Quantifying the Role of Atmospheric Forcing in Ice Edge Retreat and Advance Including Wind-Wave Coupling

LONG-TERM GOALS: 1. Representing surface fluxes and ocean waves in coupled models in the Beaufort and Chukchi Seas. 2. Understand the physics of heat and mass transfer from the ocean to the atmosphere. 3. Improve forecasting of waves on the open ocean and in the marginal ice zone.Award Numbers: N0001413WX20830 (Guest) N0001413IP20046 (Fairall, Persson

Office of Naval Research (ONR), Arctic and Global Prediction Program Department Research Initiative (DRI), Sea State and Boundary Layer Physics of the Emerging Arctic Ocean Quantifying the Role of Atmospheric Forcing in Ice Edge Retreat and Advance Including Wind-Wave Coupling

LONG-TERM GOALS: 1. Representing surface fluxes and ocean waves in coupled models in the Beaufort and Chukchi Seas. 2. Understand the physics of heat and mass transfer from the ocean to the atmosphere. 3. Improve forecasting of waves on the open ocean and in the marginal ice zone.N0001413WX20830 (Guest) N0001413IP20046 (Fairall, Persson

Snowfall and snow accumulation during the MOSAiC winter and spring seasons

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&nbsp;2019 to May&nbsp;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&thinsp;mm SWE between the end of October&nbsp;2019 and end of April&nbsp;2020. The initial SWE over first-year ice relative to second-year ice increased from 50&thinsp;% to 90&thinsp;% by end of the investigation period. Further, we found that the Vaisala Present Weather Detector&nbsp;22, an optical precipitation sensor, and installed on a railing on the top deck of research vessel&nbsp;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&nbsp;Polarstern as a lower limit of a cumulative snowfall range. Based on these findings, we suggest a cumulative snowfall of 72 to 107&thinsp;mm and a precipitation mass loss of the snow cover due to erosion and sublimation as between 47&thinsp;% and 68&thinsp;%, 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&ndash;114&thinsp;mm. &nbsp;</p

Overview of the MOSAiC expedition-Atmosphere INTRODUCTION

With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore crosscutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.Peer reviewe

Atmospheric conditions during the Arctic Clouds in Summer Experiment (ACSE): Contrasting open-water and sea-ice surfaces during melt and freeze-up seasons

The Arctic Clouds in Summer Experiment (ACSE) was conducted during summer and early autumn 2014, providing a detailed view of the seasonal transition from ice melt into freeze-up. Measurements were taken over both ice-free and ice-covered surfaces near the ice edge, offering insight into the role of the surface state in shaping the atmospheric conditions. The initiation of the autumn freeze-up was related to a change in air mass, rather than to changes in solar radiation alone; the lower atmosphere cooled abruptly, leading to a surface heat loss. During melt season, strong surface inversions persisted over the ice, while elevated inversions were more frequent over open water. These differences disappeared during autumn freeze-up, when elevated inversions persisted over both ice-free and ice-covered conditions. These results are in contrast to previous studies that found a well-mixed boundary layer persisting in summer and an increased frequency of surface-based inversions in autumn, suggesting that knowledge derived from measurements taken within the pan-Arctic area and on the central ice pack does not necessarily apply closer to the ice edge. This study offers an insight into the atmospheric processes that occur during a crucial period of the year; understanding and accurately modeling these processes is essential for the improvement of ice-extent predictions and future Arctic climate projections

Warm‐air advection, air mass transformation and fog causes rapid ice melt

Direct observations during intense warm-air advection over the East Siberian Sea reveal a period of rapid sea-ice melt. A semi-stationary, high-pressure system north of the Bering Strait forced northward advection of warm, moist air from the continent. Air-mass transfor-mation over melting sea ice formed a strong, surface-based temperature inversion in which dense fog formed. This induced a positive net longwave radiation at the surface, while reduc-ing net solar radiation only marginally; the inversion also resulted in downward turbulent heat flux. The sum of these processes enhanced the surface energy flux by an average of ~15 W m-2 for a week. Satellite images before and after the episode show sea-ice concentrations decreasing from > 90% to ~50% over a large area affected by the air-mass transformation. We argue that this rapid melt was triggered by the increased heat flux from the atmosphere due to the warm-air advection

The Critical Richardson Number and Limits of Applicability of Local Similarity Theory in the Stable Boundary Layer

Measurements of atmospheric turbulence made over the Arctic pack ice during the Surface Heat Budget of the Arctic Ocean experiment (SHEBA) are used to determine the limits of applicability of Monin-Obukhov similarity theory (in the local scaling formulation) in the stable atmospheric boundary layer. Based on the spectral analysis of wind velocity and air temperature fluctuations, it is shown that, when both of the gradient Richardson number, Ri, and the flux Richardson number, Rf, exceed a 'critical value' of about 0.20 - 0.25, the inertial subrange associated with the Richardson-Kolmogorov cascade dies out and vertical turbulent fluxes become small. Some small-scale turbulence survives even in this supercritical regime, but this is non-Kolmogorov turbulence, and it decays rapidly with further increasing stability. Similarity theory is based on the turbulent fluxes in the high-frequency part of the spectra that are associated with energy-containing/flux-carrying eddies. Spectral densities in this high-frequency band diminish as the Richardson-Kolmogorov energy cascade weakens; therefore, the applicability of local Monin-Obukhov similarity theory in stable conditions is limited by the inequalities Ri < Ri_cr and Rf < Rf_cr. However, it is found that Rf_cr = 0.20 - 0.25 is a primary threshold for applicability. Applying this prerequisite shows that the data follow classical Monin-Obukhov local z-less predictions after the irrelevant cases (turbulence without the Richardson-Kolmogorov cascade) have been filtered out.Comment: Boundary-Layer Meteorology (Manuscript submitted: 16 February 2012; Accepted: 10 September 2012

Overview of the MOSAiC expedition - Atmosphere

With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic