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The Arctic region is showing the most intense warming of the globe, because of different regional feedback mechanisms. Both observed and projected warming rates reach a maximum in the autumn and winter seasons (Bintanja and Krikken, 2016), when the Arctic surface energy budget is dominated by longwave radiation. Indeed, due to the seasonal variation of the of shortwave radiation, the longwave radiation plays a key role in the Arctic, where the annual total Downward Longwave Irradiance (DLI) is usually more than twice as large as the annual downward shortwave irradiance. Nevertheless, surface longwave irradiance measurements in the Arctic are particularly scarce, and satellite retrievals of surface radiation budget based on satellite data are notoriously problematic at high latitudes.High resolution observations of DLI, surface temperature, water vapour surface partial pressure and column amount, zenith sky IR radiance and vertical temperature profile derived by a microwave radiometer are routinely carried out at the Thule High Arctic Atmospheric Observatory (THAAO, 76.5 N, 68.8 W), in North Eastern Greenland (https://ofcsg2dvf1.dwd.de/fmlurlsvc/?fewReq=:B:JVs5MjYzOSV1PjEtMyVqZz4zMjkzMiVwamRtYnd2cWY+MTVnMjJiYmU6ZztgZ2dlYDBiNWVnO2U1NjtiNmE6OjtgNTcwNGBnMSV3PjI1NjEzOjI2NTslcmpnPjE3OkJJUDtOMzI1NDM3LjE3OkJJUDtNMzI1NDM3JXFgc3c+UHdmZWJtLVRiYGhmcUNndGctZ2YlYD43OiVrZ28+Mw==&url=https%3a%2f%2fwww.thuleatmos-it.it%2f ). In the frame of the CLouds And Radiation in the Arctic and Antarctica (CLARA2) project, a celiometer has been installed in November 2019 with the aim of strengthening the cloud observational capability at the Observatory already including, among the other instruments, upward- and downward-looking pyranometers and pyrgeometers operating at THAAO since July 2016.Preliminary statistical results for cloud base altitude, cloud depth, liquid water path (LWP), temperature profiles and presence/intensity of temperature inversion at THAAO will be shown. Analysis on the relationship between LWP and IR downward irradiance and radiance in cloudy and clear sky is also presented.ReferencesBintanja, R., Krikken, F. Magnitude and pattern of Arctic warming governed by the seasonality of radiative forcing. Sci Rep 6, 38287 (2016). https://ofcsg2dvf1.dwd.de/fmlurlsvc/?fewReq=:B:JVs5MjYzOSV1PjEtMyVqZz4zMjkzMiVwamRtYnd2cWY+MjRnOzY0ZjQ3Ojc1ZTAwNDM2NWAxYjE1NTVmNzo3N2YwYDAyNDRnMyV3PjI1NjEzOjI2NTslcmpnPjE3OkJJUDtOMzI1NDM3LjE3OkJJUDtNMzI1NDM3JXFgc3c+UHdmZWJtLVRiYGhmcUNndGctZ2YlYD42MSVrZ28+Mw==&url=https%3a%2f%2fdoi.org%2f10.1038%2fsrep38287

Atmospheric stability is a measure of atmospheric status which determines whether thermodynamically perturbed air will rise, sink, or be neutral. Atmospheric stability has a major impact on the evolution of wind turbine wakes and thus on the yield and performance of offshore wind parks. For estimations of wind park power output and for improving analyses of offshore wind park wakes, a crucial parameter was found to be profiles of atmospheric temperature and stability metrics. Atmospheric temperature profiles can be measured in-situ by balloon-borne sensors, but also estimated from the ground using remote sensing observations.Ground-based microwave radiometer (MWR) units operating in the 22-30 GHz and 50-60 GHz bands are commonly used to estimate atmospheric temperature and humidity profiles. A handful of MWR profiling types are nowadays available as off-the-shelf commercial products, and a MWR network is currently being established in the framework of EUMETNET E-PROFILE programme (Rüfenacht et al., 2021). This presentation reviews the stability metrics useful for monitoring wind park performances and provides a quantitative assessment of the value of MWR observations to estimate these stability metrics from near surface, either over land or ocean. Results from three different MWR instruments, representing the most common available on the market, will be presented, as obtained during at least three field experiments, both onshore and offshore.This contribution presents the main outcomes of the Radiometry and Atmospheric Profiling (RAP) scoping study, carried in the framework of the COST Action PROBE (https://www.probe-cost.eu/) and funded by Carbon Trust and the partner companies of the Off-shore Wind Accelerator (OWA) program: (in alphabetical order) EnBW, Equinor, Orsted, RWE, Scottish Power Renewables, Shell, SSE Renewables, Total Energies, Vattenfall.

