Workshop #3, May 23-24, 2001

Schedule

Day 1 - May 23, 2001

09:00 - 09:15	Coffee, Pasteries
09:15 - 09:35	Andrey Proshutinsky	Introduction and brief review of the AOMIP goals and objective and results obtained during the first year of research. Plan for the second year and CAMP. Financial questions.
09:40 - 10:10	Greg Flato	ACSYS/CliC NEG initiatives. Connection between AOMIP and the WCRP WGOMD, and in particular its OMIP.
10:15 - 12:00	Group Discussion	AOMIP Framework Topics
12:00 - 13.30	Lunch
13:30 -15:00	Group Discussion	AOMIP Framework Topics (con't)
15:00 - 15:30	Coffee
15:30 - 17:00	Group Discussion	AOMIP Framework Topics (con't)
17:00	Adjourn

Day 2 - May 24, 2001

08:00 - 08:30	Coffee, Pasteries
08:30 - 08:50	Aixue Hu	Response of the Arctic sea ice to the NAO transients
08:55 - 09:15	Meibing Jin	Responses of an Arctic coupled ice-ocean (POM) model to NCEP/NCAR climatology
09:20 - 09:40	Bruno Tremblay	Sea ice export through Fram Strait and high latitude atmospheric circulation patterns: AO, NAO and BO
09:45 - 10:05	Mark Johnson (presented by Proshutinsky)	Model intercomparison results based on acoustic data
10:10 - 10:30	Coffee
10:30 - 10:50	Bob Newton	Arctic river runoff: model-data comparisons
10:55 - 11:15	Bill Hibler	Modeling and observation of high frequency variability in Arctic sea ice
11:20 - 11:40	David Holland	An impact of subgrid-scale ice-ocean dynamics on sea-ice cover
11:45 - 12:00	Group Discussion	Science Presentations
12:00 - 13.30	Lunch
13:30 -	Group Discussion	AOMIP Framework Topics (con't)
15:00 - 15:30	Coffee
15:30 - 17:00	Group Writeup	First Draft - AOMIP Framework
17:00	Adjourn

Participants

Core AOMIP Researchers

• Andrey Proshutinsky, Principal Investigator, Woods Hole Oceanographic Institution SA.
• Ruediger Gerdes, Co-Principal Investigator, Alfred-Wegener-Institute, Bremerhaven, Germany
• Sirpa Hakkinen, Co-Principal Investigator, NASA Goddard Space Flight Center, USA
• David Holland, Co-Principal Investigator, Courant Institute of Mathematical Sciences, New York University, USA
• Greg Holloway, Co-Principal Investigator, Institute of Ocean Sciences, Sidney, Canada
• Meibing Jin, Co-Principal Investigator, International Arctic Research Center, University of Alaska Fairbanks, USA
• Cornelia Koberle, Co-Principal Investigator, Alfred-Wegener-Institute, Bremerhaven, Germany
• Wieslaw Maslowski, Co-Principal Investigator, Naval Postgraduate School, Monterey, USA
• Mike Steele, Co-Principal Investigator, Polar Sciences Center, University of Washington, USA

Invited Experts

• Greg Flato, Canadian Center for Climate Modeling and Analyses, University of Victoria, Canada
• Bill Hibler, International Arctic Research Center, University of Alaska Fairbanks, USA
• Aixue Hu, Rosenstiel School of Marine and Atmospheric Sciences, University of Miami, USA
• Bob Newton, Lamont-Doherty Earth Observatory, Columbia University, USA
• Bruno Tremblay, Lamont-Doherty Earth Observatory, Columbia University, USA
• John Walsh, University of Illinois, Urbana-Champaign, USA

Logistics

Local Transport

• Bus service from Boston Logan Airport to Falmouth is provided by Bonanza.

Accommodations

• A block of rooms is reserved at the Ramada Inn on Falmouth Square, in Falmouth.
  (Call 1-800-676-0000 & mention the AOMIP Group.)

