Measurements of Atmospheric Variability during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Expedition

Mapping Intimacies ◽

10.5194/ems2021-37 ◽

2021 ◽

Author(s):

Julia Schmale ◽

Keyword(s):

Sea Ice ◽

Large Scale ◽

High Arctic ◽

Physical Structure ◽

Surface Energy Budget ◽

Arctic Climate ◽

Cloud Formation ◽

The Arctic ◽

Atmospheric Variability ◽

Atmospheric Measurements

The MOSAiC expedition was designed to better understand the local and remote processes influencing the Arctic climate system. The Arctic is warming two to three times faster than the global average, a process known as Arctic amplification. One of the most significant consequences is the retreat of sea ice, which has already diminished by roughly 40 % since satellite measurements began. The Arctic atmospheric, marine and terrestrial changes have important effects on local processes, such as moisture sources, cloud formation, radiative and energy transfer, amongst other. They also have the potential to induce changes to large-scale circulation, which can impact the mid-latitudes of Eurasia and North America. &#160;&#160;&#160;Between September 2019 and October 2020 the MOSAiC expedition performed a large number of atmospheric measurements in the high Arctic, drifting most of the time with the sea ice. Instrumentation was operated from the icebreaker Polarstern (Alfred Wegener Institute), on the sea ice and on flying platforms. Observations covered generally: (i) the atmospheric physical structure (e.g., temperature, humidity, wind speed and direction profiles) with radio soundings, ground-based remote sensing, as well as towers; (ii) clouds and precipitation with a host of lidars, radars and radiometers, as well as distrometers and specific hydrometeor observations; (iii) aerosols and trace gases with real-time measurements as well as offline techniques for chemical and microphysical properties; and (iv) the surface energy budget with measurements of radiation, turbulent fluxes and conductive fluxes. &#160;The year-round measurements allow for the study of atmospheric variability during the annual cycle with the important processes of sea ice freeze-up and melting. Other event-based features, such as warm air mass intrusions, cyclones, storms, and lead opening, were studied in detail to understand the implications of these processes for the Arctic system. MOSAiC observations are in addition contributing to the evaluation of satellite-based observations such as radiation fluxes or cloud properties, as well as to the evaluation and improvement of numerical simulations, ranging from simpler box to complex Earth System Models. &#160;This presentation will provide an overview of the first atmospheric observational results during MOSAiC.

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Arctic Ocean sea ice snow depth evaluation and bias sensitivity in CCSM

The Cryosphere Discussions ◽

10.5194/tcd-7-1495-2013 ◽

2013 ◽

Vol 7 (2) ◽

pp. 1495-1532 ◽

Cited By ~ 6

Author(s):

B. A. Blazey ◽

M. M. Holland ◽

E. C. Hunke

Keyword(s):

Sea Ice ◽

Arctic Ocean ◽

Large Scale ◽

System Model ◽

Arctic Climate ◽

The Arctic ◽

Blowing Snow ◽

Climate System Model ◽

The Arctic Ocean ◽

Ice Conditions

Abstract. Sea ice cover in the Arctic Ocean is a continued focus of attention. This study assesses the capability of hindcast simulations of the Community Climate System Model (CCSM) to reproduce observed snow depths and densities overlying the Arctic Ocean sea ice. The model is evaluated using measurements provided by historic Russian polar drift stations. Following the identification of seasonal biases produced in the simulations, the thermodynamic transfer through the snow – ice column is perturbed to determine model sensitivity to these biases. This study concludes that perturbations on the order of the observed biases result in modification of the annual mean conductive flux of 0.5 W m−2 relative to an unmodified simulation. The results suggest that the ice has a complex response to snow characteristics, with ice of different thicknesses producing distinct reactions. Consequently, we suggest that the inclusion of additional snow evolution processes such as blowing snow, densification, and seasonal changes in snow conductivity in sea ice models would increase the fidelity of the model with respect to the physical system. Moreover, our results suggest that simulated high latitude precipitation biases have important effects on the simulated ice conditions, resulting in impacts on the Arctic climate in general in large-scale climate.

