Abstract. Sea salt aerosols play an important role in the radiationbudget and atmospheric composition over the Arctic, where the climate israpidly changing. Previous observational studies have shown that Arctic sea ice leads are an important source of sea salt aerosols, and modeling efforts have also proposed blowing snow sublimation as a source. In this study,size-resolved atmospheric particle number concentrations and chemicalcomposition were measured at the Arctic coastal tundra site ofUtqiaġvik, Alaska, during spring (3 April–7 May 2016). Blowing snow conditions were observed during 25 % of the 5-week study period andwere overpredicted by a commonly used blowing snow parameterization based solely on wind speed and temperature. Throughout the study, open leads werepresent locally. During periods when blowing snow was observed, significantincreases in the number concentrations of 0.01–0.06 µm particles(factor of 6, on average) and 0.06–0.3 µm particles (67 %, on average) and a significant decrease (82 %, on average) in 1–4 µmparticles were observed compared to low wind speed periods. These size distribution changes were likely caused by the generation of ultrafineparticles from leads and/or blowing snow, with scavenging of supermicronparticles by blowing snow. At elevated wind speeds, both submicron andsupermicron sodium and chloride mass concentrations were enhanced,consistent with wind-dependent local sea salt aerosol production. Atmoderate wind speeds below the threshold for blowing snow as well as during observed blowing snow, individual sea spray aerosol particles were measured.These individual salt particles were enriched in calcium relative to sodiumin seawater due to the binding of this divalent cation with organic matter in the sea surface microlayer and subsequent enrichment during seawaterbubble bursting. The chemical composition of the surface snowpack alsoshowed contributions from sea spray aerosol deposition. Overall, theseresults show the contribution of sea spray aerosol production from leads onboth aerosols and the surface snowpack. Therefore, if blowing snowsublimation contributed to the observed sea salt aerosol, the snow beingsublimated would have been impacted by sea spray aerosol deposition rather than upward brine migration through the snowpack. Sea spray aerosol production from leads is expected to increase, with thinning and fracturingof sea ice in the rapidly warming Arctic.
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A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I—Model Description
A Lagrangian snow‐evolution model (SnowModel‐LG) was used to produce daily, pan‐Arctic, snow‐on‐sea‐ice, snow property distributions on a 25 × 25‐km grid, from 1 August 1980 through 31 July 2018 (38 years). The model was forced with NASA's Modern Era Retrospective‐Analysis for Research and Applications‐Version 2 (MERRA‐2) and European Centre for Medium‐Range Weather Forecasts (ECMWF) ReAnalysis‐5th Generation (ERA5) atmospheric reanalyses, and National Snow and Ice Data Center (NSIDC) sea ice parcel concentration and trajectory data sets (approximately 61,000, 14 × 14‐km parcels). The simulations performed full surface and internal energy and mass balances within a multilayer snowpack evolution system. Processes and features accounted for included rainfall, snowfall, sublimation from static‐surfaces and blowing‐snow, snow melt, snow density evolution, snow temperature profiles, energy and mass transfers within the snowpack, superimposed ice, and ice dynamics. The simulations produced horizontal snow spatial structures that likely exist in the natural system but have not been revealed in previous studies spanning these spatial and temporal domains. Blowing‐snow sublimation made a significant contribution to the snowpack mass budget. The superimposed ice layer was minimal and decreased over the last four decades. Snow carryover to the next accumulation season was minimal and sensitive to the melt‐season atmospheric forcing (e.g., the average summer melt period was 3 weeks or 50% longer with ERA5 forcing than MERRA‐2 forcing). Observed ice dynamics controlled the ice parcel age (in days), and ice age exerted a first‐order control on snow property evolution.
