Measurements are essential to provide information on the actual state of the atmosphere for nowcasting purposes, for climate monitoring, for assimilation into numerical weather prediction (NWP) systems and to improve our understanding of atmospheric processes and their role in the climate system. In particular, there is a strong need for complex observations suitable to develop, improve and validate parameterizations used in NWP and climate models and to provide ground-truth against which to compare atmospheric parameters derived from satellite data. With a new generation of high-resolution forecast models (1-3 km) used for the prediction of high-impact weather, dense observational networks focusing on measurements in the lower few kilometers of the atmosphere are required.
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 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 invited that make use of advanced data sets for satellite data validation.
The International Soil Moisture Network (ISMN, https://ismn.earth) is international cooperation to establish and maintain a unique centralized global data hosting facility, making in-situ soil moisture data easily and freely accessible (Dorigo et al., 2021). Initiated in 2009 as a community effort through international cooperation (ESA, GEWEX, GTN-H, GCOS, TOPC, HSAF, QA4SM, C3S, etc.), the ISMN is an essential means for validating and improving global satellite soil moisture products, land surface-, climate-, and hydrological models.
The ISMN is a widely used, reliable, and consistent in-situ data source (surface and sub-surface) collected by a myriad of data organizations on a voluntary basis. The in-situ soil moisture measurements are collected, harmonized in terms of units and sampling rates, advanced quality control is applied and the data is then stored in a database and made available online, where users can download it for free. Currently, 71 networks are participating with more than 2800 stations distributed on a global scale and a steadily increasing number of user communities. Long term time series with mainly hourly timestamps from 1952 – up to near-real-time are stored in the database, including daily near-real-time updates. Besides soil moisture in our database are stored other meteorological variables as well (air temperature, soil temperature, precipitation, snow depth, etc.).
The ISMN provides benchmark data for several operational services such as ESA CCI Soil Moisture, the Copernicus Climate Change (C3S) and Global Land Service (CGLS), and the online validation tool QA4SM. ISMN data is widely used in a variety of scientific fields (e.g., climate, water, agriculture, disasters, ecosystems, weather, biodiversity, etc).
To validate the land surface representations of meteorological forecasting models soil moisture from the ISMN has often been used. The development of various generations of TESSEL models used both in the Integrated Forecasting Systems and reanalysis products of ECMWF, greatly profited from soil moisture and temperature data from the ISMN. Using ISMN data several studies assessed the soil moisture skill of the Weather Research and Forecasting Model (WRF) and assessed the forecast skill or new implementations of numerical weather prediction models.
We greatly acknowledge the financial support provided by ESA through various projects: SMOSnet International Soil Moisture Network, IDEAS+, and QA4EO.
To ensure a long-term funding for the ISMN operations, several ideas were perused together with ESA. A partner for this task could be found within the International Center for Water Resources and Global Change (ICWRGC) hosted by the German Federal Institute of Hydrology (BfG).
In this session, we want to give an overview and future outlook of the ISMN, highlighting its unique features and discuss challenges in supporting the hydrological research community in need of freely available, standardized, and quality-controlled datasets.
How to cite: Petrakovic, I., Himmelbauer, I., Aberer, D., Schremmer, L., Goryl, P., Crapolicchio, R., Sabia, R., Dietrich, S., and Dorigo, W. A.: The International Soil Moisture Network: an open-source data hosting facility in support of meteorology and climate science, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-368, https://doi.org/10.5194/ems2021-368, 2021.
From the perspective of numerical weather prediction and nowcasting, the atmospheric boundary layer (ABL) is one of the most undersampled regions of the atmosphere due to difficulties of spaceborne remote sensing at these altitudes. Ground-based microwave radiometers (MWR) have the potential to contribute to the closing of this gap. Indeed, commercial K- and V-band (20-60 GHz) radiometers provide observations of temperature profile, water vapour and liquid water and are most sensitive to the ABL due to their choice of spectral channels and observation geometry.
EUMETNET's E-PROFILE observation programme has thus evaluated the potential for a European network of ground-based microwave radiometers. The stakeholder needs were inferred from WMO and EUMETNET Statements of Guidance, OSCAR and a dedicated user survey. The maturity and effectivity of the technology was assessed through a literature review and experts judgements comprising recent large-scale campaigns, experiences with long-term usage and assimilation trials and outcomes of the recent COST action TOPROF. Last but not least, the availability of existing instrumentation from which a European network could be built up was investigated.
Based on this study, EUMETNET decided to establish an operational MWR network by 2023 with continuous near real-time provision of brightness temperatures, humidity and temperature information from a centralised retrieval as well as forecast indices for fore- and nowcasting. The products will come along with different monitoring quality control stages at timescales from near real-time to monthly. Special care will be dedicated to ensure reliable absolute calibration results by accounting for the recent developments and recommendations from TOPROF. In the setting up and operation of the network as well as in the implementation of retrievals and monitoring, important synergies with the ACTRIS programme and the scientific community gathered in the COST action PROBE are expected.
The presentation will briefly outline the reasoning for setting up the network but mainly focusses on the operational aspects and services that E-PROFILE MWR will provide. Moreover, the first steps taken towards an operational network will be discussed and the general roadmap outlined.
How to cite: Rüfenacht, R., Bircher-Ardot, S., Pospichal, B., Cimini, D., Knist, C., Martinet, P., Orlandi, E., Czekala, H., Loehnert, U., Sugier, J., Turp, M., and Haefele, A.: An upcoming European network of microwave radiometers for operational temperature profiling and humidity observations, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-227, https://doi.org/10.5194/ems2021-227, 2021.
Ceilometers are known to be robust, stand-alone and cost-effective lidar-based remote sensing instruments. Typically, ceilometers are used in aviation to detect cloud base heights. Ceilometers are also used for atmospheric profiling, however, and the applications of profile information are increasing. The focus of this presentation is on potential new developments for operational ceilometer networks, such as the use of depolarization ratio profiles.
High-quality vertical profiles of total attenuated backscatter enable the detailed observation of cloud, boundary-layer, and elevated aerosol layer structures. Further developments in conventional ceilometers, such as the addition of the depolarization ratio profile measurement capability, allow more effective atmospheric sensing and new application areas can be more accurately covered. Depolarization ratio profiles enable the differentiation of hydrometeors – differentiation of liquid droplets, drizzle and raindrops, snow and ice crystals. These are important to a wide range of applications in the fields of aviation, meteorology, and air quality.
In this presentation we demonstrate depolarization ratio profile measurements using a new Vaisala CL61 Lidar Ceilometer with depolarization ratio profiling capability. We show measurements collected with 910.55 nm wavelength in different field campaigns and the comparison results with research grade lidars in varying weather and climate. The results correlate well and the depolarization ratio measurements show the physical characteristics of liquid and ice clouds, as well as the effects of multiple scattering in liquid cloud layers. This new depolarization capability in ceilometers allows multiple applications to be served, and enables the buildup of operational networks that provide improved vertical profiling in all weather conditions.
How to cite: Tuononen, M., Lehtinen, R., Kallio, J., Tuominen, P., and Roininen, R.: New profiling capability for operational ceilometer networks, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-80, https://doi.org/10.5194/ems2021-80, 2021.
Atmospheric motion and turbulence are essential parameters for weather and topics related to air quality. Therefore, wind profile measurements play an important role in atmospheric research and meteorology. One source of wind profile data are Doppler wind lidars, which are laser-based remote sensing instruments that measure wind speed and wind direction up to a few hundred meters or even a few kilometers. Commercial wind lidars use the laser wavelength of 1.5 µm and therefore backscatter is mainly from aerosols while clear air backscatter is minimal, limiting the range to the boundary layer typically.
We have carried out a two-year intercomparison of the ZephIR 300M (ZX Lidars) short-range wind lidar and tall mast wind measurements at Cabauw . We have focused on the (height-dependent) data availability of the wind lidar under various meteorological conditions and the data quality through a comparison with in situ wind measurements at several levels in the 213m tall meteorological mast. We have found an overall availability of quality-controlled wind lidar data of 97% to 98 %, where the missing part is mainly due to precipitation events exceeding 1 mm/h or fog or low clouds below 100 m. The mean bias in the horizontal wind speed is within 0.1 m/s with a high correlation between the mast and wind lidar measurements, although under some specific conditions (very high wind speed, fog or low clouds) larger deviations are observed. This instrument is being deployed within North Sea wind farms.
Recently, a scanning long-range wind lidar Windcube 200S (Leosphere/Vaisala) has been installed at Cabauw, as part of the Ruisdael Observatory program . The scanning Doppler wind lidars will provide detailed measurements of the wind field, aerosols and clouds around the Cabauw site, in coordination with other instruments, such as the cloud radar.
 Knoop, S., Bosveld, F. C., de Haij, M. J., and Apituley, A.: A 2-year intercomparison of continuous-wave focusing wind lidar and tall mast wind measurements at Cabauw, Atmos. Meas. Tech., 14, 2219–2235, 2021
How to cite: Knoop, S., Bosveld, F., de Haij, M., and Apituley, A.: Doppler wind lidar activities at Cabauw, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-136, https://doi.org/10.5194/ems2021-136, 2021.
A Start-Up company (Meteosense, a subsidiary of Meteopress, Czech republic, and Idokep, Hungary) in collaboration with a National Meteorological Office in Austria (ZAMG) is preparing and deploying a radar network consisting of affordable X-band weather radars. With a minimum team of three people and based on Lean methodology (Build-Measure-Learn) the plan was set-up with milestones along the way.
The presentation will describe Stage Zero - radar site selection criteria, planning and simulating, Stage One - upgrading existing radar in Vienna to 2.4 meters antenna and Stage Two - planning and deployment of second radar in Austria. Currently, Stage Two is on the way. Stages Three and further will be also briefly described and mistakes and lessons learned will be revealed.
In Stage Zero we will describe how we chose locations for new radars and how we plan the expansion of our radar network in Austria with the help of our radar simulators and experience from building weather radar network in the Czech Republic, Slovakia, Hungary and Croatia.
In Stage One we will describe how we upgraded previously installed radar in Vienna from 1.2-meters antenna to 2.4-meters antenna. We will show the problems that occurred during installation and lessons learned will be revealed. We will also show the results and data from this radar.
In Stage Two we will describe the planning and deployment of our second radar in Austria and this stage will also include how we plan and prepare radar installation in general.
Stages Three and further will include our future plans in Austria.
How to cite: Peštová, Z. and Najman, M.: Case Study: Planning a low-cost X-band radar network from scratch in Austria, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-202, https://doi.org/10.5194/ems2021-202, 2021.
Between June and August 2020 an observational network of 103 autonomous ground-based stations covered the greater area (50 km × 35 km) of Hamburg (Germany) within the framework of the FESST@HH field experiment. The purpose of the experiment was to conduct meteorological measurements at sub-mesoscale resolution (500 m to 5 km) to observe phenomena that typically remain unresolved in operational networks. The experimental design focuses on studying cold pools that form through evaporation underneath precipitating clouds and spread on the Earth’s surface.
During the experiment 82 low-cost APOLLO (Autonomous cold POoL LOgger) stations sampled air temperature and pressure at 1 s resolution to adequately capture the rapid signals of horizontally propagating cold-pool fronts. A secondary network of 21 autonomous weather stations with commercial sensors provided additional information on relative humidity, wind speed and precipitation at 10 s resolution. This work introduces the novel type of instruments, describes the generated data set, and presents first results of the experiment.
Over the three-month period the FESST@HH network experienced more than 30 cold-pool events of different strength and size. Case studies demonstrate that the observations allow to capture the internal structure and growth of a cold pool and to infer its vertical depth based on the hydrostatic assumption. The data set does not only provide novel insights into the life cycle of cold pools, but also opens new perspectives on phenomena like the urban heat island. Moreover, the experiment may serve as a prototype for the design of future observational networks, including citizen science approaches.
How to cite: Kirsch, B., Ament, F., Hohenegger, C., and Klocke, D.: Illuminating the blind spot of sub-mesoscale phenomena with a dense station network, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-118, https://doi.org/10.5194/ems2021-118, 2021.
The Starzach site in the upper Neckar valley, Germany, is known for its natural degassing of carbon dioxide (CO₂). During the last century, the gas has been mined industrially until yields stagnated and the extraction wells were sealed. Interestingly, CO₂ exhalation spots have reappeared across the site over the last years. Neither the total emission rate across the site, nor the diurnal or seasonal variations of the CO₂ degassing on the site have been quantified scientifically yet.
In this project, an autarkic wireless sensor network is developed to monitor the CO₂ concentrations in the Neckar valley continuously and investigate the spatial and temporal variability. In the project's second phase, gas transport simulations with a numerical dispersion model will be used to assess the actual CO₂ emissions into the lower atmosphere. Ultimately, the developed methods may be exported to other regions with similar gas emission phenomena.
To account for the spatial heterogeneity of the CO₂ outgassing, a dense sensor network is needed. Deploying several dozen stations requires each station to be of reasonable cost. Currently, commercially available, deployable and self-sustaining measurement systems for CO₂ are very expensive. So to facilitate a targeted network with a 10-meter scale mesh size, we developed an infrastructure that meets our requirements. The network’s modular setup permits flexible sensor extension or spatial expansion. A Campbell Scientific IRGASON eddy-covariance station supplements the network as a punctual high-precision reference. Live gathered data are offered to the science community via the publicly accessible OpenSenseMap.org measurement data platform.
In this talk, the sensor network infrastructure is introduced and the low-cost CO₂ sensor performance is assessed. First long-term measurements at the site reveal a clear diurnal cycle of meteorological parameters and especially for the atmospheric CO₂ concentration and stratification. The site's valley location with surrounding hills is shown to create complex flow dynamics.
How to cite: Büchau, Y., van Kesteren, B., Platis, A., Leven, C., and Bange, J.: Measuring Atmospheric Dynamics at a Site with Natural CO₂ Emissions with an Autarkic Wireless Sensor Network, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-439, https://doi.org/10.5194/ems2021-439, 2021.
Clouds generally cool the atmosphere due to a negative net radiative forcing. However the Cirrus clouds warm the climate, despite they co-occur with other cloud types, or are the only cloud layer present. Consequently, changes in Cirrus frequency are important for understanding the climate change and climate variations. Manual, ground-based observations of Cirrus are the longest climate record on that variable. The reliability of those observations is questionable, because of viewing geometry (middle/low-level clouds obscure the high-level clouds), and observers ability to detect optically thin media in the upper atmosphere.
