The extent of Arctic perennial sea ice, the year‐round ice cover, was significantly reduced between March 2005 and March 2007 by 1.08 × 106 km2, a 23% loss from 4.69 × 106 km2 to 3.61 × 106 km2, as observed by the QuikSCAT/SeaWinds satellite scatterometer (QSCAT). Moreover, the buoy‐based Drift‐Age Model (DM) provided long‐term trends in Arctic sea‐ice age since the 1950s. Perennial‐ice extent loss in March within the DM domain was noticeable after the 1960s, and the loss became more rapid in the 2000s when QSCAT observations were available to verify the model results. QSCAT data also revealed mechanisms contributing to the perennial‐ice extent loss: ice compression toward the western Arctic, ice loading into the Transpolar Drift (TD) together with an acceleration of the TD carrying excessive ice out of Fram Strait, and ice export to Baffin Bay. Dynamic and thermodynamic effects appear to be combining to expedite the loss of perennial sea ice.

The Department of Energy (DOE) supported Parallel Climate Model (PCM) makes use of the NCAR Community Climate Model (CCM3) and Land Surface Model (LSM) for the atmospheric and land surface components, respectively, the DOE Los Alamos National Laboratory Parallel Ocean Program (POP) for the ocean component, and the Naval Postgraduate School sea-ice model. The PCM executes on several distributed and shared memory computer systems. The coupling method is similar to that used in the NCAR Climate System Model (CSM) in that a¯ux coupler ties the components together, with interpolations between the dierent grids of the component models. Flux adjustments are not used in the PCM. The ocean component has 2/3°average horizontal grid spacing with 32 vertical levels and a free surface that allows calculation of sea level changes. Near the equator, the grid spacing is approximately 1/2°in latitude to better capture the ocean equatorial dynamics. The North Pole is rotated over northern North America thus producing resolution smaller than 2/3°in the North Atlantic where the sinking part of the world conveyor circulation largely takes place. Because this ocean model component does not have a computational point at the North Pole, the Arctic Ocean circulation systems are more realistic and similar to the observed. The elastic viscous plastic sea ice model has a grid spacing of 27 km to represent small-scale features such as ice transport through the Canadian Archipelago and the East Greenland current region. Results from a 300 year present-day coupled climate control simulation are presented, as well as for a transient 1% per year compound CO 2 increase experiment which shows a global warming of 1.27°C for a 10 year average at the doubling point of CO 2 and 2.89°C at the quadrupling point. There is a gradual warming beyond the doubling and quadrupling points with CO 2 held constant. Globally averaged sea level rise at the time of CO 2 doubling is approximately 7 cm and at the time of quadrupling it is 23 cm. Some of the regional sea level changes are larger and re¯ect the adjustments in the temperature, salinity, internal ocean dynamics, surface heat¯ux, and wind stress on the ocean. A 0.5% per year CO 2 increase experiment also was performed showing a global warming of 1.5°C around the time of CO 2 doubling and a similar warming pattern to the 1% CO 2 per year increase experiment. El NinÄ o and La NinÄ a events in the tropical Paci®c show approximately the observed frequency distribution and amplitude, which leads to near observed levels of variability on interannual time scales.

1980s drafts were composed largely of ice exceeding 3.5 m, while the early 1990s drafts contained more ice in thinner categories. The differences in drafts between the two periods appear to be related largely to ice dynamics effects associated with the presence and strength of the Beaufort Gyre, which weakened considerably in the early 1990s.

Arctic air masses have direct impacts on the weather and climatic extremes of midlatitude areas such as central North America. Arctic physical processes pose special and very important problems for global atmospheric models used for climate simulation and numerical weather prediction. At present, the observational database is inadequate to support research aimed at overcoming these problems. Three interdependent Arctic field programs now being planned will help to remedy this situation: SHEBA, which will operate an ice camp in the Arctic for a year; ARM, which will supply instruments for use at the SHEBA ice camp and which will also conduct longer-term measurements near Barrow, Alaska; and FIRE, which will conduct one or more aircraft campaigns, in conjunction with remote-sensing investigations focused on the SHEBA ice camp. This paper provides an introductory overview of the physics of the Arctic from the perspective of large-scale modelers, outlines some of the modeling problems that arise in attempting to simulate these processes, and explains how the data to be provided by the three field programs can be used to test and improve large-scale models.