more » « less- Award ID(s):
- 1820927
- NSF-PAR ID:
- 10375527
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Oceans
- Volume:
- 125
- Issue:
- 10
- ISSN:
- 2169-9275
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract The rate of growth or retreat of the Greenland and Antarctic ice sheets remains a highly uncertain component of future sea level change. Here we examine the simulation of Greenland ice sheet surface mass balance (GrIS SMB) in a development branch of the ModelE2 version of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM). GCMs are often limited in their ability to represent SMB compared with polar region regional climate models. We compare ModelE2‐simulated GrIS SMB for present‐day (1996–2005) simulations with fixed ocean conditions, at a spatial resolution of 2° latitude by 2.5° longitude (~200 km), with SMB simulated by the Modèle Atmosphérique Régionale (MAR) regional climate model (1996–2005 at a 25‐km resolution). ModelE2 SMB agrees well with MAR SMB on the whole, but there are distinct spatial patterns of differences and large differences in some SMB components. The impacts of changes to the ModelE2 surface are tested, including a subgrid‐scale representation of SMB with surface elevation classes. This has a minimal effect on ice sheet‐wide SMB but corrects local biases. Replacing fixed surface albedo with satellite‐derived values and an age‐dependent scheme has a larger impact, increasing simulated melt by 60%–100%. We also find that lower surface albedo can enhance the effects of elevation classes. Reducing ModelE2 surface roughness length to values closer to MAR reduces sublimation by ~50%. Further work is required to account for meltwater refreezing in ModelE2 and to understand how differences in atmospheric processes and model resolution influence simulated SMB.
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Abstract. Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumulative snow water equivalent (SWE) over the sea ice based on snow depth and density retrievals from a SnowMicroPen and approximately weekly measured snow depths along fixed transect paths. We used the derived SWE from the snow cover to compare with precipitation sensors installed during MOSAiC. The data were also compared with ERA5 reanalysis snowfall rates for the drift track. We found an accumulated snow mass of 38 mm SWE between the end of October 2019 and end of April 2020. The initial SWE over first-year ice relative to second-year ice increased from 50 % to 90 % by end of the investigation period. Further, we found that the Vaisala Present Weather Detector 22, an optical precipitation sensor, and installed on a railing on the top deck of research vessel Polarstern, was least affected by blowing snow and showed good agreements with SWE retrievals along the transect. On the contrary, the OTT Pluvio2 pluviometer and the OTT Parsivel2 laser disdrometer were largely affected by wind and blowing snow, leading to too high measured precipitation rates. These are largely reduced when eliminating drifting snow periods in the comparison. ERA5 reveals good timing of the snowfall events and good agreement with ground measurements with an overestimation tendency. Retrieved snowfall from the ship-based Ka-band ARM zenith radar shows good agreements with SWE of the snow cover and differences comparable to those of ERA5. Based on the results, we suggest the Ka-band radar-derived snowfall as an upper limit and the present weather detector on RV Polarstern as a lower limit of a cumulative snowfall range. Based on these findings, we suggest a cumulative snowfall of 72 to 107 mm and a precipitation mass loss of the snow cover due to erosion and sublimation as between 47 % and 68 %, for the time period between 31 October 2019 and 26 April 2020. Extending this period beyond available snow cover measurements, we suggest a cumulative snowfall of 98–114 mm.more » « less
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Abstract. We use the GEOS-Chem chemical transport model to examine theinfluence of bromine release from blowing-snow sea salt aerosol (SSA) onspringtime bromine activation and O3 depletion events (ODEs) in theArctic lower troposphere. We evaluate our simulation against observations oftropospheric BrO vertical column densities (VCDtropo) from the GOME-2 (second Global Ozone Monitoring Experiment)and Ozone Monitoring Instrument (OMI) spaceborne instruments for 3 years (2007–2009), as well asagainst surface observations of O3. We conduct a simulation withblowing-snow SSA emissions from first-year sea ice (FYI; with a surface snowsalinity of 0.1 psu) and multi-year sea ice (MYI; with a surface snowsalinity of 0.05 psu), assuming a factor of 5 bromide enrichment