Meeting Facilities

• The workshop will be held in the Conference Room (room 509) of Clark Laboratory of the Quissett Campus of WHOI.

Workshop Organizer

• The workshop is organized by Andrey Proshutinsky of the Woods Hole Oceanographic Institute. Further details on the workshop and the AOMIP can be obtained by contacting him via email, telephone (508-289-2796), or in person (room 218, Clarke Laboratory, Quissett Campus).

Presentations

Pilot OMIP Simulations

Rudiger Gerdes

The following is a summary of preliminary results presented by Rudiger Gerdes concerning the pilot OMIP simulations. In those simulations, the MOM2 and HOPE models were forced using the OMIP Climatological Forcing. Although OMIP covers a global domain, the focus here is on the performance of the OMIP models in the Arctic basin only. These OMIP findings and experineces may thus be relevant to the upcoming AOMIP simulations.

• Both model results are very similar. Most of the time it is difficult to decide which result is better based on available data sets.
• The model results are close to the climatological fields in many cases.
• The Gent-McWilliams parameterizations has mixed effects on the model results.
• Longer integration times are necessary to assess the more subtle differences in model physics.
• Pole filtering should be avoided because it contaminates low-latitude, downstream downstream results (e.g., the East Greenland Current in MOM2).
• Pronounced model-data discrepancies exist in the Arctic basin.
• Exchanges between the Arctic and neighboring oceans must be improved.
• The sea-ice export from the Arctic basin to the Greenland Sea is too low.
• The Arctic halocline is overly thick, partly because of the anomalously low sea-ice export. This will potentially result in an undesirable, reduced model sensitivity to climate forcing in longer model runs.

Abstracts

Response of the Arctic sea ice to transients in the North Atlantic Oscillation (NAO)
Aixue Hu

Variations of the Arctic sea ice condition with idealized NAO variations were studied by using MICOM coupled with the EVP sea ice model. Model solutions suggest a significant diminishing in sea ice extent along Eurasian coastal region in high NAO summers, a thinner (thicker) ice with lower (higher) compactness on the Eurasian (Canadian) side of Arctic and a higher rate of sea ice export via Fram Strait in high NAO years. These changes in sea ice condition are caused by the NAO-related anomalous wind and air temperatures, and the anomalous exchanges of heat between air and ice-ocean. The stronger than normal wind blowing from the Eurasian continent towards Canada causes a divergence (convergence) of sea ice on the Eurasian (Canadian) side of Arctic, and also drive a higher sea ice export to GIN Seas. The redistribution of sea-ice mass results in an anomalous heat exchanges which further feedback to the sea-ice anomalies.

Responses of the IARC Coupled Arctic Ice-Ocean (POM) Model (CIOM) to NCAR/NCEP Climatology
Jia Wang and Meibing Jin

The responses of the International Arctic Research Center (IARC) coupled ice-ocean Model (CIOM) to NCAR/NCEP Climatology was discussed. The ice model is the Hibler model with 8 ice categories. The ocean model is POM with 16 sigma layers and a horizontal resolution of 27.5km by 27.5km. Model results with initial ocean T, S and climatology data from NODC WOA98 and from PHC 2.0 (Steele et al., 2001) were compared, and found that PHC 2.0 provides more reasonable T, S field and hence circulation in the Arctic. Atmospheric forcing was climatology data of the NCAR/NCEP reanalysis (1958-1998). The general transport under daily forcing was much larger than monthly forcing.

As a first step, the annual mean was computed under daily wind and other atmospheric forcings using the NCEP/NCAR reanalysis data of 1990, restored to the surface monthly climatological temperature and salinity. The simulated total transport of the Labrador Sea is about 50 Sv, consistent with historical estimates. The western North Atlantic is dominated by the cyclonic Labrador Current system, while the eastern North Atlantic is dominated by the anticyclonic gyres. Greenland Basin has a cyclonic gyre of about 25-30 Sv, while the Norwegian Basin has a cyclonic gyre of about 25 Sv. In Fram Strait, the model simulated an outflow of Arctic surface water from the Greenland side (~5.5 Sv) and inflow of the North Atlantic Water from the eastern side (~4 Sv). The simulated temperature and salinity in Fram Strait indicate the intrusion of the Atlantic Water and the outflow of the Arctic surface water. In the Arctic Basin, the simulated total transport is cyclonic in both the Eurasian Basin and the Canadian Basin although the surface ocean current is anticyclonic.

