scholarly journals Ship-based estimates of momentum transfer coefficient over sea ice and recommendations for its parameterization

2021 ◽  
Author(s):  
Piyush Srivastava ◽  
Ian M. Brooks ◽  
John Prytherch ◽  
Dominic J. Salisbury ◽  
Andrew D. Elvidge ◽  
...  
Keyword(s):  
Sea Ice ◽  
Late Summer ◽  
The Arctic ◽  
Climate Projections ◽  
Surface Drag ◽  
Momentum Exchange ◽  
Surface Exchange ◽  
Arctic Clouds ◽  
Wide Range ◽  
Automated Processing

Abstract. A major source of uncertainty in both climate projections and seasonal forecasting of sea ice is inadequate representation of surface–atmosphere exchange processes. The observations needed to improve understanding and reduce uncertainty in surface exchange parameterizations are challenging to make and rare. Here we present a large dataset of ship-based measurements of surface momentum exchange (surface drag) in the vicinity of sea ice from the Arctic Clouds in Summer Experiment (ACSE) in July–October 2014, and the Arctic Ocean 2016 experiment (AO2016) in August–September 2016. The combined dataset provides an extensive record of momentum flux over a wide range of surface conditions spanning the late summer melt and early autumn freeze-up periods, and a wide range of atmospheric stabilities. Surface exchange coefficients are estimated from in situ eddy covariance measurements. The local sea-ice fraction is determined via automated processing of imagery from ship-mounted cameras. The surface drag coefficient, CD10n, peaks at local ice fractions of 0.6–0.8, consistent with both recent aircraft-based observations and theory. Two state-of-the-art parameterizations have been tuned to our observations with both providing excellent fits to the measurements.

Airborne in-situ observations of Arctic clouds in spring and summer above sea ice and the open ocean

2021 ◽  
Author(s):  
Manuel Moser ◽  
Christiane Voigt ◽  
Valerian Hahn ◽  
Olivier Jourdan ◽  
Christophe Gourbeyre ◽  
...  
Keyword(s):  
Sea Ice ◽  
Water Content ◽  
Late Summer ◽  
Open Ocean ◽  
The Arctic ◽  
Arctic Clouds ◽  
Cloud Properties ◽  
Cloud Water Content ◽  
Median Volume ◽  
Ice Water

<p>Two airborne campaigns (AFLUX and MOSAiC-ACA) were conducted in spring 2019 and late summer 2020 to investigate low- and midlevel clouds and related atmospheric parameters in the central Arctic. The measurements aim at better understanding the role of Arctic clouds and their interactions with the surface - open ocean or sea ice - in light of amplified climate change in the Arctic.<br>During the campaigns the Basler BT-67 research aircraft Polar 5 based in Svalbard (78.24 N, 15.49 E) equipped with a comprehensive in-situ cloud payload performed in total 24 flights over the Arctic ocean and in the Fram Strait. A combination of size spectrometers (CDP and CAS) and 2-dimensional imaging probes (CIP and PIP) covering the size range of Arctic cloud hydrometeors from 0.5µm to 6.2mm measured the total particle number concentration, the particle size distribution and the median volume diameter. Liquid water content and ice water content were measured with the Nevzorov bulk probe. The cloud water content (liquid and ice water content) from the Nevzorov probe is compared to the cloud water content derived from particle size measurements using consistent mass-dimension relationships.<br>Here we give an overview of the microphysical cloud properties measured in spring and late summer in high northern latitudes at altitudes up to 4 km. We derive the temperature and altitude dependence of liquid, mixed phase and ice cloud properties and investigate their seasonal variability. Differences in cloud properties above the sea ice and the open ocean are examined, supporting the hypothesis of an enhanced median volume diameter over open ocean compared to clouds formed over the sea ice. The comprehensive data set on microphysical cloud properties enhances our understanding of cloud formation and mixed phase cloud processes over the Arctic ocean, it can be used to validate remote sensing retrievals and models and helps to assess the role of clouds for stronger impact of climate change in the Arctic. </p>

scholarly journals A Robust Arctic Amplification Factor Throughout the Last 21,000 Years

2022 ◽  
Author(s):  
Yuzhen Yan ◽  
Xinyu Wen
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Projections ◽  
Arctic Amplification ◽  
The Past ◽  
Wide Range ◽  
Arctic Sea ◽  
New Evidence

