An Assessment of State-of-the-Art Mean Sea Surface and Geoid Models of the Arctic Ocean: Implications for Sea Ice Freeboard Retrieval

State-of-the-art Arctic Ocean mean sea surface (MSS) models and global geoid models (GGMs) are used to support sea ice freeboard estimation from satellite altimeters, as well as in oceanographic studies such as mapping sea level anomalies and mean dynamic ocean topography. However, errors in a given model in the high frequency domain, primarily due to unresolved gravity features, can result in errors in the estimated along-track freeboard. These errors are exacerbated in areas with a sparse lead distribution in consolidated ice pack conditions. Additionally model errors can impact ocean geostrophic currents, derived from satellite altimeter data, while remaining biases in these models may impact longer-term, multi-sensor oceanographic time-series of sea level change in the Arctic. This study focuses on an assessment of five state-of-the-art Arctic MSS models (UCL13/04, DTU15/13/10) and a commonly used GGM (EGM2008). We describe errors due to unresolved gravity features, inter-satellite biases, and remaining satellite orbit errors, and their impact on the derivation of sea ice freeboard. The latest MSS models, incorporating CryoSat-2 sea surface height measurements, show improved definition of gravity features, such as the Gakkel Ridge. The standard deviation between models ranges 0.03-0.25 m. The impact of remaining MSS/GGM errors on freeboard retrieval can reach several decimeters in parts of the Arctic. While the maximum observed freeboard difference found in the central Arctic was 0.59 m (UCL13 MSS minus EGM2008 GGM), the standard deviation in freeboard differences is 0.03-0.06 m

Mean Dynamic Topography of the Arctic Ocean

ICESat and Envisat altimetry data provide measurements of the instantaneous sea surface height (SSH) across the Arctic Ocean, using lead and open water elevation within the sea ice pack. First, these data were used to derive two independent mean sea surface (MSS) models by stacking and averaging along-track SSH profiles gathered between 2003 and 2009. The ICESat and Envisat MSS data were combined to construct the high-resolution ICEn MSS. Second, we estimate the 5.5-year mean dynamic topography (MDT) of the Arctic Ocean by differencing the ICEn MSS with the new GOCO02S geoid model, derived from GRACE and GOCE gravity. Using these satellite-only data we map the major features of Arctic Ocean dynamical height that are consistent with in situ observations, including the topographical highs and lows of the Beaufort and Greenland Gyres, respectively. Smaller-scale MDT structures remain largely unresolved due to uncertainties in the geoid at short wavelengths

A long-term record of sea ice thickness in the Canadian Arctic

Sea ice plays a vital role in the Arctic region and affects numerous processes: it influences the radiative budget by reflecting sunlight and acts as a barrier for heat transport between atmosphere and ocean; it influences Arctic ecosystems as a habitat for different species; it is important for hunting and travel for local communities; and it acts as a hazard for marine shipping. Monitoring sea ice, specifically its thickness, is essential in understanding how it is changing with ongoing global warming.This thesis presents a novel method to create a long-term record (1996-2020) for sea ice thickness in the Canadian Arctic and assesses how sea ice thickness changed and what the impacts of these changes are.This thesis initially aimed to extract a long-term sea ice thickness record for the Canadian Arctic from satellite altimetry. However, it revealed that assumptions regarding the snowpack, sea ice density, and processing algorithms highly influence conclusions on sea ice thickness state and trends, and this approach was rejected. Instead, this thesis presents a proxy sea ice thickness product for the Canadian Arctic using ice charts, which for the first time consistently covers the Canadian Arctic Archipelago. In the final research chapter, this sea ice thickness proxy product and ice charts are used to assess sea ice changes in the Canadian Arctic Archipelago and their impact on accessibility.Sea ice has thinned across most of the Canadian Arctic region, with a mean change over the full area of 38.5 cm for November and 20.5 cm for April over the period 1996-2020. Moreover, the marine navigability is shown to increase in the access channels to the Canadian Arctic Archipelago, which enhances the possibilities for resupply for local communities. However, with continuing dynamic influx of old and thick sea ice, there is no change in full navigability of the Northwest Passage connecting the Atlantic and Pacific Oceans

Latest Altimetry-Based Sea Ice Freeboard and Volume Inter-Annual Variability in the Antarctic over 2003–2020

