Florence Fetterer

A record minimum arctic sea ice extent and area in 2002

[1] Arctic sea ice extent and area in September 2002 reached their lowest levels recorded since 1978. These conditions likely resulted from (1) anomalous warm southerly winds in spring, advecting ice poleward from the Siberian coast (2) persistent low pressure and high temperatures over the Arctic Ocean in summer, promoting ice divergence and rapid melt.

Observations of melt ponds on Arctic sea ice

In an introductory section we review the physical processes influencing the formation and evolution of melt ponds on sea ice during the Arctic summer. As melt progresses, the changing properties of the surface interact strongly with the surface heat balance. The small interannual variability of the seasonal ice extent suggests an interannual variability of the surface heat balance of ±1 W m−2 or less. The interannual variance of atmospheric forcing represented by the transport of moist static energy into the Arctic is an order of magnitude greater. This appears to contradict the notion of a highly sensitive sea ice cover and emphasizes the need to generate albedo as an important internal variable in interactive models. Observations of melt ponds are needed in order to derive improved relationships between surface albedo and parameters such as the amount of snow, the onset and termination of melting, the ice thickness distribution, and ice deformation. Here classified (National Technical Means) imagery is used to measure melt pond coverage as it evolves over a summer on ice surrounding a drifting buoy. Local variability of pond cover is greatest at the beginning of the melt season, that is, pond coverage from 5% to 50% depending on ice type, as previously found by Russian investigators. An important distinction is found in the temporal change of pond cover: it decreases with time on thick ice, and it increases with time on thin ice (eventually leading to the disappearance of thin ice at the end of summer). An attempt to relate pond coverage to ice concentrations derived from passive microwave data proved unsuccessful.

Whither Arctic sea ice? A clear signal of decline regionally, seasonally and extending beyond the satellite record

Abstract The Arctic sea ice has been pointed to as one of the first and clearest indicators of climate change. Satellite passive microwave observations from 1979 through 2005 now indicate a significant –8.4±1.5% decade–1 trend (99% confidence level) in September sea-ice extent, a larger trend than earlier estimates due to acceleration of the decline over the past 41 years. There are differences in regional trends, with some regions more stable than others; not all regional trends are significant. The largest trends tend to occur in months where melt is at or near its peak for a given region. A longer time series of September extents since 1953 was adjusted to correct biases and extended through 2005. The trend from the longer time series is –7.7±0.6% decade–1 (99%), slightly less than from the satellite-derived data that begin in 1979, which is expected given the recent acceleration in the decline.

Reductions in Arctic sea ice cover no longer limited to summer

Summer sea ice in the Arctic has shown a significant downward trend of 8% per decade since the late 1970s, leading to a reduction of approximately 20% in sea ice extent in September (when the annual minimum occurs) (Stroeve et al., 2005). The past three summers (2002–2004) have been among the lowest on record, and 2002 was the extreme minimum. Despite decreasing summer extents, the sea ice extent has typically rebounded to near-normal levels during the winter season, yielding an annual average trend of only −3%. This is not surprising since as temperatures drop below freezing, sea ice quickly forms.

Surface roughness characterizations of sea ice and ice sheets: case studies with MISR data

This work is an examination of potential uses of multiangular remote sensing imagery for mapping and characterizing sea ice and ice sheet surfaces based on surface roughness properties. We use data from the Multi-angle Imaging SpectroRadiometer (MISR) to demonstrate that ice sheet and sea ice surfaces have characteristic angular signatures and that these angular signatures may be used in much the same way as spectral signatures are used in multispectral classification. Three case studies are examined: sea ice in the Beaufort Sea off the north coast of Alaska, the Jakobshavn Glacier on the western edge of the Greenland ice sheet, and a region in Antarctica south of McMurdo station containing glaciers and blue-ice areas. The MISR sea ice image appears to delineate different first-year ice types and, to some extent, the transition from first-year to multiyear ice. The MISR image shows good agreement with sea ice types that are evident in concurrent synthetic aperture radar (SAR) imagery and ice analysis charts from the National Ice Center. Over the Jakobshavn Glacier, surface roughness data from airborne laser altimeter transects correlate well with MISR-derived estimates of surface roughness. In Antarctica, ablation-related blue-ice areas, which are difficult to distinguish from bare ice exposed by crevasses, are easily detected using multiangular data.

