Kerstin Ebell

Understanding the role of water vapor in Arctic amplification requires a detailed evaluation of its spatio‐temporal variability. In this work, we use an integrated water vapor (IWV) data set from a ground‐based microwave radiometer at Ny‐Ålesund, Svalbard, covering 2012–2024, to characterize temporal IWV variability. We also identify extreme atmospheric moistening and drying events based on a new detection method and relate them to large‐scale circulation patterns and airmass pathways. IWV exhibits a pronounced annual cycle with values ranging from 0.6 to 33 kg . While absolute IWV variability within a month is smaller in winter than in summer, relative variability is nearly twice as large. We identified 352 extreme moistening and 371 extreme drying events, accounting for 20% of the study period. Extreme drying occurs primarily through continuous drying, whereas extreme moistening events include a higher fraction of consecutive moistening episodes and therefore last longer. Most events occur on synoptic time scales of 1–3 days. Extreme moistening events are linked to large‐scale circulation patterns that facilitate the advection of moist airmasses toward Svalbard from southeasterly to westerly directions, which account for 52% of all moistening events. Extreme drying occurs under similar circulation patterns, but is mainly linked to a reduction in the poleward moisture transport due to an eastward shift of the prevailing pressure centers. 45% of extreme drying events follow directly after an extreme moistening event. Given the comprehensive ground‐based observations available at Ny‐Ålesund, the identified events provide a useful framework to study their impact on clouds, precipitation, radiation, and surface conditions.

Marine combined carbohydrates in aerosol particles (CCHOaer) have the potential to influence cloud formation and properties, but it remains unclear to what extent they reach altitudes relevant for cloud processes. Balloon-borne measurements of major sea spray aerosol (SSA) constituents, including sodium (Naaer+) and CCHOaer, were conducted in autumn 2021 and spring 2022 in Ny-Ålesund (Svalbard). Total suspended particles were collected at 321–1112 m, covering both the marine boundary layer and the free troposphere, with Naaer+ ranging 23–850 ng m−3 and CCHOaer 3.8–274 ng m−3. The chemical composition of balloon-borne aerosol samples was compared with synchronized ground level measurements at the balloon's winch (Naaer+: 35–3710 ng m−3; CCHOaer: 1.9–194 ng m−3), and at the Old Pier (Naaer+: 140–1470 ng m−3; CCHOaer: 1.6–10.0 ng m−3), where freshly emitted SSA particles were sampled. Surface seawater from the Kongsfjorden was analyzed to evaluate the sea-air transfer of marine CCHO. Air mass histories, atmospheric mixing, and cloud conditions were evaluated for three selected cases to explain vertical concentration patterns. A strong correlation (R=0.78, p<0.001) between combined xylose (< 0.2–14.1 ng m−3) in CCHOaer and oxalateaer (< 1–67 ng m−3) across all altitudes, suggests either coproduction or a connection through atmospheric processing. These results provide a first comprehensive picture of how local primary sea-air transfer of marine combined carbohydrates, long-range transport, in-situ formation, and atmospheric processing together shape their distribution.

Marine carbohydrates are produced by a wide range of micro- and macroorganisms in seawater and are transferred to the atmosphere via sea spray aerosol (SSA). Recent laboratory and modelling studies suggest that these compounds can influence fog and cloud microphysics as ice nucleating particles. However, observational evidence from the atmosphere remains limited, as most field studies have relied on ship- or land-based filter samples, leaving their relevance for cloud processes at cloud-relevant altitudes largely unconstrained.Here, we present new measurements of marine carbohydrates and other SSA components at altitudes between 300 and 1200 m, obtained using a tethered helium balloon in Ny-Ålesund (Svalbard) during 2021-2022. These observations are compared with fresh SSA directly collected at the Kongsfjorden coast and with surface seawater samples to assess contributions beyond local ocean emissions. Our results highlight the key role of meteorological conditions in lifting and redistributing SSA constituents, including marine carbohydrates, to higher atmospheric layers. The study further examines potential additional sources and formation pathways, providing new insights into the atmospheric behaviour of marine carbohydrates and their implications for cloud microphysics.We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Project Number 268020496—TRR 172, within the framework of the Transregional Collaborative Research Center “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3”

