ALBERT

Description: Maximum ice extents in the Arctic in 2005 and 2006 have been observed to be significantly lower (by about 6%) than the average of those of previous years starting in 1979. Since the winter maxima had been relatively stable with the trend being only about -1.5% per decade (compared to about -10% per decade for the perennial ice area), this is a significant development since signals from greenhouse warming are expected to be most prominent in winter. Negative ice anomalies are shown to be dominant in 2005 and 2006 especially in the Arctic basin and correlated with winds and surface temperature anomalies during the same period. Progressively increasing winter temperatures in the central Arctic starting in 1997 is observed with significantly higher rates of increase in 2005 and 2006. The Atlantic Oscillation (AO) indices correlate weakly with the sea ice and surface temperature anomaly data but may explain the recent shift in the perennial ice cover towards the western region. Results suggest that the trend in winter ice is finally in the process of catching up with that of the summer ice cover.

Description: Much of what we know about the large scale characteristics of the Okhotsk Sea ice cover has been provided by ice concentration maps derived from passive microwave data. To understand what satellite data represent in a highly divergent and rapidly changing environment like the Okhotsk Sea, we take advantage of concurrent satellite, aircraft, and ship data acquired on 7 February and characterized the sea ice cover at different scales from meters to hundreds of kilometers. Through comparative analysis of surface features using co-registered data from visible, infrared and microwave channels we evaluated the general radiative and physical characteristics of the ice cover as well as quantify the distribution of different ice types in the region. Ice concentration maps from AMSR-E using the standard sets of channels, and also only the 89 GHz channel for optimal resolution, are compared with aircraft and high resolution visible data and while the standard set provides consistent results, the 89 GHz provides the means to observe mesoscale patterns and some unique features of the ice cover. Analysis of MODIS data reveals that thick ice types represents about 37% of the ice cover indicating that young and new ice types represent a large fraction of the ice cover that averages about 90% ice concentration according to passive microwave data. These results are used to interpret historical data that indicate that the Okhotsk Sea ice extent and area are declining at a rapid rate of about -9% and -12 % per decade, respectively.

Description: Much of what we know about the large scale characteristics of the Okhotsk Sea ice cover comes from ice concentration maps derived from passive microwave data. To understand what these satellite data represents in a highly divergent and rapidly changing environment like the Okhotsk Sea, we analyzed concurrent satellite, aircraft, and ship data and characterized the sea ice cover at different scales from meters to tens of kilometers. Through comparative analysis of surface features using co-registered data from visible, infrared and microwave channels we evaluated how the general radiative and physical characteristics of the ice cover changes as well as quantify the distribution of different ice types in the region. Ice concentration maps from AMSR-E using the standard sets of channels, and also only the 89 GHz channel for optimal resolution, are compared with aircraft and high resolution visible data and while the standard set provides consistent results, the 89 GHz provides the means to observe mesoscale patterns and some unique features of the ice cover. Analysis of MODIS data reveals that thick ice types represents about 37% of the ice cover indicating that young and new ice represent a large fraction of the lice cover that averages about 90% ice concentration, according to passive microwave data. A rapid decline of -9% and -12 % per decade is observed suggesting warming signals but further studies are required because of aforementioned characteristics and because the length of the ice season is decreasing by only 2 to 4 days per decade.

Description: Sea ice in the Southern Ocean is a major controlling factor on phytoplankton productivity and growth, but the relationship is modified by regional differences in atmospheric and oceanographic conditions. We used the phytoplankton biomass (binned at 7-day intervals), PAR and cloud cover data from SeaWiFS, ice concentrations data from SSM/I and AMSR-E, and sea-surface temperature data from AVHRR, in combination with a vertically integrated model to estimate primary productivity throughout the Southern Ocean (south of 60"s). We also selected six areas within the Southern Ocean and analyzed the variability of the primary productivity and trends through time, as well as the relationship of sea ice to productivity. We found substantial interannual variability in productivity from 1997 - 2005 in all regions of the Southern Ocean, and this variability appeared to be driven in large part by ice dynamics. The most productive regions of Antarctic waters were the continental shelves, which showed the earliest growth, the maximum biomass, and the greatest areal specific productivity. In contrast, no large, sustained blooms occurred in waters of greater depth (〉 1,000 m). We suggest that this is due to the slightly greater mixed layer depths found in waters off the continental shelf, and that the interactive effects of iron and irradiance (that is, increased iron requirements in low irradiance environments) result in the limitation of phytoplankton biomass over large regions of the Southern Ocean.

