IceBird Summer 2022 Campaign - Sea ice surveys with Polar 6 from Station Nord

Changes in Arctic sea ice thickness are the result of complex interactions of the dynamic and variable ice cover with atmosphere and ocean. The availability of satellite-based estimates of Arctic-wide sea ice thickness changes is limited to the winter months. However, in light of recent model predictions of a nearly ice-free Arctic in summer and to understand the role of sea ice for the causes and consequences of a warming climate, long-term and large-scale sea ice thickness and surface observations during the melt season are more important than ever. The AWI airborne sea ice survey program ‘IceBird Summer’ aims to close this gap by conducting regular measurements over sea ice in summer in key regions of the Arctic Ocean. The survey program comprises and continues all airborne ice thickness measurements obtained since 2001 in the central Arctic, Fram Strait and the last ice area. The objective is to ensure the long-term availability of a unique data record of direct sea ice thickness and surface state observations (deliverable of AWI research program POFIV, Topic 2.1: Warming Climates). Sea ice thickness measurements are obtained with a tethered electromagnetic sensor, the AEM-Bird. Jointly with the ice thickness measurements, optical and laser systems are operated to derive sea ice surface models and melt pond distribution

Kilometer-scale digital elevation models of the sea ice surface with airborne laser scanning during MOSAiC

An integrated sensor platform including an inertial navigation system (INS) and a commercial airborne laser scanner (ALS) among other sensor was mounted in the cargo compartment in one of the Polarstern helicopters during MOSAiC. ALS data was acquired from more than 60 flights between October 2019 and September 2020 with a range of survey types intended to map changes of the sea ice surface during the full annual cycle at high spatial resolution and coverage. Here, we provide an overview of the collected data, the challenge of achieving centimeter elevation accuracy with a helicopter platform at high polar latitudes as well as the content and specifications of ALS data products. The high spatial resolution and repeated coverage of the larger area around Polarstern allow studying various surface features (e.g. pressure ridges, floes, melt ponds, snow drifts, etc.), their seasonal evolution, and their impact on atmosphere and ocean. Finally, we outline methods for planned applications, such as identifying individual floes and surface types using both measured freeboard and surface reflectance. Collocated helicopter-based optical and infrared imagery allow analyzing sea ice properties in further applications and to upscale comparable in-situ observations

Multi-sensor airborne observations of freeboard, snow depth, and sea-ice thickness in the Arctic

Sea-ice thickness is a key factor and indicator in understanding the impact of the global climate change. Deriving basin-wide sea-ice thickness estimates from satellite laser and radar altimetry relies on freeboard measurements. The freeboard-to-thickness conversion in turn requires information of snow mass and the density of the sea-ice layer that have unknown spatio-temporal variabilities and trends directly translating into the uncertainty of decadal sea-ice thickness data records. In addition, inter-mission biases arise from, e.g., different sensor types and frequencies as well as varying footprint sizes affected by surface roughness across regions and seasons. Therefore, carrying out validation and inter-calibration studies is crucial for reliable and continuous observation of the Earth’s cryosphere. To achieve this, it is beneficial to have simultaneous measurements of freeboard, snow depth, and sea-ice thickness, which provide reference data for both direct satellite observations and geophysical target parameters. Here, we present Alfred Wegener Institute’s (AWI) IceBird program, which is a series of fixed-wing aircraft campaigns to measure Arctic sea ice and to monitor its change. During two late-winter campaigns in the western Arctic Ocean in 2017 and 2019, we have carried out surveys with the unique scientific instrument configuration including an airborne laser scanner (ALS) for surface topography and freeboard measurements, a tethered electromagnetic induction sounding instrument (EM-Bird) for total (snow+ice) thickness measurements, and an ultrawideband frequency-modulated continuous-wave microwave radar to measure snow thickness. Therefore, we are able to observe all three bounding interfaces in the sea-ice–snow system in high resolution along survey tracks on regional scales. During the ship-based drift expedition Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) between October 2019 and September 2020, helicopter surveys were carried out in high spatio-temporal resolution throughout the year, including the polar night, to measure freeboard and roughness with the ALS both in local grid pattern and in larger scale. Coincident EM-Bird ice thickness data and information from snow measurements on the ground will help linking these parameters and monitor them and their effect on satellite retrievals for a full seasonal cycle. The individual parameters are important for describing and monitoring the state of the Arctic sea ice and validating retrievals from satellite data, but combined they offer further possibilities to characterise sea ice. By assuming isostatic equilibrium, we are able to estimate up-to-date bulk density values for different sea-ice types from the IceBird data and to derive a parametrisation of sea-ice bulk density based on sea-ice freeboard. These data allow us to explore spatio-temporal variations in sea-ice parameters observable from space and to evaluate the validity of the freeboard-to-thickness conversion in satellite altimetry through comparison against dedicated satellite overpasses and orbit collections

Melt pond fraction and spectral sea ice albedo retrieval from MERIS data – Part 1: Validation against in situ, aerial, and ship cruise data

