A scatterometer record of sea ice extents and backscatter: 1992–2016

This paper presents the first long-term climate data record of sea ice extents and backscatter derived from intercalibrated satellite scatterometer missions (ERS, QuikSCAT and ASCAT) extending from 1992 to present date. This record provides a valuable independent account of the evolution of Arctic and Antarctic sea ice extents, one that is in excellent agreement with the passive microwave records during the fall and winter months but shows higher sensitivity to lower concentration and melting sea ice during the spring and summer months. The scatterometer record also provides a depiction of sea ice backscatter at C and Ku-band, allowing the separation of seasonal and perennial sea ice in the Arctic, and further differentiation between second year (SY) and older multiyear (MY) ice classes, revealing the emergence of SY ice as the dominant perennial ice type after the historical sea ice loss in 2007, and bearing new evidence on the loss of multiyear ice in the Arctic over the last 25 years. The relative good agreement between the backscatter-based sea ice (FY, SY and older MY) classes and the ice thickness record from Cryosat suggests its applicability as a reliable proxy in the historical reconstruction of sea ice thickness in the Arctic

Inter-comparison and evaluation of Arctic sea ice type products

oai:publications.copernicus.org:tc102910Arctic sea ice type (SITY) variation is a sensitive indicator of climate change. However, systematic inter-comparison and analysis for SITY products are lacking. This study analysed eight daily SITY products from five retrieval approaches covering the winters of 1999–2019, including purely radiometer-based (C3S-SITY), scatterometer-based (KNMI-SITY and IFREMER-SITY) and combined ones (OSISAF-SITY and Zhang-SITY). These SITY products were inter-compared against a weekly sea ice age product (i.e. NSIDC-SIA – National Snow and Ice Data Center sea ice age) and evaluated with five synthetic aperture radar (SAR) images. The average Arctic multiyear ice (MYI) extent difference between the SITY products and NSIDC-SIA varies from -1.32×106 to 0.49×106 km2. Among them, KNMI-SITY and Zhang-SITY in the QuikSCAT (QSCAT) period (2002–2009) agree best with NSIDC-SIA and perform the best, with the smallest bias of -0.001×106 km2 in first-year ice (FYI) extent and -0.02×106 km2 in MYI extent. In the Advanced Scatterometer (ASCAT) period (2007–2019), KNMI-SITY tends to overestimate MYI (especially in early winter), whereas Zhang-SITY and IFREMER-SITY tend to underestimate MYI. C3S-SITY performs well in some early winter cases but exhibits large temporal variabilities like OSISAF-SITY. Factors that could impact performances of the SITY products are analysed and summarized. (1) The Ku-band scatterometer generally performs better than the C-band scatterometer for SITY discrimination, while the latter sometimes identifies FYI more accurately, especially when surface scattering dominates the backscatter signature. (2) A simple combination of scatterometer and radiometer data is not always beneficial without further rules of priority. (3) The representativeness of training data and efficiency of classification are crucial for SITY classification. Spatial and temporal variation in characteristic training datasets should be well accounted for in the SITY method. (4) Post-processing corrections play important roles and should be considered with caution.</p

Sea ice classification in the Weddell Sea based on scatterometer data

Sea ice type is an important factor for accurately calculating sea ice parameters such as sea ice concentration, sea ice area and sea ice thickness using satellite remote sensing data. In this study, sea ice in the Weddell Sea was classified from scatterometer data by the histogram threshold method and the Spreen model method, and evaluated and validated with the Antarctic Sea Ice Processes and Climate (ASPeCt) sea ice type ship-based observations. The results show that the two methods can both distinguish multi-year (MY) ice and first-year (FY) ice during the ice growth season, and that the histogram threshold method has a relatively larger MY ice classification extent than the Spreen model. The classification accuracy of the histogram threshold method is 77.8%, while the Spreen model method accuracy is 80.3% compared with the ship-based observations, thus indicating that the Spreen model method is better for discriminating MY ice from FY ice from scatterometer data. These results provide a basis and reference for further retrieval of long-time sea ice type information for the whole Antarctica

Master of Science

thesisRecent accelerated mass loss offset by increased Arctic precipitation highlights the importance of a comprehensive understanding of the mechanisms controlling mass balance on the Greenland ice sheet. Knowledge of the spatiotemporal variability of snow accumulation is critical to accurately quantify mass balance, yet, considerable uncertainty remains in current snow accumulation estimates. Previous studies have shown the potential for large-scale retrievals of snow accumulation rates in regions that experience seasonal melt-refreeze metamorphosis using active microwave remote sensing. Theoretical backscatter models used in these studies to validate the hypothesis that observed decreasing freezing season backscatter signatures are linked to snow accumulation rates suggest the relationship is inverse and linear (dB). The net backscatter measurement is dominated by a Mie scattering response from the underlying ice-facie. Two-way attenuation resulting from a Raleigh scattering response within the overlying layer of snow accumulation forces a decrease in the backscatter measurement over time with increased snow accumulation rates. Backscatter measurements acquired from NASA's Ku-band SeaWinds scatterometer on the QuikSCAT satellite together with spatially calibrated snow accumulation rates acquired from the Polar MM5 mesoscale climate model are used to evaluate this relationship. Regions that experienced seasonal melt-refreeze metamorphosis and potentially formed dominant scattering layers are delineated, iv freeze-up and melt-onset dates identifying the freezing season are detected on a pixel-by-pixel basis, freezing season backscatter time series are linearly regressed, and a microwave snow accumulation metric is retrieved. A simple empirical relationship between the retrieved microwave snow accumulation metric (dB), , and spatially calibrated Polar MM5 snow accumulation rates (m w. e.), , is derived with a negative correlation coefficient of R=-.82 and a least squares linear fit equation of . Results indicate that an inverse relationship exists between decreasing freezing season backscatter decreases and snow accumulation rates; however, this technique fails to retrieve accurate snow accumulation estimates. An alternate geometric relationship is suggested between decreasing freezing season backscatter signatures, snow accumulation rates, and snowpack stratigraphy in the underlying ice-facie, which significantly influences the microwave scattering mechanism. To understand this complex relationship, additional research is required

