that energy exchange at the surface must be conserved. Accurately resolving the SEB and its constituent components is essential to better understand our climate and for developing and evaluating predictive models. However, it is well established that in many locations and conditions around the globe, the SEB does not close. The Royal Netherlands Meteorological Institute's (KNMI) Cabauw observational site forms a unique dataset to monitor and better understand the interactions between the surface and the atmosphere. Since 1972, this mid-latitude grassland has hosted various instruments performing a variety of relevant observations and is particularly distinguished by its 213 m tall mast. The long-term, near real-time profiles of standard measurements such as temperature, relative humidity, wind direction/speed, and visibility, provide an excellent foundation for scientific exploration. For instance, the neighbouring energy balance field (EB-field) is occupied by various instruments which measure each component of the SEB.
This poster provides an overview of these instruments and observational methods. Incoming and outgoing longwave and shortwave radiation at the EB-field are measured and combined to determine the net radiation. The net radiation is verified by comparing to the Cabauw Baseline Surface Radiation Network. The soil heat flux is determined via two methods using detailed profiles of soil temperature and soil heat flux plates. These observations have been particularly affected by sinking and are more difficult to verify. The sensible heat flux and latent heat flux can be derived from the turbulence measurements (3D sonic anemometer and open pathway sensor) and in addition, a psychrometer mast which measures air temperature and dewpoint temperature at 1, 2, and 4 m. In recent years, latent energy has also been measured directly at the surface using a lysimeter. These long-term and detailed measurements provide a unique opportunity to investigate both the SEB closure, and the processes that determine the exchange between the surface and atmosphere in great detail.
How to cite: Strickland, J. M. I., de Bruijn, C. (E. I. F. )., Koning, M. (A. M. )., Knap, W. H., and Ronda, R. J.: Measuring the Surface Energy Balance at the Cabauw Observational Site , EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-604, https://doi.org/10.5194/ems2026-604, 2026.
Turbulence measurements up to 180 m have been performed for over 25 years along the Cabauw tower, The Netherlands, providing a unique data set. Such long-term observations are essential to better understand the turbulent structures in various weather conditions (e.g. convective transport, gravity waves, dominating timescales and eddy sizes) and provide a foundation for weather modelling. For example, such in-situ measurements are increasingly important for the wind energy industry as the turbulence profiles can provide invaluable insight into the impacts of wind (shear) and turbulence intensity which impacts turbine loading and safe operation.
The observations are obtained via a 3D sonic anemometer, providing high-frequency wind measurements and sonic temperature and an open-path gas analyser that measures water vapour and carbon dioxide fluctuations. Over the course of this measurement programme, the measurements have been subject to transition. For instance, the instrumentation is intermittently exchanged for calibration or maintenance, and they have been renewed, upgraded or repaired. Also, data acquisition systems are modernised, set-ups have been moved or altered due to environmental changes or innovation, and processing software to obtain the fluxes has been upgraded with new insights. Now, after 20 years of measurements with similar instrumentation, the sonic anemometer will be replaced by a different brand and different processing software will be incorporated.
The current renewals and frequent requests for turbulence data have encouraged us to investigate the historic data sets, towards standardising and aligning the different time periods into a high-value data set that improves data usability and efficiency. To that end, we first build a complete change log from existing documentation to identify where inhomogeneities can occur. Then we reprocess the data to have the same naming convention and units, apply calibration factors, perform the same coordinate rotation, corrections, averaging, etc. Afterwards we will detect and quantify the discontinuities by visual inspection and statistical tests and find methods to. Last, a consistent quality control will be applied. All processing steps are documented and motivated.
This poster gives an overview of the complex process as well as the challenges we face in making this data set research and poses research questions to which this data is well suited to explore.
How to cite: Koning, M., Strickland, J., and Ronda, R.: Transforming more than 25 years of turbulence measurements along the Cabauw tower into a high-value research data set., EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-448, https://doi.org/10.5194/ems2026-448, 2026.
The turbulent fluxes of heat and water vapor are key land surface – atmosphere interaction process variables in local, regional, and global energy and water cycles. Scintillometry can be considered as the only experimental technique presently available for the operational determination of these fluxes at a horizontal scale of a few kilometers – measurements necessary to validate fluxes simulated by regional atmospheric models or derived from satellite images.
Scintillometers measure the fluctuations of electromagnetic radiation propagating horizontally over a path of typically a few hundred meters up to several kilometers in length. These signal intensity fluctuations can be attributed to fluctuations of the refractive index of the air, i.e., of temperature and humidity, caused by turbulent processes in the near-surface atmospheric boundary layer (ABL). Using similarity theory relationships, the turbulent heat fluxes can be derived. Combining an optical and a microwave scintillometer (OMS), the fluxes of both sensible and latent heat can be obtained.
