I went through the last 45 days of preprints at The Cryosphere journal looking for new Mosaic articles. There was a third one there, another N-ICE2015 piece now five years out, and quite a few others of interest to this and other Arctic forums, select ones below.
Most of the articles have quite readable sections, better than the abstracts. It's seldom a good idea to get too far from the mainstream in forum posts so these provide a good baseline for those wanting anchors to reality.
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Never forget that extraordinary claims require extraordinary evidence. The burden of proof is always on the proposer; there is no burden of disproof on the non-believer.
Estimating statistical errors in retrievals of ice velocity and deformation parameters from satellite images and buoy arrays
https://tc.copernicus.org/articles/14/2999/2020/Sea ice drifts under the influence of wind and ocean currents. Spatial gradients in the sea ice motion lead to distortion of the sea ice cover, termed deformation. The retrieval of sea ice drift vectors and deformation parameters from pairs or sequences of satellite synthetic aperture radar (SAR) images has gained increased attention during recent years because of the growing availability of suitable data.. Sea ice kinematics is also studied based on data from arrays of buoys or GPS receivers which in addition can serve as reference in comparisons to motion vectors obtained from SAR images. The knowledge of spatially detailed motion and deformation fields is potentially useful in ice navigation to locate divergent or compressive ice areas, as complementary information for operational sea ice mapping, for validation of models for forecasting of ice conditions, and for assimilation into ice models.
Seasonal transition dates can reveal biases in Arctic sea ice simulations
https://tc.copernicus.org/articles/14/2977/2020/Arctic sea ice experiences a dramatic annual cycle, and seasonal ice loss and growth can be characterized by various metrics: melt onset, breakup, opening, freeze onset, freeze-up, and closing. By evaluating a range of seasonal sea ice metrics, CMIP6 sea ice simulations can be evaluated in more detail than by using traditional metrics alone, such as sea ice area. We show that models capture the observed asymmetry in seasonal sea ice transitions, with spring ice loss taking about 1–2 months longer than fall ice growth. The largest impacts of internal variability are seen in the inflow regions for melt and freeze onset dates, but all metrics show pan-Arctic model spreads exceeding the internal variability range, indicating the contribution of model differences. Through climate model evaluation in the context of both observations and internal variability, we show that biases in seasonal transition dates can compensate for other unrealistic aspects of simulated sea ice. In some models, this leads to September sea ice areas in agreement with observations for the wrong reasons.
New insights into radiative transfer in sea ice derived from autonomous ice internal measurements
https://tc.copernicus.org/preprints/tc-2020-184/The radiative transfer of short-wave solar radiation through the sea ice cover of the polar oceans is a crucial aspect of energy partitioning at the atmosphere-ice-ocean interface. A detailed understanding of how sunlight is reflected and transmitted by the sea ice cover is needed for an accurate representation of critical processes in climate and ecosystem models, such as the ice-albedo feedback. Due to the challenges associated with ice internal measurements, most information about radiative transfer in sea ice has been gained by optical measurements above and below the sea ice. To improve our understanding of radiative transfer processes within the ice itself, we developed a new kind of instrument equipped with a number of multispectral light sensors that can be frozen into the ice. A first prototype consisting of a 2.3 m long chain of 48 sideward planar irradiance sensors with a vertical spacing of 0.05 m was deployed at the geographic North Pole in late August 2018, providing autonomous, vertically resolved light measurements within the ice cover during the autumn season. Here we present the first results of this instrument, discuss the advantages and application of the prototype and provide first new insights into the spatiotemporal aspect of radiative transfer within the sea ice itself. In particular, we investigate how measured attenuation coefficients relate to the optical properties of the ice pack, and show that sideward planar irradiance measurements are equivalent to measurements of total scalar irradiance.
