Wieslaw Maslowski

The Arctic Ocean Response to the North Atlantic Oscillation

The climatically sensitive zone of the Arctic Ocean lies squarely within the domain of the North Atlantic oscillation (NAO), one of the most robust recurrent modes of atmospheric behavior. However, the specific response of the Arctic to annual and longer-period changes in the NAO is not well understood. Here that response is investigated using a wide range of datasets, but concentrating on the winter season when the forcing is maximal and on the postwar period, which includes the most comprehensive instrumental record. This period also contains the largest recorded low-frequency change in NAO activity—from its most persistent and extreme low index phase in the 1960s to its most persistent and extreme high index phase in the late 1980s/early 1990s. This longperiod shift between contrasting NAO extrema was accompanied, among other changes, by an intensifying storm track through the Nordic Seas, a radical increase in the atmospheric moisture flux convergence and winter precipitation in this sector, an increase in the amount and temperature of the Atlantic water inflow to the Arctic Ocean via both inflow branches (Barents Sea Throughflow and West Spitsbergen Current), a decrease in the late-winter extent of sea ice throughout the European subarctic, and (temporarily at least) an increase in the annual volume flux of ice from the Fram Strait.

Ridging, strength, and stability in high-resolution sea ice models

[1] In multicategory sea ice models the compressive strength of the ice pack is often assumed to be a function of the potential energy of pressure ridges. This assumption, combined with other standard features of ridging schemes, allows the ice strength to change dramatically on short timescales. In high-resolution (∼10 km) sea ice models with a typical time step (∼1 hour), abrupt strength changes can lead to large internal stress gradients that destabilize the flow. The unstable flow is characterized by large oscillations in ice concentration, thickness, strength, velocity, and strain rates. Straightforward, physically motivated changes in the ridging scheme can reduce the likelihood of abrupt strength changes and improve stability. In simple test problems with flow toward and around topography, stability is significantly enhanced by eliminating the threshold fraction G* in the ridging participation function. Use of an exponential participation function increases the maximum stable time step at 10-km resolution from less than 30 min to about 2 hours. Modifying the redistribution function to build thinner ridges modestly improves stability and also gives better agreement between modeled and observed thickness distributions. Allowing the ice strength to increase linearly with the mean ice thickness improves stability but probably underestimates the maximum stresses.

Modeling Recent Climate Variability in the Arctic Ocean

Dramatic changes in the circulation of sea ice andtheupperlayersoftheArcticOceanhavebeenreported during the last decade. Similar variability is modeled using a regional, coupled ice-ocean model. Realistic atmospheric forcingeldsfor1979-93 aretheonlyinterannualsignalpre- scribed in the model. Our results show large-scale changes inseaiceandoceanicconditionswhencomparingresultsfor the late 1970s / early 1980s and the 1990s. We hypothesize thatthesechangesareinresponsetoevenlargerscaleatmo- spheric variability in the Northern Hemisphere that can be denedaseithertheArcticOscillationortheNorthAtlantic Oscillation. Agreement between the direction and scale of change in the model and observations, in the absence of in- terannual forcing from the global ocean thermohaline circu- lation, suggests that the atmospheric variability by itself is sucienttoproducebasin-scalechangesintheArcticOcean and sea ice system.

Evaluation of Arctic sea ice thickness simulated by Arctic Ocean Model Intercomparison Project models

Six AOMIP model simulations are compared with estimates of sea ice thickness derived from pan-arctic satellite freeboard measurements (2004-2008), airborne electromagnetic measurements (2001-2009), ice-draft data from moored instruments in Fram Strait, the Greenland Sea and the Beaufort Sea (1992- 2008) and from submarines (1975-2000), drill hole data from the Arctic basin, Laptev and East Siberian marginal seas (1982-1986) and coastal stations (1998-2009). Despite an assessment of six models that differ in numerical methods, resolution, domain, forcing, and boundary conditions, the models generally overestimate the thickness of measured ice thinner than ~2 m and underestimate the thickness of ice measured thicker than about ~2 m. In the regions of flat immobile land-fast ice (shallow Siberian Seas with depths less than 25-30 m), the models generally overestimate both the total observed sea ice thickness and rates of September and October ice growth from observations by more than four times and more than one standard deviation, respectively. The models do not reproduce conditions of fast-ice formation and growth. Instead, the modeled fast-ice is replaced with pack ice which drifts, generates ridges of increasing ice thickness, in addition to thermodynamic ice growth. Considering all observational data sets, the better correlations and smaller differences from observations are from the ECCO2 and UW models.

Arctic Ocean Study: Synthesis of Model Results and Observations

Model development and simulations represent a comprehensive synthesis of observations with advances in numerous disciplines (physics; mathematics; and atmospheric, oceanic, cryospheric, and related sciences), enabling hypothesis testing via numerical experiments. For the Arctic Ocean, modeling has become one of the major instruments for understanding past conditions and explaining recently observed changes. In this context, the international Arctic Ocean Model Intercomparison Project (AOMiphttp://fish.cims.nyu.edu/project_aomip/overview. html) has investigated various aspects of ocean and sea ice changes for the time period 1948 to present. Among the major AOMIP themes are investigations of the origin and variability of Atlantic water (AW) circulation, mechanisms of accumulation and release of fresh water (FW), causes of sea level rise, and the role of tides in shaping climate.

