scholarly journals The Granular Sea Ice Model in Spherical Coordinates and Its Application to a Global Climate Model

2007 ◽  
Vol 20 (24) ◽  
pp. 5946-5961 ◽  
Author(s):  
Jan Sedlacek ◽  
Jean-François Lemieux ◽  
Lawrence A. Mysak ◽  
L. Bruno Tremblay ◽  
David M. Holland
Keyword(s):  
Growth Rate ◽  
Sea Ice ◽  
Climate Model ◽  
Heat Budget ◽  
Global Climate ◽  
Global Climate Model ◽  
Internal Heat ◽  
The Arctic ◽  
Spherical Coordinates ◽  
Ice Model

Abstract The granular sea ice model (GRAN) from Tremblay and Mysak is converted from Cartesian to spherical coordinates. In this conversion, the metric terms in the divergence of the deviatoric stress and in the strain rates are included. As an application, the GRAN is coupled to the global Earth System Climate Model from the University of Victoria. The sea ice model is validated against standard datasets. The sea ice volume and area exported through Fram Strait agree well with values obtained from in situ and satellite-derived estimates. The sea ice velocity in the interior Arctic agrees well with buoy drift data. The thermodynamic behavior of the sea ice model over a seasonal cycle at one location in the Beaufort Sea is validated against the Surface Heat Budget of the Arctic Ocean (SHEBA) datasets. The thermodynamic growth rate in the model is almost twice as large as the observed growth rate, and the melt rate is 25% lower than observed. The larger growth rate is due to thinner ice at the beginning of the SHEBA period and the absence of internal heat storage in the ice layer in the model. The simulated lower summer melt is due to the smaller-than-observed surface melt.

Oil exploration and sea ice projections in the Arctic

Polar Record ◽  
2013 ◽  
Vol 51 (1) ◽  
pp. 91-106 ◽  
Author(s):  
Øistein Harsem ◽  
Knut Heen ◽  
J.M.P. Rodrigues ◽  
Terje Vassdal
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Barents Sea ◽  
Global Climate ◽  
Global Climate Model ◽  
Ice Cover ◽  
The Arctic ◽  
Oil Exploration ◽  
Comparative Cost ◽  
The North

ABSTRACTThe aim of this study is to investigate how reduction in the sea ice cover may affect oil activity in the Arctic during the next 30 years. The Arctic is divided into 21 oil provinces. A multidisciplinary approach is applied drawing on both the comparative cost techniques as developed in location theory and sea ice cover projections. The comparative cost technique implies a systematic listing of cost differentials by oil provinces. The sea ice projections are based on the NCAR CCSM3 global climate model under the A1B and A2 emission scenarios. The article concludes that the north Norwegian Sea, and south and west Barents Sea will remain the most attractive areas for oil exploration in the coming 30 years. Furthermore, due to sea ice decline, the north and east Barents Sea and north and west Kara Sea will become more attractive. However, most Arctic provinces will remain high cost regions.

scholarly journals Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 174
Author(s):  
Günther Heinemann ◽  
Sascha Willmes ◽  
Lukas Schefczyk ◽  
Alexander Makshtas ◽  
Vasilii Kustov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
The Arctic ◽  
Late Winter ◽  
Good Representation ◽  
Hourly Temperature ◽  
Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

An Intraseasonal Mode Linking Wintertime Surface Air Temperature over Arctic and Eurasian Continent

2021 ◽  
pp. 1-47
Keyword(s):  
Air Temperature ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Free Atmosphere ◽  
Temperature Anomalies ◽  
Downward Longwave Radiation

