Leif Toudal Pedersen

Intercomparison of passive microwave sea ice concentration retrievals over the high-concentration Arctic sea ice

[1] Measurements of sea ice concentration from the Special Sensor Microwave Imager (SSM/I) using seven different algorithms are compared to ship observations, sea ice divergence estimates from the Radarsat Geophysical Processor System, and ice and water surface type classification of 59 wide-swath synthetic aperture radar (SAR) scenes. The analysis is confined to the high-concentration Arctic sea ice, where the ice cover is near 100%. During winter the results indicate that the variability of the SSM/I concentration estimates is larger than the true variability of ice concentration. Results from a trusted subset of the SAR scenes across the central Arctic allow the separation of the ice concentration uncertainty due to emissivity variations and sensor noise from other error sources during the winter of 2003–2004. Depending on the algorithm, error standard deviations from 2.5 to 5.0% are found with sensor noise between 1.3 and 1.8%. This is in accord with variability estimated from analysis of SSM/I time series. Algorithms, which primarily use 85 GHz information, consistently give the best agreement with both SAR ice concentrations and ship observations. Although the 85 GHz information is more sensitive to atmospheric influences, it was found that the atmospheric contribution is secondary to the influence of the surface emissivity variability. Analysis of the entire SSM/I time series shows that there are significant differences in trend between sea ice extent and area, using different algorithms. This indicates that long-term trends in surface and atmospheric properties, unrelated to sea ice concentration, influence the computed trends.

Seasonal and interannual variability of the Odden ice tongue and a study of environmental effects

The Odden ice tongue is an ice cover phenomenon in the Greenland Sea that covers all or part of the area of influence of the Jan Mayen Current and that encloses a bay of open water called Nordbukta. The yearly attributes of the spatial distribution of the Odden from 1979 through 1998 have been quantified in terms of average concentration, standard deviation of ice concentrations, persistence, maximum extent, and anomalies in extent, and the results show vastly different formation characteristics and seasonalities during different years. The monthly average extents of the Odden are shown to have a strong negative correlation with monthly surface air temperatures recorded at Jan Mayen Island and monthly temperatures retrieved from satellite infrared data, with correlation coefficients of 0.74 and 0.89, respectively. Wind effect is also shown to be an important factor at daily and shorter timescales, directly influencing size and shape and sometimes initiating the formation of Nordbukta. The Odden was most extensive in 1979, 1982, 1986, and 1997 and most persistent in 1988, 1989, and 1997 but did not appear in 1984, 1994, and 1995, suggesting decadal periodicity for the 20 year period. With the use of the 75 year temperature record at Jan Mayen Island as a proxy for Odden size, spectral analysis also shows a periodicity of 10–12 years. A correlation study of North Atlantic Oscillation (NAO) indices with extents of the Odden, as derived from satellite data, yields a correlation coefficient of 0.4, which suggests that the interannual variability of the Odden may be influenced but not controlled by NAO. Regression analysis of the Jan Mayen surface temperature record also yields a slight warming (0.06 K decade−1) and a decrease in Odden area (−0.14×104 km2 decade−1) from 1979 to 1996, but during the past 75 years, there has actually been a slight cooling (−0.15 K decade−1), suggesting either that the Odden had actually been smaller in size several decades ago or that it had occurred farther north.

On the Estimation of Melt Pond Fraction on the Arctic Sea Ice With ENVISAT WSM Images

The accuracy of microwave radiometer ice concentration (IC) retrievals in the Arctic is degraded by melt ponds on sea ice during the melting season. For the development of IC retrieval algorithms and for the quantification of their uncertainties, data sets on the area fraction of melt ponds (f_mp) are needed. f_mp retrieval with optical satellite data is limited by clouds. Thus, we have studied f_mp retrieval with ENVISAT wide swath mode (WSM) synthetic aperture radar (SAR) images which have large daily coverage over the Arctic Sea ice in 2007-2012. The WSM images used here were acquired north of the Fram Strait in June-August 2009. Data on f_mp were available from the Integrated Climate Data Centers daily Moderate Resolution Imaging Spectroradiometer (MODIS) f_mp product in a 12.5-km grid. Relationships between SAR σ° and MODIS f_mp were studied visually by comparing daily SAR mosaics andfmp charts and by analyzing f_mp and σ° time series and spatially and temporally coincident f_mp and σ° data. The correspondence between the changes of f_mp and the σ° statistics is too low to suggest f_mp estimation from the WSM images. In some cases, there was a 2-3-dB σ° increase during the ponding period. It is assumed that the variation of snow and sea ice characteristics diminishes σ° changes due to the melt ponding and drainage. Good correlation between σ° and f_mp has only been observed for smooth landfast first-year ice in previous studies. A very interesting observation was the large temporal σ° variations during the late melting season, which are likely linked to the atmospherically forced freezing-melting events. These events may also influence radiometer IC retrievals.