EUMETNET's E-PROFILE programme aims to gather, centrally process and deliver profiles of wind, temperature, humidity and aerosols including volcanic ash in near real-time. It consists of a data hub to collect process and distribute data while the instruments are owned and operated by EUMETNET members as well as partners from academia and industry. As of today, E-PROFILE integrates operationally 30 radar wind profilers and more than 400 automatic lidars and ceilometers (ALC) producing profiles of wind speed and direction and attenuated backscatter coefficient, respectively. Most radar wind profilers are assimilated into ECMWF's Integrated Forecasting System (IFS) and an extensive analysis of Forecast Sensitivity to Observation (FSO) data from ECMWF confirms the positive impact of those data on the forecast quality. ALC data are calibrated centrally by E-PROFILE using natural atmospheric targets and provide a basic yet quantitative information of aerosols including volcanic ash and durst, which are considered airborne hazards for aviation. With more than 400 operational sites, E-PROFILE's ALC network is a valuable complement to satellite observations and surface based research lidar networks. In the current programme phase (2019 - 2023) we are working on an advanced processing chain to retrieve aerosol extinction coefficients and aerosol mass concentration from ALCs to better meet the user requirements. Finally, E-PROFILE has been tasked to integrate microwave radiometers and Doppler lidars and to collect, process and distribute temperature, humidity and wind measurements from these instruments. This new component of the E-PROFILE programme aims at filling the observational gap in the atmospheric boundary layer. We present briefly the operational components of E-PROFILE, give a detailed update on the ongoing developments and highlight how E-PROFILE serves NWP and informs about airborne hazards.

Meteorological and air quality surface sensor networks sample atmospheric variables close to the ground while satellite observations provide global spatial coverage of the upper atmosphere. There is however, an observation gap on the temporal variability and vertical structure of atmospheric parameters in the atmospheric boundary layer (ABL). The ABL is the lowest 2 – 3 km of atmosphere above ground where the vertical structure is driven by surface-atmosphere exchanges, ABL-to-free-troposphere exchanges, in addition to larger-scale processes. Most human activities take place in the ABL, it is hence very important to improve our ability to characterize those processes that affect weather conditions, air quality, transport and energy provision systems, and longer-term issues such as climate change adaptation and mitigation, of particular importance in urban settings.Motivated by the overarching objective to support the efficient exploitation of ABL data and to maximize their societal impact, the PROBE COST action is creating a cooperation hub where a wide range of stakeholders from Academia, Research structures, Industry, Operational agencies, and general end-users can share advances and expertise on ABL profiling.In the first two years of the action, the PROBE partners were able to attract a diverse community of more than 200 users that share information through webinars (on instruments, networks, and high-quality observations) and working group meetings (on ABL profiling in complex terrain and urban environments), and engage the community in a wide range of activities through efficient multi-media communication (http://www.probe-cost.eu/, newsletters, videos, social channels). No less than 5 working groups on thermodynamics, clouds, ABL height, wind and turbulence, and aerosol profiling reported on key ABL parameters, their applications and end-user requirements. A comprehensive document is being compiled that gives insights on “overview, access and benefits” of existing ABL profiling networks (e.g. E-PROFILE, ACTRIS, ICOS, …). Also less known (“hidden”) networks were identified. 5 specific instrument task groups (on microwave radiometers, cloud radars, doppler lidars, automatic lidars and ceilometers, and drones) are developing recommendations for configuration, operation, calibration, and quality control procedures.Over the remaining period of the PROBE COST action (until fall 2023), the partners will continue to develop a solid literature (technical reports and scientific publications) on the topic of ABL profiling, improving content through short term scientific visits (either in person or virtual) and focused working groups (mostly virtual). Some partners will participate in a large international effort to better characterize the ABL in urban environments through an intensive measurement campaign to be held in the Paris region (France) in summer 2022 while others are involved in the TEAMx collaboration initiative observing the mountain boundary layer. Finally, the PROBE community is launching an inter-journal special issue, offering an opportunity for the advances in ABL profile observations and applications to gain visibility. For example, a very detailed review paper on ABL height retrievals from ground-based remote sensing was just submitted, resulting from several years of intense review work.The presentation will provide an overview of recent achievements and upcoming activities.

