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Julienne Stroeve and Konrad Steffen

Abstract

The Advanced Very High Resolution Radiometer is used to derive surface temperatures for one satellite pass under clear skies over the Greenland ice sheet from 1989 through 1993. The results of these temperatures are presented as monthly means, and their spatial and temporal variability are discussed. Accuracy of the dry snow surface temperatures is estimated to be better than 1 K during summer. This error is expected to increase during polar night due to problems in cloud identification. Results indicate the surface temperature of the Greenland ice sheet is strongly dominated by topography, with minimum surface temperatures associated with the high elevation regions. In the summer, maximum surface temperatures occur during July along the western coast and southern tip of the ice sheet. Minimum temperatures are found at the summit during summer and move farther north during polar night. Large interannual variability in surface temperatures occurs during winter associated with katabatic storm events. Summer temperatures show little variation, although 1992 stands out as being colder than the other years. The reason for the lower temperatures during 1992 is believed to be a result of the 1991 eruption of Mount Pinatubo.

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Julienne Stroeve, Marcel Haefliger, and Konrad Steffen

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The relationship between Along Track Scanning Radiometer (ATSR) thermal radiances and snow surface temperature for the Greenland ice sheet is examined through forward calculations of the LOWTRAN 7 radiative transfer model. Inputs to the model include in situ radiosonde profile measurements of temperature, pressure and humidity, surface temperatures, and cloud observations for spring-summer 1990 and 1991 from the ETH-CU research camp, located at 69°34′N, 49°18′W on the Greenland ice sheet. Atmospheric correction coefficients were determined through a statistical analysis of daily clear-sky profiles for three different combinations of the ATSR thermal infrared (TIR) channels. Using all available ATSR TIR information, the 11- and 12-μm channels in both the nadir and forward views showed the smallest rms error of less than 0.2 K in the estimated surface temperature. This dual-view algorithm was found to be least sensitive to changes in concentrations of atmospheric constituents, in contrast to the standard “split-window” technique. Assuming accurate surface emissivities can be obtained, the dual-view algorithm is recommended for applications in polar regions where the variety of atmospheric conditions can be large.

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William Gregory, Michel Tsamados, Julienne Stroeve, and Peter Sollich

Abstract

Reliable predictions of the Arctic sea ice cover are becoming of paramount importance for Arctic communities and industry stakeholders. In this study pan-Arctic and regional September mean sea ice extents are forecast with lead times of up to 3 months using a complex network statistical approach. This method exploits relationships within climate time series data by constructing regions of spatiotemporal homogeneity (i.e., nodes), and subsequently deriving teleconnection links between them. Here the nodes and links of the networks are generated from monthly mean sea ice concentration fields in June, July, and August; hence, individual networks are constructed for each respective month. Network information is then utilized within a linear Gaussian process regression forecast model, a Bayesian inference technique, in order to generate predictions of sea ice extent. Pan-Arctic forecasts capture a significant amount of the variability in the satellite observations of September sea ice extent, with detrended predictive skills of 0.53, 0.62, and 0.81 at 3-, 2-, and 1-month lead times, respectively. Regional forecasts are also performed for nine Arctic regions. On average, the highest predictive skill is achieved in the Canadian Archipelago, Beaufort, Chukchi, East Siberian, Laptev, and Kara Seas, although the ability to accurately predict many of these regions appears to be changing over time.

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Tomoko Koyama, Julienne Stroeve, John Cassano, and Alex Crawford

Abstract

Extensive summer sea ice loss has occurred within the Beaufort, Chukchi, East Siberian, and Laptev Seas over the last decade. Associated anomalies in sensible and latent heat fluxes in autumn have increased Arctic atmospheric precipitable water and air temperatures, with the potential to impact autumn and winter cyclone activity. To examine if a connection exists between recent Arctic sea ice loss and cyclone activity, several cyclone metrics from 60° to 90°N are analyzed. Results show that following years with less September sea ice, there is a subsequent increase in moisture availability, regional baroclinicity, and changes in vertical stability that favor cyclogenesis. However, tracking of individual cyclones indicates no coherent increase in cyclone frequency or intensity associated with sea ice loss. Furthermore, no robust northward progression of extreme cyclones is observed.

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Linette N. Boisvert, Alek A. Petty, and Julienne C. Stroeve

Abstract

Atmospheric data from the Atmospheric Infrared Sounder (AIRS) were used to study an extreme warm and humid air mass transported over the Barents–Kara Seas region by an Arctic cyclone at the end of December 2015. Temperature and humidity in the region was ~10°C (>3σ above the 2003–14 mean) warmer and ~1.4 g kg−1 (>4σ above the 2003–14 mean) wetter than normal during the peak of this event. This anomalous air mass resulted in a large and positive flux of energy into the surface via the residual of the surface energy balance (SEB), compared to the weakly negative SEB from the surface to the atmosphere expected for that time of year. The magnitude of the downwelling longwave radiation during the event was unprecedented compared to all other events detected by AIRS in December/January since 2003. An approximate budget scaling suggests that this anomalous SEB could have resulted in up to 10 cm of ice melt. Thinning of the ice pack in the region was supported by remotely sensed and modeled estimates of ice thickness change. Understanding the impact of this anomalous air mass on a thinner, weakened sea ice state is imperative for understanding future sea ice–atmosphere interactions in a warming Arctic.

