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We explore the potential of a new method for the estimation of profiles of turbulence statistics in the stable boundary layer (SBL). By applying gradient-based scaling to multicopter unoccupied aircraft system (UAS) profiles of temperature and wind, sampled over sea-ice during the 2018 Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR18) field campaign, turbulence profiles can be derived. We first validate this method by scaling turbulence observations from three levels on a 10-m mast with the corresponding scaling parameters, and compare the resulting non-dimensional parameters to the semi-empirical similarity functions proposed for this scaling scheme. The scaled data of turbulent fluxes and variances from the three levels collapse to their corresponding similarity functions. After the successful validation, we estimate turbulence statistics from UAS profiles by computing profiles of the gradient Richardson number to which we then apply the similarity functions. These UAS profiles are processed from raw time-series data by applying low-pass filters, time-response corrections, altitude corrections, and temporal averaging across successive flights. We present three case studies covering a broad range of SBL conditions to demonstrate the validity of this approach. Comparisons against turbulence statistics from the 10-m mast and a sodar indicate the broad agreement and physically meaningful results of the method. Successful implementation of the method thus offers a powerful diagnostic tool that requires only a multicopter UAS with a simple thermodynamic sensor payload.

Clouds play an important role in Arctic amplification. This term represents the recently observed enhanced warming of the Arctic relative to the global increase of near-surface air temperature. However, there are still important knowledge gaps regarding the interplay between Arctic clouds and aerosol particles, and surface properties, as well as turbulent and radiative fluxes that inhibit accurate model simulations of clouds in the Arctic climate system. In an attempt to resolve this so-called Arctic cloud puzzle, two comprehensive and closely coordinated field studies were conducted: the Arctic Cloud Observations Using Airborne Measurements during Polar Day (ACLOUD) aircraft campaign and the Physical Feedbacks of Arctic Boundary Layer, Sea Ice, Cloud and Aerosol (PASCAL) ice breaker expedition. Both observational studies were performed in the framework of the German Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC) project. They took place in the vicinity of Svalbard, Norway, in May and June 2017. ACLOUD and PASCAL explored four pieces of the Arctic cloud puzzle: cloud properties, aerosol impact on clouds, atmospheric radiation, and turbulent dynamical processes. The two instrumented Polar 5 and Polar 6 aircraft; the icebreaker Research Vessel (R/V) Polarstern; an ice floe camp including an instrumented tethered balloon; and the permanent ground-based measurement station at Ny-Ålesund, Svalbard, were employed to observe Arctic low- and mid-level mixed-phase clouds and to investigate related atmospheric and surface processes. The Polar 5 aircraft served as a remote sensing observatory examining the clouds from above by downward-looking sensors; the Polar 6 aircraft operated as a flying in situ measurement laboratory sampling inside and below the clouds. Most of the collocated Polar 5/6 flights were conducted either above the R/V Polarstern or over the Ny-Ålesund station, both of which monitored the clouds from below using similar but upward-looking remote sensing techniques as the Polar 5 aircraft. Several of the flights were carried out underneath collocated satellite tracks. The paper motivates the scientific objectives of the ACLOUD/PASCAL observations and describes the measured quantities, retrieved parameters, and the applied complementary instrumentation. Furthermore, it discusses selected measurement results and poses critical research questions to be answered in future papers analyzing the data from the two field campaigns.