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Atmospheric processes in the Central Arctic during MOSAiC

10.5194/egusphere-egu21-10447 ◽

2021 ◽

Author(s):

Matthew Shupe ◽

Markus Rex ◽

Keyword(s):

Sea Ice ◽

Large Scale ◽

Model Development ◽

Surface Fluxes ◽

Climate System ◽

Assessment Model ◽

Arctic Climate ◽

The Arctic ◽

Model Assessment ◽

Research Activities

The atmosphere plays a central role in the Arctic climate system and its recent changes. Enhanced Arctic atmospheric warming over the past decades is linked with many key processes, including variability in large-scale circulation patterns, changes in fluxes of heat, sea-ice decline, impacts on the ecosystem, and many more. It is this collection of interdependent processes, and their recent changes, that has motivated the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC, 2019-2020) expedition. Based on the Polarstern icebreaker, an international and interdisciplinary team of scientists conducted an intensive, year-long scientific exploration of the Central Arctic climate system while drifting with the sea ice. This presentation highlights the atmospheric components of this scientific expedition. These include the most comprehensive set of field observations to ever be made of the Central Arctic atmosphere, spanning from the stratosphere to the surface. Specific research activities examine atmospheric structure, winds, clouds, precipitation, aerosols, and surface fluxes of heat, momentum, gases, and moisture. Complementing these observational aspects are numerous modeling activities, including observation-based model assessment, model development, and regional process studies, among others. Finally, key links between the atmosphere and the sea ice, snow, and ocean through a variety of physical, chemical, and biological processes are discussed.

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Evaluating Arctic meteorology modelled with the Unified Model and Integrated Forecasting System

10.5194/egusphere-egu2020-9643 ◽

2020 ◽

Author(s):

Gillian Young ◽

Jutta Vüllers ◽

Peggy Achtert ◽

Paul Field ◽

Jonathan Day ◽

...

Keyword(s):

Boundary Layer ◽

Sea Ice ◽

Weather Forecasting ◽

Numerical Models ◽

Model Performance ◽

High Arctic ◽

Unified Model ◽

Surface Energy Budget ◽

The Arctic ◽

Forecasting System

State-of-the-art numerical models such as the UK Met Office Unified Model and European Centre for Medium-Range Weather Forecasting Integrated Forecasting System are crucial tools for forecasting future Arctic warming. However, their ability to reproduce clouds and boundary layer meteorology in the high Arctic has not been thoroughly evaluated following significant model developments over the last 10 years. Model evaluation is key to understanding where remaining process weaknesses lie, thus informing further parametrization developments to improve the simulated surface energy budget.Here, we evaluate model performance with comparison to observations made during the Arctic Ocean 2018 expedition, where a suite of remote-sensing instrumentation was active aboard the Swedish icebreaker Oden measuring summertime Arctic cloud and boundary layer properties. We find that both models do not reproduce cloud fractions well at altitude (up to 8 km) and overestimate the occurrence of low (<1 km) clouds during the sea ice melt period of the expedition. Low cloud agreement with observations improves when the sea ice begins to refreeze; however, the underestimation of cloud aloft remains consistent regardless of sea ice conditions. In this presentation, we will indicate which model processes need to be improved to capture these summertime Arctic clouds more effectively.

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Relative contributions of internal atmospheric variability and surface processes to the interannual variations in wintertime Arctic surface air temperatures

Journal of Climate ◽

10.1175/jcli-d-20-0779.1 ◽

2021 ◽

pp. 1-48

Author(s):

Fengmin Wu ◽

Wenkai Li ◽

Peng Zhang ◽

Wei Li

Keyword(s):