An OMS system has been operated at the Land-Atmosphere Feedback Observatory site at the University of Hohenheim during the General Observations Period of the Land-Atmosphere Feedback Initiative cluster project over a period of eight months from mid-March to mid-November, 2025. The 1093 m long path covered different types of crops, including rape, maize, wheat, oat and soybean. These measurements were intended to provide flux values representing a heterogeneous agricultural landscape.
We will describe the data handling and processing of the scintillometer data for this quasi-operational setup. Derived fluxes are compared with local eddy-covariance measurements above two distinct fields below the scintillometer path. Moreover, an attempt will be made to relate the OMS-based fluxes with flux estimates from inside the ABL based on synergetic lidar measurements.
How to cite: Winkelmann, A., Beyrich, F., Rajtschan, V., Ingwersen, J., von Klitzing, L., and Wulfmeyer, V.: Scintillometer Measurements at the Hohenheim Land-Atmosphere Feedback Observatory, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-755, https://doi.org/10.5194/ems2026-755, 2026.
Split International Airport (LDSP), situated on the eastern Adriatic coast, presents a complex meteorological environment for aviation operations. The airport's location at the base of the Dinaric Alps creates a unique intersection between synoptic-scale flows and sub-mesoscale coastal circulations.
Following a collaboration between the University of Split, Split Airport, and Croatia Control (air navigation service provider) continuous SODAR (SOnic Detection And Ranging) measurements have been operational since June 2022 at the airport location. The primary objective of this university project was the collection of research data, but since it was installed at the airport, it’s real-time measurements can also provide very useful information for aviation forecasters.
The data is collected using a Scintec MFAS (Multi-Frequency Flat Array SODAR). While the instrument is capable of a vertical range up to 1000 m, it is optimized for high-resolution monitoring within the lowest 500 m of the troposphere—the most critical zone for aircraft approach and departure. Data is processed at 20-minute intervals, providing a detailed vertical profile of wind direction and speed.
The four-year dataset captures the seasonal and diurnal variability of the four dominant local wind regimes:
- Bora (Bura): A gusty north-easterly wind, often associated with severe mechanical turbulence due to the nearby mountains.
- Sirocco (Jugo): A moist, south-easterly flow, sometimes with wind speeds above 25m/s in the 500m surface layer.
- Sea-Breeze (Maestral): A predictable but significant south-westerly coastal circulation that dictates runway changes from standard instrumental approach to a more complex visual approach from north-east, due to mountain proximity on that side of the airport.
- North-westerly gap flow : Katabatic flow from the mountain gap north-west of the airport, but also a tramontana, typical post-frontal flow (synoptic + orography).
Moreover, in aviation meteorology information from SODAR instrument can be very useful for detecting vertical wind shear.
This poster will present some typical examples of wind profiles at Split airport, wind roses at different altitudes (e.g., 50m, 150m, 300m), and examples of significant wind shear episodes.
These findings emphasize the necessity of ground-based remote sensing for enhancing safety and operational efficiency at topographically challenged coastal airports.
How to cite: Šoljan, V., Jurković, J., and Šepić, J.: Vertical Structure of Coastal Wind Regimes: Four Years of Continuous SODAR Observations at Split Airport, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-460, https://doi.org/10.5194/ems2026-460, 2026.
Turbulent mixing in complex terrain introduces significant uncertainty in weather and climate models, as critical processes within the mountain boundary layer (MoBL) are not represented. While common mesoscale models neglect the horizontal shear production of turbulent kinetic energy (TKE), this assumption is invalid in mountainous regions, necessitating 3D boundary layer parameterizations including these contributions. However, observational data quantifying horizontal versus vertical shear production remains scarce. To address this gap, we deployed a measurement strategy combining small uncrewed aircraft systems (UAS) and remote sensing systems, notably Doppler Wind Lidar (DWL), during the TEAMx (Multi-scale transport and exchange processes in the atmosphere over mountains - programme and experiment) 2025 campaign the Inn Valley in Austria. Commercially available and automatically operating multi-rotor UAS equipped with fast-response sensors measured temperature, humidity and aerosols, as well as the 3D wind vector up to 4 Hz, resolving eddies of 2.5 m at 10 ms−1 mean wind speed. Four UAS simultaneously recorded vertical profiles up to 2 km above mean sea level and horizontal cross-sections across key valley locations (valley floor, sidewall foot, slope, and crest), with the spacing representative of targeted operational weather forecast grids. This was coordinated with three DWL systems providing continuous wind profiles at the same locations. The combined measurements enabled an analysis of spatially and temporally resolved MoBL dynamics. For thermally driven up-valley flows, TKE increases horizontally from the valley center toward the mountain, peaking vertically near the mountain ridge. This observed rise in TKE coincides with strong horizontal wind shear up to 10 ms−1 wind speed difference per km. By integrating UAS and remote sensing observations with model development in the TEAMx framework, we aim to advance physically consistent turbulence parameterizations for high-resolution numerical weather simulations, enhancing forecast reliability in complex terrain.