The relatively stable conditions of the sea ice cover in the Antarctic, observed for almost 40 years, seem to be changing recently. Therefore, it is essential to provide sea ice thickness (SIT) and volume (SIV) estimates in order to anticipate potential multi-scale changes in the Antarctic sea ice. For that purpose, the main objectives of this work are: (1) to assess a new sea ice freeboard, thickness and volume altimetry dataset over 2003–2020 and (2) to identify first order impacts of the sea ice recent conditions. To produce these series, we use a neuronal network to calibrate Envisat radar freeboards onto CryoSat-2 (CS2). This method addresses the impacts of surface roughness on Low Resolution Mode (LRM) measurements. During the 2011 common flight period, we found a mean deviation between Envisat and CryoSat-2 radar freeboards by about 0.5 cm. Using the Advanced Microwave Scanning Radiometer (AMSR) and the dual-frequency Altimetric Snow Depth (ASD) data, our solutions are compared with the Upward looking sonar (ULS) draft data, some in-situ measurement of the SIMBA campaign, the total freeboards of 6 Operation Ice Bridge (OIB) missions and ICESat-2 total freeboards. Over 2003–2020, the global mean radar freeboard decreased by about −14% per decade and the SIT and SIV by about −10% per decade (considering a snow depth climatology). This is marked by a slight increase through 2015, which is directly followed by a strong decrease in 2016. Thereafter, freeboards generally remained low and even continued to decrease in some regions such as the Weddell sea. Considering the 2013–2020 period, for which the ASD data are available, radar freeboards and SIT decreased by about −40% per decade. The SIV decreased by about −60% per decade. After 2016, the low SIT values contrast with the sea ice extent that has rather increased again, reaching near-average values in winter 2020. The regional analysis underlines that such thinning (from 2016) occurs in all regions except the Amundsen-Bellingshausen sea sector. Meanwhile, we observed a reversal of the main regional trends from 2016, which may be the signature of significant ongoing changes in the Antarctic sea ice

Satellite laser altimetry over sea ice.

The Arctic region plays an important role in the global climate system through various feedbacks, involving surface albedo, oceanic deep-water formation, and sea surface salinity, which can amplify climate variability and change. We investigate the exploitation of data collected by the first Earth-orbiting laser altimeter carried onboard ICESat over the sea-ice covered regions of the Arctic Ocean. We extract parameters associated with the study of the polar climate system including the time-varying component of sea surface topography and sea ice freeboard. We assess an existing method for the retrieval of Arctic sea surface height from ICESat data. We present an alternative method for sea surface height retrieval, based on surface reflectivity and analysis of parameters associated with the shape of the received echo. This method aims to discriminate echoes originating over leads or thin ice. We provide the first maps of Arctic sea surface height as derived from ICESat. We examine the accuracy of our results through comparisons with independent sea surface height estimates derived from ENVISAT radar altimetry. We demonstrate the use of sea surface height data for oceanographic and geodetic applications in the Arctic Ocean. We derive an ICESat mean sea surface which, when combined with the recently developed Arctic hybrid geoid model, can be used to analyse mean dynamic ocean topography. In addition we investigate the use of ICESat sea surface height measurements to map marine gravity anomalies up to the limit of coverage at 86 N. By combining ICESat surface elevation measurements with sea surface height estimates, we derive sea ice freeboard throughout the Arctic up to 86 N. We compare our results to coincident estimates of sea ice freeboard from ENVISAT. Finally, we explore the feasibility of combining satellite laser and radar altimetric measurements of sea ice freeboard to measure the depth of snow loading on sea ice

Comparing elevation and backscatter retrievals from CryoSat-2 and ICESat-2 over Arctic summer sea ice

The CryoSat-2 radar altimeter and ICESat-2 laser altimeter can provide complimentary measurements of the freeboard and thickness of Arctic sea ice. However, both sensors face significant challenges for accurately measuring the ice freeboard when the sea ice is melting in summer months. Here, we used crossover points between CryoSat-2 and ICESat-2 to compare elevation retrievals over summer sea ice between 2018&ndash;2021. We focused on the electromagnetic (EM) bias documented in CryoSat-2 measurements, associated with surface melt ponds over summer sea ice which cause the radar altimeter to underestimate elevation. The laser altimeter of ICESat-2 is not susceptible to this bias, but has other biases associated with melt ponds. So, we compared the elevation difference and reflectance statistics between the two satellites. We found that CryoSat-2 underestimated elevation compared to ICESat-2 by a median difference of 2.4 cm and by a median absolute deviation of 5.3 cm, while the differences between individual ICESat-2 beams and CryoSat-2 ranged between 1&ndash;3.5 cm. Spatial and temporal patterns of the bias were compared to surface roughness information derived from the ICESat-2 elevation data, the ICESat-2 photon rate (surface reflectivity), the CryoSat-2 backscatter and melt pond fraction derived from Seintnel-3 OLCI data. We found good agreement between theoretical predictions of the CryoSat-2 EM melt pond bias and our new observations; however, at typical roughness &lt;0.1 m the experimentally measured bias was larger (5&ndash;10 cm) compared to biases resulting from the theoretical simulations (0&ndash;5 cm). This intercomparison will be valuable for interpreting and improving the summer sea ice freeboard retrievals from both altimeters.</p

