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Modeling the Arctic sea ice age

  • February 2012
DOI:10.13140/RG.2.2.20730.70089
  • Conference: Ocean Sciences meeting
  • At: Salt Lake City
Authors:
Pierre Rampal at French National Centre for Scientific Research
Pierre Rampal
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Abstract

Satellite observations show a continued shrinking in Arctic sea ice extent over the last three decades. The shrinkage is accompanied by a strong thinning over the Arctic basin with an average trend of about 16 (±7.0)% per decade for the period 1980-2008. Over the last few years, this thinning seems to have accelerated as a consequence of large losses of multi-year (MY) ice, i.e. of ice that has survived at least one melting season. We introduce a new module of the MIT coupled sea ice-ocean model (MITgcm) that allows the tracking of sea ice age over the Arctic region. We present results of a simulation for the period 1979-2010 in terms of seasonal and inter-annual variability, as well as long-term trends. We evaluate our model using MY ice fraction estimates derived from QuikSCAT satellite data for the period 2000-2009. Finally, we discuss the weight of the different physical processes involved in the strong reduction of MY ice as observed over that same period.
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2. ECCO2 regional model configuration:
Ocean model:
• 9-km horizontal grid spacing, 50 vertical levels
• Volume-conserving, C-grid
•  Bathymetry: S2004 blend of GEBCO and
Smith and Sandwell [1997] [Marks and Smith, 2006]
•  KPP mixing [Large et al., 1994]
• BCs from the global optimized solution
Sea-ice model:
• C-grid
• Multi-categories zero-layer thermodynamics
[Hibler, 1980; Fenty et al., in prep.]
•  Viscous plastic dynamics [Hibler, 1979]
•  Prognostic snow and sea-ice salinity
Model parameters:
taken from Nguyen et al. 2011 (see table 2)
Atmospheric forcing:
JRA-25
Simulation:
Duration: 1979-2010
On modeling Arctic sea-ice age and the recent
Multi-Year ice decline: 2000-2009
Pierre Rampal1, Patrick Heimbach1, Ron Kwok2 and Dimitris Menemenlis2
1 Massachusetts Institute of Technology, Cambridge, MA
2 Jet Propulsion Laboratory, Pasadena, CA
Contact: rampal@mit.edu
1. Project Objectives:
(i)  Implement a new package in the MITgcm code to track sea-ice and snow
passive tracers such as age, salt, biological species, chemical compounds …
(ii)  Focus on reproducing the recent Multi-Year (MY) ice decline as observed
from satellite data since 2000
(iii)  Find out the main physical processes involved in the recent Arctic sea ice
volume loss by understanding the most important mechanisms acting on the
different ice types (and in particular by weighting the relative importance of export
versus thermodynamics processes)
Figure 1. Observed (Black) and modeled
(blue) MY sea ice area on January 1st for
the period 2000-2009. The amount of MY ice
area, the inter-annual variability and the negative trend
are all well captured by the simulation. However, some
differences remain, for example in terms of spatial
repartition of the MY ice.
Acknowledgments:
This work has been supported by the ECCO2 project and the NASA SURP program. We gratefully acknowledge
computational resources and support from the NASA Advanced Supercomputing (NAS) Division.
3.1 Results: Model versus Observations
Figure 2. Observed (left) and modeled (middle) multi-year (MY) sea-ice area fraction
over the Arctic Ocean on January 1st 2008. Right panel shows the difference (model
minus observations). The white line shows QuikSCAT 0.1 MY fraction isopleth. The dashed white line in
the middle panel represents this same isopleth for the model. The general pattern is reasonnably reproduced in
the model, with the high concentrated MY ice cover located north of Greenland. In addition, the tongue of MY
ice crossing the central Arctic from the North of Greenland to the Laptev Sea is remarkably well reproduced.
Model’s discrepancies are significant in the Beaufort sea and in the central Arctic.
3.2 Results: Focus on January 2008
4. Results: MY ice loss contribution to the sea-ice decline
1999 2001 2003 2005 2007 2009
0
5000
10000
15000
20000
Year
January 1st ice volume (km3)
1999 2001 2003 2005 2007 2009
0
5000
10000
15000
20000
Year
Previous september 15th ice volume (km3)
Overall
MY
FY
Overall
MY
FY
−395 km3/year
−320 km3/year
+55 km3/year
−60 km3/year
−340 km3/year
−380 km3/year
−380 km
3
/year
Figure 3. Modeled ice volumes on the 1st of January (left) and the previous 15th of
September for the period 2000-2009. In the model, the MY ice volume loss over this period seems to
contribute largely to the total volume loss, in accordance with the observations of Kwok et al. 2009. The trend of the
FY ice (left panel) is slightly positive (i.e. 55km3/year), and can be explained by an increase of ice-free surface at the
end of the melting season over the same period. The negative trend of the total ice volume at the end of the melting
season (right panel, in black) is smaller than that at the beginning of the following winter (left panel, in red). This
means, if one considers the net melting to be negligible between September 15th and January 1st, that the export of
MY ice has slightly increased on average over the period (left panel, black arrows).
References:
Nguyen et al. (2011), Arctic ice-ocean simulation with optimized model parameters: Approach and assessment, J.
Geophys. Res., 116, C04025, doi:10.1029/2010JC006573.
Kwok, R. et al. (2009), Thinning and volume loss of the arctic ocean sea ice cover: 2003-2008. J. Geophys. Res., 114,
C07005, doi:10.1029/2009JC005312.
Rampal et al. (2012), Modeling the multi-year sea ice loss in the Arctic over the period 2000-2009: export versus melt
contributions to the observed sea ice decline, in preparation.
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Arctic ice-ocean simulation with optimized model parameters: Approach and assessment
Article
Full-text available
  • Apr 2011
We present an optimized 1992–2008 coupled ice-ocean simulation of the Arctic Ocean. A Green's function approach adjusts a set of parameters for best model-data agreement. Overall, model-data differences are reduced by 45%. The optimized simulation reproduces the negative trends in ice extent in the satellite records. Volume and thickness distributions are comparable to those from the Ice, Cloud, and land Elevation Satellite (2003–2008). The upper cold halocline is consistent with observations in the western Arctic. The freshwater budget of the Arctic Ocean and volume/heat transports of Pacific and Atlantic waters across major passages are comparable with observation-based estimates. We note that the optimized parameters depend on the selected atmospheric forcing. The use of the 25 year Japanese reanalysis results in sea ice albedos that are consistent with field observations. Simulated Pacific Water enters the Bering Strait and flows off the Chukchi Shelf along four distinct channels. This water takes ∼5–10 years to exit the Arctic Ocean at the Canadian Arctic Archipelago, Nares, or Fram straits. Atlantic Water entering the Fram Strait flows eastward, merges with the St Ana Trough inflow, and splits into two branches at the southwest corner of the Makarov Basin. One branch flows along Lomonosov Ridge back to Fram Strait. The other enters the western Arctic, circulates cyclonically below the halocline, and exits mainly through the Nares and Fram straits. This work utilizes the record of available observations to obtain an Arctic Ocean simulation that is in agreement with observations both within and beyond the optimization period and that can be used for tracer and process studies.
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Modeling the multi-year sea ice loss in the Arctic over the period 2000-2009: export versus melt contributions to the observed sea ice decline
  • Jan 2012
  • Rampal
Rampal et al. (2012), Modeling the multi-year sea ice loss in the Arctic over the period 2000-2009: export versus melt contributions to the observed sea ice decline, in preparation.