[1] Recent progress in sea ice concentration remote sensing by satellite microwave radiometers has been stimulated by two developments: First, the new sensor Advanced Microwave Scanning Radiometer-EOS (AMSR-E) offers spatial resolutions of approximately 6 Â 4 km at 89 GHz, nearly 3 times the resolution of the standard sensor SSM/I at 85 GHz (15 Â 13 km). Second, a new algorithm enables estimation of sea ice concentration from the channels near 90 GHz, despite the enhanced atmospheric influence in these channels. This allows full exploitation of their horizontal resolution, which is up to 4 times finer than that of the channels near 19 and 37 GHz, the frequencies used by the most widespread algorithms for sea ice retrieval, the NASA-Team and Bootstrap algorithms. The ASI algorithm used combines a model for retrieving the sea ice concentration from SSM/I 85-GHz data proposed by Svendsen et al. (1987) with an ocean mask derived from the 18-, 23-, and 37-GHz AMSR-E data using weather filters. During two ship campaigns, the correlation of ASI, NASA-Team 2, and Bootstrap algorithms ice concentrations with bridge observations were 0.80, 0.79, and 0.81, respectively. Systematic differences over the complete AMSR-E period (2002AMSR-E period ( -2006 between ASI and NASA-Team 2 are below À2 ± 8.8%, and between ASI and Bootstrap are 1.7 ± 10.8%. Among the geophysical implications of the ASI algorithm are: (1) Its higher spatial resolution allows better estimation of crucial variables in numerical atmospheric and ocean models, for example, the heat flux between ocean and atmosphere, especially near coastlines and in polynyas. (2) It provides an additional time series of ice area and extent for climate studies.

Large freshwater anomalies clearly exist in the Arctic Ocean. For example, liquid freshwater has accumulated in the Beaufort Gyre in the decade of the 2000s compared to 1980-2000, with an extra ≈ 5000 km 3-about 25%-being stored. The sources of freshwater to the Arctic from precipitation and runoff have increased between these periods (most of the evidence comes from models).

The Arctic icescape is rapidly transforming from a thicker multiyear ice cover to a thinner and largely seasonal first-year ice cover with significant consequences for Arctic primary production. One critical challenge is to understand how productivity will change within the next decades. Recent studies have reported extensive phytoplankton blooms beneath ponded sea ice during summer, indicating that satellite-based Arctic annual primary production estimates may be significantly underestimated. Here we present a unique time-series of a phytoplankton spring bloom observed beneath snow-covered Arctic pack ice. The bloom, dominated by the haptophyte algae Phaeocystis pouchetii, caused near depletion of the surface nitrate inventory and a decline in dissolved inorganic carbon by 16 ± 6 g C m−2. Ocean circulation characteristics in the area indicated that the bloom developed in situ despite the snow-covered sea ice. Leads in the dynamic ice cover provided added sunlight necessary to initiate and sustain the bloom. Phytoplankton blooms beneath snow-covered ice might become more common and widespread in the future Arctic Ocean with frequent lead formation due to thinner and more dynamic sea ice despite projected increases in high-Arctic snowfall. This could alter productivity, marine food webs and carbon sequestration in the Arctic Ocean.

[1] We examine the basinwide trends in sea ice circulation and drift speed and highlight the changes between 1982 and 2009 in connection to regional winds, multiyear sea ice coverage, ice export, and the thinning of the ice cover. The polarity of the Arctic Oscillation (AO) is used as a backdrop for summarizing the variance and shifts in decadal drift patterns. The 28-year circulation fields show a net strengthening of the Beaufort Gyre and the Transpolar Drift, especially during the last decade. The imprint of the arctic dipole anomaly on the mean summer circulation is evident (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)) and enhances summer ice area export at the Fram Strait. Between 2001 and 2009, the large spatially averaged trends in drift speeds (winter: þ23.6%/decade, summer: þ17.7%/decade) are not explained by the much smaller trends in wind speeds (winter: 1.46%/decade, summer: À3.42%/decade). Notably, positive trends in drift speed are found in regions with reduced multiyear sea ice coverage. Over 90% of the Arctic Ocean has positive trends in drift speed and negative trends in multiyear sea ice coverage. The increased responsiveness of ice drift to geostrophic wind is consistent with a thinner and weaker seasonal ice cover and suggests large-scale changes in the air-ice-ocean momentum balance. The retrieved mean ocean current field from decadal-scale average ice motion captures a steady drift from Siberia to the Fram Strait, an inflow north of the Bering Strait, and a westward drift along coastal Alaska. This mean current is comparable to geostrophic currents from satellite-derived dynamic topography.Citation: Kwok, R., G. Spreen, and S. Pang (2013), Arctic sea ice circulation and drift speed: Decadal trends and ocean currents, J.