The Roles of the S3MPC: Monitoring, Validation and Evolution of Sentinel-3 Altimetry Observations

The Sentinel-3 Mission Performance Centre (S3MPC) is tasked by the European Space Agency (ESA) to monitor the health of the Copernicus Sentinel-3 satellites and ensure a high data quality to the users. This paper deals exclusively with the effort devoted to the altimeter and microwave radiometer, both components of the Surface Topography Mission (STM). The altimeters on Sentinel-3A and -3B are the first to operate in delay-Doppler or SAR mode over all Earth surfaces, which enables better spatial resolution of the signal in the along-track direction and improved noise reduction through multi-looking, whilst the radiometer is a two-channel nadir-viewing system. There are regular routine assessments of the instruments through investigation of telemetered housekeeping data, calibrations over selected sites and comparisons of geophysical retrievals with models, in situ data and other satellite systems. These are performed both to monitor the daily production, assessing the uncertainties and errors on the estimates, and also to characterize the long-term performance for climate science applications. This is critical because an undetected drift in performance could be misconstrued as a climate variation. As the data are used by the Copernicus Services (e.g., CMEMS, Global Land Monitoring Services) and by the research community over open ocean, coastal waters, sea ice, land ice, rivers and lakes, the validation activities encompass all these domains, with regular reports openly available. The S3MPC is also in charge of preparing improvements to the processing, and of the development and tuning of algorithms to improve their accuracy. This paper is thus the first refereed publication to bring together the analysis of SAR altimetry across all these different domains to highlight the benefits and existing challenges

Retrieving Sea Level and Freeboard in the Arctic: A Review of Current Radar Altimetry Methodologies and Future Perspectives

Spaceborne radar altimeters record echo waveforms over all Earth surfaces, but their interpretation and quantitative exploitation over the Arctic Ocean is particularly challenging. Radar returns may be from all ocean, all sea ice, or a mixture of the two, so the first task is the determination of which surface and then an interpretation of the signal to give range. Subsequently, corrections have to be applied for various surface and atmospheric effects before making a comparison with a reference level. This paper discusses the drivers for improved altimetry in the Arctic and then reviews the various approaches that have been used to achieve the initial classification and subsequent retracking over these diverse surfaces, showing examples from both LRM (low resolution mode) and SAR (synthetic aperture radar) altimeters. The review then discusses the issues concerning corrections, including the choices between using other remote-sensing measurements and using those from models or climatology. The paper finishes with some perspectives on future developments, incorporating secondary frequency, interferometric SAR and opportunities for fusion with measurements from laser altimetry or from the SMOS salinity sensor, and provides a full list of relevant abbreviations

Estimating snow depth over Arctic sea ice from calibrated dual-frequency radar freeboards

Snow depth on sea ice remains one of the largest uncertainties in sea ice thickness retrievals from satellite altimetry. Here we outline an approach for deriving snow depth that can be applied to any coincident freeboard measurements after calibration with independent observations of snow and ice freeboard. Freeboard estimates from CryoSat-2 (Ku band) and AltiKa (Ka band) are calibrated against data from NASA's Operation IceBridge (OIB) to align AltiKa with the snow surface and CryoSat-2 with the ice–snow interface. Snow depth is found as the difference between the two calibrated freeboards, with a correction added for the slower speed of light propagation through snow. We perform an initial evaluation of our derived snow depth product against OIB snow depth data by excluding successive years of OIB data from the analysis. We find a root-mean-square deviation of 7.7, 5.3, 5.9, and 6.7&thinsp;cm between our snow thickness product and OIB data from the springs of 2013, 2014, 2015, and 2016 respectively. We further demonstrate the applicability of the method to ICESat and Envisat, offering promising potential for the application to CryoSat-2 and ICESat-2, which launched in September 2018.</p