Abstract Key processes associated with the leading intraseasonal variability mode of wintertime surface air temperature (SAT) over Eurasia and the Arctic region are investigated in this study. Characterized by a dipole distribution in SAT anomalies centered over north Eurasia and the Arctic, respectively, and coherent temperature anomalies vertically extending from the surface to 300hPa, this leading intraseasonal SAT mode and associated circulation have pronounced influences on global surface temperature anomalies including the East Asian winter monsoon region. By taking advantage of realistic simulations of the intraseasonal SAT mode in a global climate model, it is illustrated that temperature anomalies in the troposphere associated with the leading SAT mode are mainly due to dynamic processes, especially via the horizontal advection of winter mean temperature by intraseasonal circulation. While the cloud-radiative feedback is not critical in sustaining the temperature variability in the troposphere, it is found to play a crucial role in coupling temperature anomalies at the surface and in the free-atmosphere through anomalous surface downward longwave radiation. The variability in clouds associated with the intraseasonal SAT mode is closely linked to moisture anomalies generated by similar advective processes as for temperature anomalies. Model experiments suggest that this leading intraseasonal SAT mode can be sustained by internal atmospheric processes in the troposphere over the mid-to-high latitudes by excluding forcings from Arctic sea ice variability, tropical convective variability, and the stratospheric processes.

scholarly journals Remote sensing of aerosols in the Arctic for an evaluation of global climate model simulations

2014 ◽  
Vol 119 (13) ◽  
pp. 8169-8188 ◽  
Author(s):  
Paul Glantz ◽  
Adam Bourassa ◽  
Andreas Herber ◽  
Trond Iversen ◽  
Johannes Karlsson ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
The Arctic ◽  
Model Simulations ◽  
Climate Model Simulations

scholarly journals Sea-ice and North Atlantic climate response to CO2-induced warming and cooling conditions

2006 ◽  
Vol 52 (178) ◽  
pp. 433-439 ◽  
Author(s):  
Larissa Nazarenko ◽  
Nickolai Tausnev ◽  
James Hansen
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
Surface Pressure ◽  
Climate Model ◽  
Global Climate Model ◽  
Ice Cover ◽  
The Arctic ◽  
Normal Surface ◽  
Sea Ice Extent ◽  
Polar Cell

AbstractUsing a global climate model coupled with an ocean and a sea-ice model, we compare the effects of doubling CO2 and halving CO2 on sea-ice cover and connections with the atmosphere and ocean. An overall warming in the 2 × CO2 experiment causes reduction of sea-ice extent by 15%, with maximum decrease in summer and autumn, consistent with observed seasonal sea-ice changes. The intensification of the Northern Hemisphere circulation is reflected in the positive phase of the Arctic Oscillation (AO), associated with higher-than-normal surface pressure south of about 50° N and lower-than-normal surface pressure over the high northern latitudes. Strengthening the polar cell causes enhancement of westerlies around the Arctic perimeter during winter. Cooling, in the 0.5 × CO2 experiment, leads to thicker and more extensive sea ice. In the Southern Hemisphere, the increase in ice-covered area (28%) dominates the ice-thickness increase (5%) due to open ocean to the north. In the Northern Hemisphere, sea-ice cover increases by only 8% due to the enclosed land/sea configuration, but sea ice becomes much thicker (108%). Substantial weakening of the polar cell due to increase in sea-level pressure over polar latitudes leads to a negative trend of the winter AO index. The model reproduces large year-to-year variability under both cooling and warming conditions.

scholarly journals Northern Hemisphere storminess in the Norwegian Earth System Model (NorESM1-M)

2014 ◽  
Vol 7 (6) ◽  
pp. 8975-9015
Author(s):  
E. M. Knudsen ◽  
J. E. Walsh
Keyword(s):  
Sea Ice ◽  
Sea Level ◽  
Northern Hemisphere ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
System Model ◽  
High Latitudes ◽  
Earth System ◽  
Projected Changes