of surfacesnow relative to seawater. This simulation captures the magnitude ofobserved March–April GOME-2 and OMI VCDtropo to within 17 %, as wellas their spatiotemporal variability (r=0.76–0.85). Many of the large-scalebromine explosions are successfully reproduced, with the exception of eventsin May, which are absent or systematically underpredicted in the model. Ifwe assume a lower salinity on MYI (0.01 psu), some of the bromine explosionsevents observed over MYI are not captured, suggesting that blowing snow overMYI is an important source of bromine activation. We find that the modeledatmospheric deposition onto snow-covered sea ice becomes highly enriched inbromide, increasing from enrichment factors of ∼5 inSeptember–February to 10–60 in May, consistent with composition observations of freshly fallen snow. We propose that this progressive enrichment indeposition could enable blowing-snow-induced halogen activation to propagateinto May and might explain our late-spring underestimate in VCDtropo.We estimate that the atmospheric deposition of SSA could increase snow salinityby up to 0.04 psu between February and April, which could be an importantsource of salinity for surface snow on MYI as well as FYI covered by deepsnowpack. Inclusion of halogen release from blowing-snow SSA in oursimulations decreases monthly mean Arctic surface O3 by 4–8 ppbv(15 %–30 %) in March and 8–14 ppbv (30 %–40 %) in April. We reproduce atransport event of depleted O3 Arctic air down to 40∘ Nobserved at many sub-Arctic surface sites in early April 2007. While oursimulation captures 25 %–40 % of the ODEs observed at coastal Arctic surfacesites, it underestimates the magnitude of many of these events and entirelymisses 60 %–75 % of ODEs. This difficulty in reproducing observed surfaceODEs could be related to the coarse horizontal resolution of the model, theknown biases in simulating Arctic boundary layer exchange processes, thelack of detailed chlorine chemistry, and/or the fact that we did not includedirect halogen activation by snowpack chemistry.more » « less
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Abstract A field campaign at Siple Dome in West Antarctica during the austral summer 2019/20 offers an opportunity to evaluate climate model performance, particularly cloud microphysical simulation. Over Antarctic ice sheets and ice shelves, clouds are a major regulator of the surface energy balance, and in the warm season their presence occasionally induces surface melt that can gradually weaken an ice shelf structure. This dataset from Siple Dome, obtained using transportable and solar-powered equipment, includes surface energy balance measurements, meteorology, and cloud remote sensing. To demonstrate how these data can be used to evaluate model performance, comparisons are made with meteorological reanalysis known to give generally good performance over Antarctica (ERA5). Surface albedo measurements show expected variability with observed cloud amount, and can be used to evaluate a model’s snowpack parameterization. One case study discussed involves a squall with northerly winds, during which ERA5 fails to produce cloud cover throughout one of the days. A second case study illustrates how shortwave spectroradiometer measurements that encompass the 1.6-
μ m atmospheric window reveal cloud phase transitions associated with cloud life cycle. Here, continuously precipitating mixed-phase clouds become mainly liquid water clouds from local morning through the afternoon, not reproduced by ERA5. We challenge researchers to run their various regional or global models in a manner that has the large-scale meteorology follow the conditions of this field campaign, compare cloud and radiation simulations with this Siple Dome dataset, and potentially investigate why cloud microphysical simulations or other model components might produce discrepancies with these observations.significance statement Antarctica is a critical region for understanding climate change and sea level rise, as the great ice sheets and the ice shelves are subject to increasing risk as global climate warms. Climate models have difficulties over Antarctica, particularly with simulation of cloud properties that regulate snow surface melting or refreezing. Atmospheric and climate-related field work has significant challenges in the Antarctic, due to the small number of research stations that can support state-of-the-art equipment. Here we present new data from a suite of transportable and solar-powered instruments that can be deployed to remote Antarctic sites, including regions where ice shelves are most at risk, and we demonstrate how key components of climate model simulations can be evaluated against these data.