We have validated the reliability of ground-based observations of Cirrus using state-of-the-art lidar data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission. Focusing on the observer’s sensitivity to Cirrus, we only evaluated the observations under a perfect conditions: no clouds at middle/low level. We found that probability of Cirrus detection was 67% during the day time, and was controlled by the Cirrus optical depth (60% for subvisual clouds, and >95% for depth >5). During the night the probability of detection decreased to 35%. Presence of the illuminated Moon positively impacted the hit rate, but only when lunar phase was greater than 50%. Evaluation of the visual method, as a whole, considered clouds at any level, as they occur in real, true-weather conditions. We found that probability of Cirrus detection was 48% daytime, and as little as 28% nighttime. The increase of the sky sealing by low/middle-level clouds negatively impacted the accuracy. Sharp decrease in Cirrus detection efficiency was observed when cloud fraction for middle/low clouds exceeded 50%-60% (daytime), and 10%-25% (nighttime).
Based on the results, we conclude that in the majority of cases, accuracy we found can be achieved just by an accident: "Cirrus"/"no Cirrus" can be reported with no looking at the sky, and the resulting accuracy will be the same as for the real, empirical data from stations. Consequently, the manual observations are highly uncertain and may be unreliable for deriving a long-term climate trends. Even at best, the surface-based, manual observations are less reliable than those collected with a satellite imagers (specifically the MODIS-VIIRS cloud product).
How to cite: Kotarba, A. and Nguyen Huu, Ż.: Validation of manual, surface-based detections of Cirrus with CALIPSO space lidar, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-451, https://doi.org/10.5194/ems2021-451, 2021.
Fog forecasts still remain quite inaccurate due to the complexity, non linearities and fine scale of the main physical processes driving the fog lifecycle. Additionally to the complex modelling of fog processes, current numerical weather prediction models are known to suffer from a lack of operational observations in the atmospheric boundary layer and more generally during cloudy-sky conditions. Continuous observations of both thermodynamics and microphysics during the fog lifecycle are thus essential to develop future operational networks with the aim of validating current physical parameterizations and improving the model initial state through data assimilation techniques. In this context, an international network of 8 ground-based microwave radiometers (MWRs) has been deployed at a regional-scale on a 300 x 300 km domain during the SOFOG3D (SOuth FOGs 3D experiment for fog processes study) that has been conducted from October 2019 to April 2020. The MWR network has been extended with ceilometers at all MWR sites and additional microphysical observations from the 95 GHz cloud radar BASTA at two major sites as well as wind measurements from a Doppler lidar deployed at the super-site. After an overview of the SOFOG3D objectives and experimental set-up, preliminary results exploiting mainly the MWR network and cloud radar observations will be presented. Firstly, the capability of MWRs to provide temperature and humidity retrievals within fog and stratus clouds will be evaluated and discussed against radiosoundings launched during intensive observation periods (IOPs). Secondly, first retrievals of liquid water content profiles within fog and stratus clouds derived from the synergy between MWRs and the BASTA cloud radar will be presented. To that end, a one dimensional variational approach (1D-Var) directly assimilating MWR brightness temperatures and cloud-radar reflectivities has been developed. 1D-Var retrievals will be validated through a dataset of simulated observations and real fog cases of the SOFOG3D experiment. The capability of MWR and cloud radar observations to improve the initial state of the AROME model during fog conditions will be discussed with a focus on selected case studies. Finally, the usefulness of ground-based remote sensing networks to improve our understanding of fog processes and to validate physical parameterizations will be illustrated using the operational AROME model and the AROME Ensemble Prediction System
How to cite: Martinet, P., Burnet, F., Bell, A., Kremer, A., Letillois, M., Löhnert, U., Antoine, S., Caumont, O., Cimini, D., Delanöe, J., Hervo, M., Huet, T., Georgis, J.-F., Orlandi, E., Price, J., Raynaud, L., Rottner, L., Seity, Y., and Unger, V.: Benefit of microwave radiometer and cloud radar observations for data assimilation and fog process studies during the SOFOG3D experiment, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-232, https://doi.org/10.5194/ems2021-232, 2021.
Characteristic phenomena in the Pannonian basin during the winter half year are the mist (500-1000 hours/year), the fog (150-300 hours/year) and the cold air pool with high air pollution concentrations. Formation, development and dissipation of fog events are complex processes that are impacted by short- and longwave radiation, condensation and evaporation, turbulent exchange, furthermore fog chemistry. The research presented here aims at exploring the interaction of these processes using field observations. To this end, complex field campaigns were conducted in Budapest (WMO code: 12843) and in the Sió Valley, 6 km away from Siófok (12935) during 1 to 3-month periods in the last three winter half years.
Besides air chemistry and standard meteorological variables, the leaf wetness, surface and soil temperature, soil moisture, soil heat flux (Huskeflux), radiation budget components (CNR1) and turbulent fluxes based on eddy covariance (CSAT3, EC150) and gradient methods were measured above the grassland. Time resolutions of measurements for slow sensors were 10 sec or rather 1 minute and for eddy covariance system 10 Hz. The mist and fog periods were detected using a cloud camera (in Sió Valley) and by synoptic observations in Budapest and Siófok.
Additional measurements in Budapest were i) the wind speed (U), air temperature (T) and relative humidity (RH) profiles together with Gill sonic anemometer at the top of a 30 m high tower, ii) LUFT CHM 15k ceilometer. SODAR and aviation meteorological measurements were also available from the Budapest Ferenc Liszt International Airport (LHBP) at 8 km distance. Other field experiments were done in the wet leeward Sió Valley in 2018-19 and 2019-20. Vaisala WXT530 sensor, LUFT CHM 15k ceilometer, tethered balloon measurements with GRAW radiosondes and METEK SODAR measurements were also provided as additional information behind the energy budget measurements.
Our results confirmed that according to the expectations, we have recorded more foggy situations in the Sió Valley than in Budapest (12843) and Siófok (12935). Radiation and advection type fog events were formed in most cases. The measured RH was above 95 and gradually increased during the onset period of fog. RH was around 100%, fluctuations could be measured less accurately. Dissipation of the fog is usually characterized by wind intensification and rise in the incoming solar radiation. The data of two field campaigns will be analyzed i) a cold pool situation in Sió Valley in January 2020 and ii) the foggy season 2020-21 in Budapest. The developed complex (micrometeorological, furthermore air and liquid chemistry) database gives opportunity to validate numerical model results (WRF, CHIMERE and detailed box model) and to improve parameterizations of the numerical models.
How to cite: Weidinger, T., Gyöngyösi, A. Z., Arun, G., Tordai, Á., Krámer, T., Torma, P., Rehák, A., Szilágyi, M., Horváth, Á., Horváth, G., Bottyán, Z., Cséplő, A., Lázár, I., Imre, K., Kardos, P., and Geresdi, I.: Micrometeorological fog experiments in Budapest and in Sió Valley near Lake Balaton (2018-2021), EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-304, https://doi.org/10.5194/ems2021-304, 2021.
The Regional Agency for the Environment of Veneto (ARPAV - North East Italy) through its Meteorological Center, has been managing some passive radiometers since 2005, one located in the Po Valley in the historic center of Padua (210,000 inh.) and the other in a wide pre-Alpine valley (Val Belluna) in the municipality of Feltre (20,000 inh.). Both instruments are located on the roof of the host building and scan the atmosphere with a thermal profile every 5 min. In the Po Valley and in Val Belluna there are frequent episodes of fog, especially in the autumn / winter season, which can sometimes persist throughout the day.