Abstract. Metrics of storm activity in Northern Hemisphere high- and midlatitudes are evaluated from historical output and future projections by the Norwegian Earth System Model (NorESM1-M) coupled global climate model. The European Re-Analysis Interim (ERA-Interim) and the Community Climate System Model (CCSM4), a global climate model of the same vintage as NorESM1-M, provide benchmarks for comparison. The focus is on the autumn and early winter (September through December), the period when the ongoing and projected Arctic sea ice retreat is greatest. Storm tracks derived from a vorticity-based algorithm for storm identification are reproduced well by NorESM1-M, although the tracks are somewhat better resolved in the higher-resolution ERA-Interim and CCSM4. The tracks are projected to shift polewards in the future as climate changes under the Representative Concentration Pathway (RCP) forcing scenarios. Cyclones are projected to become generally more intense in the high-latitudes, especially over the Alaskan region, although in some other areas the intensity is projected to decrease. While projected changes in track density are less coherent, there is a general tendency towards less frequent storms in midlatitudes and more frequent storms in high-latitudes, especially the Baffin Bay/Davis Strait region. Autumn precipitation is projected to increase significantly across the entire high-latitudes. Together with the projected increases in storm intensity and sea level and the loss of sea ice, this increase in precipitation implies a greater vulnerability to coastal flooding and erosion, especially in the Alaskan region. The projected changes in storm intensity and precipitation (as well as sea ice and sea level pressure) scale generally linearly with the RCP value of the forcing and with time through the 21st century.

scholarly journals Data assimilation in sea-ice monitoring

2000 ◽  
Vol 31 ◽  
pp. 327-332 ◽  
Author(s):  
Ronald L. S. Weaver ◽  
Konrad Steffen ◽  
John Heinrichs ◽  
James A. Maslanik ◽  
Gregory M. Flato
Keyword(s):  
Remote Sensing ◽  
Data Assimilation ◽  
Sea Ice ◽  
Global Climate ◽  
Remote Sensing Data ◽  
The Arctic ◽  
Physical Processes ◽  
Error Statistics ◽  
Sensing Data ◽  
Ice Model

AbstractThe detection of small changes in concentration or thickness in the Arctic or Antarctic ice cover is an important topic in the current global-climate-change debate. Change detection using satellite data alone requires rigorous error analysis for their derived ice products, including inter-satellite validation for long time series. All models of physical processes are only approximations, and the best models of complicated physical processes have errors and uncertainties. A promising approach is data assimilation, combining model, in situ data and satellite remote-sensing data. Sea-ice monitoring from satellite, ice-model estimates, and the potential benefit of combining the two are discussed in some detail. In a case-study we demonstrate how the sea-ice backscatter for the Beaufort Sea region was derived using a backscattering model in combination with an ice model. We conclude that, for data assimilation, the first steps include the use of simple models, moving, with success at this level, to progressively more complex models. We also recommend reconfiguring the current remote-sensing data to include precise time tags with each pixel. For example, the current Special Sensor Microwave Imager data might be reissued in a time-tagged orbital (or gridded) format as opposed to the currently available daily averaged gridded data. Finally, error statistics and quality-control information also need to be readily available in a form useful for assimilation. The effectiveness of data-assimilation techniques is directly linked to the availability of data error statistics.

scholarly journals Strong future increases in Arctic precipitation variability linked to poleward moisture transport

2020 ◽  
Author(s):  
Richard Bintanja ◽  
Karin van der Wiel ◽  
Eveline van der Linden ◽  
Jesse Reusen ◽  
Linda Bogerd ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Moisture Transport ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Arctic Region ◽  
The Arctic ◽  
Climate Model Simulations ◽  
Mean Climate ◽  
Increasing Precipitation

<p>The Arctic region is projected to experience amplified warming as well as strongly increasing precipitation rates. Equally important to trends in the mean climate are changes in interannual variability, but changes in precipitation fluctuations are highly uncertain and the associated processes unknown. Here we use various state-of-the-art global climate model simulations to show that interannual variability of Arctic precipitation will likely increase markedly (up to 40% over the 21<sup>st</sup> century), especially in summer. This can be attributed to increased poleward atmospheric moisture transport variability associated with enhanced moisture content, possibly modulated by atmospheric dynamics. Because both the means and variability of Arctic precipitation will increase, years/seasons with excessive precipitation will occur more often, as will the associated impacts.</p>

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