Sea Ice ◽

Large Scale ◽

Surface Air Temperature ◽

Surface Processes ◽

The Arctic ◽

Interannual Variations ◽

Atmospheric Variability ◽

Near Surface ◽

Atmospheric Circulations ◽

Downward Longwave Radiation

AbstractSuperimposed on a warming trend, Arctic winter surface air temperature (SAT) exhibits substantial interannual variability, whose underlying mechanisms are unclear, especially regarding the role of sea-ice variations and atmospheric processes. Here, atmospheric reanalysis data and idealized atmospheric model simulations are used to reveal the mechanisms by which sea-ice variations and atmospheric anomalous conditions affect interannual variations in wintertime Arctic SAT. Results show that near-surface interannual warming in the Arctic is accompanied by comparable warming throughout large parts of the Arctic troposphere and large-scale anomalous atmospheric circulation patterns. Within the Arctic, changes in large-scale atmospheric circulations due to internal atmospheric variability explain a substantial fraction of interannual variation in SAT and tropospheric temperatures, which lead to an increase in moisture and downward longwave radiation, with the rest likely coming from sea ice-related and other surface processes. Arctic winter sea-ice loss allows the ocean to release more heat and moisture, which enhances Arctic warming; however, this effect on SAT is confined to the ice-retreat area and has a limited influence on large-scale atmospheric circulations.

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Large-scale patterns preceding Arctic warm events

10.5194/egusphere-egu2020-13541 ◽

2020 ◽

Author(s):

Sonja Murto ◽

Rodrigo Caballero ◽

Gunilla Svensson

Keyword(s):

Sea Ice ◽

Large Scale ◽

High Arctic ◽

Arctic Sea Ice ◽

The Arctic ◽

Identification Algorithm ◽

Geophysical Research ◽

Upper Level ◽

Almost All

Atmospheric blockings are defined as quasi-stationary synoptic-scale systems of high pressure that can influence different weather events. Previous studies have examined the role of blockings in favoring intense poleward moisture transport into the Arctic and the role of polar anticyclones to Arctic sea-ice loss (e.g. Woods et al. 2013; Wernli & Papritz 2018). However, the mechanisms and theories for blocking formation and maintenance, in combination with their contributions to the Arctic climate, are yet not fully understood. This study presents a detailed northern hemisphere climatological analysis of large-scale patterns during 50 warm events of extreme wintertime (NDJFM) Arctic surface temperature anomalies, as defined by Messori et al. (2018), for the ERA-Interim period of 1979-2016. In contrast to the previous mentioned study, the main focus in this study is to relate the warm events with atmospheric blockings, identified as upper level anticyclonic PV anomalies following a dynamically-based blocking identification algorithm (Schwierz et al. 2004). In order to classify the events by their spatially and temporally varying blocking patterns, we calculate regional averages of the blocking frequencies for sector areas defined above 50 &#176;N. General patterns and anomalies in meteorological variables in the different area clusters are quantified. Based on the blocking fractions for 90th and 95th percentiles, we can relate up to 80 % of the warm events to strong blockings. Additionally, we show that the remaining events obtain similar patterns, though with weaker or shorter-lived blocks. Overall, it can be conducted that almost all warm events in the clusters precede with a significant blocking located in the area around the Urals and the nearby parts of the Arctic Ocean. Despite the similarities found in the high Arctic for most of the events, there are different patterns identified in the periphery between the clusters. A North-Atlantic block is often found in the same cluster as with the Ural blocking, however with some temporal lag prior to the latter one. Therefore, the connection with the NAO-index during the warm events is also investigated. Our study gives a deeper insight into the large-scale patterns and emphasizes the importance of the large-scale settings prior to the Arctic warm events, primarily focusing on the importance of the atmospheric blockings. The formation of these blockings and the dynamical processes on different scales driving these warm events are further discussed using trajectory-analysis in an upcoming study. These two studies aim to improve the understanding of the preconditions needed for these Arctic warm events to occur and, furthermore, the mechanisms that control these events in high latitudes.&#160;Woods, C., Caballero, R., & Svensson, G. (2013). Large-scale circulation associated with moisture intrusions into the Arctic during winter. Geophysical Research Letters, 40(17), 4717-4721.Wernli, H., & Papritz, L. (2018). Role of polar anticyclones and mid-latitude cyclones for Arctic summertime sea-ice melting.&#160;Nature Geoscience,&#160;11(2), 108.Messori, G., Woods, C., & Caballero, R. (2018). On the drivers of wintertime temperature extremes in the High Arctic.&#160;Journal of Climate,&#160;31(4), 1597&#8211;1618.Schwierz, C., Croci-Maspoli, M. & Davies, H. C. 2004). Perspicacious indicators of atmospheric blocking. Geophys. Res. Lett. 31, L06125.

