Melt ponds play an important role in the seasonal evolution of Arctic sea ice. During the melt season, snow atop the sea ice begins to metamorphose and melt, forming ponds on the ice. These ponds reduce the albedo of the surface, allowing for increased solar energy absorption and thus further melting of snow and ice. Analyzing the spatial distribution and temporal evolution of melt ponds helps us understand the sea ice processes that occur during the summer melt season. It has been shown that the inclusion of melt pond parameters in sea ice models increases the skill of predicting the summer sea ice minimum extent. Previous studies have used remote sensing imagery to characterize surface features and calculate melt pond statistics. Here we use new observations of melt ponds obtained by the Digital Mapping System (DMS) flown onboard NASA Operation IceBridge (OIB) during two Arctic summer melt campaigns which surveyed thousands of kilometers of sea ice and resulted in more than 45,000 images. One campaign was conducted in the Beaufort Sea (July 2016), and one in the Lincoln Sea and the Arctic Ocean north of Greenland (July 2017). Using these data we expect to advance our understanding of the differences and similarities between melt pond features on young, thin sea ice seen in the Beaufort Sea versus those on multi-year ice. We have developed a pixel-based classification scheme by considering the different RGB spectral values associated with each surface type. We identify four sea ice surface types (level ice, rubbled ice, open water, and melt ponds). The classification scheme enables the calculation of parameters including melt pond fraction, ice concentration, melt pond area, and melt pond dimensions. We compare results with data from the Airborne Topographic Mapper (ATM), a laser altimeter also operated during these OIB missions. Given the extent over which the OIB data are available, regional information may be derived. Leveraging existing satellite data products, we examine whether the high-resolution airborne statistics are representative of the region and can be scaled up for comparison against satellite-derived parameters such as ice concentration and extent.

Over recent years, remote sensing of sea ice has advanced at a rapid pace. However, there are inherent limitations in the ability of existing space and airborne sensors to observe changes in the properties of near-shore sea ice, especially over short (hourly) time scales. This information is of critical importance to the livelihood of local communities and to meteorologists who depend on knowledge of near-shore ice conditions for weather prediction. The use of near-real-time data from coastal seismic arrays promises to advance coastal ice observations by measuring the amplitude of background seismic noise, known as microseism. The microseism signal is generated by interactions between oceanic waves, the ocean floor, and the shoreline. Previous studies have shown that along polar coastlines the microseism is modulated by the presence of sea ice. In this feasibility study, we explore the use of power spectral density (PSD) measurements from the Utqiagvik station of the EarthScope Transportable Array (TA) to provide information about sea ice conditions off the northern coast of Alaska. PSD signals are compared with daily estimates of near-shore ice extent and concentration within the Beaufort and Chukchi seas. These are derived from satellite passive microwave radiometer data as well as visible and short-wave infrared imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments. The amplitude of microseism at a frequency near 1 Hz is statistically correlated with ice coverage to determine if microseismic signals from a coastal station can be used to reliably identify particular ice events, including the onset date of summer melt, fast-ice breakup and formation, and the development of near-shore flaw-leads and polynas. Data from the Utqiagvik TA station is compared with observations from other northern coastal stations to determine if sea ice related microseismic signals are consistent across a range of geological and topographical environments. The expansion of the EarthScope TA seismic network to the Arctic coastline since 2011 presents a developing approach to sea ice observation. In the future it may complement established remote sensing techniques to provide a more complete picture of coastal ice conditions as they evolve.

Pressure ridges are deformation features within the sea ice pack created through the collision of sea ice floes. Pressure ridges play an important role in ice drift and influence the mass and energy budgets of the Arctic Ocean. Over the past decade annual airborne surveys over Arctic sea ice have been conducted in late winter (March and April) by NASA’s Operation IceBridge (OIB) mission. A total of 74 OIB flights between 2010 and 2018 surveyed tens of thousands of kilometers of sea ice, providing observations of pressure ridges at a higher spatial and temporal resolution than previous airborne studies. Here we utilize Digital Mapping System (DMS) imagery to identify shadows cast by pressure ridge sails and, then, use these shadows to derive sail height. Over 64,000 DMS images were analyzed, allowing for more than 33 million individual sail height measurements to be calculated. We present the full sail-height distributions of new pressure ridges recently formed across a range of ice conditions on first-year (FYI) and multiyear ice (MYI), and we assess year-to-year variability. We find distinct characteristics depending on the ice type in which the pressure ridge formed. The mean and standard deviation of sail heights on FYI is ~20-30 cm lower than those formed on MYI. Maximum sail heights on FYI are ~1.5 m lower on average. Arctic sea ice is getting younger, shifting from predominantly MYI to predominantly FYI. Our results may inform new model parameterizations of pressure ridges on sea ice in the changing Arctic, thereby supporting advances in sea ice forecasting.