Day 1 - May 23, 2001
Day 2 - May 24, 2001
Core AOMIP Researchers
Pilot OMIP Simulations
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.
Response of the Arctic sea ice to transients in the North Atlantic Oscillation (NAO)
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
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
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
ABSTRACT NOT YET AVAILABLE
An impact of subgrid-scale ice-ocean dynamics on sea-ice cover
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.