Both radiometers are MTP-5 HE produced by Attex and are able to obtain the thermal profile up to 1 km, with an interpolated value every 50 m, in almost all weather conditions, using a single channel centered on the absorption of the molecular oxygen microwave at 60 GHz. This simple type of radiometer, very useful for studying the characteristics of thermal inversion, or super-adiabatic heating of the first layers of the atmosphere, is widely used to characterize the PBL (Planetary Boundary Layer) in terms of atmospheric stability.
The proposed study seeks to explore the possibility of using thermal profile data from passive radiometers to study fog evolution only at the Padua site, where other meteorological information is also available, such as professional weather stations, webcams and visibilimeters. A statistic of the phenomenon will be presented, with the help of satellite images, from data series of over 10 years, together with some case studies, which will try to highlight the limits and effectiveness of this new approach.
How to cite: Ferrario, M. E. and Maria, S.: Possible contribution of passive radiometers to the analysis of the evolution of fog episodes, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-157, https://doi.org/10.5194/ems2021-157, 2021.
Accurate measurement of physically relevant parameters through cloudy atmospheres is crucial for climate studies and radiative transfer modelling. In particular, small perturbations in the Liquid Water Path (LWP) retrieval within liquid water clouds greatly affect longwave and shortwave radiative fluxes when LWP is lower than 100 g/m2. Since a large fraction of liquid water clouds in all climate regimes feature such a condition, improving the retrieval of low LWP amounts from ground-based observations is highly desirable. In fact, uncertainties for LWP retrievals from Microwave radiometer (MWR) are generally acceptable for the high LWP values, but are relatively large for lower values typically observed in fog conditions. Further work is therefore required to achieve the accuracy needed when the LWP is small. In this work, we show the benefit of a combined infrared (IR) and microwave (MW) approach, to improve ground-based liquid water path retrievals during fog. We consider a 14 MWR profiler operating in the 22-58 GHz frequency range and a IR radiometer operating at 10.5um. The research is conducted over a simulated dataset of atmospheric profiles from a numerical weather prediction model (AROME) and radiative transfer calculations from MonoRTM and RTTOV-gb radiative transfer models. The IR signal is shown to be very sensitive for LWP values lower than 100 g/m2, spanning a temperature range as high as 80 K. To that end, statistical (linear and quadratic) regressions are first trained with synthetic observations. We analyse the differences in LWP retrieval with and without the IR contribution, in order to evaluate its impact. As a future step, these coefficients will be applied to real measurements from the Météo-France SOFOG3D experiment (Burnet et al., 2020; Martinet et al., 2020) for evaluation. This work is conducted in the framework of COST Action PROBE (CA18235, Profiling the atmospheric Boundary layer at European scale, http://probe-cost.eu/) (Cimini et al., 2020).
Burnet et al., https://doi.org/10.5194/egusphere-egu2020-17836, 2020.
Cimini et al., https://doi.org/10.1007/s42865-020-00003-8, 2020.
Martinet et al., https://doi.org/10.5194/amt-13-6593-2020, 2020.
How to cite: Gallucci, D., Martinet, P., and Cimini, D.: Infrared-Microwave synergy to improve low values Liquid Water Path retrievals in fog conditions., EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-357, https://doi.org/10.5194/ems2021-357, 2021.
Clouds have a key role in weather and climate forecasting due to their effect on global radiation and water budget. Clouds change the radiation energy in the Earth-atmosphere system by reducing both incoming and outgoing parts, depending on their macro- and microphysical characteristics such as cloud base height (CBH), optical properties etc. These clouds properties are generally related to cloud types, so the effects in weather and climate caused by various cloud types differ greatly. It is known that high clouds cause the earth's surface to heat up, while low clouds cause cooling. Obviously, cloud radiation forcing is an important source of uncertainty in the numerical weather and climate models, so the registered and expected changes in the properties of clouds due to a warming climate need in-depth studies. But cloud base height is not only important for weather and climate forecasting, but also for airplane traffic safety. Nowadays, retrieving the CBH is mainly based on satellite and ground-based observations. Satellite-borne instruments provide tempting spatial coverage but uncertainty in CBH estimation should be considered. In contrast, many ground-based observations of the CBH are characterized by higher accuracy. Nowadays, ceilometers - lidars specifically designed to detect CBH, that operate continuously and unattended, providing high vertical and time-resolution data, are reference instrument in CBH measurement. In addition, rawinsondes provide in-situ measurements of temperature, humidity, and pressure, so that the CBH can be evaluated by the lifting condensation level or by threshold value in relative humidity. In areas where only surface measurements are available, a simple adiabatic model of a rising air parcel can be applied in the CBH assessment. In this work, based on ceilometer, rawinsonde and surface measurements, the characteristics of CBH over Sofia, Bulgaria are studied in detail. We start with an intercomparison between CBHs obtained from three types of ground-based observations, considering the individual advantages and disadvantages of the methods by using ceilometer as reference. Finally, the daily, seasonal and interannual variability of CBH over Sofia are interpreted.
How to cite: Levi, V., Vladimirov, E., and Danchovski, V.: Investigating long-term variations in cloud base height over Sofia, Bulgaria, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-197, https://doi.org/10.5194/ems2021-197, 2021.
Measuring submesoscale variability is the core task of the field campaign FESSTVaL (Field Experiment on Sub-Mesoscale Spatio-Temporal Variability in Lindenberg). FESSTVaL focuses on three sources of submesoscale variability: cold pools, wind gusts and boundary layer pattern. It took place in the summer months of 2021 at the Meteorological Observatory Lindenberg – Richard-Aßmann-Observatory (MOL-RAO) of the German Weather Service (DWD) near Berlin and was initiated by the Hans-Ertel-Center for Weather Research (HErZ).
In order to capture phenomena at the submesoscale (500 m – 5 km), generally not captured by conventional measurement network, a hierarchical measurement strategy is adopted. This includes wind profiling stations with a coordinated scanning strategy of several Doppler Lidars, two mobile profilers to measure thermodynamic properties and precipitation, more than 100 stations with near-surface measurements of air temperature, pressure and soil moisture, more than 20 automatic weather stations, an X-Band radar, and a number of energy balance stations. This equipment is augmented by the extensive ground-based remote sensing array at the MOL-RAO, operated by DWD and by flights operated by Unmanned Aerial Systems. Complementing to this, the benefit of a citizen-science measurement network is investigated during the campaign with “Internet-of-things” based technology and low-cost sensors built and maintained by citizens. The measurements are supplemented by high-resolution large-eddy simulations (ICON-LES).
Originally planned for the summer 2020, FESSTVaL had to be postponed to 2021 and replaced by three local individual campaigns, conducted in Bayern, Lindenberg and Hamburg in 2020. Those three test campaigns demonstrated the ability of the envisionned measurement strategy and planned instruments to capture submesoscale variability and submesoscale weather phenomean. This talk will give a brief overview on the results of these three campaigns, as a foretaste to FESSTVaL, together with some of the very first measurements taken during FESSTVaL.
How to cite: Hohenegger, C., Ament, F., Beyrich, F., Duran, I. B., Löhnert, U., Göber, M., Masbou, M., Rust, H., Sakradzija, M., Schmidli, J., and Wiesner, S.: FESSTVaL: Field Experiment on sub-mesoscale spatio-temporal variability in Lindenberg – the campaign 2021 an its predecessors, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-296, https://doi.org/10.5194/ems2021-296, 2021.