Abstract Arctic amplification (AA), a phenomenon that a larger change in temperature near the Arctic areas than the Northern Hemisphere average in the past 100+ years, has significant impacts on mid-latitude weather and climate, and therefore is of great concern in current climate projections. Previous studies suggest a wide range of AA factors from 1.0 to 12.5 using either the 20th century observations or climate model hindcasts. In the present paper, we explore the diversity of AA factor in a long-term transient simulation covering the past glacial-to-interglacial years. It is shown that the natural AA phenomenon is essentially linked with North Atlantic sea ice changes through ice-albedo feedback with a narrowed and robust AA factor of 2.5±0.8 throughout the last 21,000 years. Current observed AA phenomenon is a mixed result combining sea ice melting induced AA mode with GHGs induced global uniform warming, and thus has an AA factor slightly less than 2.5. In the future, as Arctic sea ice gradually melts off, we speculate that AA phenomenon might fade off accordingly and the AA factor will decline close to 1.0 in 1-2 centuries. Our findings provide new evidence for better understanding the range of AA factor and associated key physical processes, and provide new insights for AA’s projection in current anthropogenic warming climate.

Investigations of past climate and sea-ice variability in the fjord area by Station Nord, eastern North Greenland

1969 ◽  
Vol 35 ◽  
pp. 67-70 ◽  
Author(s):  
Niels Nørgaard-Pedersen ◽  
Sofia Ribeiro ◽  
Naja Mikkelsen ◽  
Audrey Limoges ◽  
Marit-Solveig Seidenkrantz
Keyword(s):  
Sea Ice ◽  
Outer Part ◽  
Late Summer ◽  
Field Work ◽  
The Arctic ◽  
Research Station ◽  
Fjord System ◽  
Sea Bottom ◽  
Satellite Radar ◽  
North Greenland

The marine record of the Independence–Danmark fjord system extending out to the Wandel Hav in eastern North Greenland (Fig. 1A) is little known due to the almost perennial sea-ice cover, which makes the region inaccessible for research vessels (Nørgaard-Pedersen et al. 2008), and only a few depth measurements have been conducted in the area. In 2015, the Villum Research Station, a new logistic base for scientific investigations, was opened at Station Nord. In contrast to the early exploration of the region, it is now possible to observe and track the seasonal character and changes of ice in the fjord system and the Arctic Ocean through remote sensing by satellite radar systems. Satellite data going back to the early 1980s show that the outer part of the Independence–Danmark fjord system is characterised by perennial sea ice whereas both the southern part of the fjord system and an area 20–30 km west of Station Nord are partly ice free during late summer (Fig. 1B). Hence, marine-orientated field work can be conducted from the sea ice using snow mobiles, and by drilling through the ice to reach the underlying water and sea bottom.

scholarly journals The Influence of Cloud and Surface Properties on the Arctic Ocean Shortwave Radiation Budget in Coupled Models*

2008 ◽  
Vol 21 (5) ◽  
pp. 866-882 ◽  
Author(s):  
Irina V. Gorodetskaya ◽  
L-Bruno Tremblay ◽  
Beate Liepert ◽  
Mark A. Cane ◽  
Richard I. Cullather
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Liquid Water ◽  
Surface Albedo ◽  
Liquid Water Content ◽  
Radiation Budget ◽  
The Arctic ◽  
Coupled Models ◽  
Arctic Clouds ◽  
The Arctic Ocean

Abstract The impact of Arctic sea ice concentrations, surface albedo, cloud fraction, and cloud ice and liquid water paths on the surface shortwave (SW) radiation budget is analyzed in the twentieth-century simulations of three coupled models participating in the Intergovernmental Panel on Climate Change Fourth Assessment Report. The models are the Goddard Institute for Space Studies Model E-R (GISS-ER), the Met Office Third Hadley Centre Coupled Ocean–Atmosphere GCM (UKMO HadCM3), and the National Center for Atmosphere Research Community Climate System Model, version 3 (NCAR CCSM3). In agreement with observations, the models all have high Arctic mean cloud fractions in summer; however, large differences are found in the cloud ice and liquid water contents. The simulated Arctic clouds of CCSM3 have the highest liquid water content, greatly exceeding the values observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) campaign. Both GISS-ER and HadCM3 lack liquid water and have excessive ice amounts in Arctic clouds compared to SHEBA observations. In CCSM3, the high surface albedo and strong cloud SW radiative forcing both significantly decrease the amount of SW radiation absorbed by the Arctic Ocean surface during the summer. In the GISS-ER and HadCM3 models, the surface and cloud effects compensate one another: GISS-ER has both a higher summer surface albedo and a larger surface incoming SW flux when compared to HadCM3. Because of the differences in the models’ cloud and surface properties, the Arctic Ocean surface gains about 20% and 40% more solar energy during the melt period in the GISS-ER and HadCM3 models, respectively, compared to CCSM3. In twenty-first-century climate runs, discrepancies in the surface net SW flux partly explain the range in the models’ sea ice area changes. Substantial decrease in sea ice area simulated during the twenty-first century in CCSM3 is associated with a large drop in surface albedo that is only partly compensated by increased cloud SW forcing. In this model, an initially high cloud liquid water content reduces the effect of the increase in cloud fraction and cloud liquid water on the cloud optical thickness, limiting the ability of clouds to compensate for the large surface albedo decrease. In HadCM3 and GISS-ER, the compensation of the surface albedo and cloud SW forcing results in negligible changes in the net SW flux and is one of the factors explaining moderate future sea ice area trends. Thus, model representations of cloud properties for today’s climate determine the ability of clouds to compensate for the effect of surface albedo decrease on the future shortwave radiative budget of the Arctic Ocean and, as a consequence, the sea ice mass balance.