Atmospheric stability is a measure of atmospheric status which determines whether thermodynamically perturbed air will rise, sink, or be neutral. Atmospheric stability has a major impact on the evolution of wind turbine wakes and thus on the yield and performance of offshore wind parks. For estimations of wind park power output and for improving analyses of offshore wind park wakes, a crucial parameter was found to be profiles of atmospheric temperature and stability metrics. Atmospheric temperature profiles can be measured in-situ by balloon-borne sensors, but also estimated from the ground using radiometric observations. This presentation reviews the stability metrics useful for monitoring wind park performances and provides a quantitative assessment of the value of microwave radiometer (MWR) observations to estimate these stability metrics from near surface, either over land or ocean. Results from three different MWR instruments, representing the most common available on the market, and at least three field experiments will be presented. This work has been funded by Carbon Trust and the partner companies of the Off-shore Wind Accelerator program: (in alphabetical order) EnBW, Equinor, Orsted, RWE, Scottish Power Renewables, Shell, SSE Renewables, Total Energies, Vattenfall.

The rapid technological development of the past few decades has allowed for an unprecedented wealth of data about ourselves and our planet. The cost reduction of space platforms, the microelectronic revolution and the nearly exponential increase in computer power have been generating novel opportunities to explore and understand the world around us. Tools and theoretical approaches, capable of putting together all the insights we may possibly gain from all these new streams of data in a multidisciplinary framework, are still being developed. We are hence faced with both a unique challenge and an opportunity to make a significant progress in many scientific fields, first and foremost in the atmospheric and climate sciences. We are pleased to announce here the launch of the Bulletin of Atmospheric Science and Technology (BAST), a new peer-reviewed journal which is meant to bridge this gap in the broad area of the atmospheric sciences. The journal encourages a cross-disciplinary approach with an emphasis on new sensor technologies and systems, combined observational and modeling techniques, innovative numerical methods, data analysis, and retrieval techniques. BAST offers a platform to share new ideas and fresh developments to stimulate research activities focusing on urban, coastal, marine, rural, and mountain environments. Particular attention will be given to cross-disciplinary studies, especially those involving citizens for the collection of crowd-sourced data and those devoted to the characterization of uncertainties and homogenization of methods.

The atmospheric boundary layer (ABL) is the layer closest to the Earth’s surface within which most human activities take place. The vertical profile of atmospheric thermodynamic parameters in the ABL impact weather, air quality and climate. However, surface sensor networks and satellite observations do not provide sufficient information on the high temporal variability and strong vertical gradients that occur in the ABL. Thus, the ABL represents an important but rather under-sampled part of the atmosphere. This observational gap currently hampers progress in numerical weather prediction, air quality forecasting and climate assessment. Due to recent technological and methodological advances, ground-based remote sensing instruments are now able to provide high-quality profiles of ABL parameters such as temperature, humidity, wind, aerosol and cloud properties. However, even though state-of-the-art ABL profilers are deployed at numerous sites in Europe, efficient science and technology networking and coordination is still required to exploit this rich dataset effectively. The current lack of data and procedure harmonization often diminishes the potential societal benefits of the existing ABL profiling data. This paper introduces PROBE, a new initiative funded by the European Cooperation in Science and Technology (COST), that aims to broaden the bridge between a wide range of user needs and the science and technology expertise residing in industry and academia, while strengthening and harmonizing methods and procedures to yield higher quality ABL observational data. Here, the challenges, objectives and implementation plan for PROBE are described, highlighting some preliminary results that will be further developed into operational applications during the 4-year duration (2019–2023) of this collaborative project.

