Ice Roughness Research Articles

Ice crystal characterization in cirrus clouds III: retrieval of ice crystal shape and roughness from observations of halo displays

Abstract. In this study, which is the third part of the HaloCam series after Forster et al. (2017, 2020), we present a novel technique to retrieve quantitative information about ice crystal optical and microphysical properties using ground-based imaging observations of halo displays. Comparing HaloCam's calibrated RGB images of 22 and 46∘ halo observations against a lookup table of simulated radiances, this technique allows the retrieval of the sizes and shapes of randomly oriented crystals as well as the fraction of smooth and rough ice crystals for cirrus clouds. We analyzed 4400 HaloCam images between September 2015 and November 2016 showing a visible 22∘ halo. The optical properties of hexagonal 8-element aggregates of columns with a mean ice crystal effective radius of about 20 µm and a mixture of 37 % smooth and 63 % rough crystals on average best match the HaloCam observations. Implemented on different sites, HaloCam in combination with the machine-learning-based halo detection algorithm HaloForest can provide a consistent dataset for climatological studies of ice crystal properties representing typical cirrus clouds. Representative ice crystal optical properties are required for remote sensing of cirrus clouds as well as climate modeling. Since ground-based passive imaging observations provide information about the forward scattering part of the ice crystal optical properties, the results of this work ideally complement the results of satellite-based and airborne studies.

Quantitative Measurement Method for Ice Roughness on an Aircraft Surface

When an aircraft passes through clouds containing supercooled water droplets, the leading edge’s surface will gradually accumulate ice. Ice surface roughness is an important parameter affecting the local convective heat transfer coefficient and the water collection coefficient, which in turn affect the ice’s shape. However, because the surface roughness of aircraft icing is a transient value varying in time and space, it is extremely difficult to measure with existing methods in real time. In this study, a noncontact ultrasonic pulse-echo (UPE) technique is applied to characterize the ice roughness of an airfoil model’s surface. A multilayer model with equivalent bead-like roughness profiles is established to study the effects of changes in ice roughness on ultrasonic echo signals. A series of simulations indicated that ice roughness can be measured quantitatively and effectively in the range of [11.6, 120] μm. Based on these simulations, an experimental UPE device was developed to measure echo signals on top of the ice corresponding to surface roughness. The results show that for both the regular and irregular surface roughness samples, the maximum relative error in the roughness is less than 15%. Meanwhile, we designed and supplemented the experiment with the NACA-0012 airfoil model to realize the online measurement of ice roughness in an icing research tunnel.

A New Data Processing System for Generating Sea Ice Surface Roughness Products from the Multi-Angle Imaging SpectroRadiometer (MISR) Imagery

Sea ice roughness can serve as a proxy for other sea ice characteristics such as ice thickness and ice age. Arctic-wide maps that represent spatial patterns of sea ice roughness can be used to better characterize spatial patterns of ice convergence and divergence processes. Sea ice surface roughness can also control and quantify turbulent exchange between sea ice surface and atmosphere and therefore influence surface energy balance at the basin scale. We have developed a data processing system that produces georeferenced sea ice roughness rasters that can be mosaicked to produce Arctic-wide maps of sea ice roughness. This approach starts with Top-of-Atmosphere radiance data from the Multi-angle Imaging SpectroRadiometer (MISR). We used red-band angular data from three MISR cameras (Ca, Cf, An). We created a training data set in which MISR pixels were matched with co-located and concurrent lidar-derived roughness measurements from the Airborne Topographic Mapper (ATM). We used a K-nearest neighbor algorithm with the training data to calibrate the multi-angle data to values of surface roughness and then applied the algorithm to Arctic-wide MISR data for two 16-day periods in April (spring) and July (summer). After georeferencing the roughness rasters, we then mosaicked each 16-day roughness dataset to produce Arctic-wide maps of sea ice roughness for spring and summer. Assessment of the results shows good agreement with independent ATM roughness data, not used in model development. A preliminary exploration of spatial and seasonal changes in sea ice roughness for two locations shows the ability to characterize the roughness of different ice types and the results align with previous studies. This processing system and its data products can help the sea ice research community to gain insights into the seasonal and interannual changes in sea ice roughness over the Arctic.