Arctic sea ice is diminishing with climate warming 1 at a rate unmatched for at least 1,000 years 2 . As the receding ice pack raises commercial interest in the Arctic 3 , it has become more variable and mobile 4 , which increases safety risks to maritime users 5 . Satellite observations of sea-ice thickness are currently unavailable during the crucial melt period from May to September, when they would be most valuable for applications such as seasonal forecasting 6 , owing to major challenges in the processing of altimetry data 7 . Here we use deep learning and numerical simulations of the CryoSat-2 radar altimeter response to overcome these challenges and generate a pan-Arctic sea-ice thickness dataset for the Arctic melt period. CryoSat-2 observations capture the spatial and the temporal patterns of ice melting rates recorded by independent sensors and match the time series of sea-ice volume modelled by the Pan-Arctic Ice Ocean Modelling and Assimilation System reanalysis 8 . Between 2011 and 2020, Arctic sea-ice thickness was 1.87 ± 0.10 m at the start of the melting season in May and 0.82 ± 0.11 m by the end of the melting season in August. Our year-round sea-ice thickness record unlocks opportunities for understanding Arctic climate feedbacks on different timescales. For instance, sea-ice volume observations from the early summer may extend the lead time of skilful August–October sea-ice forecasts by several months, at the peak of the Arctic shipping season. Deep learning and numerical simulations of CryoSat-2 radar altimeter data are used to generate a pan-Arctic sea-ice thickness dataset for the Arctic melt period.

The potential of recent Arctic changes to influence hemispheric weather is a complex and controversial topic with considerable uncertainty, as time series of potential linkages are short (<10 yr) and understanding involves the relative contribution of direct forcing by Arctic changes on a chaotic climatic system. A way forward is through further investigation of atmospheric dynamic mechanisms. During several exceptionally warm Arctic winters since 2007, sea ice loss in the Barents and Kara Seas initiated eastward-propagating wave trains of high and low pressure. Anomalous high pressure east of the Ural Mountains advected Arctic air over central and eastern Asia, resulting in persistent cold spells. Blocking near Greenland related to low-level temperature anomalies led to northerly flow into eastern North America, inducing persistent cold periods. Potential Arctic connections in Europe are less clear. Variability in the North Pacific can reinforce downstream Arctic changes, and Arctic amplification can accentuate the impact of Pacific variability. The authors emphasize multiple linkage mechanisms that are regional, episodic, and based on amplification of existing jet stream wave patterns, which are the result of a combination of internal variability, lower-tropospheric temperature anomalies, and midlatitude teleconnections. The quantitative impact of Arctic change on midlatitude weather may not be resolved within the foreseeable future, yet new studies of the changing Arctic and subarctic low-frequency dynamics, together with additional Arctic observations, can contribute to improved skill in extended-range forecasts, as planned by the WMO Polar Prediction Project (PPP).

Observations of ocean currents in the Arctic interior show a curious, and hitherto unexplained, vertical and temporal distribution of mesoscale activity. A marked seasonal cycle is found close to the surface: strong eddy activity during summer, observed from both satellites and moorings, is followed by very quiet winters. In contrast, subsurface eddies persist all year long within the deeper halocline and below. Informed by baroclinic instability analysis, we explore the origin and evolution of mesoscale eddies in the seasonally ice-covered interior Arctic Ocean. We find that the surface seasonal cycle is controlled by friction with sea ice, dissipating existing eddies and preventing the growth of new ones. In contrast, subsurface eddies, enabled by interior potential vorticity gradients and shielded by a strong stratification at a depth of approximately 50 m, can grow independently of the presence of sea ice. A high-resolution pan-Arctic ocean model confirms that the interior Arctic basin is baroclinically unstable all year long at depth. We address possible implications for the transport of water masses between the margins and the interior of the Arctic basin, and for climate models’ ability to capture the fundamental difference in mesoscale activity between ice-covered and ice-free regions.