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Cryospheric Impacts of Soviet River Diversion Schemes

Annals of Glaciology ◽

10.3189/1984aog5-1-61-68 ◽

1984 ◽

Vol 5 ◽

pp. 61-68 ◽

Cited By ~ 4

Author(s):

T. Holt ◽

P. M. Kelly ◽

B. S. G. Cherry

Keyword(s):

Sea Ice ◽

Arctic Ocean ◽

River Discharge ◽

Large Scale ◽

Arctic Sea Ice ◽

The Arctic ◽

Sea Ice Concentration ◽

Ice Concentration ◽

The Arctic Ocean ◽

The Impact

Soviet plans to divert water from rivers flowing into the Arctic Ocean have led to research into the impact of a reduction in discharge on Arctic sea ice. We consider the mechanisms by which discharge reductions might affect sea-ice cover and then test various hypotheses related to these mechanisms. We find several large areas over which sea-ice concentration correlates significantly with variations in river discharge, supporting two particular hypotheses. The first hypothesis concerns the area where the initial impacts are likely to which is the Kara Sea. Reduced riverflow is associated occur, with decreased sea-ice concentration in October, at the time of ice formation. This is believed to be the result of decreased freshening of the surface layer. The second hypothesis concerns possible effects on the large-scale current system of the Arctic Ocean and, in particular, on the inflow of Atlantic and Pacific water. These effects occur as a result of changes in the strength of northward-flowing gradient currents associated with variations in river discharge. Although it is still not certain that substantial transfers of riverflow will take place, it is concluded that the possibility of significant cryospheric effects and, hence, large-scale climate impact should not be neglected.

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Near Real Time Arctic sea ice thickness and volume from CryoSat-2

10.5194/tc-2016-21 ◽

2016 ◽

Cited By ~ 3

Author(s):

R. L. Tilling ◽

A. Ridout ◽

A. Shepherd

Keyword(s):

Sea Ice ◽

Real Time ◽

Arctic Sea Ice ◽

Arctic Climate ◽

The Arctic ◽

Ice Thickness ◽

Satellite Orbits ◽

Sea Ice Thickness ◽

Arctic Sea ◽

Arctic Sea Ice Thickness

Abstract. Timely observations of sea ice thickness help us to understand Arctic climate, and can support maritime activities in the Polar Regions. Although it is possible to calculate Arctic sea ice thickness using measurements acquired by CryoSat-2, the latency of the final release dataset is typically one month, due to the time required to determine precise satellite orbits. We use a new fast delivery CryoSat-2 dataset based on preliminary orbits to compute Arctic sea ice thickness in near real time (NRT), and analyse this data for one sea ice growth season from October 2014 to April 2015. We show that this NRT sea ice thickness product is of comparable accuracy to that produced using the final release CryoSat-2 data, with an average thickness difference of 5 cm, demonstrating that the satellite orbit is not a critical factor in determining sea ice freeboard. In addition, the CryoSat-2 fast delivery product also provides measurements of Arctic sea ice thickness within three days of acquisition by the satellite, and a measurement is delivered, on average, within 10, 7 and 6 km of each location in the Arctic every 2, 14 and 28 days respectively. The CryoSat-2 NRT sea ice thickness dataset provides an additional constraint for seasonal predictions of Arctic climate change, and will allow industries such as tourism and transport to navigate the polar oceans with safety and care.