Large Decadal Decline of the Arctic Multiyear Ice Cover

The perennial ice area was drastically reduced to 38% of its climatological average in 2007 but recovered somewhat in 2008, 2009 and 2010 with the areas being 10%, 24%, and 11% higher than in 2007, respectively. However, the trends in the extent and area remain strongly negative at -12.2% and -13.5 %/decade, respectively. The thick component of the perennial ice, called multiyear ice, as detected by satellite data in the winters of 1979 to 2011 was studied and results reveal that the multiyear ice extent and area are declining at an even more rapid rate of -15.1% and -17.2 % per decade, respectively, with record low value in 2008 followed by higher values in 2009, 2010 and 2011. Such high rate in the decline of the thick component of the Arctic ice cover means a reduction in average ice thickness and an even more vulnerable perennial ice cover. The decline of the multiyear ice area from 2007 to 2008 was not as strong as that of the perennial ice area from 2006 to 2007 suggesting a strong role of second year ice melt in the latter. The sea ice cover is shown to be strongly correlated with surface temperature which is increasing at about three times global average in the Arctic but appears weakly correlated with the AO which controls the dynamics of the region. An 8 to 9-year cycle is apparent in the multiyear ice record which could explain in part the slight recovery in the last three years

First-Year and Multiyear Sea Ice Incidence Angle Normalization of Dual-Polarized Sentinel-1 SAR Images in the Beaufort Sea

Automatic and visual sea ice classification of SAR imagery is impeded by the incidence angle dependence of backscatter intensities. Knowledge of the angular dependence of different ice types is therefore necessary to account for this effect. While consistent estimates exist for HH polarization for different ice types, they are lacking HV polarization data, especially for multiyear sea ice. Here we investigate the incidence angle dependence of smooth and rough/deformed first-year and multiyear ice of different ages for wintertime dual-polarization Sentinel-1 C-band SAR imagery in the Beaufort Sea. Assuming a linear relationship, this dependence is determined using the difference in incidence angle and backscatter intensities from ascending and descending images of the same area. At cross-polarization rough/deformed first-year sea ice shows the strongest angular dependence with -text{0.11} dB/1{circ } followed by multiyear sea ice with -text{0.07} dB/text{1}{circ }, and old multiyear ice (older than three years) with -text{0.04} dB/text{1}{circ }. The noise floor is found to have a strong impact on smooth first-year ice and estimated slopes are therefore not fully reliable. At co-polarization, we obtained slope values of -0.24, -0.20, -text{0.15}, and -text{0.10} dB/text{1}{circ } for smooth first-year, rough/deformed first-year, multiyear, and old multiyear sea ice, respectively. Furthermore, we show that imperfect noise correction of the first subswath influences the obtained slopes for multiyear sea ice. We demonstrate that incidence angle normalization should not only be applied to co-polarization but should also be considered for cross-polarization images to minimize intra ice type variation in backscatter intensity throughout the entire image swath

Investigation of ice formation and water mass modification in eastern Laptev Sea polynyas by means of satellites and models

Salt expelled during the formation of ice in polynyas leads to a downward precipitation of brine that causes thermohaline convection and erodes the density stratification of the water column. In this thesis we investigate by means of flux models and satellite data the ability of the Western New Siberian (WNS) flaw polynya to modify the stratification of the water column and to form saline bottom water. The accuracy of existent microwave satellite-based polynya monitoring methods is assessed by a comparison of derived estimates with airborne electromagnetic ice thickness measurements and aerial photographs taken across the polynya. The cross-validation indicates that in the narrow flaw polynyas of the Laptev Sea the coarse resolution of commonly used microwave channel combinations provokes errors through mixed signals at the fast and pack ice edges. Likewise, the accuracy of flux models is tested by comparing model results to ice thickness and ice production estimates derived from high-resolution thermal infrared satellite observations. We find that if a realistic fast ice boundary and parameterization of the collection depth H is used and if the movement of the pack ice edge is prescribed correctly, the model is an appropriate tool for studying polynya dynamics and estimating associated fluxes. Hence, a flux model is used to examine the effect of ice production on the stratification of the water column. The ability of the polynya to form dense shelf bottom water is investigated by adding the brine released during an except ionally strong WNS polynya event in 2004 to the average winter density stratification of the water body. Owing to the strong density stratification and the apparent lack of extreme polynya events in the eastern Laptev Sea, we find the likelihood of convective mixing down to the bottom to be extremely low. We conclude that the recently observed breakdown of the stratification during polynya events is therefore predominantly related to wind- and tidally-driven turbulent mixing