Richard E. Moritz

The large‐scale freshwater cycle of the Arctic

This paper synthesizes our understanding of the Arctics large-scale freshwater cycle. It combines terrestrial and oceanic observations with insights gained from the ERA-40 reanalysis and land surface and ice-ocean models. Annual mean freshwater input to the Arctic Ocean is dominated by river discharge (38%), inflow through Bering Strait (30%), and net precipitation (24%). Total freshwater export from the Arctic Ocean to the North Atlantic is dominated by transports through the Canadian Arctic Archipelago (35%) and via Fram Strait as liquid (26%) and sea ice (25%). All terms are computed relative to a reference salinity of 34.8. Compared to earlier estimates, our budget features larger import of freshwater through Bering Strait and larger liquid phase export through Fram Strait. While there is no reason to expect a steady state, error analysis indicates that the difference between annual mean oceanic inflows and outflows (∼8% of the total inflow) is indistinguishable from zero. Freshwater in the Arctic Ocean has a mean residence time of about a decade. This is understood in that annual freshwater input, while large (∼8500 km3), is an order of magnitude smaller than oceanic freshwater storage of ∼84,000 km3. Freshwater in the atmosphere, as water vapor, has a residence time of about a week. Seasonality in Arctic Ocean freshwater storage is nevertheless highly uncertain, reflecting both sparse hydrographic data and insufficient information on sea ice volume. Uncertainties mask seasonal storage changes forced by freshwater fluxes. Of flux terms with sufficient data for analysis, Fram Strait ice outflow shows the largest interannual variability.

Surface Heat Budget of the Arctic Ocean

A summary is presented of the Surface Heat Budget of the Arctic Ocean (SHEBA) project, with a focus on the field experiment that was conducted from October 1997 to October 1998. The primary objective of the field work was to collect ocean, ice, and atmospheric datasets over a full annual cycle that could be used to understand the processes controlling surface heat exchanges—in particular, the ice–albedo feedback and cloud–radiation feedback. This information is being used to improve formulations of arctic ice–ocean–atmosphere processes in climate models and thereby improve simulations of present and future arctic climate. The experiment was deployed from an ice breaker that was frozen into the ice pack and allowed to drift for the duration of the experiment. This research platform allowed the use of an extensive suite of instruments that directly measured ocean, atmosphere, and ice properties from both the ship and the ice pack in the immediate vicinity of the ship. This summary describes the project goal...

An annual cycle of Arctic surface cloud forcing at SHEBA

[1] We present an analysis of surface fluxes and cloud forcing from data obtained during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment, conducted in the Beaufort and Chuchki Seas and the Arctic Ocean from November 1997 to October 1998. The measurements used as part of this study include fluxes from optical radiometer sets, turbulent fluxes from an instrumented tower, cloud fraction from a depolarization lidar and ceilometer, and atmospheric temperature and humidity profiles from radiosondes. Clear-sky radiative fluxes were modeled in order to estimate the cloud radiative forcing since direct observation of fluxes in cloud-free conditions created large statistical sampling errors. This was particularly true during summer when cloud fractions were typically very high. A yearlong data set of measurements, obtained on a multiyear ice floe at the SHEBA camp, was processed in 20-day blocks to produce the annual evolution of the surface cloud forcing components: upward, downward, and net longwave and shortwave radiative fluxes and turbulent (sensible and latent heat) fluxes. We found that clouds act to warm the Arctic surface for most of the annual cycle with a brief period of cooling in the middle of summer. Our best estimates for the annual average surface cloud forcings are -10 W m -2 for shortwave, 38 W m -2 for longwave, and -6 W m -2 for turbulent fluxes. Total cloud forcing (the sum of all components) is about 30 W m -2 for the fall, winter, and spring, dipping to a minimum of -4 W m -2 in early July. We compare the results of this study with satellite, model, and drifting station data.

Maintenance of the Sea-Ice Edge

Abstract A coupled global climate model is used to evaluate processes that determine the equilibrium location of the sea-ice edge and its climatological annual cycle. The extent to which the wintertime ice edge departs from a symmetric ring around either pole depends primarily on coastlines, ice motion, and the melt rate at the ice–ocean interface. At any location the principal drivers of the oceanic heat flux that melts sea ice are absorbed solar radiation and the convergence of heat transported by ocean currents. The distance between the ice edge and the pole and the magnitude of the ocean heat flux convergence at the ice edge are inversely related. The chief exception to this rule is in the East Greenland Current, where the ocean heat flux convergence just east of the ice edge is relatively high but ice survives due to its swift southward motion and the protection of the cold southward-flowing surface water. In regions where the ice edge extends relatively far equatorward, absorbed solar radiation is t...

Sea Ice Response to Atmospheric and Oceanic Forcing in the Bering Sea

Abstract A coupled sea ice–ocean model is developed to quantify the sea ice response to changes in atmospheric and oceanic forcing in the Bering Sea over the period 1970–2008. The model captures much of the observed spatiotemporal variability of sea ice and sea surface temperature (SST) and the basic features of the upper-ocean circulation in the Bering Sea. Model results suggest that tides affect the spatial redistribution of ice mass by up to 0.1 m or 15% in the central-eastern Bering Sea by modifying ice motion and deformation and ocean flows. The considerable interannual variability in the pattern and strength of winter northeasterly winds leads to southwestward ice mass advection during January–May, ranging from 0.9 × 1012 m3 in 1996 to 1.8 × 1012 m3 in 1976 and averaging 1.4 × 1012 m3, which is almost twice the January–May mean total ice volume in the Bering Sea. The large-scale southward ice mass advection is constrained by warm surface waters in the south that melt 1.5 × 1012 m3 of ice in mainly t...