Description: We use two algorithms to process AMSR-E data in order to determine algorithm dependence, if any, on the estimates of sea ice concentration, ice extent and area, and trends and to evaluate how AMSR-E data compare with historical SSM/I data. The monthly ice concentrations derived from the two algorithms from AMSR-E data (the AMSR-E Bootstrap Algorithm, or ABA, and the enhanced NASA Team algorithm, or NT2) differ on average by about 1 to 3%, with data from the consolidated ice region being generally comparable for ABA and NT2 retrievals while data in the marginal ice zones and thin ice regions show higher values when the NT2 algorithm is used. The ice extents and areas derived separately from AMSR-E using these two algorithms are, however, in good agreement, with the differences (ABA-NT2) being about 6.6 x 10(exp 4) square kilometers on average for ice extents and -6.6 x 10(exp 4) square kilometers for ice area which are small compared to mean seasonal values of 10.5 x 10(exp 6) and 9.8 x 10(exp 6) for ice extent and area: respectively. Likewise, extents and areas derived from the same algorithm but from AMSR-E and SSM/I data are consistent but differ by about -24.4 x 10(exp 4) square kilometers and -13.9 x 10(exp 4) square kilometers, respectively. The discrepancies are larger with the estimates of extents than area mainly because of differences in channel selection and sensor resolutions. Trends in extent during the AMSR-E era were also estimated and results from all three data sets are shown to be in good agreement (within errors).

Description: Arguably, the most remarkable manifestation of change in the polar regions is the rapid decline (of about -10 %/decade) in the Arctic perennial ice cover. Changes in the global sea ice cover, however, are more modest, being slightly positive in the Southern Hemisphere and slightly negative in the Northern Hemisphere, the significance of which has not been adequately assessed because of unknown errors in the satellite historical data. We take advantage of the recent and more accurate AMSR-E data to evaluate the true seasonal and interannual variability of the sea ice cover, assess the accuracy of historical data, and determine the real trend. Consistently derived ice concentrations from AMSR-E, SSM/I, and SMMR data were analyzed and a slight bias is observed between AMSR-E and SSM/I data mainly because of differences in resolution. Analysis of the combine SMMR, SSM/I and AMSR-E data set, with the bias corrected, shows that the trends in extent and area of sea ice in the Arctic region is -3.4 +/- 0.2 and -4.0 +/- 0.2 % per decade, respectively, while the corresponding values for the Antarctic region is 0.9 +/- 0.2 and 1.7 .+/- 0.3 % per decade. The higher resolution of the AMSR-E provides an improved determination of the location of the ice edge while the SSM/I data show an ice edge about 6 to 12 km further away from the ice pack. Although the current record of AMSR-E is less than 5 years, the data can be utilized in combination with historical data for more accurate determination of the variability and trends in the ice cover.

Description: Since microwave radiometric signals from sea-ice strongly reflect physical conditions of a layer near the ice surface, a relationship of brightness temperature with thickness is possible especially during the early stages of ice growth. Sea ice is most saline during formation stage and as the salinity decreases with time while at the same time the thickness of the sea ice increases, a corresponding change in the dielectric properties and hence the brightness temperature may occur. This study examines the extent to which the relationships of thickness with brightness temperature (and with emissivity) hold for thin sea-ice, approximately less than 0.2 -0.3 m, using near concurrent measurements of sea-ice thickness in the Sea of Okhotsk from a ship and passive microwave brightness temperature data from an over-flying aircraft. The results show that the brightness temperature and emissivity increase with ice thickness for the frequency range of 10-37 GHz. The relationship is more pronounced at lower frequencies and at the horizontal polarization. We also established an empirical relationship between ice thickness and salinity in the layer near the ice surface from a field experiment, which qualitatively support the idea that changes in the near-surface brine characteristics contribute to the observed thickness-brightness temperature/emissivity relationship. Our results suggest that for thin ice, passive microwave radiometric signals contain, ice thickness information which can be utilized in polar process studies.