[1] We examine the spatial trends in Arctic sea ice drift speed from satellite data and the role of wind forcing for the winter months of October through May. Between 1992 and 2009, the spatially averaged trend in drift speed within the Arctic Basin is 10.6% ± 0.9%/decade, and ranges between −4% and 16%/decade depending on the location. The mean trend is dominated by the second half of the period. In fact, for the five years after a clear break point in March 2004, the average trend increased to 46% ± 5%/decade. Over the 1992-2009 period, averaged trends of wind speed from four atmospheric reanalyses are only 1% to 2%/decade. Regionally, positive trends in wind speed (of up to 9%/decade) are seen over a large fraction of the Central Arctic, where the trends in drift speeds are highest. Spatial correlations between the basin-wide trends in wind and drift speeds are moderate (between 0.40 and 0.52). Our results suggest that changes in wind speed explain a fraction of the observed increase in drift speeds in the Central Arctic but not over the entire basin. In other regions thinning of the ice cover is a more likely cause of the increase in ice drift speed.

Arctic sea ice has displayed significant thinning as well as an increase in drift speed in recent years. Taken together this suggests an associated rise in sea ice deformation rate. A winter and spring expedition to the sea ice covered region north of Svalbard–the Norwegian young sea ICE2015 expedition (N‐ICE2015)—gave an opportunity to deploy extensive buoy arrays and to monitor the deformation of the first‐year and second‐year ice now common in the majority of the Arctic Basin. During the 5 month long expedition, the ice cover underwent several strong deformation events, including a powerful storm in early February that damaged the ice cover irreversibly. The values of total deformation measured during N‐ICE2015 exceed previously measured values in the Arctic Basin at similar scales: At 100 km scale, N‐ICE2015 values averaged above 0.1 d−1, compared to rates of 0.08 d−1 or less for previous buoy arrays. The exponent of the power law between the deformation length scale and total deformation developed over the season from 0.37 to 0.54 with an abrupt increase immediately after the early February storm, indicating a weakened ice cover with more free drift of the sea ice floes. Our results point to a general increase in deformation associated with the younger and thinner Arctic sea ice and to a potentially destructive role of winter storms.

Clouds play an important role in Arctic amplification. This term represents the recently observed enhanced warming of the Arctic relative to the global increase of near-surface air temperature. However, there are still important knowledge gaps regarding the interplay between Arctic clouds and aerosol particles, and surface properties, as well as turbulent and radiative fluxes that inhibit accurate model simulations of clouds in the Arctic climate system. In an attempt to resolve this so-called Arctic cloud puzzle, two comprehensive and closely coordinated field studies were conducted: the Arctic Cloud Observations Using Airborne Measurements during Polar Day (ACLOUD) aircraft campaign and the Physical Feedbacks of Arctic Boundary Layer, Sea Ice, Cloud and Aerosol (PASCAL) ice breaker expedition. Both observational studies were performed in the framework of the German Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC) project. They took place in the vicinity of Svalbard, Norway, in May and June 2017. ACLOUD and PASCAL explored four pieces of the Arctic cloud puzzle: cloud properties, aerosol impact on clouds, atmospheric radiation, and turbulent dynamical processes. The two instrumented Polar 5 and Polar 6 aircraft; the icebreaker Research Vessel (R/V) Polarstern; an ice floe camp including an instrumented tethered balloon; and the permanent ground-based measurement station at Ny-Ålesund, Svalbard, were employed to observe Arctic low- and mid-level mixed-phase clouds and to investigate related atmospheric and surface processes. The Polar 5 aircraft served as a remote sensing observatory examining the clouds from above by downward-looking sensors; the Polar 6 aircraft operated as a flying in situ measurement laboratory sampling inside and below the clouds. Most of the collocated Polar 5/6 flights were conducted either above the R/V Polarstern or over the Ny-Ålesund station, both of which monitored the clouds from below using similar but upward-looking remote sensing techniques as the Polar 5 aircraft. Several of the flights were carried out underneath collocated satellite tracks. The paper motivates the scientific objectives of the ACLOUD/PASCAL observations and describes the measured quantities, retrieved parameters, and the applied complementary instrumentation. Furthermore, it discusses selected measurement results and poses critical research questions to be answered in future papers analyzing the data from the two field campaigns.

[1] Satellite-based estimates of monthly sea ice volume exports through Fram Strait for the years 2003 to 2008 are presented. These are obtained from individual satellite observations of sea ice thickness, area, and drift. First, sea ice freeboard is inferred from ICESat laser altimeter observations and then converted to ice thickness estimates. Sea ice area and drift are derived from AMSR-E 89 GHz data. Retrieved sea ice thickness estimates compare within 0.5 m with the few ULS data available in the Fram Strait. The mean, minimum, and maximum observed monthly Fram Strait sea ice volume export amounts to 217, 92, and 420 km 3 /month, respectively. In comparison to former Fram Strait sea ice volume export estimates obtained during the 1990s our estimates are slightly smaller (À33 km 3 /month) but are within the natural variability and no significant change of the total amount of Fram Strait sea ice export can be observed.