Simulation of acoustic reflection from Arctic ice

The acoustic reflection from an ice sheet in the arctic, as observed by an upward looking sonar, is simulated. The reflection from a smooth ice sheet is modeled using OASES, using material properties that may be found in the published literature. Depending on the bandwidth of the signal, specular reflections from the top and bottom of the ice, as well as one or more resonances that are identified as leaky Lamb waves should be detectable. If the speed of the Lamb wave is faster than the speed of sound in water, it will leak energy back into the water. The leaky Lamb wave has a characteristic resonant frequency that is a function of the ice thickness and shear speed. The reflection and backscatter from a rough ice sheet is modeled using SPECFEM2D. Scattering from a rough interface may obscure the expected signals, depending on the severity of the roughness. [Work supported by ONR, Ocean Acoustics Program.]

Sea Ice Elevation in the Western Weddell Sea, Antarctica: Observations From Field Campaign

AbstractSea ice elevation is crucial in the characterization of three‐dimensional (3D) sea ice patterns, providing physical insights to advance sea ice dynamic models. Moreover, how sea ice elevation may be related to the ocean geophysical environment is still a significant knowledge gap, especially in Antarctica. A radar theory relating electromagnetic scattering mechanisms to sea ice elevation over old and deformed rough ice has been reported in a prior companion paper. This follow‐up paper presents the validated model function and synthetic aperture radar (SAR)‐retrieved sea ice elevations based on the field data acquired during the Operation IceBridge and TanDEM‐X Antarctic Science Campaign. A high‐resolution sea ice digital elevation model (DEM) is generated extensively over a 19 × 450 km sector in the Western Weddell Sea, achieving a good accuracy with a low root‐mean‐square error of 0.23 m. From the SAR‐retrieved sea ice DEM, 3D sea ice patterns including roughness height, auto‐correlation lengths, correlation ellipticity, and orientation angles are calculated over the old and deformed rough sea ice. The 3D sea ice patterns give a comprehensive characterization of sea ice topography in the Western Weddell Sea and show the potential to be used for understanding sea ice formation processes in the Antarctic.

Developing Water-Quality Model for Jingpo Lake Based on EFDC

Water-quality model simulation is the key to understanding hydrological processes and water-quality dynamic(s). In this study, Jingpo Lake, which is the most typical lake in the northern cold region of China, was selected as the research object. A numerical simulation model for transporting and diffusing the chemical oxygen demand (CODMn) and ammonia nitrogen (NH3N) with ice-covered and open-water periods was constructed and calibrated using the Environmental Fluid Dynamics Code (EFDC). Parameters such as the bottom roughness, ice roughness, diffusion coefficient, horizontal momentum diffusivity, molecular eddy viscosity, molecular diffusivity, buoyancy influence coefficient, CODMn decay rate and NH3N decay rate were validated. The research findings show that there were differences in the hydrodynamic water-quality changing process during the ice-covered and open-water periods, as well as for the seasonal ice-covered waterbody. The key parameter decay rates of the CODMn and NH3N in the ice-covered periods were lower than those in the open-water periods due to the water-temperature decline. The R2 of the CODMn and NH3N reached 90.71% and 79.79%, respectively. Thus, it may be concluded that the EFDC model could well reflect changes in the water level of Jingpo Lake, as well as the transport and diffusion of the CODMn and NH3N in Jingpo Lake.

Acoustic Float Tracking with the Kalman Smoother

Abstract Acoustically-tracked subsurface floats provide insights into ocean complexity and were first deployed over 60 years ago. A standard tracking method uses a Least-Squares algorithm to estimate float trajectories based on acoustic ranging from moored sound sources. However, infrequent or imperfect data challenge such estimates, and Least-Squares algorithms are vulnerable to non-Gaussian errors. Acoustic tracking is currently the only feasible strategy for recovering float positions in the sea ice region, a focus of this study. Acoustic records recovered from under-ice floats frequently lack continuous sound source coverage. This is because environmental factors such as surface sound channels and rough sea ice attenuate acoustic signals, while operational considerations make polar sound sources expensive and difficult to deploy. Here we present a Kalman Smoother approach that, by including some estimates of float behavior, extends tracking to situations with more challenging data sets. The Kalman Smoother constructs dynamically constrained, error-minimized float tracks and variance ellipses using all possible position data. This algorithm outperforms the Least-Squares approach and a Kalman Filter in numerical experiments. The Kalman Smoother is applied to previously-tracked floats from the southeast Pacific (DIMES experiment), and the results are compared with existing trajectories constructed using the Least- Squares algorithm. The Kalman Smoother is also used to reconstruct the trajectories of a set of previously untracked, acoustically-enabled Argo floats in the Weddell Sea.