How to cite: Kippenberger, M., Schön, M., Ruhl, M., Wahl, E., Freddi, G., Gohm, A., Lehner, M., Bange, J., and Platis, A.: Measuring Horizontal Shear and Turbulence in Mountain Valleys using UAS and Lidar, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-739, https://doi.org/10.5194/ems2026-739, 2026.
Turbulent kinetic energy (TKE) is a fundamental parameter for characterizing atmospheric turbulence and is essential for assessing hazardous weather conditions that directly impact Urban Air Mobility (UAM) operations. Accurate estimation of turbulence intensity is particularly important for ensuring the safety and efficiency of low-altitude urban airspace, where UAM vehicles operate under complex and highly variable atmospheric conditions. While three-dimensional sonic anemometers are widely regarded as the reference standard for TKE estimation due to their high temporal resolution and accuracy, their measurements are inherently limited in spatial representativeness, especially in heterogeneous urban environments.
Doppler lidar has emerged as a promising remote sensing technology capable of providing spatially distributed wind and turbulence information over extended areas, making it highly suitable for operational applications in UAM. In this study, TKE estimates derived from Doppler lidar are systematically compared with those obtained from three-dimensional sonic anemometers collocated on a 300 m meteorological tower. The analysis reveals that lidar-derived TKE is consistently higher than that measured by the sonic anemometer.
To investigate the underlying causes of this discrepancy, several potential error sources are examined, including volume averaging effects associated with the lidar measurement volume, instrumental noise, limitations in scanning strategies, and assumptions involved in retrieving velocity variances. Furthermore, multiple correction techniques are explored to enhance the reliability of lidar-based TKE estimates, such as noise filtering, spectral correction methods, and adjustments accounting for spatial averaging effects. The performance of these correction approaches is quantitatively evaluated through direct comparison with reference measurements from the sonic anemometer.
The findings of this study improve the accuracy of Doppler lidar–derived turbulence measurements and support the development of reliable hazardous weather information systems for conditions such as turbulence, wind shear, and crosswind. Ultimately, this research provides a robust scientific foundation for real-time turbulence monitoring and contributes to safer and more efficient UAM operations in complex urban environments.
How to cite: Kwon, B. H., Yu, A., and Jung, Y.: Evaluation and Correction of Doppler Lidar–Derived Turbulent Kinetic Energy for Urban Air Mobility Applications, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-257, https://doi.org/10.5194/ems2026-257, 2026.
Atmospheric ducting has a significant effect on radio and microwave propagation, as signals trapped in atmospheric layers travel unexpected distances and may cause interference in radar measurements and radio communications. The ducts are generally caused by non-standard refractive index gradients, which are dependent on meteorological conditions, mainly temperature and humidity inversions.
Atmospheric ducts have been mainly studied in the troposphere, with an emphasis on surface ducts in maritime and coastal regions. Studies have often used radiosondes, Numerical Weather Prediction (NWP) models, and radar measurements. Elevated ducts, however, have received less attention, and particularly the occurrence of anomalous signal propagation in the stratosphere remains largely unexamined. Studying atmospheric ducts above the troposphere is challenging due to the scarcity of observations, and their insufficient vertical resolution to capture this phenomenon.
The meteorological conditions in the stratosphere can be studied using the atmospheric parameters retrieved from limb observations of propagation path bending between satellites functioning as transmitter-receiver satellite pairs for Global Navigation Satellite System (GNSS) signals. These observations may be inverted to obtain vertical profile information on temperature, humidity and pressure in the atmosphere. For propagation condition analysis, it should be noted that humidity and temperature gradients are relevant for tropospheric propagation, whereas temperature and pressure gradients drive stratospheric propagation conditions.
Here we present initial results for a study into the occurrence of the meteorological conditions allowing anomalous propagation in the lower stratosphere. We analyse refractivity profiles from radio occultation data from the Radio Occultation Meteorology Satellite Application Facility (ROM SAF) to understand both the frequency and distribution of atmospheric ducting as well as the data requirements to capture the phenomena, with a focus on the European region. The results are compared to reanalysis data from the European Centre for Medium Range Weather Forecasts Reanalysis v5 (ERA5) as well as radiosonde observations.
How to cite: Kallio-Myers, V., Riihelä, A., and Eresmaa, R.: The Anomalous Propagation of Radio and Microwaves in the Stratosphere, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-568, https://doi.org/10.5194/ems2026-568, 2026.
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