Multinational effort studies differences among arctic ocean models

The Arctic Ocean is an important component of the global climate system. The processes occurring in the Arctic Ocean affect the rate of deep and bottom water formation in the convective regions of the high North Atlantic and influence ocean circulation across the globe. This fact is highlighted by global climate modeling studies that consistently show the Arctic to be one of the most sensitive regions to climate change. But an identification of the differences among models and model systematic errors in the Arctic Ocean remains unchecked, despite being essential to interpreting the simulation results and their implications for climate variability. For this reason, the Arctic Ocean Model Intercomparison Project (AOMIP), an international effort, was recently established to carry out a thorough analysis of model differences and errors. The geographical focus of this effort is shown in Figure 1.

Impact of mesoscale ocean currents on sea ice in high-resolution Arctic ice and ocean simulations

A high-resolution sea ice model is designed for simulating the Arctic. The grid resolution is ∼18 km, and the domain contains the main Arctic Ocean, Nordic Seas, Canadian Archipelago, and the subpolar North Atlantic. The model is based on a widely used dynamic and thermodynamic model with more efficient numerics. The oceanic forcing is from an Arctic Ocean model with the same horizontal resolution as the ice model and 30 levels. The atmospheric forcing is from 3-day average 1990-1994 European Centre for Medium-Range Weather Forecasts operational data. Results from the ice model are compared against satellite passive-microwave observations and drifting buoys. The model realistically simulates ice tongues and eddies in the Greenland Sea. The mesoscale ocean eddies along the East Greenland Current (EGC) are demonstrated to be responsible for the presence of ice eddies and tongues out of the Greenland Sea ice edge. Large shear and divergence associated with the mesoscale ice eddies and strong ice drift, such as the one above the EGC, result in thinner and less compact ice. The mesoscale ocean eddies along the Alaskan Chukchi shelf break, the Northwind Ridge, and the Alpha-Mendeleyev Ridge are major contributors to mesoscale reduction of ice concentration, in addition to atmospheric storms which usually lead to a broad-scale reduction of ice concentration. The existence of mesoscale ocean eddies greatly increases nonuniformity of ice motion, which means stronger ice deformation and more open water. An eddy-resolving coupled ice-ocean model is highly recommended to adequately simulate the small but important percentage of open water in the Arctic pack ice, which can significantly change the heat fluxes from ocean to atmosphere and affect the global climate.

Sea level variability in the Arctic Ocean from AOMIP models

[1] Monthly sea levels from five Arctic Ocean Model Intercomparison Project (AOMIP) models are analyzed and validated against observations in the Arctic Ocean. The AOMIP models are able to simulate variability of sea level reasonably well, but several improvements are needed to reduce model errors. It is suggested that the models will improve if their domains have a minimum depth less than 10 m. It is also recommended to take into account forcing associated with atmospheric loading, fast ice, and volume water fluxes representing Bering Strait inflow and river runoff. Several aspects of sea level variability in the Arctic Ocean are investigated based on updated observed sea level time series. The observed rate of sea level rise corrected for the glacial isostatic adjustment at 9 stations in the Kara, Laptev, and East Siberian seas for 1954–2006 is estimated as 0.250 cm/yr. There is a well pronounced decadal variability in the observed sea level time series. The 5-year running mean sea level signal correlates well with the annual Arctic Oscillation (AO) index and the sea level atmospheric pressure (SLP) at coastal stations and the North Pole. For 1954–2000 all model results reflect this correlation very well, indicating that the long-term model forcing and model reaction to the forcing are correct. Consistent with the influences of AO-driven processes, the sea level in the Arctic Ocean dropped significantly after 1990 and increased after the circulation regime changed from cyclonic to anticyclonic in 1997. In contrast, from 2000 to 2006 the sea level rose despite the stabilization of the AO index at its lowest values after 2000.

Comparing modeled streamfunction, heat and freshwater content in the Arctic Ocean

Within the framework of the Arctic Ocean Model Intercomparison Project results from several coupled sea ice–ocean models are compared in order to investigate vertically integrated properties of the Arctic Ocean. Annual means and seasonal ranges of streamfunction, freshwater and heat content are shown. For streamfunction the entire water column is integrated. For heat and freshwater content integration is over the upper 1000 m. The study represents a step toward identifying differences among model approaches and will serve as a base for upcoming studies where all models will be executed with common forcing. In this first stage only readily available outputs are compared, while forcing as well as numerical parameterizations differ. The intercomparison shows streamfunctions differing in pattern and by several Sverdrups in magnitude. Differences occur as well for the seasonal range, where streamfunction is subject to large variability.

On large-scale shifts in the Arctic Ocean and sea-ice conditions during 1979-98

Abstract Results from a regional model of the Arctic Ocean and sea ice forced with realistic atmospheric data are analyzed to understand recent climate variability in the region. The primary simulation uses daily-averaged 1979 atmospheric fields repeated for 20 years and then continues with interannual forcing derived from the European Centre for Medium-range Weather Forecasts for 1979−98. An eastward shift in the ice-ocean circulation, fresh-water distribution and Atlantic Water extent has been determined by comparing conditions between the early 1980s and 1990s. A new trend is modeled in the late 1990s, and has a tendency to return the large-scale sea-ice and upper ocean conditions to their state in the early 1980s. Both the sea-ice and the upper ocean circulation as well as fresh-water export from the Russian shelves and Atlantic Water recirculation within the Eurasian Basin indicate that the Arctic climate is undergoing another shift. This suggests an oscillatory behavior of the Arctic Ocean system. Interannual atmospheric variability appears to be the main and sufficient driver of simulated changes. The ice cover acts as an effective dynamic medium for vorticity transfer from the atmosphere into the ocean.