Doppler wind lidars are used to measure boundary layer turbulence, which is an important process to transfer heat and moisture within the boundary layer. Turbulence measurements using Doppler wind lidars were conducted during FESSTVaL@MOL field experiment from June to August 2020. The FESSTVaL@MOL 2020 is a part of the FESSTVaL (Field Experiment on sub-mesoscale spatio-temporal variability in Lindenberg) measurement campaign conducted at the boundary layer site Falkenberg, a part of the Lindenberg Meteorological Observatory – Richard-Aßmann-Observatorium (MOL-RAO). One Doppler wind lidar has been operated in vertical stare mode to characterize turbulence in the convective boundary layer during the summer. Two other Doppler wind lidars have been operated in low elevation angle PPI scan mode and one Doppler wind lidar has been operated in RHI scan mode. These three scanning configurations are used to investigate the dominant coherent structures near the surface.
The retrieved wind data from vertical stare mode are categorized into cloud-topped boundary layer and cloud-free boundary layer days. We will analyze the intensity of the turbulence using vertical velocity variance and dissipation rate of the turbulent kinetic energy and the source of turbulence using a skewness profile for both categories. These profiles will be combined with low elevation angle PPI scan mode to categorize the coherent structures near the surface by their intensity and origin. Besides, we will present the overview of the preliminary study about the evolution of mixing layer height before and after cold-pool passage from several cases during FESSTVaL@MOL 2020 using vertical stare and RHI scan data.
How to cite: Dewani, N., Sakradzija, M., Schlemmer, L., and Schmidli, J.: Turbulence characteristics and coherent structures in the convective boundary layer analyzed using Doppler wind lidars during FESSTVaL@MOL 2020, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-329, https://doi.org/10.5194/ems2021-329, 2021.
To foster our understanding of the role that the vertical distribution of atmospheric aerosols and water vapor plays on the climate system, the Cabauw Experimental Site for Atmospheric Research in the Netherlands has been providing measurements with its high performance multi-wavelength Raman lidar (Caeli) on a regular basis and during intensive periods of observations.
From late August to early October, 2019, the Cabauw site was the central point for the active remote sensing activities during the TROpomi vaLIdation eXperiment (TROLIX’19), a campaign which used a combination of in-situ and remote sensing measurements, both ground and air-borne based, for the validation of Sentinel-5p/TROPOMI level 2 products. During this campaign, Raman lidar measurements were performed under a variety of atmospheric conditions.
In this work, we present the Caeli simultaneous measurements of aerosol optical properties and water vapor mixing ratio profiles during the TROLIX'19 campaign. A general clean atmosphere was observed, with eventual occurrence of mid-tropospheric aerosol layers and a persistent stratospheric layer observed for many days. Profiles of extinction and backscatter coefficients have been processed both locally and through the central processing facilities of the European lidar network (ACTRIS-EARLINET). The precision of the day and nighttime water vapor mixing ratio retrievals were accessed, showing that high resolution profiles were possible in the planetary boundary layer (PBL) during daytime and throughout the troposphere during nighttime, allowing the measurement of dry air mixing in the PBL and information for heat flux studies. Time and vertically resolved aerosol and water vapor fields around cloud formation events are explored.
How to cite: Gouveia, D. and Apituley, A.: Day and nighttime observations of water vapor and aerosol optical profiles in the boundary layer observed by Caeli Raman lidar during the TROpomi vaLIdation eXperiment (TROLIX’19), EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-114, https://doi.org/10.5194/ems2021-114, 2021.
Understanding future changes of the terrestrial water cycle and their interaction with human activity, with emphasis on agricultural areas, was selected as one of the World Climate Research Programme (WCRP) Grand Challenges, entitled “Water for the Food Baskets of the World”. Within this framework, the scientific objectives of the “Human Imprint on Land surface Interactions with the Atmosphere over the Iberian Semi-arid Environment” (HILIAISE) are the characterization of evapotranspiration and other key processes of water cycle in semi-arid environments. For this purpose, an international field campaign, scheduled for 2021, has been planned focused on a region with highly contrast surface characteristics (irrigated vs non-irrigated areas), particularly during summer.
An overview and preliminary results of a specific project (WISE-PreP) within HILIAISE is given here. WISE-PreP was designed to study precipitation processes aiming to characterize possible differences in precipitation induced by surface characteristics. For this purpose, planned instrumentation for the campaign includes the deployment of three sites equipped each with a vertical radar Doppler Micro Rain Radar (MRR) and a laser disdrometer (PARSIVEL), covering both irrigated and non-irrigated sites, with three disdrometers (model PARSIVEL-2) and three MRRs (one model MRR-2 and two MRR-PROs). Time series of vertical precipitation profiles will be recorded to study microphysical processes trough the evolution of raindrop size distributions and related variables including precipitation intensity or convective vs stratiform rainfall regimes. Additional observations include raingauge data, C-band Doppler weather radar observations, and satellite products, as well as high resolution deterministic numerical weather prediction model data plus Ensemble Prediction Systems (EPS) model output. Funding for this research was provided by “Analysis of Precipitation Processes in the Eastern Ebro Subbasin” (WISE-PreP, RTI2018-098693-B-C32) and the Water Research Institute (IdRA) of the University of Barcelona.
How to cite: Bech, J., Udina, M., Codina, B., Gonzalez, S., Garcia, A., Altube, P., Mercader, J., Callado, A., Arús, J., Rodríguez, O., Casellas, E., Roura-Adserias, F., Rosell, À., Polls, F., Peinó, E., Kosovic, B., Montornès, À., Escribà, P., Trapero, L., and Paci, A. and the more authors: Preliminary results of the Analysis of Precipitation Processes in the Eastern Ebro Subbasin (WISE-PreP) Field Campaign within HILIAISE, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-269, https://doi.org/10.5194/ems2021-269, 2021.
The vertical and horizontal structure of the atmosphere and the typical timescales of atmospheric phenomena and processes largely determine the design and performance of atmospheric measurement techniques. Each meteorological process can be characterized by typical spatial and temporal scales. This is based on the spectral organization of atmospheric turbulence and on wavelike processes, where relevant wavelength ranges (spatial dimensions) relate to distinct durations (frequencies). The development of a suitable measurement strategy for any observational task should therefore be based on a careful consideration of the specific processes to be described and resolved. This should govern the decision on, e.g., the measurement range, the measurement levels / range resolution, the horizontal spacing of sensors or sites, the measurement frequencies and averaging times, and sensor characteristics such as response time, resolution, accuracy, sensitivity etc. When using in-situ technologies, a wide variety of measuring platforms can be used, from the classic weather station arrangements, masts, and towers to balloons or controlled airborne platforms (including both manned and remotely piloted aerial vehicles). With remote sensing technology, various measurement systems (both passive and active) are available in terms of measured variables, pointing and scanning options, altitude range, spatial and temporal resolution. It will be shown that the extensive overview tables in the recently published Springer Handbook of Atmospheric Measurements can provide guidance on how in-situ and remote sensing techniques can be optimally used for both routine observations and process studies (field campaigns) for a large variety of applications and how measurement concepts, strategies and networks can be designed.
How to cite: Foken, T., Beyrich, F., and Wulfmeyer, V.: Application of suitable measurement strategies depending on the scales of atmospheric processes, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-184, https://doi.org/10.5194/ems2021-184, 2021.