scholarly journals First in situ estimations of small phytoplankton carbon and nitrogen uptake rates in the Kara, Laptev, and East Siberian seas

2018 ◽  
Author(s):  
Bhavya P. Sadanandan ◽  
Jang Han Lee ◽  
Ho Won Lee ◽  
Jae Joong Kaang ◽  
Jae Hyung Lee ◽  
...  
Keyword(s):  
Sea Ice ◽  
Nitrogen Uptake ◽  
N Uptake ◽  
Total Carbon ◽  
The Arctic ◽  
Carbon And Nitrogen ◽  
Uptake Rates ◽  
Wide Range ◽  
Small Phytoplankton

Abstract. Carbon and nitrogen uptake rates by small phytoplankton (0.7–5 μm) in the Kara, Laptev, and East Siberian seas in the Arctic Ocean were quantified using in situ isotope labelling experiments for the first time as part of the NABOS (Nansen and Amundsen Basins Observational System) program during August 21 to September 22, 2013. The depth integrated C, NO3−, and NH4+ uptake rates by small phytoplankton showed a wide range from 0.54 to 15.96 mg C m−2 h−1, 0.05 to 1.02 and 0.11 to 3.73 mg N m−2 h−1, respectively. The contributions of small phytoplankton towards the total C, NO3−, and NH4+ was varied from 24 to 89 %, 32 to 89 %, and 28 to 89 %, respectively. The turnover times for NO3− and NH4+ by small phytoplankton during the present study point towards the longer residence times (years) of the nutrients in the deeper waters, particularly for NO3−. Relatively, higher C and N uptake rates by small phytoplankton obtained during the present study at locations with less sea ice concentrations points towards the possibility of small phytoplankton thrive under sea ice retreat under warming conditions. The high contributions of small phytoplankton towards the total carbon and nitrogen uptake rates suggest capability of small size autotrophs to withstand in the adverse hydrographic conditions introduced by climate change.

scholarly journals Variability scaling and consistency in airborne and satellite altimetry measurements of Arctic sea ice

2020 ◽  
Vol 14 (2) ◽  
pp. 751-767
Author(s):  
Shiming Xu ◽  
Lu Zhou ◽  
Bin Wang
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Snow Depth ◽  
Spatial Scales ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
First Year ◽  
Noise Levels ◽  
Wide Range

Abstract. Satellite and airborne remote sensing provide complementary capabilities for the observation of the sea ice cover. However, due to the differences in footprint sizes and noise levels of the measurement techniques, as well as sea ice's variability across scales, it is challenging to carry out inter-comparison or consistently study these observations. In this study we focus on the remote sensing of sea ice thickness parameters and carry out the following: (1) the analysis of variability and its statistical scaling for typical parameters and (2) the consistency study between airborne and satellite measurements. By using collocating data between Operation IceBridge and CryoSat-2 (CS-2) in the Arctic, we show that consistency exists between the variability in radar freeboard estimations, although CryoSat-2 has higher noise levels. Specifically, we notice that the noise levels vary among different CryoSat-2 products, and for the European Space Agency (ESA) CryoSat-2 freeboard product the noise levels are at about 14 and 20 cm for first-year ice (FYI) and multi-year ice (MYI), respectively. On the other hand, for Operation IceBridge and NASA's Ice, Cloud, and land Elevation Satellite (ICESat), it is shown that the variability in snow (or total) freeboard is quantitatively comparable despite more than a 5-year time difference between the two datasets. Furthermore, by using Operation IceBridge data, we also find widespread negative covariance between ice freeboard and snow depth, which only manifests on small spatial scales (40 m for first-year ice and about 80 to 120 m for multi-year ice). This statistical relationship highlights that the snow cover reduces the overall topography of the ice cover. Besides this, there is prevalent positive covariability between snow depth and snow freeboard across a wide range of spatial scales. The variability and consistency analysis calls for more process-oriented observations and modeling activities to elucidate key processes governing snow–ice interaction and sea ice variability on various spatial scales. The statistical results can also be utilized in improving both radar and laser altimetry as well as the validation of sea ice and snow prognostic models.