Implications of surface flooding on airborne thickness measurements of snow on sea ice
https://tc.copernicus.org/preprints/tc-2020-168/Snow thickness observations from airborne snow radars, such as the NASA’s Operation IceBridge (OIB) mission, have recently been used in altimeter-derived sea ice thickness estimates, as well as for model parameterization. A number of validation studies comparing airborne and in situ snow thickness measurements have been conducted in the western Arctic Ocean, demonstrating the utility of the airborne data. However, there have been no validation studies in the Atlantic sector of the Arctic. Recent observations in this region suggest a significant and predominant shift towards a snow-ice regime, caused by deep snow on thin sea ice. During the Norwegian young sea ICE expedition (N-ICE2015) in the area north of Svalbard, a validation study was conducted on March 19, 2015, during which ground truth data were collected during an OIB overflight. Snow and ice thickness measurements were obtained across a two dimensional (2-D) 400 m × 60 m grid. Additional snow and ice thickness measurements collected in situ from adjacent ice floes helped to place the measurements obtained at the gridded survey field site into a more regional context. Widespread negative freeboards and flooding of the snow pack were observed during the N-ICE2015 expedition, due to the general situation of thick snow on relatively thin sea ice. These conditions caused brine wicking and saturation into the basal snow layers, causing more diffuse scattering and influenced the airborne radar signal to detect the radar main scattering horizon well above the snow/sea ice interface
Trends and spatial variation in rain-on-snow events over the Arctic Ocean during the early melt season
https://tc.copernicus.org/preprints/tc-2020-214/ Rain-on-snow (ROS) events can accelerate the surface ablation of sea ice, thus greatly influencing the ice-albedo feedback. However, the variability of ROS events over the Arctic Ocean is poorly understood due to limited historical station data in this region. In this study early melt season ROS events were investigated based on four widely-used reanalysis products (ERA-Interim, JRA-55, MERRA2 and ERA5) in conjunction with available observations at Arctic coastal stations. The performance of the reanalysis products in representing the timing of ROS events and the phase change of precipitation was assessed. Our results show that ERA-Interim better represents the onset date of ROS events in spring and ERA5 better represents the phase change of precipitation associated with ROS events. All reanalyses indicate that ROS event timing has shifted to earlier dates in recent decades (with maximum trends up to −4 to −6 days/decade in some regions in ERA-Interim), and that sea ice melt onset in the Pacific sector and most of the Eurasian marginal seas is correlated with this shift. There has been a clear transition from solid to liquid precipitation, leading to more ROS events in spring, although large discrepancies were found between different reanalysis products. In ERA5, the shift from solid to liquid precipitation phase during the early melt season has directly contributed to a reduction in spring snow depth on sea ice by more than −0.5 cm/decade averaged over the Arctic Ocean since 1980, with the largest contribution (about −2.0 cm/decade) in the Kara-Barents Seas and Canadian Arctic Archipelago.
Methane cycling within sea ice; results from drifting ice during late spring, north of Svalbard
https://tc.copernicus.org/preprints/tc-2020-208/tc-2020-208.pdfSea ice is an important component of the Arctic system playing a significant role for gas exchange between ocean and atmosphere. However, global warming has led to a sharp retreat of sea ice coverage in the Arctic Ocean during the last decades. During 2019 sea ice covered 4.15 million km2 in summer representing a decrease of 33 % compared to the 1981-2010 average (Perovich et al., 2019). The negative downward trend in Arctic summer sea ice coverage has been observed for more than 30 years. This tendency is expected to continue over the next decades including a cascade of possible associated effects. In particular, sea ice retreat may quickly induce enhanced methane (CH4) emissions into the atmosphere due to the loss of its barrier function
for sea-air gas exchange. Because the Arctic holds large natural sources of this highly potent
greenhouse gas, this effect has to be considered as positive feedback of global warming. Moreover, the resulting decreased temporal flux retention of methane under the ice reduces oxidation intensity to the less potent CO2
Seasonal changes in sea ice kinematics and deformation in the Pacific Sector of the Arctic Ocean in 2018/19
https://tc.copernicus.org/preprints/tc-2020-211/Arctic sea ice kinematics and deformation play significant roles in heat and momentum exchange between atmosphere and ocean. However, mechanisms regulating their changes at seasonal scales remain poorly understood. Using position data of 32 buoys in the Pacific sector of the Arctic Ocean (PAO), we characterized spatiotemporal variations in ice kinematics and deformation for autumn–winter 2018/19. In autumn, sea ice drift response to wind forcing and inertia were stronger in the southern and western than in the northern and eastern parts of the PAO. These spatial heterogeneities decreased gradually from autumn to winter, in line with the seasonal evolution of ice concentration and thickness. Areal localization index decreased by about 50 % from autumn to winter, suggesting the enhanced localization of intense ice deformation as the increased ice mechanical strength. In winter 2018/19, a highly positive Arctic Dipole and a weakened high pressure system over the Beaufort Sea led to a distinct change in ice drift direction and an temporary increase in ice deformation. During the freezing season, ice deformation rate in the northern part of the PAO was about 2.5 times that in the western part due to the higher spatial heterogeneity of oceanic and atmospheric forcing in the north. North–south and east–west gradients in sea ice kinematics and deformation of the PAO observed in autumn 2018 are likely to become more pronounced in the future as sea ice losses at higher rates in the western and southern than in the northern and western parts.