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Sea ice melt pond fraction estimation from dual-polarisation C-band SAR – Part 2: Scaling in situ to Radarsat-2

The Cryosphere Discussions ◽

10.5194/tcd-8-845-2014 ◽

2014 ◽

Vol 8 (1) ◽

pp. 845-885 ◽

Cited By ~ 1

Author(s):

R. K. Scharien ◽

K. Hochheim ◽

J. Landy ◽

D. G. Barber

Keyword(s):

Sea Ice ◽

Large Scale ◽

Temporal Frequency ◽

Model Performance ◽

Free Water ◽

Light Transmittance ◽

The Arctic ◽

Ice Melt ◽

Melt Pond

Abstract. Observed changes in the Arctic have motivated efforts to understand and model its components as an integrated and adaptive system at increasingly finer scales. Sea ice melt pond fraction, an important summer sea ice component affecting surface albedo and light transmittance across the ocean-sea ice–atmosphere interface, is inadequately parameterized in models due to a lack of large scale observations. In this paper, results from a multi-scale remote sensing program dedicated to the retrieval of pond fraction from satellite C-band synthetic aperture radar (SAR) are detailed. The study was conducted on first-year sea (FY) ice in the Canadian Arctic Archipelago during the summer melt period in June 2012. Approaches to retrieve the subscale FY ice pond fraction from mixed pixels in RADARSAT-2 imagery, using in situ, surface scattering theory, and image data are assessed. Each algorithm exploits the dominant effect of high dielectric free-water ponds on the VV/HH polarisation ratio (PR) at moderate to high incidence angles (about 40° and above). Algorithms are applied to four images corresponding to discrete stages of the seasonal pond evolutionary cycle, and model performance is assessed using coincident pond fraction measurements from partitioned aerial photos. A RMSE of 0.07, across a pond fraction range of 0.10 to 0.70, is achieved during intermediate and late seasonal stages. Weak model performance is attributed to wet snow (pond formation) and synoptically driven pond freezing events (all stages), though PR has utility for identification of these events when considered in time series context. Results demonstrate the potential of wide-swath, dual-polarisation, SAR for large-scale observations of pond fraction with temporal frequency suitable for process-scale studies and improvements to model parameterizations.

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Recent advances in understanding the Arctic climate system state and change from a sea ice perspective: a review

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-14-10929-2014 ◽

2014 ◽

Vol 14 (7) ◽

pp. 10929-10999 ◽

Cited By ~ 3

Author(s):

R. Döscher ◽

T. Vihma ◽

E. Maksimovich

Keyword(s):

Global Warming ◽

Sea Ice ◽

Ice Cover ◽

Arctic Sea Ice ◽

Climate System ◽

Arctic Climate ◽

The Arctic ◽

Atlantic Sector ◽

Sea Ice Decline ◽

Arctic Sea

Abstract. The Arctic sea ice is the central and essential component of the Arctic climate system. The depletion and areal decline of the Arctic sea ice cover, observed since the 1970's, have accelerated after the millennium shift. While a relationship to global warming is evident and is underpinned statistically, the mechanisms connected to the sea ice reduction are to be explored in detail. Sea ice erodes both from the top and from the bottom. Atmosphere, sea ice and ocean processes interact in non-linear ways on various scales. Feedback mechanisms lead to an Arctic amplification of the global warming system. The amplification is both supported by the ice depletion and is at the same time accelerating the ice reduction. Knowledge of the mechanisms connected to the sea ice decline has grown during the 1990's and has deepened when the acceleration became clear in the early 2000's. Record summer sea ice extents in 2002, 2005, 2007 and 2012 provided additional information on the mechanisms. This article reviews recent progress in understanding of the sea ice decline. Processes are revisited from an atmospheric, ocean and sea ice perspective. There is strong evidence for decisive atmospheric changes being the major driver of sea ice change. Feedbacks due to reduced ice concentration, surface albedo and thickness allow for additional local atmosphere and ocean influences and self-supporting feedbacks. Large scale ocean influences on the Arctic Ocean hydrology and circulation are highly evident. Northward heat fluxes in the ocean are clearly impacting the ice margins, especially in the Atlantic sector of the Arctic. Only little indication exists for a direct decisive influence of the warming ocean on the overall sea ice cover, due to an isolating layer of cold and fresh water underneath the sea ice.

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