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Passive microwave measurements of Arctic sea ice have been conducted over the last 50 years from space and during airborne, ship- and ground-based measurement campaigns. The different radiometric signatures of distinct surface types have led to satellite retrievals of, e.g., sea-ice concentration. In contrast, ground-based upward-viewing radiometers measure radiation emitted from the atmosphere and are used to retrieve atmospheric variables. Here, we present results from a ship-based radiometer setup with a mirror construction, which allows us to switch between atmospheric and surface measurements flexibly. This way, in summer 2022, surface observations in the Arctic marginal sea-ice zone could be performed from the research vessel Polarstern by two radiometers covering the frequency range from 22 to 243 GHz. At low frequencies, the brightness temperatures show clear signatures of different surface conditions. We estimate emissivities at 53∘ zenith angle from infrared-based skin temperatures. Predominantly vertically polarized 22–31 GHz emissivities are between 0.51 and 0.55 for open ocean and around 0.95 for sea ice. Predominantly horizontally polarized 243 GHz ocean emissivities are around 0.78 and ice surfaces exhibit a large variability from 0.67 to 0.82. Our results can improve the characterization of surface emissions in satellite retrieval algorithms.

Two airborne field campaigns focusing on observations of Arctic mixed-phase clouds and boundary layer processes and their role with respect to Arctic amplification have been carried out in spring 2019 and late summer 2020 over the Fram Strait northwest of Svalbard. The latter campaign was closely connected to the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Comprehensive datasets of the cloudy Arctic atmosphere have been collected by operating remote sensing instruments, in-situ probes, instruments for the measurement of turbulent fluxes of energy and momentum, and dropsondes on board the AWI research aircraft Polar 5. In total, 24 flights with 111 flight hours have been performed over open ocean, the marginal sea ice zone, and sea ice. The datasets follow documented methods and quality assurance and are suited for studies on Arctic mixed-phase clouds and their transformation processes, for studies with a focus on Arctic boundary layer processes, and for satellite validation applications. All datasets are freely available via the world data center PANGAEA. Measurement(s) navigation data • temperature of air • atmospheric humidity • radar reflectivity • brightness temperature • cloud properties • radiation • atmospheric wind Technology Type(s) GPS navigation system • dropsondes • radar • microwave radiometer • particle count and size analyzer • imager • noseboom sensors Factor Type(s) temporal • location Sample Characteristic - Environment atmosphere Sample Characteristic - Location Arctic Ocean region

Correction to: Scientific Data https://doi.org/10.1038/s41597-022-01900-7, published online 29 December 2022.Several of the units in the original version were published in metres, rather than μm; several ± signs were omitted from numerical values; and Table 2 was incorrectly formatted to cause certain rows and columns to mis-align. These have been corrected in the pdf and HTML versions of the article.

In this study, we analyse the contribution of atmospheric rivers (ARs), cyclones, and fronts to the total precipitation in the Arctic. We focus on two distinct periods of different weather conditions from two airborne campaigns: ACLOUD (Arctic Cloud Observations Using airborne measurements during polar day; May/June 2017) and AFLUX (Aircraft campaign Arctic Boundary Layer Fluxes; March/April 2019). Both campaigns covered the northern North Atlantic sector, the area in the Arctic that is affected by the highest precipitation rates. Using ERA5 reanalysis, we identify pronounced regional anomalies with enhanced precipitation rates compared to the climatology during ACLOUD due to these weather systems, whereas during AFLUX enhanced precipitation rates occur over most of the area. We have established a new methodology that allows us to analyse the contribution of ARs, cyclones, and fronts to precipitation rates based on ERA5 reanalysis and different detection algorithms. Here, we distinguish whether these systems occur co-located or separately. The contributions differ between the two periods. During ACLOUD (early summer), the precipitation rates are mainly associated with AR- (40 %) and front-related (55 %) components, especially if they are connected, while cyclone-related components (22 %) play a minor role. However, during AFLUX (early spring) the precipitation is mainly associated with cyclone-related components (62 %). For both campaign periods, snow is the dominant form of precipitation, and the small rain occurrence is almost all associated with ARs. About one-third of the precipitation can not be attributed to one of the weather systems, the so-called residual. While the residual can be found more frequently as convective than as large-scale precipitation, the rare occasion of convective precipitation (roughly 20 %) can not completely explain the residual. The fraction of precipitation classified as residual is reduced significantly when a precipitation threshold is applied that is often used to eliminate “artificial” precipitation. However, a threshold of 0.1 mm h−1 reduces the total accumulated precipitation by a factor of 2 (ACLOUD) and 3 (AFLUX), especially affecting light precipitation over the Arctic Ocean. We also show the dependence of the results on the choice of the detection algorithm serving as a first estimate of the uncertainty. In the future, we aim to apply the methodology to the full ERA5 record to investigate whether the differences found between the campaign periods are typical for the different seasons in which they were performed and whether any trends in precipitation associated with these weather systems can be identified.