Sea ice type maps from Alaska Synthetic Aperture Radar Facility imagery: An assessment

Synthetic aperture radar (SAR) imagery received at the Alaska SAR Facility is routinely and automatically classified on the Geophysical Processor System (GPS) to create ice type maps. We evaluated the wintertime performance of the GPS classification algorithm by comparing ice type percentages from supervised classification with percentages from the algorithm. The RMS difference for multiyear ice is about 6%, while the inconsistency in supervised classification is about 3%. The algorithm separates first-year from multiyear ice well, although it sometimes fails to correctly classify new ice and open water owing to the wide distribution of backscatter for these classes. Our results imply a high degree of accuracy and consistency in the growing archive of multiyear and first-year ice distribution maps. These results have implications for heat and mass balance studies which are furthered by the ability to accurately characterize ice type distributions over a large part of the Arctic.

A database for depicting Arctic sea ice variations back to 1850

Abstract Arctic sea ice data from a variety of historical sources have been synthesized into a database extending back to 1850 with monthly time‐resolution. The synthesis procedure includes interpolation to a uniform grid and an analog‐based estimation of ice concentrations in areas of no data. The consolidated database shows that there is no precedent as far back as 1850 for the 21st centurys minimum ice extent of sea ice on the pan‐Arctic scale. A regional‐scale exception to this statement is the Bering Sea. The rate of retreat since the 1990s is also unprecedented and especially large in the Beaufort and Chukchi Seas. Decadal and multidecadal variations have occurred in some regions, but their magnitudes are smaller than that of the recent ice loss. Interannual variability is prominent in all regions and will pose a challenge to sea ice prediction efforts.

Sea ice index monitors polar ice extent

In September 2002, Arctic sea ice extent reached a minimum unprecedented in 24 years of satellite passive microwave observations, and almost certainly unmatched in 50 years of charting Arctic ice [Serreze et al., 2003]. Again, in September 2003, ice retreated to an unusually low extent, almost equaling the previous years minimum (Figure l). The Sea Ice Index (http://nsidc.org/data/seaice_index/), an easy-to-use source of information on sea ice trends and anomalies, assists in observing these minima. The Sea Ice Index is intended for both researchers and the scientifically inclined general public.

How do sea-ice concentrations from operational data compare with passive microwave estimates? Implications for improved model evaluations and forecasting

Abstract Passive microwave sensors have produced a 35 year record of sea-ice concentration variability and change. Operational analyses combine a variety of remote-sensing inputs and other sources via manual integration to create high-resolution, accurate charts of ice conditions in support of navigation and operational forecast models. One such product is the daily Multisensor Analyzed Sea Ice Extent (MASIE). The higher spatial resolution along with multiple input data and manual analysis potentially provide more precise mapping of the ice edge than passive microwave estimates. However, since MASIE is based on an operational product, estimates may be inconsistent over time due to variations in input data quality and availability. Comparisons indicate that MASIE shows higher Arctic-wide extent values throughout most of the year, largely because of the limitations of passive microwave sensors in some conditions (e.g. surface melt). However, during some parts of the year, MASIE tends to indicate less ice than estimated by passive microwave sensors. These comparisons yield a better understanding of operational and research sea-ice data products; this in turn has important implications for their use in climate and weather models.

Multi-year ice concentration from RADARSAT

The U.S. National Ice Center requires a robust multiyear ice classification algorithm that can handle variability in backscatter across uncalibrated 500 km RADARSAT scenes. ERS-1 images are used to test a dynamic threshold algorithm. The best results were obtained with a window size of 32, delta of 0.8, Fisher partition criterion and closing.