The Arctic environment has an amplified response to global climatic change. It is sensitive to human activities that mostly take place elsewhere. For this study, a multi-year set of observed aerosol number size distributions in the diameter range of 10 to 500 nm from five sites around the Arctic Ocean (Alert, Villum Research Station – Station Nord, Zeppelin, Tiksi and Barrow) was assembled and analysed.A cluster analysis of the aerosol number size distributions revealed four distinct distributions. Together with Lagrangian air parcel back-trajectories, they were used to link the observed aerosol number size distributions with a variety of transport regimes. This analysis yields insight into aerosol dynamics, transport and removal processes, on both an intra- and an inter-monthly scale. For instance, the relative occurrence of aerosol number size distributions that indicate new particle formation (NPF) event is near zero during the dark months, increases gradually to  ∼ 40 % from spring to summer, and then collapses in autumn. Also, the likelihood of Arctic haze aerosols is minimal in summer and peaks in April at all sites.The residence time of accumulation-mode particles in the Arctic troposphere is typically long enough to allow tracking them back to their source regions. Air flow that passes at low altitude over central Siberia and western Russia is associated with relatively high concentrations of accumulation-mode particles (Nacc) at all five sites – often above 150 cm−3. There are also indications of air descending into the Arctic boundary layer after transport from lower latitudes.The analysis of the back-trajectories together with the meteorological fields along them indicates that the main driver of the Arctic annual cycle of Nacc, on the larger scale, is when atmospheric transport covers the source regions for these particles in the 10-day period preceding the observations in the Arctic. The scavenging of these particles by precipitation is shown to be important on a regional scale and it is most active in summer. Cloud processing is an additional factor that enhances the Nacc annual cycle.There are some consistent differences between the sites that are beyond the year-to-year variability. They are the result of differences in the proximity to the aerosol source regions and to the Arctic Ocean sea-ice edge, as well as in the exposure to free-tropospheric air and in precipitation patterns – to mention a few. Hence, for most purposes, aerosol observations from a single Arctic site cannot represent the entire Arctic region. Therefore, the results presented here are a powerful observational benchmark for evaluation of detailed climate and air chemistry modelling studies of aerosols throughout the vast Arctic region.

We review the capability of current and scheduled satellite observations of atmospheric methane in the shortwave infrared (SWIR) to quantify methane emissions from the global scale down to point sources. We cover retrieval methods, precision and accuracy requirements, inverse and mass balance methods for inferring emissions, source detection thresholds, and observing system completeness. We classify satellite instruments as area flux mappers and point source imagers, with complementary attributes. Area flux mappers are high-precision (<1 %) instruments with 0.1–10 km pixel size designed to quantify total methane emissions on regional to global scales. Point source imagers are fine-pixel (<60 m) instruments designed to quantify individual point sources by imaging of the plumes. Current area flux mappers include GOSAT (2009–present), which provides a high-quality record for interpretation of long-term methane trends, and TROPOMI (2018–present), which provides global continuous daily mapping to quantify emissions on regional scales. These instruments already provide a powerful resource to quantify national methane emissions in support of the Paris Agreement. Current point source imagers include the GHGSat constellation and several hyperspectral and multispectral land imaging sensors (PRISMA, Sentinel-2, Landsat-8/9, WorldView-3), with detection thresholds in the 100–10 000 kg h−1 range that enable monitoring of large point sources. Future area flux mappers, including MethaneSAT, GOSAT-GW, Sentinel-5, GeoCarb, and CO2M, will increase the capability to quantify emissions at high resolution, and the MERLIN lidar will improve observation of the Arctic. The averaging times required by area flux mappers to quantify regional emissions depend on pixel size, retrieval precision, observation density, fraction of successful retrievals, and return times in a way that varies with the spatial resolution desired. A similar interplay applies to point source imagers between detection threshold, spatial coverage, and return time, defining an observing system completeness. Expanding constellations of point source imagers including GHGSat and Carbon Mapper over the coming years will greatly improve observing system completeness for point sources through dense spatial coverage and frequent return times.