Observations of profiles of winds, aerosol, clouds, winds, temperature and humidity in the lowest few km of the atmosphere from networks of ceilometers, Doppler wind lidars and microwave radiometers are starting to flow in real time to forecasting centers in Europe.\ud \ud To realise the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few km are hardly accessible by satellite, especially in dynamically-active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real-time to forecast centers. The three classes of instruments are: (i) Automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog and volcanic ash, the last two being especially important for air traffic control; (ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind-gusts and low-level jets; and (iii) Microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. Twenty-two European countries and fifteen European National Weather Services are collaborating in the project, that involves the implementation of common operating procedures, instrument calibrations, data formats and retrieval algorithms. Currently, data from 220 ceilometers in 17 countries are being distributed in near real-time to national weather forecast centers; this should soon rise to many hundreds. The wind lidars should start delivering real time data in late 2018, and the plan is to incorporate the microwave radiometers in 2019. Initial data assimilation tests indicate a positive impact of the new data.

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.

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

Cloud microphysics in terms of their liquid/ice water content and particle size are the principal factors addressed to study and understand the behavior behind the climate change phenomenon. Based on remotely sensed measurements, in the last decades, some evidence exists that an increase in temperature leads to an increase in cloud liquid water content (CLWC). The temperature dependence of ice water content (CIWC) is also evident from measurements of midlatitude cirrus clouds. Hence, innovative methods, such as those based on the use of Artificial Intelligence (AI) allowing a more relevant investigation of how clouds influence the hydrological cycle and radiative components of the Earth's climate system, are required. This work investigates the capability of a statistical regression scheme of CLWC and CIWC, implemented through the use of a multilayer feed-forward neural network (NN). The whole methodology is applied to a set of simulated IASI-NG L1C and MWS acquisitions, covering the global scale. The NN regression analysis shows good agreement with the test data. The retrieved cloud liquid water and ice profiles have an accuracy of 20 to 60% depending on the given layer. Finally, the layer with the maximum concentration is accurately identified.

The water vapor line at 183 GHz was studied over the temperature range of 219–358 K using a spectrometer with radioacoustic detection of absorption, providing a signal-to-noise ratio of up to 8000. The study includes the first measurement of speed-dependent collisional broadening and shifting of this line for both self- and air-broadening, and their temperature dependences. The sign of self-shifting changes at about 280 K. Line-shape parameters are obtained for Voigt and quadratic speed-dependent Voigt shape factors. Temperature dependences of the line parameters are analyzed using empirical models from the literature. Theoretical Modified Complex Robert–Bonamy calculations of the line shape parameters, their temperature and speed-dependence are made over the temperature range of 200–3000 K. The measurements and calculations show very good agreement, although with some discrepancies for line shift parameters. The impact of the newly-measured line parameters on atmospheric water-vapor estimation from ground-based and satellite instruments is evaluated by simulation of downwelling and upwelling brightness temperatures and retrieved water-vapor mixing ratio, for atmospheric conditions typical of six climate zones. For the case of ground-based or limb-scanning radiometry with a background of cold space, the impact of speed-dependence is comparable to or exceeds that of measurement error and will introduce systematic errors if neglected. Therefore, consideration of speed-dependence is necessary for accurate estimation of water vapor with this line. The impact on upwelling brightness temperature is smaller.

Sun-tracking microwave (ST-MW) radiometry is a ground-based technique where the Sun is used as a beacon source to infer the atmospheric path attenuation in all-weather conditions. ST-MW radiometry shows an appealing potential for overcoming the difficulties to perform satellite-to-Earth radiopropagation experiments in the unexplored millimeter-wave and submillimeter-wave frequency region, especially where experimental data from beacon receivers are not available. The theoretical framework, the ad hoc procedures and data processing will be presented, together with the estimate of the overall error budget. The applications and challenges during field deployments, such as the recent WRad campaign in Italy based on ST-MW data analysis, funded by ESA and carried out together with AFRL (NY, USA), will be discussed.

Ground-based microwave radiometer (MWR) observations of downwelling brightness temperature (TB) are commonly used to estimate the atmospheric attenuation at relative transparent channels for radiopropagation and telecommunication purposes. The atmospheric attenuation is derived from TB by inverting the radiative transfer equation with a priori knowledge of the mean radiating temperature (TMR). TMR is usually estimated by either time-variant site climatology (e.g., monthly average computed from atmospheric thermodynamical profiles) or condition-variant estimation from surface meteorological sensors. However, information on TMR may also be extracted directly from MWR measurements at other channels than those used to estimate atmospheric attenuation. This paper proposes a novel approach to estimate TMR in clear and cloudy sky from independent MWR profiler measurements. A linear regression algorithm is trained with a simulated dataset obtained by processing one year of radiosonde observations of atmospheric thermodynamic profiles. The algorithm is trained to estimate TMR at K-, and V/W-band frequencies (22–31 and 72–82 GHz, respectively) from independent MWR observations at V-band (54–58 GHz). The retrieval coefficients are then applied to a one-year dataset of real V-band observations, and the estimated TMR at K- and V/W-band are compared with estimates from nearly collocated and simultaneous radiosondes. The proposed method provides TMR estimates in better agreement with radiosondes than a traditional method, with 32–38 % improvement depending on frequency. This maps into an expected improvement in atmospheric attenuation of 10–20 % for K-band and ~ 30 % for V/W-band channels.

