Most Arctic clouds occur below 2 km altitude, as revealed by CloudSat satellite observations. However, recent studies suggest that the relatively coarse spatial resolution, low sensitivity, and blind zone of the radar installed on CloudSat may not enable it to comprehensively document low-level clouds. We investigate the impact of these limitations on the Arctic low-level cloud fraction, which is the number of cloudy points with respect to all points as a function of height, derived from CloudSat radar observations. For this purpose, we leverage highly resolved vertical profiles of low-level cloud fraction derived from down-looking Microwave Radar/radiometer for Arctic Clouds (MiRAC) radar reflectivity measurements. MiRAC was operated during four aircraft campaigns that took place in the vicinity of Svalbard during different times of the year, covering more than 25 000 km. This allows us to study the dependence of CloudSat limitations on different synoptic and surface conditions. A forward simulator converts MiRAC measurements to synthetic CloudSat radar reflectivities. These forward simulations are compared with the original CloudSat observations for four satellite underflights to prove the suitability of our forward-simulation approach. Above CloudSat's blind zone of 1 km and below 2.5 km, the forward simulations reveal that CloudSat would overestimate the MiRAC cloud fraction over all campaigns by about 6 percentage points (pp) due to its horizontal resolution and by 12 pp due to its range resolution and underestimate it by 10 pp due to its sensitivity. Especially during cold-air outbreaks over open water, high-reflectivity clouds appear below 1.5 km, which are stretched by CloudSat's pulse length causing the forward-simulated cloud fraction to be 16 pp higher than that observed by MiRAC. The pulse length merges multilayer clouds, whereas thin low-reflectivity clouds remain undetected. Consequently, 48 % of clouds observed by MiRAC belong to multilayer clouds, which reduces by a factor of 4 for the forward-simulated CloudSat counterpart. Despite the overestimation between 1 and 2.5 km, the overall low-level cloud fraction is strongly reduced due to CloudSat's blind zone that misses a cloud fraction of 32 % and half of the total (mainly light) precipitation amount.

The growth of ice crystals in presence of supercooled liquid droplets represents the most important process for precipitation formation in the mid-latitudes. However, such mixed-phase interaction processes remain relatively unknown, as capturing the complexity in cloud dynamics and microphysical variabilities turns to be a real observational challenge. Ground-based radar systems equipped with fully polarimetric and Doppler capabilities in high temporal and spatial resolutions such as the S-band transportable atmospheric radar (TARA) are best suited to observe mixed-phase growth processes. In this paper, measurements are taken with the TARA radar during the ACCEPT campaign (analysis of the composition of clouds with extended polarization techniques). Besides the common radar observables, the 3-D wind field is also retrieved due to TARA unique three beam configuration. The novelty of this paper is to combine all these observations with a particle evolution detection algorithm based on a new fall streak retrieval technique in order to study ice particle growth within complex precipitating mixed-phased cloud systems. In the presented cases, three different growth processes of ice crystals, plate-like crystals, and needles are detected and related to the presence of supercooled liquid water. Moreover, TARA observed signatures are assessed with co-located measurements obtained from a cloud radar and radiosondes. This paper shows that it is possible to observe ice particle growth processes within complex systems taking advantage of adequate technology and state of the art retrieval algorithms. A significant improvement is made towards a conclusive interpretation of ice particle growth processes and their contribution to rain production using fall streak rearranged radar data.

The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite developed by the European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) launched in May 2024 carries a novel 94 GHz cloud profiling radar (CPR) with Doppler capability. This work describes the open-source instrument simulator Orbital-Radar, which transforms high-resolution radar data from field observations or forward simulations of numerical models to CPR primary measurements and uncertainties. The transformation accounts for sampling geometry and surface effects. We demonstrate Orbital-Radar's ability to provide realistic CPR views of typical cloud and precipitation scenes. The presented case studies show small-scale convection, marine stratus clouds, and Arctic mixed-phase cloud cases. These results provide valuable insights into the capabilities and challenges of the EarthCARE CPR mission and its advantages over the CloudSat CPR. Finally, Orbital-Radar allows for evaluating kilometre-scale numerical weather prediction models with EarthCARE CPR observations. So, Orbital-Radar can generate calibration and validation (Cal/Val) data sets already pre-launch. Nevertheless, an evaluation of synthetic CPR output data to accurate EarthCARE CPR data is missing.