Clouds are still a major source of uncertainty in projections of the future climate because of complex feedback mechanisms and their interplay with other atmospheric and surface properties (i.e., through solar and thermal-infrared radiation and precipitation). In the Arctic, where the climate is projected to warm the strongest, clouds pose a particular challenge to current climate and weather forecast models because of the difficulties in simulating the frequently occurring mixed-phase clouds and the sparsity of observational data.In this study, we aim to improve our understanding of Arctic clouds on multi-annual time scales by performing statistical analyses of cloud states and their transitions using cloud radar data from the research site Ny-Ålesund, Svalbard. We have gathered nine years of comprehensive cloud and precipitation observations with the 94-GHz cloud radars, which were operated at the German-French Arctic Research Base AWIPEV observatory in synthesis with other in-situ and remote sensing instruments (i.e., microwave radiometers, lidar, disdrometers, ...). The additional meteorological measurements also allow us to study how atmospheric conditions affect the cloud states and transitions.Modern machine learning algorithms are well suited to analyse big data sets and reveal features imperceptible to the human eye because of the complexity of the problem. We train a Vision Transformer [1-3] with height-resolved cloud radar reflectivities, Doppler velocities, ceilometer data and liquid water path-sensitive brightness temperatures at 89 GHz in a self-supervised framework. The Vision Transformer learns to identify distinct features in the training data and therefore find different cloud states without direct human intervention.Here, we present our first steps focussing on the interpretation of the machine learning model output and fine tune the settings to better discern the cloud states. Different cloud macro- and microphysical properties are tested to understand the nature of each cluster the machine learning algorithm produced.Later, we will apply the trained machine learning algorithm to synthetic radar data simulated with the Passive and Active Microwave radiative TRAnsfer (PAMTRA, [4]) model based on the output of the ICOsahedral Non-hydrostatic (ICON, [5]) model in large-eddy configuration. By comparing the observation-based analysis with the one performed on the simulated radar data we aim to further shed light on the strengths and weaknesses of ICON regarding cloud states and transitions. We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project Number 268020496 - TRR 172, within the framework of the Transregional Collaborative Research Center "ArctiC Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC)³". We also acknowledge the support of AWIPEV for the project AWIPEV_0016.[1]: Vaswani, A., et al., 2017, Inc. arXiv, 1706.03762, https://arxiv.org/abs/1706.03762.[2]: Caron, M., et al., 2021, arXiv, 2104.14294, https://arxiv.org/abs/2104.14294.[3]: Chatterjee, D., et al., 2024, Geophys. Res. Lett., 51, 12, e2024GL108889, doi: 10.1029/2024GL108889.[4]: Mech, M. et al., 2020, Geosci. Model Dev., 13, 4229-4251, doi: 10.5194/gmd-13-4229-2020.[5]: Zängl, G. et al., 2015, Q. J. R. Meteorolog. Soc., 141, 563-579, doi: 10.1002/qj.2378.

The role of Water Vapor (WV) in Arctic amplification remains uncertain and is under investigation (Wendisch and coauthors, 2023). Understanding its role in the mechanisms driving Arctic amplification requires detailed information on its spatio-temporal variability. However, WV variability in the Arctic has rarely been examined. Temporally highly resolved integrated water vapor (IWV) data from ground-based MWR observations are ideally suited for the analysis of WV temporal variability. In this study, we make use of 13 years of measurements of the Humidity and Temperature PROfiler (HATPRO) at the AWIPEV atmospheric observatory (Ny-Ålesund, Svalbard). Extreme events of atmospheric moistening and drying are identified, characterized, and further related to the prevailing circulation weather systems. Since WV transport into the Arctic is episodic and primarily occurs through brief, intense events typically associated with cyclones (Henderson et al., 2021), it is essential to analyze these events in further detail. To analyze these events, we identify minima and maxima in the IWV time series. We define “extreme” using a threshold in IWV amplitudes within a respective time interval. An event can either consist of only one maximum (moistening) or minimum (drying) or of multiple maxima/minima.When focusing on extreme atmospheric moistening and drying events, we find that absolute IWV amplitudes are highest in summer and lowest in winter. The events last between 2 and 142 hours. By contrast, winter shows a greater relative variability (with respect to the monthly mean) than summer, with IWV changes exceeding 250% within a few hours in some cases. Events with only one maximum (moistening) or one minimum (drying) are short-lived (75% last less than 24 hours), while those with multiple maxima/minima last longer, with a mean of 48 hours. We find that extreme atmospheric moistening and drying at Ny-Ålesund proceed differently: drying happens more rapidly but with smaller amplitudes than moistening. Also, the synoptic regimes favoring moistening and drying differ. For moistening the weather types ASW, AW, AS, and CSE account for half of the extreme moistening events, with the anticyclonic types transporting moisture over the North Atlantic. In contrast, CSE is associated with moisture transport over Scandinavia and West Russia, spanning the Barents and Kara Seas. For drying, significantly different weather systems can be responsible. Other studies found a positive trend in cyclone activity over the Barents Sea (e.g., Wickström et al., 2019), which could favor greater moisture transport driven by CSE.We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 268020496 – TRR 172, within the framework of the Transregional Collaborative Research Center “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)³”. We thank the AWIPEV team for their support in operating our instruments at AWIPEV within the project AWIPEV_0016.