Description: Time-series of remotely sensed distributions of phytoplankton, sea ice, surface temperature, albedo, and clouds were examined to evaluate the impact of the variability of environmental conditions and physical forcing on the phytoplankton distribution in the Beaufort and Chukchi Seas. Large-scale distributions of these parameters were studied for the first time using weekly and monthly composites from April 1998 through September 2002. The basic data set used in this study are phytoplankton pigment concentration derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), ice concentration obtained from the Special Sensor Microwave Imager (SSM/I) and surface temperature, cloud cover, and albedo derived from the Advanced Very High Resolution Radiometer (AVHRR). Seasonal variations of the sea ice cover was observed to be the dominant environmental factor as the ice edge blooms followed the retreating marginal ice zones northward. Blooms were most prominent in the southwestern Chukchi Sea, and were especially persistent immediately north of the Bering Strait in nutrient- rich Anadyr water and in some fronts. Chlorophyll concentrations are shown to increase from a nominal value during onset of melt in April to a maximum value in mid-spring or summer depending on location. Large interannual variability of ice cover and phytoplankton distributions was observed with the year 1998 being uniquely associated with an early season occurrence of a massive bloom. This is postulated to be caused in part by a rapid response of phytoplankton to an early retreat of the sea ice cover in the Beaufort Sea region. Correlation analyses showed relatively high negative correlation between chlorophyll and ice concentration with the correlation being highest in May, the correlation coefficient being -0.45. 1998 was also the warmest among the five years globally and the sea ice cover was least extensive in the Beaufort-Khukchi Sea region, partly because of the 1997-98 El Nino. Strong correlations were noted between ice extent and surface temperature, the correlation coefficient being highest at - 0.79 in April, during the onset of the bloom period

Description: Global warming signals are expected to be amplified in the Arctic primarily because of ice-albedo feedback associated with the high reflectivity of ice and snow that blankets much of the region. The Arctic had been a poorly explored territory basically because of its general inaccessibility on account of extremely harsh weather conditions and the dominant presence of thick perennial ice in the region. The advent of satellite remote sensing systems since the 1960s, however, enabled the acquisition of synoptic data that depict in good spatial detail the temporal changes of many Arctic surface parameters. Among the surface parameters that have been studied using space based systems are surface temperature, sea ice concentration, snow cover, surface albedo and phytoplankton concentration. Associated atmospheric parameters, such as cloud cover, temperature profile, ozone concentration, and aerosol have also been derived. Recent observational and phenomenological studies have indeed revealed progressively changing conditions in the Arctic during the last few decades (e g , Walsh et al. 1996; Serreze et al 2000; Comiso and Parkinson 2004). The changes included declines in the extent and area of surfaces covered by sea ice and snow, increases in melt area over the Greenland ice sheets, thawing of the permafrost, warming in the troposphere, and retreat of the glaciers. These observations are consistent with the observed global warming that has been associated with the increasing concentration of greenhouse gases in the atmosphere (Karl and Trenberth 2003) and confirmed by modeling studies (Holland and Bitz, 2003). The Arctic system, however, is still not well understood complicated by a largely fluctuating wind circulation and atmospheric conditions (Proshutinsky and Johnson 1997) and controlled by what is now known as the Arctic Oscillation (AO) which provides a measure of the strength of atmospheric activities in the region (Thompson and Wallace 1998). Meanwhile, the observed Arctic conditions since the 1970s have been shown to exhibit a linear behavior that directly contradicts what has been expected from the A0 (Overland, 2005). The decade of the 1990s has been regarded as the warmest decade in the last century and current data indicates that the 2000s may be even a warmer decade than the 1990s further supporting the linear variability. In this paper, we use satellite data to gain insights into the warming Arctic and how the abnormally warm conditions during the last few years are reflected in the region.

Description: Preliminary results are presented from the first validation of geophysical data products (ice concentration, snow thickness on sea ice (h(sub s) and ice temperature (T(sub i))fr om the NASA EOS Aqua AMSR-E sensor, in East Antarctica (in September-October 2003). The challenge of collecting sufficient measurements with which to validate the coarse-resolution AMSR-E data products adequately was addressed by means of a hierarchical approach, using detailed in situ measurements, digital aerial photography and other satellite data. Initial results from a circumnavigation of the experimental site indicate that, at least under cold conditions with a dry snow cover, there is a reasonably close agreement between satellite- and aerial-photo-derived ice concentrations, i.e. 97.2+/-.6% for NT2 and 96.5+/-2.5% for BBA algorithms vs 94.3% for the aerial photos. In general, the AMSR-E concentration represents a slight overestimate of the actual concentration, with the largest discrepancies occurring in regions containing a relatively high proportion of thin ice. The AMSR-E concentrations from the NT2 and BBA algorithms are similar on average, although differences of up to 5% occur in places, again related to thin-ice distribution. The AMSR-E ice temperature (T(sub i)) product agrees with coincident surface measurements to approximately 0.5 C in the limited dataset analyzed. Regarding snow thickness, the AMSR h(sub s) retrieval is a significant underestimate compared to in situ measurements weighted by the percentage of thin ice (and open water) present. For the case study analyzed, the underestimate was 46% for the overall average, but 23% compared to smooth-ice measurements. The spatial distribution of the AMSR-E h(sub s) product follows an expected and consistent spatial pattern, suggesting that the observed difference may be an offset (at least under freezing conditions). Areas of discrepancy are identified, and the need for future work using the more extensive dataset is highlighted.