Clouds damp the radiative impacts of polar sea ice loss
https://tc.copernicus.org/articles/14/2673/2020/Clouds play an important role in the climate system: (1) cooling Earth by reflecting incoming sunlight to space and (2) warming Earth by reducing thermal energy loss to space. Cloud radiative effects are especially important in polar regions and have the potential to significantly alter the impact of sea ice decline on the surface radiation budget. Using CERES (Clouds and the Earth's Radiant Energy System) data and 32 CMIP5 (Coupled Model Intercomparison Project) climate models, we quantify the influence of polar clouds on the radiative impact of polar sea ice variability. Our results show that the cloud short-wave cooling effect strongly influences the impact of sea ice variability on the surface radiation budget and does so in a counter-intuitive manner over the polar seas: years with less sea ice and a larger net surface radiative flux show a more negative cloud radiative effect. Our results indicate that 66±2% of this change in the net cloud radiative effect is due to the reduction in surface albedo and that the remaining 34±1 % is due to an increase in cloud cover and optical thickness. The overall cloud radiative damping effect is 56±2 % over the Antarctic and 47±3 % over the Arctic. Thus, present-day cloud properties significantly reduce the net radiative impact of sea ice loss on the Arctic and Antarctic surface radiation budgets. As a result, climate models must accurately represent present-day polar cloud properties in order to capture the surface radiation budget impact of polar sea ice loss and thus the surface albedo feedback.
A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data
https://tc.copernicus.org/articles/14/2567/2020/Melt ponds are key elements in the energy balance of Arctic sea ice. Observing their temporal evolution is crucial for understanding melt processes and predicting sea ice evolution. Remote sensing is the only technique that enables large-scale observations of Arctic sea ice. However, monitoring melt pond deepening in this way is challenging because most of the optical signal reflected by a pond is defined by the scattering characteristics of the underlying ice. Without knowing the influence of meltwater on the reflected signal, the water depth cannot be determined. To solve the problem, we simulated the way meltwater changes the reflected spectra of bare ice. We developed a model based on the slope of the log-scaled remote sensing reflectance at 710 nm as a function of depth that is widely independent from the bottom albedo and accounts for the influence of varying solar zenith angles. We validated the model using 49 in situ melt pond spectra and corresponding depths from shallow ponds on dark and bright ice Our results indicate that our model enables the accurate retrieval of pond depth on Arctic sea ice from optical data under clear sky conditions without having to consider pond bottom albedo. This technique is potentially transferrable to hyperspectral remote sensors on unmanned aerial vehicles, aircraft and satellites.
Surface-Based Ku- and Ka-band Polarimetric Radar for Sea Ice Studies
https://tc.copernicus.org/preprints/tc-2020-151/ Mosaic
To improve our understanding of how snow properties influence sea ice thickness retrievals from presently operational and upcoming satellite radar altimeter missions, as well as investigating the potential for combining dual frequencies to simultaneously map snow depth and sea ice thickness, a new, surface-based, fully-polarimetric Ku- and Ka-band radar (KuKa radar) was built and deployed during the 2019–2020 year-long MOSAiC International Arctic drift expedition. This instrument, built to operate both as an altimeter (stare mode) and a scatterometer (scanning mode), provided the first in situ Ku- and Ka-band dual frequency radar observations from autumn freeze-up through mid-winter, and covering newly formed ice in leads, first-year and second-year ice floes. Data gathered in the altimeter mode, will be used to investigate the potential for estimating snow depth as the difference between dominant radar scattering horizons in the Ka- and Ku-band data. In the scatterometer mode, the Ku- and Ka-band radars operated under a wide range of azimuth and incidence angle ranges, continuously assessing changes in the polarimetric radar backscatter and derived polarimetric parameters, as snow properties varied under varying atmospheric conditions. These observations allow for characterizing radar backscatter responses to changes in atmospheric and surface geophysical conditions. In this paper, we describe the KuKa radar and illustrate examples of these data and demonstrate their potential for these investigations.
Simulated Ka- and Ku-band radar altimeter scattering horizon on snow-covered Arctic sea ice
https://tc.copernicus.org/preprints/tc-2020-196/Surface-Based Ku- and Ka-band Polarimetric Radar for Sea Ice Studies
Owing to differing and complex snow geophysical properties, radar waves of different wavelengths undergo variable penetration through snow-covered sea ice. However, the mechanisms influencing radar altimeter backscatter from snow-covered sea ice, especially at Ka- and Ku-band frequencies, and its impact on the Ka- and Ku-band radar scattering horizon or the "track point" (i.e. the scattering layer depth detected by the radar re-tracker), are not well understood. In this study, we evaluate the Ka- and Ku-band radar scattering horizon with respect to radar penetration and ice floe buoyancy using a first-order scattering model and Archimedes’ principle. Our simulations demonstrate that the Ka- and Ku-band track point difference is a function of snow depth, however, the simulated track point difference is much smaller than what is reported in the literature from the CryoSat-2 Ku-band and SARAL/AltiKa Ka-band satellite radar altimeter observations. We argue that this discrepancy in the Ka- and Ku-band track point differences are sensitive to ice type and snow depth and its associated geophysical properties. Snow salinity is first increasing the Ka- and Ku-band track-point difference when the snow is thin and then decreasing the difference when the snow is thick (> 10 cm). A relationship between the Ku-band radar scattering horizon and snow depth is found. This relationship has implications for 1) the use of snow climatology in the conversion of radar freeboard into sea ice thickness and 2) the impact of variability in measured snow depth on the derived ice thickness.