Sea ice export through Fram Strait and high latitude atmospheric circulation patterns: Arctic (AO), North Atlantic (NAO), and Barents Sea (BO) Oscillations
Bruno Tremblay

An EOF analysis of a constructed time series mimicking the Northern Hemisphere SLP variability of the last 50 years shows that the Barents Oscillation (BO) appears as a means to represent the sudden eastward shift of the northern center of action associated with the Arctic Oscillation (AO) observed in the mid-seventies. This sudden shift (non-stationarity) appears in an EOF analysis as a step change in the relative phase between the principal components associated with the EOFs of the AO and BO. The results also show that an EOF analysis of a constant amplitude signal can produce artificial trends and/or amplitude changes in the principal component associated with a given mode (e.g., AO) when such non-stationarities are present in the signal. In this case, different modes of variability represented by EOFs cannot be considered independently from one another. In the example presented, although the principal components are completely uncorrelated from one another, perfect correlation and anti-correlation are present in the first and second parts of the time series respectively.

Modeling river runoff in the Arctic, and model-data comparisons
Bob Newton

Results from a high-resolution model of the Arctic (18 km by 18 km by 30 levels grid), are presented. The 9 largest rivers have been added as a buoyancy source and passive dye tracers had been added. The results are compared to detailed tracer observations over the Arctic shelves and along deep-water transects. It is shown that the influence of the modeled river inputs on buoyancy is strongly dominated by the "weak" relaxation to Levitus climatology at the surface. Further, it is shown that the model must have a damped thermodynamic cycle, relative to the climatology; and that the climatology, itself, is damped relative to the observed annual cycle of salinity in the coastal regions of the Arctic shelf seas. The differences between the model and the observed river inputs is placed in the context of theoretical studies of buoyant coastal discharges. It is demonstrated that the rivers and the model each behave approximately as predicted by the theory; but that they lie in two distinct regions of the appropriate parameter space. Despite the problems with behavior of the coastal freshwater plumes, it is shown that the model is capable of simulating an observed redistribution of meteoric waters over the central Arctic Basin. It is proposed that the shift in freshwater fronts is largely wind-driven, as this is the only mechanism available to the model for such temporal changes.

Modeling and observation of high frequency variability in Arctic sea ice
Bill Hibler

ABSTRACT NOT YET AVAILABLE

An impact of subgrid-scale ice-ocean dynamics on sea-ice cover
David Holland

A coupled sea-ice-ocean numerical model is used to study the impact of an ill-resolved subgrid-scale sea-ice-ocean dynamical process on the areal coverage of the sea-ice field. The process of interest is the transmission of stress from the ocean into the sea-ice cover and its subsequent interaction with the sea-ice internal stress field. An idealized experiment is performed to highlight the difference in evolution of the sea-ice cover in the circumstance of a relatively coarse-resolution grid versus that of a fine-resolution one. The experiment shows that the ubiquitous presence of instabilities in the near-surface ocean flow field as seen on a fine-resolution grid effectively leads to a sink of sea-ice areal coverage that does not occur when such flow instabilities are absent, as on a coarse-resolution grid. This result also implies that a fine-resolution grid may have a more efficient atmosphere-sea-ice-ocean thermodynamic exchange than a coarse one. This sink of sea-ice areal coverage arises because the sea-ice undergoes sporadic, irreversible plastic failure on a fine-resolution grid that, by contrast, does not occur on a coarse-resolution grid. This demonstrates yet again that coarse-resolution coupled climate models are not reaching fine enough resolution in the polar regions of the world ocean to claim that their numerical solutions have reached convergence.