This paper investigates the potential benefit of ground-based microwave radiometers (MWRs) to improve the initial state (analysis) of current numerical weather prediction (NWP) systems during fog conditions. To this end, temperature, humidity and liquid water path (LWP) retrievals have been performed by directly assimilating brightness temperatures using a one-dimensional variational technique (1D-Var). This study focuses on a fog-dedicated field-experiment performed over winter 2016–2017 in France. In situ measurements from a 120 m tower and radiosoundings are used to assess the improvement brought by the 1D-Var analysis to the background. A sensitivity study demonstrates the importance of the cross-correlations between temperature and specific humidity in the background-error-covariance matrix as well as the bias correction applied on MWR raw measurements. With the optimal 1D-Var configuration, root-mean-square errors smaller than 1.5 K (respectively 0.8 K) for temperature and 1 g kg−1 (respectively 0.5 g kg−1) for humidity are obtained up to 6 km altitude (respectively within the fog layer up to 250 m). A thin radiative fog case study has shown that the assimilation of MWR observations was able to correct large temperature errors of the AROME (Application of Research to Operations at MEsoscale) model as well as vertical and temporal errors observed in the fog life cycle. A statistical evaluation through the whole period has demonstrated that the largest impact when assimilating MWR observations is obtained on the temperature and LWP fields, while it is neutral to slightly positive for the specific humidity. Most of the temperature improvement is observed during false alarms when the AROME forecasts tend to significantly overestimate the temperature cooling. During missed fog profiles, 1D-Var analyses were found to increase the atmospheric stability within the first 100 m above the surface compared to the initial background profile. Concerning the LWP, the RMSE with respect to MWR statistical regressions is decreased from 101 g m−2 in the background to 27 g m−2 in the 1D-Var analysis. These encouraging results led to the deployment of eight MWRs during the international SOFOG3D (SOuth FOGs 3D experiment for fog processes study) experiment conducted by Météo-France.

Reliable values of relative humidity are basic inputs for modelling in many disciplines and in the most disparate scientific fields. Unfortunately, humidity variables remain less focused than other meteorological parameters and generally suffer from considerable uncertainty mainly due to the fact that their observations are not widely available, fostering the use of the observations of other meteorological quantities to estimate them. The aim of this work is to assess the loss in daily maximum and minimum relative humidity accuracy when sampling interval becomes coarser than one hour. For this purpose, meteorological data from the ERA5 dataset, the most advanced reanalysis product released by the European Centre for Medium-Range Weather Forecasts (ECMWF), are used. Among the many advantages of ERA5 over the previous release ERA-Interim are the finer temporal resolution and data archived at the hourly time step. Near-surface relative humidity is derived using 1- and 3-hourly reanalysis data of 2-m temperature, 2-m dew-point temperature and surface pressure. Deviations from the actual values, as obtained from reference measures acquired at 15 minute intervals, are evaluated. Results show that the biases of the ERA5-based values are consistently reduced compared to its predecessor and that the performance of the calculated 1-hourly time resolution relative humidity data is almost equivalent to using observations. Reducing the sampling interval from three to one hour provides a significant improvement in data quality. The results indicate significant increases in errors in the estimates when the temporal resolution of the meteorological inputs becomes coarser than one hour, exceeding also the numerical and approximation errors due to simplifying assumptions in the theoretical and empirical formulas used. The positive impact of improving temporal resolution from ERA-Interim to ERA5 reanalysis is also quantified by the number of the correct relative humidity extremes increasing by 50%.