Multiwavelength radar observations have demonstrated great potential in improving microphysical retrievals of cloud properties especially in ice and snow precipitation systems. Advancements in spaceborne radar technology have already fostered the launch in 2014 of the first multiwavelength radar system in space, while several future spaceborne multiwavelength radar concepts are under consideration. However, due to antenna size limitations, the sampling volume of spaceborne radars is considerably larger than those achieved by surface- and airborne-based radars. Here, the impact of these large sampling volumes in the information content of the Dual-Wavelength Ratio estimates at Ka-W, Ku-Ka is investigated. High-resolution airborne multiwavelength radar observations during the Olympic Mountain Experiment (OLYMPEx) are used to perform retrievals of ice/snow characteristic particle size, such as mass-weighted particle diameter. To mimic the different satellite sampling volumes, a moving average is applied to the airborne measurements. The radar-observed variables (reflectivity and dual-wavelength ratios) and retrieved microphysical properties at the coarser resolution are compared against those at the original resolution. Our analysis indicates that future Ka-W spaceborne radar missions should take into account the impact of the radar resolution volume on the retrieval of microphysical properties and avoid footprints larger than 2–3 km.

In the framework of the Joint Aeolus Tropical Atlantic Campaign (JATAC), the ASKOS experiment was implemented in Cabo Verde during summer and autumn of 2021 and 2022. The main objective of ASKOS was the collection of an unprecedented dataset of synergistic measurements in the region, to be used to address a wide range of scientific objectives, namely the support of the validation of Aeolus mission’s products, the study of the processes affecting dessert dust transport (water vapor, giant particles, mixing with boundary layer dynamics), the characterization of the cloud microphysics, the effect of dust particles in the cloud formation over the region, the effect of the large dust particles on radiation and others.During the ASKOS experiment, intense ground-based remote sensing and airborne in situ measurements took place on and above Mindelo on the island of São Vicente, Cabo Verde. At the Ocean Science Center in Mindelo (OSCM), a full ACTRIS remote sensing super site was set up in 2021, including a multiwavelength-Raman-polarization lidar PollyXT, an AERONET sun photometer, a Scanning Doppler wind lidar, a microwave radiometer and a cloud radar belonging to ESA fiducial reference network (FRM4Radar). Additionally, the ESA’s reference lidar system eVe, a combined linear/circular polarization lidar with Raman capabilities, was deployed. In 2022, the operations were enhanced with the deployment of airborne in-situ aerosol measurements on-board UAVs deployed by the Cyprus Institute, solar radiation measurements supported by PMOD/WRC, dust particle orientation measurements from the WALL-E lidar of National Observatory of Athens, and radiosonde releases equipped with additional electric field and electric charge measurements. The campaign was supported by dedicated numerical weather and dust simulations from CAMS and ECMWF, and tailored WRF simulations with nested domains above the campaign site. From the ASKOS dataset, three cases have been selected as "golden cases” where multiple JATAC airborne platforms and Aeolus satellite performed collocated measurements alongside with the ground-based instrumentation around the ASKOS operations site. Furthermore, multiple synergistic measurements with the JATAC airborne platforms were performed in the broader Cabo Verde region. Here, we quickly introduce ASKOS measurements and present first results.

The growth of ice crystals in presence of super-cooled liquid droplets represents the most important process for precipitation formation in the mid-latitudes. Such mixed-phase interaction processes remain however pretty much unknown, as capturing the complexity in cloud dynamics and microphysical variabilities turns to be a real observational challenge. Ground-based radar systems equipped with fully polarimetric and Doppler capabilities in high temporal and spatial resolutions 5 such as the S-band Transportable Atmospheric Radar (TARA) are best suited to observe mixed-phase growth processes. In this paper, measurements are taken with the TARA radar during the ACCEPT campaign (Analysis of the Composition of Clouds with Extended Polarization Techniques). Besides the common radar observables, the 3D wind field is also retrieved due to TARA unique three beam configuration. The novelty of this paper is to combine all these observations with a particle evolution detection algorithm based on a new fall streak retrieval technique in order to study ice particle growth within complex 10 precipitating mixed-phased cloud systems. In the presented cases, three different growth processes of ice crystals, plate-like crystals, and needles, are detected and related to the presence of supercooled liquid water. Moreover, TARA observed signatures are assessed with co-located measurements obtained from a cloud radar and radiosondes. This paper shows that it is possible to observe ice particle growth processes within complex systems taking advantage of adequate technology and state of the art retrieval algorithms. A significant improvement is made towards a conclusive interpretation of ice particle growth processes 15 and their contribution to rain production using fall streak rearranged radar data.