Recent observations show that dust emitted within the Arctic (Arctic dust) has a remarkably high ice nucleating ability, especially between −20°C and −5°C, but its impacts on the number concentrations of ice nucleating particles (INPs) and radiative balance in the Arctic are not well understood. Here we incorporate an observation‐based ice‐nucleation parameterization indicating the high ice nucleating ability of Arctic dust into a global aerosol‐climate model. A simulation using this parameterization better reproduces INP observations in the Arctic and estimates >100 times higher dust INP number concentrations with ∼100% contribution from Arctic dust in the Arctic lower troposphere (>60°N and >700 hPa) during summer and fall (June–November) than a simulation applying a standard ice‐nucleation parameterization suitable for desert dust to Arctic dust. Our results demonstrate the importance of considering an ice‐nucleation parameterization suitable for Arctic dust when simulating INPs and their effects on aerosol‐cloud interactions in the Arctic. Plain Language Summary Dust is an important aerosol type acting as “ice nucleating particles,” which initiate the formation of ice crystals within mixed‐phase clouds (consisting of both supercooled water droplets and ice crystals) and influence the cloud lifetime and distribution. Recent observations show that dust is emitted from ice‐ and vegetation‐free areas in the Arctic region (hereafter Arctic dust), which has a remarkably high ice nucleating ability, compared with desert dust such as Asian dust and Saharan dust, because of the presence of certain organic matter. However, the impacts of Arctic dust with high ice nucleating ability on ice nucleating particles and mixed‐phase clouds in the Arctic are unknown. In this study, we investigate the importance of Arctic dust with high ice nucleating ability for ice nucleating particles in the Arctic using a global aerosol‐climate model. Our simulation results show that Arctic dust accounts for almost all dust ice nucleating particles in the Arctic lower troposphere (>60°N and about 0–3 km) during summer and fall (June–November). This study demonstrates the importance of considering the high ice nucleating ability of Arctic dust when simulating ice nucleating particles and their impacts on mixed‐phase clouds and radiative balance in the Arctic. Key Points Arctic dust, emitted within the Arctic, accounts for most of dust ice nucleating particles in the Arctic lower troposphere in summer to fall Importance of Arctic dust as ice nucleating particles in the Arctic strongly depends on its high ice nucleating ability at high temperatures Considering an ice‐nucleation parameterization suitable for Arctic dust is crucial for aerosol‐cloud‐climate simulations in the Arctic

El Niño–Southern Oscillation (ENSO) and its teleconnections form the leading mode of interannual variability in the global climate system, yet the small sample size of ENSO events during which we have reliable Arctic observations makes constraining its influence on Arctic sea ice challenging. We compare the influence of ENSO on Arctic sea ice in six models from the Multi-Model Large Ensemble Archive with that in observations. Each model simulates reduced Arctic sea ice area and volume in the seasons following an El Niño relative to a La Niña. The patterns of sea ice concentration and thickness responses to ENSO are spatially heterogeneous, with regions of increased and decreased sea ice. The small sample size of ENSO events in observations is shown to preclude a statistically significant sea ice response from being identified. While models agree with one another on many aspects of the sea ice response to ENSO, some features are model dependent. For example, the CESM1-LE alone displays a delayed melting response in summer, driven by reduced surface albedo and increased shortwave absorption. A positive Arctic Oscillation and a deepened Aleutian low are common responses to ENSO across models and observations. These patterns of atmospheric variability are quantitatively shown to be key in linking ENSO to Arctic sea ice in most models, acting primarily through sea ice dynamics to generate anomalous sea ice thickness and concentration patterns.

Large-scale chemical depletion of ozone due to anthropogenic emissions occurs over Antarctica as well as, to a lesser degree, the Arctic. Surface climate predictability in the Northern Hemisphere might be improved due to a previously proposed, albeit uncertain, link to springtime ozone depletion in the Arctic. Here we use observations and targeted chemistry–climate experiments from two models to isolate the surface impacts of ozone depletion from complex downward dynamical influences. We find that springtime stratospheric ozone depletion is consistently followed by surface temperature and precipitation anomalies with signs consistent with a positive Arctic Oscillation, namely, warm and dry conditions over southern Europe and Eurasia and moistening over northern Europe. Notably, we show that these anomalies, affecting large portions of the Northern Hemisphere, are driven substantially by the loss of stratospheric ozone. This is due to ozone depletion leading to a reduction in short-wave radiation absorption, when in turn causing persistent negative temperature anomalies in the lower stratosphere and a delayed break-up of the polar vortex. These results indicate that the inclusion of interactive ozone chemistry in atmospheric models can considerably improve the predictability of Northern Hemisphere surface climate on seasonal timescales. Ozone depletion in the Arctic stratosphere consistently disrupts surface temperature and precipitation patterns across the Northern Hemisphere, according to atmospheric chemistry–climate modelling and observations.