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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. 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 the evaluation of kilometer-scale numerical weather prediction models with EarthCARE CPR observations. [ABSTRACT FROM AUTHOR]

Upcoming submillimeter wave satellite missions require an improved understanding of the sea ice emissivity to separate atmospheric and surface microwave signals under dry polar conditions. This work investigates hectometer-scale airborne sea ice emissivity observations between 89 and 340 GHz combined with high-resolution visual imagery from two Arctic airborne field campaigns in summer 2017 and spring 2019 northwest of Svalbard, Norway. We identify four distinct sea ice emissivity spectra through K-Means clustering, which occur predominantly over multiyear ice, first-year ice, young ice, and nilas. Nilas features the highest, and multiyear ice features the lowest emissivity among the clusters. Each cluster exhibits similar nadir emissivity distributions from 183 to 340 GHz. To relate hectometer-scale airborne to kilometer-scale satellite footprints, we quantify the reduction of airborne emissivity variability with increasing footprint size. At 340 GHz, the emissivity interquartile range decreases by almost half from the hectometer scale to a footprint of 16 km, typical for satellite instruments. Furthermore, we collocate the airborne observations with polar-orbiting satellite observations. After resampling, the absolute relative bias between airborne and satellite emissivities at similar channels lies below 3 %. Additionally, spectral nadir emissivity variations on the satellite scale are low, with slightly decreasing emissivity from 183 to 243 GHz, which occurs for all hectometer-scale clusters except for predominantly multiyear ice. Our results will enable the development of microwave retrievals and assimilation over sea ice from current and future satellite missions such as Ice Cloud Imager (ICI) and European Polar System (EPS) Sterna. [ABSTRACT FROM AUTHOR]

Riming is a key precipitation formation process in mixed-phase clouds which efficiently converts cloud liquid to ice water. Here, we present two methods to quantify riming of ice particles from airborne observations with the normalized rime mass, which is the ratio of rime mass to the mass of a size-equivalent spherical graupel particle. We use data obtained during the HALO-(AC) 3 aircraft campaign, where two aircraft collected radar and in situ measurements that were closely spatially and temporally collocated over the Fram Strait west of Svalbard in spring 2022. The first method is based on an inverse optimal estimation algorithm for the retrieval of the normalized rime mass from a closure between cloud radar and in situ measurements during these collocated flight segments (combined method). The second method relies on in situ observations only, relating the normalized rime mass to optical particle shape measurements (in situ method). We find good agreement between both methods during collocated flight segments with median normalized rime masses of 0.024 and 0.021 (mean values of 0.035 and 0.033) for the combined and in situ method, respectively. Assuming that particles with a normalized rime mass smaller than 0.01 are unrimed, we obtain average rimed fractions of 88 % and 87 % over all collocated flight segments. Although in situ measurement volumes are in the range of a few cubic centimeters and are therefore much smaller than the radar volume (about 45 m footprint diameter at an altitude of 500 m above ground, with a vertical resolution of 5 m), we assume they are representative of the radar volume. When this assumption is not met due to less homogeneous conditions, discrepancies between the two methods result. We show the performance of the methods in a case study of a collocated segment of cold-air outbreak conditions and compare normalized rime mass results with meteorological and cloud parameters. We find that higher normalized rime masses correlate with streaks of higher radar reflectivity. The methods presented improve our ability to quantify riming from aircraft observations. [ABSTRACT FROM AUTHOR]

Due to their potential to either warm or cool the surface, liquid-phase clouds and their interaction with the ice-free and sea-ice-covered ocean largely determine the energy budget and surface temperature in the Arctic. Here, we use airborne measurements of solar spectral cloud reflectivity obtained during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign in summer 2017 and the Arctic Amplification: FLUXes in the Cloudy Atmospheric Boundary Layer (AFLUX) campaign in spring 2019 in the vicinity of Svalbard to retrieve microphysical properties of liquid-phase clouds. The retrieval was tailored to provide consistent results over sea-ice and open-ocean surfaces. Clouds including ice crystals that significantly bias the retrieval results were filtered from the analysis. A comparison with in situ measurements shows good agreement with the retrieved effective radii and an overestimation of the liquid water path and reduced agreement for boundary-layer clouds with varying fractions of ice water content. Considering these limitations, retrieved microphysical properties of clouds observed over the ice-free ocean and sea ice in spring and early summer in the Arctic are compared. In early summer, the liquid-phase clouds have a larger median effective radius (9.5 µ m), optical thickness (11.8) and effective liquid water path (72.3 g m -2) compared to spring conditions (8.7 µ m, 8.3 and 51.8 g m -2 , respectively). The results show larger cloud droplets over the ice-free Arctic Ocean compared to sea ice in spring and early summer caused mainly by the temperature differences in the surfaces and related convection processes. Due to their larger droplet sizes, the liquid clouds over the ice-free ocean have slightly reduced optical thicknesses and lower liquid water contents compared to the sea-ice surface conditions. The comprehensive dataset on microphysical properties of Arctic liquid-phase clouds is publicly available and could, e.g., help to constrain models or be used to investigate effects of liquid-phase clouds on the radiation budget. [ABSTRACT FROM AUTHOR]