Marine cold-air outbreaks (MCAOs) strongly affect the Arctic water cycle and, thus, climate through large-scale air mass transformations. The description of air mass transformations is still challenging, partly because previous observations do not resolve fine scales, particularly for the initial development of an MCAO, and due to a lack of information about the thermodynamical evolution starting over sea ice and continuing over open ocean and associated cloud microphysical properties. Therefore, we focus on the crucial initial development within the first 200 km over open water for two case studies in April 2022 during the HALO-(AC)3 campaign (named after the High Altitude and Long Range Research Aircraft and Transregional Collaborative Research Centre ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes and Feedback Mechanisms (AC)3). The two events, just 3 d apart, belong to a particularly long-lasting MCAO and occurred under relatively similar thermodynamic conditions. Even though both events were stronger than the climatological 75th percentile of that period, the first event was characterized by colder air masses from the central Arctic which led to an MCAO index twice as high compared to that of the second event. The evolution and structure were assessed by flight legs crossing the Fram Strait multiple times at the same location, sampling perpendicularly to the cloud streets. Airborne remote sensing and in situ measurements were used to build statistical descriptions of the boundary layer, dynamics, clouds, and precipitation. For this purpose, we established a novel approach based solely on radar reflectivity measurements to detect roll circulation that forms cloud streets. The two cases exhibit different properties of clouds, riming, and roll circulations, though the width of the roll circulation is similar. For the stronger event, cloud tops are higher; more liquid-topped clouds exist; the liquid water path, mean radar reflectivity, precipitation rate, and precipitation occurrence have increased; and riming is active. The variability in rime mass has the same horizontal scale as the roll circulation, implying the importance of roll circulation on cloud microphysics and precipitation. Boundary layer and cloud properties evolve with distance over open water, as seen by, e.g., cloud top height rising. In general, cloud streets form after traveling 15 km over open water. After 20 km, this formation enhances cloud cover to just below 100 %. After around 30 km, precipitation forms, though for the weaker event, the development of precipitation is shifted to larger distances. Within our analysis, we developed statistical descriptions of various parameters (i) within the roll circulation and (ii) as a function of distance over open water. These detailed cloud metrics are particularly well suited for the evaluation of cloud-resolving models close to the sea ice edge to evaluate their representation of dynamics and microphysics.

Ground-based precipitation observations are sparse in the Arctic but are needed to better understand precipitation processes and to provide reference data sets for models and satellite products. This study presents new, temporally highly resolved precipitation measurements from a Pluvio precipitation gauge and a Parsivel disdrometer at the Arctic research station AWIPEV, part of the Ny-Ålesund Research Station, Svalbard. Using the information on the precipitation phase by Parsivel, we derived a temperature-dependent separation of precipitation into liquid and solid mass. The Pluvio precipitation amount and the Parsivel/temperature-based precipitation type were analyzed for the period August 2017–December 2021 and related to the presence of synoptic-scale weather systems, i.e., atmospheric rivers (ARs), cyclones and fronts, detected from ERA5 reanalysis data. ARs occurred only 8 % of the time at Ny-Ålesund but contributed to about 42 % of the total precipitation amount with a high liquid mass fraction (72 %). Cyclones occurred 20 % of the time and were associated with 39 % of the precipitation, mainly in solid form (62 %). Frontal systems play a minor role in the precipitation amount at Ny-Ålesund. Extreme events, i.e., days with daily precipitation sums above the 98th percentile, contribute 18 % to the total precipitation amount. All of these events are related to enhanced water vapor transport, often in the form of ARs and in combination with fronts and a high liquid mass fraction. Liquid precipitation in winter is mainly connected to ARs. These new measurements will help to better characterize uncertainties in gauge-based precipitation observations and the local variability of precipitation.

Atmospheric rivers (ARs) are essential for the Arctic water cycle, but observations quantifying the moisture processes of individual Arctic ARs are sparse. This study quantified the evolution of the moisture budget components of an Arctic AR derived from airborne observations from two research flights on consecutive days. We investigated how poleward transport of warm and moist air masses by ARs generates precipitation near the sea ice edge and how advection and evaporation affect the local moisture amount during the dissipation of the AR. Using observations from the High-Altitude and LOng-Range Research Aircraft (HALO), we derived the atmospheric moisture budget components (local tendency of moisture, evaporation, moisture transport divergence, and precipitation) within an Arctic AR during the HALO-(𝒜𝒞)3 aircraft campaign. The budget components were quantified in sectors ahead of the AR-embedded cold front using airborne observations from dropsondes, radiometers, and a radar device and compared with values derived from reanalyses and numerical weather prediction simulations. We found that the observed moisture budget components in the pre-cold frontal sectors contribute up to ±1mmh-1 to the local moisture amount. The moisture transport divergence primarily controls the local moisture amount within the AR, while surface interactions are of minor importance. Precipitation is heterogeneous but overall weak (<0.1mmh-1), and evaporation is small. As the AR dissipated, the budget components changed from drying to moistening, mainly due to moisture advection. We demonstrated the feasibility of closing the moisture budget using single aircraft measurements, even though we found significant residuals that model-based comparisons attribute to subscale variability.

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.

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.