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Ingrid H. Onarheim, Tor Eldevik, Lars H. Smedsrud, and Julienne C. Stroeve

Abstract

The Arctic Ocean is currently on a fast track toward seasonally ice-free conditions. Although most attention has been on the accelerating summer sea ice decline, large changes are also occurring in winter. This study assesses past, present, and possible future change in regional Northern Hemisphere sea ice extent throughout the year by examining sea ice concentration based on observations back to 1950, including the satellite record since 1979. At present, summer sea ice variability and change dominate in the perennial ice-covered Beaufort, Chukchi, East Siberian, Laptev, and Kara Seas, with the East Siberian Sea explaining the largest fraction of September ice loss (22%). Winter variability and change occur in the seasonally ice-covered seas farther south: the Barents Sea, Sea of Okhotsk, Greenland Sea, and Baffin Bay, with the Barents Sea carrying the largest fraction of loss in March (27%). The distinct regions of summer and winter sea ice variability and loss have generally been consistent since 1950, but appear at present to be in transformation as a result of the rapid ice loss in all seasons. As regions become seasonally ice free, future ice loss will be dominated by winter. The Kara Sea appears as the first currently perennial ice-covered sea to become ice free in September. Remaining on currently observed trends, the Arctic shelf seas are estimated to become seasonally ice free in the 2020s, and the seasonally ice-covered seas farther south to become ice free year-round from the 2050s.

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Louis-Philippe Caron, François Massonnet, Philip J. Klotzbach, Tom J. Philp, and Julienne Stroeve
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Louis-Philippe Caron, François Massonnet, Philip J. Klotzbach, Tom J. Philp, and Julienne Stroeve
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David J. Diner, Gregory P. Asner, Roger Davies, Yuri Knyazikhin, Jan-Peter Muller, Anne W. Nolin, Bernard Pinty, Crystal B. Schaaf, and Julienne Stroeve

The physical interpretation of simultaneous multiangle observations represents a relatively new approach to remote sensing of terrestrial geophysical and biophysical parameters. Multiangle measurements enable retrieval of physical scene characteristics, such as aerosol type, cloud morphology and height, and land cover (e.g., vegetation canopy type), providing improved albedo accuracies as well as compositional, morphological, and structural information that facilitates addressing many key climate, environmental, and ecological issues. While multiangle data from wide field-of-view scanners have traditionally been used to build up directional “signatures” of terrestrial scenes through multitemporal compositing, these approaches either treat the multiangle variation as a problem requiring correction or normalization or invoke statistical assumptions that may not apply to specific scenes. With the advent of a new generation of global imaging spectroradiometers capable of acquiring simultaneous visible/near-IR multiangle observations, namely, the Along-Track Scanning Radiometer-2, the Polarization and Directionality of the Earth's Reflectances instrument, and the Multiangle Imaging SpectroRadiometer, both qualitatively new approaches as well as quantitative improvements in accuracy are achievable that exploit the multiangle signals as unique and rich sources of diagnostic information. This paper discusses several applications of this technique to scientific problems in terrestrial atmospheric and surface geophysics and biophysics.

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Mira Berdahl, Asa Rennermalm, Arno Hammann, John Mioduszweski, Sultan Hameed, Marco Tedesco, Julienne Stroeve, Thomas Mote, Tomoko Koyama, and Joseph R. McConnell

Abstract

Greenland’s largest precipitation flux occurs in its southeast (SE) region during the winter, controlled primarily by easterly winds and frequent cyclogenesis in the North Atlantic. Several studies have attempted to link SE Greenland precipitation to the North Atlantic Oscillation (NAO) but results are inconsistent. This work uses reanalysis, automatic weather station data, and regional climate model output to show that the east–west position of the Icelandic low is a better predictor of SE Greenland precipitation (average correlation of r = −0.48 in DJF) than climate indices such as the NAO (r = −0.06 in DJF). In years when the Icelandic low is positioned extremely west, moisture transport increases up to ~40% (or up to 40 kg m−1 s−1) off the SE Greenland coast compared to when the low is in an extreme east position. Furthermore, in years when the Icelandic low is positioned extremely west, storm track density and intensity increase just off the SE coast of Greenland. Thus, the Icelandic low’s longitudinal position dominates SE Greenland ice sheet’s wintertime precipitation, a positive term in the ice sheet mass balance. Given SE Greenland’s importance in the overall ice sheet mass balance, the position of the Icelandic low is therefore important for making projections of future sea level.

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