Riming is a key precipitation formation process in mixed-phase clouds by efficiently converting cloud liquid to ice water. Here, we present two methods to quantify riming of ice particles from airborne observations with the normalized rime mass, which is the ratio of rime mass to the mass of a size-equivalent spherical graupel particle. We use data obtained during the HALO-(AC)3 aircraft campaign, where two aircraft were collecting spatially and temporally closely collocated radar and in situ measurements over the Fram Strait west of Svalbard in spring 2022. The first method is based on an inverse Optimal Estimation algorithm to retrieve the normalized rime mass from a closure between cloud radar and in situ measurements during these collocated flight segments ('combined method'). The second method relies on in situ observations only, by relating the normalized rime mass to optical particle shape measurements ('in situ method'). We find good agreement between both methods during collocated flight segments with median normalized rime masses of 0.018 and 0.016 (mean values of 0.027 and 0.028) for combined and in situ method, respectively. Assuming particles with a normalized rime mass smaller 0.01 to be unrimed, we obtain average rimed fractions of 77 % and 75 %. Although in situ measurement volumes are in the range of a few cm3 and therefore much smaller than the radar volume (about 45 m footprint diameter), we assume they are representative of the radar volume. When this assumption is not met due to less homogeneous conditions, discrepancies between the two methods result. We compare normalized rime mass results with meteorological and cloud parameters and show the performance of the methods in two case studies, 1) a collocated segment in cold air outbreak conditions and 2) an in situ only flight close to a polar low. We find that higher normalized rime masses correlate with streaks of higher radar reflectivity. We also observe rimed particles in regions without liquid water, suggesting that particles were rimed in a liquid layer above and precipitated. The methods presented improve our ability to quantify riming from aircraft observations. [ABSTRACT FROM AUTHOR]

Riming is a key precipitation formation process in mixed-phase clouds by efficiently converting cloud liquid to ice water. Here, we present two methods to quantify riming of ice particles from airborne observations with the normalized rime mass, which is the ratio of rime mass to the mass of a size-equivalent spherical graupel particle. We use data obtained during the HALO-(AC) 3 aircraft campaign, where two aircraft were collecting spatially and temporally closely collocated radar and in situ measurements over the Fram Strait west of Svalbard in spring 2022. The first method is based on an inverse Optimal Estimation algorithm to retrieve the normalized rime mass from a closure between cloud radar and in situ measurements during these collocated flight segments ("combined method"). The second method relies on in situ observations only, by relating the normalized rime mass to optical particle shape measurements ("in situ method"). We find good agreement between both methods during collocated flight segments with median normalized rime masses of 0.018 and 0.016 (mean values of 0.027 and 0.028) for combined and in situ method, respectively. Assuming particles with a normalized rime mass smaller 0.01 to be unrimed, we obtain average rimed fractions of 77% and 75%. Although in situ measurement volumes are in the range of a few cm³ and therefore much smaller than the radar volume (about 45 m footprint diameter), we assume they are representative of the radar volume.When this assumption is not met due to less homogeneous conditions, discrepancies between the two methods result. We compare normalized rime mass results with meteorological and cloud parameters and show the performance of the methods in two case studies, 1) a collocated segment in cold air outbreak conditions and 2) an in situ only flight close to a polar low.We find that higher normalized rime masses correlate with streaks of higher radar reflectivity.We also observe rimed particles in regions without liquid water, suggesting that particles were rimed in a liquid layer above and precipitated. The methods presented improve our ability to quantify riming from aircraft observations. [ABSTRACT FROM AUTHOR]

As part of the EUREC4A field campaign, the research vessel Maria S. Merian probed an oceanic region between 6° N and 13.8° N and 51° W to 60° W for approximately 32 days. Trade wind cumulus clouds were sampled in the trade-wind alley region east of Barbados as well as in the transition region between the trades and the intertropical convergence zone, where the ship crossed some mesoscale oceanic eddies. We collected continuous observations of cloud and precipitation profiles at unprecedented vertical resolution (7-10 m in the first 3000 m) and high temporal resolution (1-3 s) using a W-band radar and micro-rain radar (MRR-PRO), installed on an active stabilization platform to reduce the impact of ship motions on the observations. The paper describes the ship motion correction algorithm applied to the Doppler observations to extract corrected hydrometeors vertical velocities and the algorithm created to filter interference patterns in the MRR-PRO observations. Radar reflectivity, mean Doppler velocity, spectral width and skewness for W-band and attenuated reflectivity, mean Doppler velocity and rain rate for MRR-PRO are shown for a case study to demonstrate the potential of the high resolution adopted. As non-standard analysis, we also retrieved and provided liquid water path (LWP) from the 89 GHz passive channel available on the W-band radar system. All datasets and hourly and daily quicklooks are publically available. Data can be accessed and basic variables can be plotted online via the intake catalog of the online book "How to EUREC4A". [ABSTRACT FROM AUTHOR]