Ground-based microwave radiometers (MWRs) offer the capability to provide continuous, high-temporal-resolution observations of the atmospheric thermodynamic state in the planetary boundary layer (PBL) with low maintenance. This makes MWR an ideal instrument to supplement radiosonde and satellite observations when initializing numerical weather prediction (NWP) models through data assimilation. State-of-the-art data assimilation systems (e.g. variational schemes) require an accurate representation of the differences between model (background) and observations, which are then weighted by their respective errors to provide the best analysis of the true atmospheric state. In this perspective, one source of information is contained in the statistics of the differences between observations and their background counterparts (O–B). Monitoring of O–B statistics is crucial to detect and remove systematic errors coming from the measurements, the observation operator, and/or the NWP model. This work illustrates a 1-year O–B analysis for MWR observations in clear-sky conditions for an European-wide network of six MWRs. Observations include MWR brightness temperatures (TB) measured by the two most common types of MWR instruments. Background profiles are extracted from the French convective-scale model AROME-France before being converted into TB. The observation operator used to map atmospheric profiles into TB is the fast radiative transfer model RTTOV-gb. It is shown that O–B monitoring can effectively detect instrument malfunctions. O–B statistics (bias, standard deviation, and root mean square) for water vapour channels (22.24–30.0 GHz) are quite consistent for all the instrumental sites, decreasing from the 22.24 GHz line centre ( ∼ 2–2.5 K) towards the high-frequency wing ( ∼ 0.8–1.3 K). Statistics for zenith and lower-elevation observations show a similar trend, though values increase with increasing air mass. O–B statistics for temperature channels show different behaviour for relatively transparent (51–53 GHz) and opaque channels (54–58 GHz). Opaque channels show lower uncertainties (

Radio links at around 26 GHz for space communications between Earth observation satellites and ground stations at Polar latitudes are being considered in recent year to increase the downlink performance. However, the precise link budget modelling and the experimental validation of such links is still open, partially due to large propagation losses at these frequencies and partially because of the effect of the harsh Polar environment (e.g., snow) on the antenna structure (e.g., the antenna radome). This paper presents the link budget model implemented in the framework of a dedicated project (SNOWBEAR) under European Space Agency coordination and examples of validation of such a model against experimental data, including cases either in clear sky condition or during a snowstorm. In addition, possible upgrades for the model, based on the use of the ERA5 database, are outlined.

A new multi-sensor approach, named PoLCast (Probability of Lightning foreCast), for predicting the lightning activity in a complex orography geographical area is proposed and discussed. The PoLCast input information are the ground-based weather radar horizontally polarized reflectivity factor and the atmospheric instability indexes, derived from the Spin Enhanced Visible Infrared Imager (SEVIRI) radiometer onboard the Meteosat Second Generation (MSG) satellite. The weather radar data are used to calculate the probability of lightning following a direct relation between the maximum values of the reflectivity factor and the lightning occurrence, whereas the atmospheric instability indexes from SEVIRI are used to constrain the probability of lighting, derived from weather radar data, and enhance such probability in cases of more unstable troposphere. To test the PoLCast methodology, the output of the Blitzortung and the “Sistema Italiano Rilevamento Fulmini” (SIRF) ground-based lightning sensor networks are used together with the C-band Mt. Midia weather radar within its 180 km diameter coverage over the Central Italy area. Both satellite and radar data are pre-processed into PoLCast to obtain a single time series in terms of the areal probability of lightning (PoL). PoLCast performances are evaluated in terms of statistical scores using 12 heterogeneous case studies over Central Italy. Even though the number of available cases is relatively limited, quantitative results show high areal PoL (from 0 to 100%) with a case-by-case variability of false alarm rate from 3 to 72%. The advantage of a multi-sensor technique, such as PoLCast, with respect to an approach using weather radar data only, becomes more evident when lightning activity is not present and the leading time of lightning forecast exceeds 2.5 h.