A detailed understanding of atmospheric boundary layer (ABL) processes is key to improve forecasting of pollution dispersion and cloud dynamics in the context of future climate scenarios. International networks of automatic lidars and ceilometers (ALC) are gathering valuable data that allow for ABL layers to be derived in near real time. A new generation of advanced methods to automatically detect the ABL heights now exist. However, diversity in ALC models means these algorithms need to be tailored to instrument-specific capabilities. Initial evaluation of the advanced algorithms STRATfinder (for application to high signal-to-noise ratio (SNR) ALC observations) and CABAM (low-SNR measurements) to automatically derive ABL heights indicates promising performances (Kotthaus et al. 2020).
In the framework of the ABL testbed project (funded by ICOS, ACTRIS and E-PROFILE) the two algorithms are now being assessed for application in an operational network setting, such as EUMETNET E-PROFILE. A subset of 11 E-PROFILE sites in a range of geographical and land cover settings across Europe are selected where data from low-SNR and/or high-SNR ALC are available for multiple years. Automatic layer detection is implemented, including instrument-specific corrections and calibrations. Algorithm performance for layer height detection is being evaluated via comparison of results from different ALC and by including reference data from thermodynamic- and turbulence derived layer heights from radiosondes and other ground-based profiling sensors where available. Recommendations are formulated for implementation of automatic ABL height retrievals across a diverse sensor network. A prime example of collaborations within the EU COST action PROBE on profiling the atmospheric boundary layer, the ABL testbed is a crucial step towards harmonised ABL height products at the European scale.
Kotthaus, S, M Haeffelin, MA Drouin, JC Dupont, S Grimmond, A Haefele, M Hervo, Y Poltera, M Wiegner, 2020: Tailored Algorithms for the Detection of the Atmospheric Boundary Layer Height from Common Automatic Lidars and Ceilometers (ALC). Remote Sens, 12, 3259, DOI: 10.3390/rs12193259.
How to cite: Kotthaus, S., Haeffelin, M., Drouin, M.-A., Laplace, C., Bouffies-Cloche, S., Ruefenacht, R., Dupont, J.-C., Haefele, A., Collaud Coen, M., Hervo, M., and Rivier, L. and the co-authors: Automatic detection of atmospheric boundary layer heights at European scale (ABL testbed), EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-383, https://doi.org/10.5194/ems2021-383, 2021.
It is well known that anthropogenic aerosols deteriorate air quality increasing public health risk. Therefore their characterization must be one of the main objectives in atmosphere studies, although the heterogeneous distribution of the aerosols in the atmosphere hampers it. Anthropogenic aerosols are mostly concentrated within the planetary boundary layer (PBL) that extends from the surface up to a variable height that usually coincides with the presence of a temperature inversion. The PBL height, then, is affected by the radiation emitted by the surface causing turbulence and evolving along the day and in this way limiting the vertical mixing of the air pollutants generated near the surface. Therefore, it can be assumed that the lower the PBL height, the higher the aerosol concentration from local sources. Lidars have demonstrated their capabilities to study the aerosol vertical distribution and their spatio-temporal evolution can provide very complete information on both aerosol spatial distribution and their characterization. Their wavelength dependence of the backscatter and extinction coefficients allows for a more detailed discrimination of aerosol types. On the other hand, ceilometers are capable of providing continuous aerosol vertical profiles with good spatial resolution and a large range, besides ceilometers operating at 1064nm can provide backscatter and extinction coefficients as Lidar instruments. The present work has been carried out in the Madrid metropolitan area located in the center of the Iberian Peninsula, which counts with a population of nearly 6 million inhabitants and a car fleet of almost 3 million vehicles. Its main objective is the assessment of the planetary boundary layer height by means of machine learning techniques using ceilometer signals and also its validation by using multiwavelength lidar measurements and radiosoundings. Typical techniques as the wavelet and the gradient methods are unable to detect the PBL in cases with presence of low clouds or residual layers. For that purpose, several profiles stored in the Madrid database, covering different synoptic situations as long-range transport of aerosols and clean-atmosphere situations are used. These profiles have been performed by the CHM15k Nimbus ceilometer deployed next to the MDR-CIEMAT ACTRIS station (40.4565ºN, 3.7257ºW, 663 m a.s.l.), equipped with a Lidar-Raman instrument (integrated in EARLINET-ACTRIS) and located in the Madrid North-West city outskirts.
This work was supported by H2020 programme from the European Union (grant 654109, ACTRIS-2 project), the Spanish Ministry of Economy and Competitivity (CRISOL, CGL2017-85344-R) and Madrid Regional Government (TIGAS-CM, Y2018/EMT-5177).
How to cite: Barragan, R., Molero, F., and Artiñano, B.: Assessment of the planetary boundary layer height by means of machine learning techniques using ceilometer signals, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-156, https://doi.org/10.5194/ems2021-156, 2021.
In air traffic management (ATM) and monitoring of critical infrastructure, the exact description of the near surface atmospheric state - and thus the visibility - is an indispensable basis for situation awareness and any further weather forecast.
In order to overcome the drawbacks of the currently subjective reports from human observers, we present an innovative solution to automatically derive visibility measures from standard cameras by a vision based approach.
The certified state of the art for automated visibility measurement is represented by visibility sensors, such as those e.g. used for RVR (Runway Visual Range) measurements. These sensors only allow a very local measurement, whereas camera-based methods enable a representative measurement of the visibility in the entire environment of the camera location. A variety of camera-based approaches use physically based models to derive a measure of visibility (e.g. the Koschmieder model or contrast measurements, as well as models for measuring light reduction). The Dutch weather service (KNMI) uses similar visibility detectors and methods as are used for our system called “visIvis®” (e.g. feature-based methods or de-hazing methods). In addition to the restriction to a single specific method, often additional special requirements (e.g. the measurement object or the land mark must lie on a straight line with two cameras) complicate the use of these methods for a representative measurement of the entire scene.
It will be shown how the visIvis® system can detect automatically most suitable areas for visibility estimation within the camera-covered range based on a variety of detection algorithms, automatically tunes its detection parameters, and automatically derives fog covered areas. Furthermore, by coupling visIvis® with georeferenced data, a pixel-precise depth map is deduced from digital surface and terrain models and user orientated visibility classes can be defined (customized or according to meteorological relevant thresholds). Based on this mapping, visIvis® is able to derive representative visibility measures for complete visual range, that can be reported in customized or standard formats (e.g. METAR).
The presentation will give insight on a recent visibility measurement study for synoptic meteorological applications in cooperation with Deutscher Wetterdienst (DWD), the German National Meteorological Service. Special focus was laid on night scenarios, which pose challenges on a camera based measurement system, e.g. light sensitivity of the sensor or availability of representative landmarks. In addition, we will show how to generate added value by extending the concept of vision-based visibility measurement to other weather-related parameters. In the present study it was investigated, which steps are required by transfer learning principles to adapt the system towards other camera-based observations. Results will be presented from evaluations in different challenging application scenarios.
How to cite: Ganster, H. and Lang, J.: Vision-based Visibility Estimation: From Fog Detection to Complete Visual Range, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-69, https://doi.org/10.5194/ems2021-69, 2021.