scholarly journals neXtSIM: a new Lagrangian sea ice model

2016 ◽  
Vol 10 (3) ◽  
pp. 1055-1073 ◽  
Author(s):  
Pierre Rampal ◽  
Sylvain Bouillon ◽  
Einar Ólason ◽  
Mathieu Morlighem
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Dynamical Response ◽  
Ice Dynamics ◽  
Ice Drift ◽  
Wide Range ◽  
Arctic Sea ◽  
Sea Ice Drift ◽  
Ice Model

Abstract. The Arctic sea ice cover has changed drastically over the last decades. Associated with these changes is a shift in dynamical regime seen by an increase of extreme fracturing events and an acceleration of sea ice drift. The highly non-linear dynamical response of sea ice to external forcing makes modelling these changes and the future evolution of Arctic sea ice a challenge for current models. It is, however, increasingly important that this challenge be better met, both because of the important role of sea ice in the climate system and because of the steady increase of industrial operations in the Arctic. In this paper we present a new dynamical/thermodynamical sea ice model called neXtSIM that is designed to address this challenge. neXtSIM is a continuous and fully Lagrangian model, whose momentum equation is discretised with the finite-element method. In this model, sea ice physics are driven by the combination of two core components: a model for sea ice dynamics built on a mechanical framework using an elasto-brittle rheology, and a model for sea ice thermodynamics providing damage healing for the mechanical framework. The evaluation of the model performance for the Arctic is presented for the period September 2007 to October 2008 and shows that observed multi-scale statistical properties of sea ice drift and deformation are well captured as well as the seasonal cycles of ice volume, area, and extent. These results show that neXtSIM is an appropriate tool for simulating sea ice over a wide range of spatial and temporal scales.

scholarly journals A Decade of Spaceborne Observations of the Arctic Atmosphere: Novel Insights from NASA’s AIRS Instrument

2016 ◽  
Vol 97 (11) ◽  
pp. 2163-2176 ◽  
Author(s):  
Abhay Devasthale ◽  
Joseph Sedlar ◽  
Brian H. Kahn ◽  
Michael Tjernström ◽  
Eric J. Fetzer ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Numerical Models ◽  
Lower Troposphere ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Projections ◽  
Polar Regions ◽  
Arctic Atmosphere ◽  
Warming World

Abstract Arctic sea ice is declining rapidly and its annual ice extent minima reached record lows twice during the last decade. Large environmental and socioeconomic implications related to sea ice reduction in a warming world necessitate realistic simulations of the Arctic climate system, not least to formulate relevant environmental policies on an international scale. However, despite considerable progress in the last few decades, future climate projections from numerical models still exhibit the largest uncertainties over the polar regions. The lack of sufficient observations of essential climate variables is partly to blame for the poor representation of key atmospheric processes, and their coupling to the surface, in climate models. Observations from the hyperspectral Atmospheric Infrared Sounder (AIRS) instrument on board the National Aeronautics and Space Administration (NASA)’s Aqua satellite are contributing toward improved understanding of the vertical structure of the atmosphere over the poles since 2002, including the lower troposphere. This part of the atmosphere is especially important in the Arctic, as it directly impacts sea ice and its short-term variability. Although in situ measurements provide invaluable ground truth, they are spatially and temporally inhomogeneous and sporadic over the Arctic. A growing number of studies are exploiting AIRS data to investigate the thermodynamic structure of the Arctic atmosphere, with applications ranging from understanding processes to deriving climatologies—all of which are also useful to test and improve parameterizations in climate models. As the AIRS data record now extends more than a decade, a select few of many such noteworthy applications of AIRS data over this challenging and rapidly changing landscape are highlighted here.

scholarly journals Atmospheric Conditions during the Arctic Clouds in Summer Experiment (ACSE): Contrasting Open Water and Sea Ice Surfaces during Melt and Freeze-Up Seasons

2016 ◽  
Vol 29 (24) ◽  
pp. 8721-8744 ◽  
Author(s):  
Georgia Sotiropoulou ◽  
Michael Tjernström ◽  
Joseph Sedlar ◽  
Peggy Achtert ◽  
Barbara J. Brooks ◽  
...  
Keyword(s):  
Mixed Boundary ◽  
Open Water ◽  
Lower Atmosphere ◽  
The Arctic ◽  
Climate Projections ◽  
Atmospheric Conditions ◽  
Arctic Clouds ◽  
Ice Melt ◽  
Ice Edge ◽  
Insight Into

Abstract 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.

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