The Calderone glacier is at present the most southern glacier in Europe (42° 28' 15’’ N). The little apparatus (about 20.000 m2 in surface area) has been giving an interesting response both to short- and long-term climatic variations which resulted in a considerable reduction in surface area and volume. The glacial apparatus is split into two ice bodies (glacierets) since 2000. The two glacierets are located in a deep northward valley below the top of the Corno Grande (2912 m asl) in the centre of the Gran Sasso d’Italia mountain range (Central Italy). Such glacial apparatus has been subjected to a strong reduction, with a loss of total surface area of about 50% and thickness of about 65%with respect to the hypothetical size (about 105.00 m2 and 55 m at the Little Ice Age).Since early 90s the Calderone glacier has been subjected to several multidisciplinary field campaigns to monitor and evaluate its role as an environmental indicator in the framework of global warming. Starting from historical series related to more than a century of records, the variability of the different glacier properties has been estimated by using classical geomorphologic methods as well as in situ and remote sensing techniques. In particular, the last field campaigns, in 2015, 2016 and 2019, have been carried out using Ground Penetrating Radar equipped with different antenna frequencies, drone-based survey, snow pit measurements and chemical-physical sampling. The measurement campaigns have been complemented by a regional climate analysis, spanning the last fifty years, and snowpack modelling initialized with microphysical snow data (e.g., snow density, crystal shape and size, hardness). The snowpack chemical analyses include the main and trace elements, soluble inorganic and organic ions, EC/OC and PAH, with different spatial resolution depending on the analytes. We present here the methodological approach used and some preliminary results.

5 pags., 1 fig., descripción no proporcionada por scopus, The workshop was hosted by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), Darmstadt, Germany. Maria Cadeddu is supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Atmospheric Radiation Measurement Infrastructure Basic Energy Sciences, under contract DE-AC02-06CH11357. Patrick Ericksson is was supported by the Swedish National Space Agency. Ralf Bennartz was supported by NASA USPI Grant NNX17AJ09G.

The Sentinel-2 mission allows the remote sensing of coastal waters environments with detailed imagery down to 10-m resolutions. In this study we explore different approaches in the retrieval of chlorophyll-a (Chl-a) and total suspended matter (TSM) concentrations along the Adriatic and Tyrrhenian coasts in Italy, using empirical and model-based data to develop regressive and neural networks (NN) algorithms. The best performances, for both Chl-a and TSM, are obtained with NN algorithms, better suited in handling the high variance shown by in-situ target data, with a 0.33 mg m−3 root-mean-square-error (RMSE) for Chl-a and $\mathrm{RMSE} =1.95\mathrm{g}/\mathrm{m}^{3}$ for TSM. The forward bio-optical model used for the generation of synthetic training data shows inadequacies in modelling the different spectral features characterizing the oligotrophic Tyrrhenian Sea and the eutrophic Adriatic Sea. The suitability of Sentinel-2 MSI products is here confirmed, but further investigation is needed on some critical issues affecting remote sensing of coastal waters, such as the atmospheric correction problem, the analysis of bathymetric effects and the need of a large and reliable in-situ dataset.

This paper describes the first official release (v1.0) of RTTOV-gb. RTTOV-gb is a FORTRAN 90 code developed by adapting the atmospheric radiative transfer code RTTOV, focused on satellite-observing geometry, to the ground-based observing geometry. RTTOV-gb is designed to simulate ground-based upward-looking microwave radiometer (MWR) observations of atmospheric downwelling natural radiation in the frequency range from 22 to 150 GHz. Given an atmospheric profile of temperature, water vapor, and, optionally, cloud liquid water content, and together with a viewing geometry, RTTOV-gb computes downwelling radiances and brightness temperatures leaving the bottom of the atmosphere in each of the channels of the sensor being simulated. In addition, it provides the sensitivity of observations to the atmospheric thermodynamical state, i.e., the Jacobians. Therefore, RTTOV-gb represents the forward model needed to assimilate ground-based MWR data into numerical weather prediction models, which is currently pursued internationally by several weather services. RTTOV-gb is fully described in a previous paper (De Angelis et al., 2016), while several updates are described here. In particular, two new MWR types and a new parameterization for the atmospheric absorption model have been introduced since the first paper. In addition, estimates of the uncertainty associated with the absorption model and with the fast parameterization are given here. Brightness temperatures (TB) computed with RTTOV-gb v1.0 from radiosonde profiles have been compared with ground-based MWR observations in six channels (23.8, 31.4, 72.5, 82.5, 90.0, and 150.0 GHz). The comparison shows statistics within the expected accuracy. RTTOV-gb is now available to licensed users free of charge from the Numerical Weather Prediction Satellite Application Facility (NWP SAF) website, after registration. Coefficients for four MWR instrument types and two absorption model parameterizations are also freely available from the RTTOV-gb support website.