Climate change signals are especially strong in the Arctic, where warming from 1979 to 2021 proceeded at nearly four times the global average rate (Rantanen et al., 2022). The magnitude of this warming varies across the region, and the Svalbard archipelago, located in the warmest part of the Arctic, has experienced particularly intense temperature increases (Dahlke and Maturilli, 2017).The influence of clouds on the rapidly evolving Arctic climate system, as well as the processes governing their behavior, remains a key research challenge. Although detailed cloud observations are essential, only a limited number of Arctic sites provide continuous, high-resolution vertical measurements of cloud properties. One such site is the German-French Arctic Research Base AWIPEV at the Ny-Ålesund Research Station on Svalbard. Since 2016, a 94 GHz cloud radar has been operating at this location as part of the Transregional Collaborative Research Centre TR172 on Arctic Amplification (AC)³ (http://www.ac3-tr.de; Wendisch et al., 2023). In combination with complementary remote-sensing instruments, including ceilometers and microwave radiometers, this observational setup allows for continuous cloud monitoring with high temporal and vertical resolution. This presentation highlights key results derived from a decade of cloud radar observations.Clouds are present at Ny-Ålesund during roughly 78% of the time, most frequently at low levels between 0.5 and 1.5 km. While pure liquid clouds show a distinct seasonal variability, mixed-phase clouds occur year-round and account for about 42% of all cloud observations. These liquid-containing clouds have a significant influence on the Arctic surface energy budget, leading to an overall warming at Ny-Ålesund due to the enhanced longwave downward radiation flux.Based on the 10-year-long dataset, we will examine the interannual variability of clouds and precipitation at Ny-Ålesund, as well as their impact on surface radiation.Acknowledgment: We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 268020496 – TRR 172, within the framework of the Transregional Collaborative Research Center “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)³”. We also acknowledge the support of AWIPEV for the project AWIPEV_0016.

Precipitation is an essential component of the Arctic climate system as part of the hydrological cycle, linking the atmosphere and cryosphere. Much of the Arctic precipitation sublimates or evaporates before it reaches the ground due to dry sub-cloud layers. The processes are thus controlling the input of the surface mass balance.We use long-term atmospheric observations at Ny-Ålesund, Svalbard, with vertically-pointing cloud radars and backscattering lidars to identify and quantify atmospheric sublimation/evaporation. Radar observation-based sub-cloud precipitation profiles are studied by employing a virga detection tool, the so-called Virga-Sniffer (Kalesse-Los et al., 2023). The quantification of the sublimation/evaporation is based on sub-cloud vertical gradients of radar moments. First statistical results of precipitation thermodynamical phase, virga depth, and full sublimation/evaporation altitude above ground will be shown.We will show investigations on wind direction dependence on virga statistics. Air masses advected from the Arctic Ocean are more humid and lead to more precipitation reaching the ground and thus less virga. Air masses advected over Ny-Ålesund from Easterly directions are often characterized by low-humidity subcloud layers leading to more evaporation/ sublimation and hence a higher fraction of virga. Furthermore, the occurrence frequency of virga and surface precipitation observed during different weather regimes such as cyclones, fronts, and atmospheric rivers is contrasted.This work was supported by the DFG funded Transregio-project TRR 172 “Arctic Amplification (AC)3“.Refernces:Kalesse-Los, H., Kötsche, A., Foth, A., Röttenbacher, J., Vogl, T., and Witthuhn, J.: The Virga-Sniffer – a new tool to identify precipitation evaporation using ground-based remote-sensing observations, Atmos. Meas. Tech., 16, 1683–1704, https://doi.org/10.5194/amt-16-1683-2023, 2023.