The atmospheric boundary layer (ABL) is the most important under-sampled part of the atmosphere. ABL monitoring is crucial for short-range forecasting of severe weather within highly resolving numerical weather predictions (NWP). Top-priority atmospheric variables for NWP applications like temperature (T) and humidity (H) profiles are currently not adequately measured. Ground-based microwave radiometers (MWRs) like HATPRO (Humiditiy And Temperature PROfiler) are particularly well suited to obtain T-profiles in the ABL as well as coarse resolution H-profiles; yet MWR data are not assimilated by any operational NWP system. The HATPRO measures in zenith and other angles throughout the troposphere over an area with ~10 km radius and has a temporal resolution on the order of seconds. Measured brightness temperatures (TB) are used to retrieve the T- and rudimentary H-profiles. Path integrated values like IWV (Integrated Water Vapor) and LWP (Liquid Water Path) are more reliable with excellent uncertainties up to 0.5 kg/m2 and 20 g/m2, respectively.
Driven by the E-PROFILE program, a recent proposal was accepted by EUMETNET, to continuously provide suited MWR data to the European meteorological services. Also, the European Research Infrastructure for the observation of Aerosol, Clouds, and Trace gases ACTRIS or the European PROBE (PROfiling the atmospheric Boundary layer at European scale) COST action currently focus on establishing continent-wide quality and observation standards for MWR networks for research as well as for NWP applications. The German Weather Service (DWD) also investigates the potential of HATPRO networks for improving short-term weather forecasts.
For all this it is important to obtain an overview of what HATPROs are capable of in regard to their measurement uncertainty. This is done by conducting coordinated experiments at JOYCE (Jülich Observatory for Cloud Evolution) and the FESSTVaL (Field Expermient on Submesoscale Spatio-Temporal Variability at Lindenberg) campaign in 2021. The goal is to develop a standard procedure for error characterization that can be applied to any HATPRO network instrument.
During FESSTVaL, there are 4 HATPROs on site which presents the unique opportunity to assess calibration procedures and measurements in order to characterize systematic errors and random uncertainties for each channel. Important error components are absolute calibration errors (biases), drifts (instrument stability, leaps between calibrations), radiometric noise and radio frequency interference. For the absolute calibration with liquid nitrogen, the repeatability, the duration, and the time between calibrations are essential. Differences between two consecutive calibrations should be minimal, the right duration of a calibration and the right amount of time between calibrations are to be defined, as are the magnitudes of the drifts. For the determination of noise levels for each channel, covariance matrices of measured brightness temperatures from the cold- and hot-load are necessary. With these matrices, the correlated noise of each channel with itself and which each other are studied.
How to cite: Böck, T., Pospichal, B., and Löhnert, U.: Quality Assessment for HATPRO Microwave Radiometer Measurements and Calibrations, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-162, https://doi.org/10.5194/ems2021-162, 2021.
The GCOS Reference Upper Air Network (GRUAN) consists of 30 globally distributed measurement sites that provide reference observations of essential climate variables such as temperature and water vapour for climate monitoring. At these sites, radiosondes provide in-situ profiles of temperature, humidity and pressure at high vertical resolution. However, data products from commercial radiosondes often rely on black-box or proprietary algorithms, which are not disclosed to the scientific user. Furthermore, long-term time-series from these products are frequently hampered by changes in the hardware and/or the data processing. Therefore, GRUAN data products (GDP) are developed, that employ open-source and well-documented corrections to the measured data, thereby complying with the requirements for reference data, which include measurement traceability and the availability of measurement uncertainties. The GRUAN data processing is applied to the raw measurement data of temperature, humidity, pressure, altitude, and wind, and includes corrections of errors from known sources, such as for example solar radiation error for temperature and sensor time lag for humidity measurements. The vertically resolved uncertainty estimates include the uncertainty of the applied corrections and the calibration uncertainty of the sensors.
A substantial number of GRUAN sites employ the Vaisala RS41 radiosonde, and its predecessor, the RS92, before that. This large-scale change of instrumentation poses a special challenge to the network, and great care is taken to characterize the differences between these instruments in order to prevent inhomogeneities in the data records. As part of this effort, the GRUAN data products for both radiosonde types are compared. In this study we used data from approximately 1000 RS92+RS41 twin-soundings (two sondes on a rig attached to one balloon) that were performed at 11 GRUAN sites, covering the main climate zones.
The first analysis shows that daytime temperature differences in the stratosphere increase steadily with altitude, with RS92-GDP up to 0.5 K warmer than RS41-GDP above 25 km. In addition, at daytime the RS41-GDP is 0.2 K warmer than the manufacturer-processed RS41-EDT product above 15 km. Analysis of the humidity profiles shows a slight moist bias of the RS41 compared to the RS92 for both GDP and manufacturer-processed data. Differences between the RS41-EDT and GDP humidity products are most pronounced in the upper troposphere - lower stratosphere region and are attributed to the time lagcorrection. The analysis of the temperature differences will be refined by investigating the influence of the solar radiation in conjunction with sonde orientation and ventilation. Furthermore, the uncertainty of the humidity data will be assessed by comparing with coincident measurements of the water vapor profile by the Cryogenic Frostpoint Hygrometer (CFH).
Key words: Radiosonde, RS41, RS92, humidity, temperature, uncertainty, GRUAN, troposphere, lower stratosphere
How to cite: Simeonov, T., Dirksen, R., von Rohden, C., and Sommer, M.: Intercomparison of the Vaisala RS92 and RS41 Radiosonde GRUAN Data Products (GDP) in the Troposphere and Lower Stratosphere, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-190, https://doi.org/10.5194/ems2021-190, 2021.
One of the main goals of the GCOS Reference Upper Air Network (GRUAN) is to perform reference observations of profiles of atmospheric temperature and humidity for the purpose of monitoring climate change. Two essential criteria for establishing a reference observation are measurement-traceability and the availability of measurement uncertainties. Radiosoundings have proven valuable in providing in-situ profiles of temperature, humidity and pressure at unmatched vertical resolution. Data products from commercial radiosondes often rely on black-box or proprietary algorithms, which are not disclosed to the scientific user. Furthermore, long-term time-series from these products are frequently hampered by changes in the hardware and/or the data processing. GRUAN data products (GDPs) comply with the above-mentioned criteria for a reference product. Correction algorithms are open-source and well-documented and the data include vertically resolved best-estimates of the uncertainties.
This presentation discusses the quantification and the correction for the temperature error due to solar radiation that is applied in the GRUAN data processing for the Vaisala RS41 radiosonde. Heating of the temperature sensor by solar radiation is the dominant source of error for daytime radiosoundings.
At Lindenberg Observatory a dedicated laboratory set-up was built to quantify the solar temperature error of radiosondes. The setup allows to create conditions that are similar to those encountered during an actual radiosounding, with special emphasis on parameters such as pressure, air flow (ventilation), and illumination conditions. The radiosonde is placed inside a quartz tube that is integrated in a wind tunnel-like construction that can be operated between ambient pressure and 3 hPa. During the measurements the radiosonde is rotated along its longitudinal axis to mimic the spinning during ascent, and the large quartz window makes it possible to illuminate the temperature sensor together with a considerable part of the sensor boom, allowing to assess the contribution of the heat transfer from the sensor boom to the sensor. A parameterization of the heating of the sensor in terms of flux, pressure, ventilation and solar elevation is presented. This parameterization is the basis of the GRUAN correction algorithm, which in addition includes a radiation model and altitude information. In conclusion the GRUAN data product is compared to the manufacturer-processed data.