The presence of melt ponds on the Arctic sea ice strongly affects the energy balance of the Arctic Ocean in summer. It affects albedo as well as transmittance through the sea ice, which has consequences for the heat balance and mass balance of sea ice. An algorithm to retrieve melt pond fraction and sea ice albedo from Medium Resolution Imaging Spectrometer (MERIS) data is validated against aerial, shipborne and in situ campaign data. The results show the best correlation for landfast and multiyear ice of high ice concentrations. For broadband albedo, R2 is equal to 0.85, with the RMS (root mean square) being equal to 0.068; for the melt pond fraction, R2 is equal to 0.36, with the RMS being equal to 0.065. The correlation for lower ice concentrations, subpixel ice floes, blue ice and wet ice is lower due to ice drift and challenging for the retrieval surface conditions. Combining all aerial observations gives a mean albedo RMS of 0.089 and a mean melt pond fraction RMS of 0.22. The in situ melt pond fraction correlation is R2 = 0.52 with an RMS = 0.14. Ship cruise data might be affected by documentation of varying accuracy within the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol, which may contribute to the discrepancy between the satellite value and the observed value: mean R2 = 0.044, mean RMS = 0.16. An additional dynamic spatial cloud filter for MERIS over snow and ice has been developed to assist with the validation on swath data

Interannual variability in Transpolar Drift summer sea ice thickness and potential impact of Atlantification

Changes in Arctic sea ice thickness are the result of complex interactions of the dynamic and variable ice cover with atmosphere and ocean. Most of the sea ice exiting the Arctic Ocean does so through Fram Strait, which is why long-term measurements of ice thickness at the end of the Transpolar Drift provide insight into the integrated signals of thermodynamic and dynamic influences along the pathways of Arctic sea ice. We present an updated summer (July–August) time series of extensive ice thickness surveys carried out at the end of the Transpolar Drift between 2001 and 2020. Overall, we see a more than 20 % thinning of modal ice thickness since 2001. A comparison of this time series with first preliminary results from the international Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) shows that the modal summer thickness of the MOSAiC floe and its wider vicinity are consistent with measurements from previous years at the end of the Transpolar Drift. By combining this unique time series with the Lagrangian sea ice tracking tool, ICETrack, and a simple thermodynamic sea ice growth model, we link the observed interannual ice thickness variability north of Fram Strait to increased drift speeds along the Transpolar Drift and the consequential variations in sea ice age. We also show that the increased influence of upward-directed ocean heat flux in the eastern marginal ice zones, termed Atlantification, is not only responsible for sea ice thinning in and around the Laptev Sea but also that the induced thickness anomalies persist beyond the Russian shelves and are potentially still measurable at the end of the Transpolar Drift after more than a year. With a tendency towards an even faster Transpolar Drift, winter sea ice growth will have less time to compensate for the impact processes, such as Atlantification, have on sea ice thickness in the eastern marginal ice zone, which will increasingly be felt in other parts of the sea-ice-covered Arctic

Overview of the MOSAiC expedition: Snow and sea ice

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice

Melt ponds on Arctic sea ice determined from MODIS satellite data using an artificial neural network

Melt ponds on sea ice strongly reduce the surface albedo and accelerate the decay of Arctic sea ice. Due to different spectral properties of snow, ice, and water, the fractional coverage of these distinct surface types can be derived from multispectral sensors like the Moderate Resolution Image Spectroradiometer (MODIS) using a spectral unmixing algorithm. The unmixing was implemented using a multilayer perceptron to reduce computational costs. <br><br> Arctic-wide melt pond fractions and sea ice concentrations are derived from the level 3 MODIS surface reflectance product. The validation of the MODIS melt pond data set was conducted with aerial photos from the MELTEX campaign 2008 in the Beaufort Sea, data sets from the National Snow and Ice Data Center (NSIDC) for 2000 and 2001 from four sites spread over the entire Arctic, and with ship observations from the trans-Arctic HOTRAX cruise in 2005. The root-mean-square errors range from 3.8 % for the comparison with HOTRAX data, over 10.7 % for the comparison with NSIDC data, to 10.3 % and 11.4 % for the comparison with MELTEX data, with coefficient of determination ranging from <i>R</i><sup>2</sup>=0.28 to <i>R</i><sup>2</sup>=0.45. The mean annual cycle of the melt pond fraction per grid cell for the entire Arctic shows a strong increase in June, reaching a maximum of 15 % by the end of June. The zonal mean of melt pond fractions indicates a dependence of the temporal development of melt ponds on the geographical latitude, and has its maximum in mid-July at latitudes between 80° and 88° N. <br><br> Furthermore, the MODIS results are used to estimate the influence of melt ponds on retrievals of sea ice concentrations from passive microwave data. Results from a case study comparing sea ice concentrations from ARTIST Sea Ice-, NASA Team 2-, and Bootstrap-algorithms with MODIS sea ice concentrations indicate an underestimation of around 40 % for sea ice concentrations retrieved with microwave algorithms