Marine combined carbohydrates in aerosol particles (CCHO_aer) have the potential to influence cloud formation and properties, but it remains unclear to what extent they reach altitudes relevant for cloud processes. Balloon-borne measurements of major sea spray aerosol (SSA) constituents, including sodium (Na⁺_aer) and CCHO_aer, were conducted in autumn 2021 and spring 2022 in Ny-Ålesund (Svalbard). Total suspended particles were collected at 321–1112 m, covering both the marine boundary layer and the free troposphere, with Na⁺_aer ranging 23–850 ng m^-3 and CCHO_aer 3.8–274 ng m^-3. The chemical composition of balloon-borne aerosol samples was compared with synchronized ground level measurements at the balloon's winch (Na⁺_aer: 35–3710 ng m^-3; CCHO_aer: 1.9–194 ng m^-3), and at the Old Pier (Na⁺_aer: 140–1470 ng m^-3; CCHO_aer: 1.6–10.0 ng m^-3), where freshly emitted SSA particles were sampled. Surface seawater from the Kongsfjorden was analyzed to evaluate the sea-air transfer of marine CCHO. Air mass histories, atmospheric mixing, and cloud conditions were evaluated for three selected cases to explain vertical concentration patterns. A strong correlation (R=0.78, p-3) in CCHO_aer and oxalate_aer (-3) across all altitudes, suggests either coproduction or a connection through atmospheric processing. These results provide a first comprehensive picture of local primary sea-air transfer of marine combined carbohydrates and highlight the roles of long-range transport, in-situ formation, and chemical aging in shaping their atmospheric distribution.

Marine combined carbohydrates in aerosol particles (CCHO_aer) have the potential to influence cloud formation and properties, but it remains unclear to what extent they reach altitudes relevant for cloud processes. Balloon-borne measurements of major sea spray aerosol (SSA) constituents, including sodium (Na⁺_aer) and CCHO_aer, were conducted in autumn 2021 and spring 2022 in Ny-Ålesund (Svalbard). Total suspended particles were collected at 321–1112 m, covering both the marine boundary layer and the free troposphere, with Na⁺_aer ranging 23–850 ng m^-3 and CCHO_aer 3.8–274 ng m^-3. The chemical composition of balloon-borne aerosol samples was compared with synchronized ground level measurements at the balloon's winch (Na⁺_aer: 35–3710 ng m^-3; CCHO_aer: 1.9–194 ng m^-3), and at the Old Pier (Na⁺_aer: 140–1470 ng m^-3; CCHO_aer: 1.6–10.0 ng m^-3), where freshly emitted SSA particles were sampled. Surface seawater from the Kongsfjorden was analyzed to evaluate the sea-air transfer of marine CCHO. Air mass histories, atmospheric mixing, and cloud conditions were evaluated for three selected cases to explain vertical concentration patterns. A strong correlation (R=0.78, p-3) in CCHO_aer and oxalate_aer (-3) across all altitudes, suggests either coproduction or a connection through atmospheric processing. These results provide a first comprehensive picture of local primary sea-air transfer of marine combined carbohydrates and highlight the roles of long-range transport, in-situ formation, and chemical aging in shaping their atmospheric distribution.

Marine combined carbohydrates in aerosol particles (CCHO_aer) have the potential to influence cloud formation and properties, but it remains unclear to what extent they reach altitudes relevant for cloud processes. Balloon-borne measurements of major sea spray aerosol (SSA) constituents, including sodium (Na⁺_aer) and CCHO_aer, were conducted in autumn 2021 and spring 2022 in Ny-Ålesund (Svalbard). Total suspended particles were collected at 321–1112 m, covering both the marine boundary layer and the free troposphere, with Na⁺_aer ranging 23–850 ng m^-3 and CCHO_aer 3.8–274 ng m^-3. The chemical composition of balloon-borne aerosol samples was compared with synchronized ground level measurements at the balloon's winch (Na⁺_aer: 35–3710 ng m^-3; CCHO_aer: 1.9–194 ng m^-3), and at the Old Pier (Na⁺_aer: 140–1470 ng m^-3; CCHO_aer: 1.6–10.0 ng m^-3), where freshly emitted SSA particles were sampled. Surface seawater from the Kongsfjorden was analyzed to evaluate the sea-air transfer of marine CCHO. Air mass histories, atmospheric mixing, and cloud conditions were evaluated for three selected cases to explain vertical concentration patterns. A strong correlation (R=0.78, p-3) in CCHO_aer and oxalate_aer (-3) across all altitudes, suggests either coproduction or a connection through atmospheric processing. These results provide a first comprehensive picture of local primary sea-air transfer of marine combined carbohydrates and highlight the roles of long-range transport, in-situ formation, and chemical aging in shaping their atmospheric distribution.