How to cite: von Rohden, C., Sommer, M., Naebert, T., and Dirksen, R.: Experiment to quantify the solar radiative temperature error of radiosondes, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-267, https://doi.org/10.5194/ems2021-267, 2021.
Scanning Wind Doppler lidars are more and more used for operational applications for which the retrieval of wind vectors and the turbulence quantities at specific points or at high resolution in an area of interest can bring valuable information. For retrieving volume wind data, many techniques can be used to retrieve wind vectors from the combination of radial wind data at different distances and lines of sight, as the well-known Volume Velocity Processing (VVP) technique, developed formerly for Doppler Radars. Although More sophisticated techniques based on the coupling with computational fluid dynamic models exist. e, a processing based on the VVP technique, called the Volume Wind processing (VW) has been developed. This algorithm includes a Single Value Decomposition algorithm that ensures a robust filtering of the retrieved wind data, and then high accuracy and precision. In addition, radial velocity variance (RVV) algorithm has been developped to remove the constant wind speed over a scan to provide fields of turbulent radial wind speeds. Those fields can be averaged and their variances can be computed to determine the averaged turbulent radial wind speeds as well as its deviation.
In this study, the principle and the validation of the VW algorithm will be presented at different sites (offshore, rural, and urban) against reference anemometers will be firstly presented. The bias and precision on 10 minutes averaged wind speed obtained are both about 0.5 m/s. The results reveal that the accuracy is significantly better for winds along lidar beam and precision better for larger samples of instantaneous wind speeds in the averaging time. Finally, the Volume Wind and the Radial Velocity Variance algorithms have then been applied to datasets of several months measured with Windcube Scanning Lidars at two different sites characterized by complex terrain and buildings. The data processed by the algorithms are analyzed to better understand the heterogeneities of the wind fields and its variations in time.
How to cite: Thobois, L., Troiville, A., and Pontreau, L.: Understanding complex wind fields with single Doppler Lidar techniques, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-371, https://doi.org/10.5194/ems2021-371, 2021.
The technological development of ground-based active remote sensing instruments has reached a point where they have the possibility to drastically increase the temporal and spatial data density compared to conventional instruments, which would allow for a better process understanding and is expected to enhance the forecasting skills of numerical weather prediction systems and reduce its uncertainties. To test the measurement uncertainty and feasibility of Doppler Lidar systems we participated in the FESST@MOL 2020 field campaign, organized by the German Meteorological Service (DWD) in Lindenberg, Germany. During this campaign, eight Doppler Lidars were operated at the boundary layer field site (GM) Falkenberg. We evaluated different scanning strategies for the determination of the wind profile in the Atmospheric Boundary Layer (ABL) using multiple different triple Lidar virtual tower (VT) scan patterns including range height indicator (RHI) and step/stare scan modes. We compared these Lidar-based wind measurements with the data from a sonic anemometer on a 99 m tall instrumented tower also located in Falkenberg over a period of four months. The lidar and the sonic anemometer data were processed to 10- and 30- minute averages and compared to each other. The VT measurements underestimated the mean horizontal wind compared to the sonic anemometer by around 0.2 m s‑1. Besides that, we compared the VT data with those from a single fourth nearby Doppler Lidar which was running in a velocity-azimuth display (VAD) mode. The calculated mean horizontal wind values between the two different modes showed a good comparability but differed stronger with increasing height.
How to cite: Wolz, K., Beyrich, F., Steinheuer, J., Detring, C., Leinweber, R., and Mauder, M.: Can Lidars compete with sonic anemometers? - Comparison of wind measurements from different Doppler Lidar scan strategies to sonic anemometer data, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-272, https://doi.org/10.5194/ems2021-272, 2021.
In the last decades, Doppler velocity measurements from zenith pointing radars have evolved to a standard radar variable. Measuring Doppler velocities allow estimating particle sedimentation or fall velocity of hydrometeors and thus offer key information to evaluate micro-physical parametrizations in numerical weather prediction models. In the future, the joint ESA-JAXA satellite mission EarthCARE features the first Doppler capable 94-GHz Cloud Profiling Radar (CPR), with enhanced sensitivity and improved resolution compared to the CloudSat CPR. These features, especially the Doppler velocity measurements, are expected to improve the CPR-based microphysical retrievals in clouds and precipitation and for the first time provide information about convective motion in clouds.
To evaluate EarthCare CPR Doppler velocity from the ground, the Doppler velocity from five ground-based zenith pointing 94 GHz radar spread over Europa should be used in future. To increase the quality of the measured Doppler velocity the antenna miss-pointing has to be estimated. Unknown antenna miss-pointing is the main source of error in Doppler velocity measurements and can reach values on the same order as the fall velocity of pristine ice crystals. Knowing the angle of miss-pointing, the error in the measured Doppler velocity measurements can be corrected and the precision and quality improved. This is especially important for cases where Doppler velocity values are direct input for retrievals, which, e.g., employ multiple radar sensors with matching sampling(?) volumes.
Within this work we will present a retrieval technique to identify the angle of antenna miss-pointing for ground-based radar profilers and correct the measured Doppler velocity values. The retrieval technique is a statistical method requiring the uncorrected Doppler velocity measurements and additional wind information from reanalysis or in parallel measuring sensors. Evaluation of the retrieval was done using different wind input data sets, e.g., ECMWF IFS wind fields or retrieved wind information from Radar scans. Also, the retrieval was used to correct the miss-pointing angles of two in parallel measuring zenith pointing radars and, therefore, correct the velocity errors in dual Doppler velocity field.
How to cite: Pfitzenmaier, L., Kollias, P., and Löhnert, U.: Retieving antenna miss-pointing for vertical pointing cloud radar and correcting the introduced Doppler velocity errors in the measurements, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-293, https://doi.org/10.5194/ems2021-293, 2021.
In recent years, the use of radar wind profilers (RWP) at airports has grown significantly with the aim of supporting decision makers to maintain the safety of aircraft landings and takeoffs.
The RWP provide vertical profiles of averaged horizontal wind speed and direction and vertical wind velocity for the entire Atmospheric Boundary Layer (ABL) and beyond. In addition, RWP with Radio-Acoustic Sounding System (RASS) are able to retrieve virtual temperature profiles in the ABL.
RWP data evaluation is usually based on the so-called Doppler Beam Swinging method (DBS) which assumes homogeneity and stationarity of the wind field. Often, transient eddies violate this homogeneity and stationarity requirement. Hence, incorrect wind profiles can relate to transient eddies and present a problem for the forecast of high-impact weather phenomena in airports. This work intends to provide a method for removing outliers in such profiles based on historical data and other variables related to the Atmospheric Boundary Layer stability profile in the study region.
For this study, a dataset of almost one year retrieved from a RWP LAP3000 with RASS Extension is used for a wind profile correction algorithm development.
The algorithm consists of the detection of outliers in the wind profiles based on the thermodynamic structure of the ABL and the generation of the corrected profiles.
Results show that the algorithm is capable of identifying and correcting unrealistic variations in speed caused by transient eddies. The method can be applied as a complement to the RWP data processing for better data reliability.
Keywords: atmospheric boundary layer; stability profile; wind profile
How to cite: Albuquerque Neto, F., Almeida, V., and Carelli, J.: Wind profile correction algorithm based on Atmospheric Boundary Layer stability profile, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-341, https://doi.org/10.5194/ems2021-341, 2021.
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