Toward an Explanation of the Annual Cycle of Cloudiness over the Arctic Ocean

Abstract The annual cycle of low cloud amount over the Arctic Ocean is examined using climatological data and a radiative-turbulent column model. Three hypotheses for the annual cycle are formulated, compared with climatological data for consistency, and then tested using the numerical model. The hypotheses identify three factors that might explain the difference in arctic low cloud amount between summer and winter: 1) the difference in surface specific humidity between the pack ice and the surrounding continents, 2) evaporation at the surface of the ice pack, and 3) the temperature-dependent formation and precipitation of atmospheric ice. Qualitatively, the hypotheses all appear to be consistent with available climatological data, except that the transition between the winter and summer cloudiness regimes occurs one month before the influx of atmospheric moisture increases from its wintertime level, which is inconsistent with the first hypothesis. The model, which includes a turbulence-closure cloud sche...

Multiyear Volume, Liquid Freshwater, and Sea Ice Transports through Davis Strait, 2004–10*

AbstractDavis Strait is a primary gateway for freshwater exchange between the Arctic and North Atlantic Oceans including freshwater contributions from west Greenland and Canadian Arctic Archipelago glacial melt. Data from six years (2004–10) of continuous measurements collected by a full-strait moored array and concurrent high-resolution Seaglider surveys are used to estimate volume and liquid freshwater transports through Davis Strait, with respective annual averages of −1.6 ± 0.5 Sverdrups (Sv; 1 Sv ≡ 106 m3 s−1) and −93 ± 6 mSv (negative sign indicates southward transport). Sea ice export contributes an additional −10 ± 1 mSv of freshwater transport, estimated using satellite ice area transport and moored upward-looking sonar ice thickness measurements. Interannual and annual variability of the net transports are large, with average annual volume and liquid freshwater transport standard deviations of 0.7 Sv and 17 mSv and with interannual standard deviations of 0.3 Sv and 15 mSv. Moreover, there are no...

North Pole Environmental Observatory delivers early results

Scientists have argued for a number of years that the Arctic may be a sensitive indicator of global change, but prior to the 1990s, conditions there were believed to be largely static. This has changed in the last 10 years. Decadal-scale changes have occurred in the atmosphere, in the ocean, and on land [Serreze et al., 2000]. Surface atmospheric pressure has shown a declining trend over the Arctic, resulting in a clockwise spin-up of the atmospheric polar vortex. In the 1990s, the Arctic Ocean circulation took on a more cyclonic character, and the temperature of Atlantic water in the Arctic Ocean was found to be the highest in 50 years of observation [Morison et al., 2000]. Sea-ice thickness over much of the Arctic decreased 43% in 1958–1976 and 1993–1997 [Rothrock et al., 1999].

Low-Frequency Variability in the Arctic Atmosphere, Sea Ice, and Upper-Ocean Climate System

Abstract The low-frequency natural variability of the arctic climate system is modeled using a single-column, energy balance model of the atmosphere. sea ice, and upper-ocean system. Variability in the system is induced by forcing with realistic, random perturbations in the atmospheric energy transport and cloudiness. The model predicts that the volume of perennial sea ice varies predominantly on decadal timescales, while other arctic climate variables vary mostly on intraannual and interannual timescales. The variance of the simulated sea ice volume is most sensitive to perturbations of the atmospheric forcing in late spring, at the onset of melt. The variance of sea ice volume increases with the mean sea ice thickness and with the number of layers resolved in the sea ice model. This suggests that much of the simulated variance develops when the surface temperature decouples from the sea ice interior during the late spring, when melting snow abruptly exposes the sea ice surface and decreases the surface ...

Sea ice kinematics and surface properties from RADARSAT synthetic aperture radar during the SHEBA drift

[1] Satellite data are important for providing the large-scale context of the Surface Heat Budget of the Arctic Ocean (SHEBA) station and for characterizing the spatial variability of the sea ice in its vicinity. The Canadian RADARSAT satellite collected 195 synthetic aperture radar (SAR) images of the SHEBA site over the course of the 1 year drift. The RADARSAT Geophysical Processor System (RGPS) used these images to compute the spatial pattern of ice motion within 100 km of the SHEBA station by tracking features in sequential images. From the ice motion data the divergence and shear of the pack ice are estimated. The divergence is large from November to January, followed by a gradual convergence from February through July. The character of the ice motion changes at the end of July, from piecewise rigid motion to free drift. The ice motion reverts to its winterlike character in late September. Thus the “kinematic” summer runs from late July to late September. The radar backscatter also goes through seasonal transitions, capturing the abrupt onset of melt (29 May) and freeze-up (15 August). The concentration of multiyear ice is about 94% in the fall, and its backscatter signature remains stable through spring. Multiyear and first-year ice cannot be distinguished during the summer melt season, when the mean backscatter is negatively correlated with the surface air temperature. The “thermodynamic” summer runs from late May to mid-August. INDEX TERMS: 4207 Oceanography: General: Arctic and Antarctic oceanography; 4275 Oceanography: General: Remote sensing and electromagnetic processes (0689); 4540 Oceanography: Physical: Ice mechanics and air/sea/ ice exchange processes; KEYWORDS: sea ice; synthetic aperture radar (SAR); SHEBA