Simulation of the Ku-band Radar altimeter sea ice effective scattering surface

A radiative transfer model is used to simulate the sea ice radar altimeter effective scattering surface variability as a function of snow depth and density. Under dry snow conditions without layering these are the primary snow parameters affecting the scattering surface variability. The model is initialized with in situ data collected during the May 2004 GreenIce ice camp in the Lincoln Sea (73/spl deg/W; 85/spl deg/N). Our results show that the snow cover is important for the effective scattering surface depth in sea ice and thus for the range measurement, ice freeboard, and ice thickness estimation.

Response of passive microwave sea ice concentration algorithms to thin ice

The influence of sea ice thickness brightness temperatures and ice concentrations retrieved from passive microwave observations is quantified, using horizontally homogeneous sea ice thickness retrievals from ESAs SMOS sensor observations at high incidence angles. Brightness temperatures are influenced by thickness below 18 cm (89GHz) and 50 cm (1.4 GHz). Ice concentration retrievals reduced by ice thickness below 0.17 m and 0.33 m, with higher frequency algorithms being less influenced.

Polarimetric signatures of sea ice in the Greenland Sea

Polarimetric SAR data of sea ice have been acquired by the Danish polarimetric SAR (EMISAR) during a mission at the Greenland Sea in August 1994. Video recordings from a low-altitude acquisition have been used for interpretation of the SAR data. Also, ERS-1 SAR data and NOAA AVHRR-data have been acquired. Microwave signatures of mulityear ice and open water have been studied, i.e. the backscatter coefficients for VV- and HV-polarizations. The co- and cross-polarized ratios, the correlations coefficients and phase difference have been computed as a function of incidence angle. The results correspond very well with previously reported results.

North-East Water polynya: satellite observations summer 1992 and 1993

Abstract Polynyas in the Arctic have recently attracted much attention with studies of their geophysics (including water movements, heat flux and carbon dioxide flux) and their biology (including all phases from plankton over benthos to marine mammals and polar birds). A programme of remote sensing was undertaken in connection with two cruises by research vessels in the North-East Water polynya at the north-east corner of Greenland. Data from the Advanced Very High Resolution Radiometer (AVHRR) instrument on the NOAA satellites and Synthetic Aperture Radar (SAR) on ERS–1 was used supported by ground information collected by the research vessel, USCGC Polar Sea. The observations made are reported with examples of special events that control the state of the polynya. Based on repeated observations of floes the motion pattern is determined, for 1992 by means of AVHRR and for 1993 by ERS–l SAR. They confirm the anti-cyclonic movement around the Belgica Bank supported by a system of troughs surrounding the Ban...

Monitoring sea ice using Envisat ASAR — A new era starting 10 years ago

A short overview is given on the achievements made in sea ice monitoring during the last decade utilizing the technical possibilities of Envisat ASAR. In particular we discuss the improvements by employing the dual-polarization image mode, the benefits of the wide-swath capability, and the advantage to select between seven swaths at different incidence angle ranges when using the image mode.

Simulation of the CryoSat-2 satellite radar altimeter sea ice thickness retrieval uncertainty

Although it is well known that radar waves penetrate into snow and sea ice, the exact mechanisms for radar altimeter scattering and its link to the depth of the effective scattering surface from sea ice are not well known. Previously proposed mechanisms linked the snow-ice interface, i.e., the dominating scattering horizon, directly with the depth of the effective scattering surface. However, simulations using a multilayer radar scattering model show that the effective scattering surface is affected by snow-cover and ice properties. With the coming CryoSat-2 (planned launch in 2010) satellite radar altimeter, it is proposed that sea ice thickness can be derived during winter by measuring its freeboard. In this study we evaluate the radar altimeter sea ice thickness retrieval uncertainty in terms of floe buoyancy, radar penetration, and ice type distribution using both a scattering model and Archimedes’ principle. The effect of the snow cover on the floe buoyancy and radar penetration and on the ice cover spatial and temporal variability is assessed from field campaign measurements in the Arctic resulting in ice thickness uncertainties of about 0.3 m for the snow depth variability and 0.3 m for the snow density variability. In addition to these well-known uncertainties, we use high-resolution RADARSAT synthetic aperture radar (SAR) data to simulate errors due to the variability of the effective scattering surface as a result of the subfootprint spatial backscatter and elevation distribution, sometimes called preferential sampling. In particular, in areas where ridges represent a significant part of the ice volume (e.g., the Lincoln Sea), the average simulated altimeter thickness estimate of 2.68 m is lower than the real average footprint thickness of 3.85 m, making preferential sampling the single most important error source. This means that the errors are large and yet manageable if the relevant quantities are known a priori. Radar altimeter ice thickness retrieval uncertainties are discussed.

Sentinel-1 results: Sea ice operational monitoring

In the present paper we demonstrate the capabilities of the Sentinel-1 SAR data for operational sea-ice and iceberg monitoring. Most of the examples are drawn from the Copernicus Marine Environmental Monitoring Service (CMEMS) production.