Theory of Radar Polarimetric Interferometry and Its Application to the Retrieval of Sea Ice Elevation in the Western Weddell Sea, Antarctic

AbstractSea ice elevation plays a crucial role in sea ice dynamic processes driven by winds and waves, for which satellite radar remote sensing becomes indispensable to monitor snow‐covered sea ice across the vast polar regions regardless of darkness and clouds. To measure sea ice elevation, a theory of polarimetric interferometry for both monostatic and bistatic radars is developed based on analytic solutions of Maxwell's equations, accounting for realistic and complicated properties of snow, sea ice, and seawater. This analytic method inherently preserves phase information that is imperative for radar polarimetry and interferometry. Among a multitude of complex radar coefficients in the general polarimetric interferometric covariance matrix, the symmetry group theory is utilized to identify and select appropriate terms pertaining to the retrieval of sea ice elevation while avoiding radar parameters that may inadvertently introduce non‐uniqueness and excessive uncertainty. Theoretical calculations compare well with field observations for rough and old sea ice encountered in the Operation‐IceBridge and TanDEM‐X Antarctic Science Campaign over the Western Weddell Sea. The results show that the magnitude of the coefficient of normalized correlation between co‐polarized horizontal and co‐polarized vertical radar returns is inversely related to sea ice elevation, while the associate phase term is nonlinear and noisy and should be excluded. From these analyses, a protocol is set up to measure Antarctic sea ice elevation to be presented in the next companion paper.

Coupled modeling of the seasonal transmission loss in the Beaufort Sea

An eight-element drifting vertical line array was deployed overwinter 2019–20 in the Beaufort Sea to record transmissions from two moored 35 Hz sources deployed as part of the Coordinated Arctic Acoustic Thermometry Experiment (CAATEX), and seven 925 Hz sources deployed by the Arctic Mobile Observing Systems (AMOS) experiment. Transmissions were received every day on the array at ranges of 10 to 850 km. A probabilistic rough-ice canopy was integrated to a Parabolic Equation code to predict the propagation loss. Sound speed profiles and percent ice cover along the propagation paths were obtained at daily resolution from data-assimilative Global Ice Ocean Prediction System (GIOPS, 20 km spatial resolution). Sea ice roughness and keel properties are empirically determined from the GIOPS ice thickness. The ice roughness is generated using a random pulse-train model with a characteristic wavenumber spectrum slope determined by ice age. Empirical probability distributions of ice keel depth, slope, and spatial densities are used to randomly add keels. Spatial averaging is used to account for signal bandwidth and uncertainty in receiver positions. The environment files and modeling are performed in piece-wise steps to manage memory footprints over long ranges. Modeled propagation losses compare well with the data and reproduce the seasonal variability observed in the measured results.

Midfrequency sound transmission from mobile sources in a deep Arctic ocean at short and medium ranges: Time-domain modeling and data analysis

Midfrequency (2300–3000 Hz) LFM sweeps (3 s-long, one per minute) and CW 57 s-long signals at multiple frequencies (950, 1050, 1150, 2800, 2900, and 3000 Hz) were transmitted by two mobile sources EMATTs moving at three knots in circular patterns under ice in the Beaufort Sea on March 12, 2016. Acoustic pressure time series were recorded on five vertically and horizontally separated receivers Acousonde, which provided different combinations of source-receiver ranges (0.3–10 km) and depths (45–183 m). A time-domain model of propagation and reverberation is suggested that accounts for refraction in water column and scattering from ocean boundaries (bottom and ice). Effects of spatial variations of the environment, particularly the two shallow ducts, at 0–75 m and 75–250 m water depths, as well as bottom and ice roughness, are demonstrated. Preliminary results of the model-data comparisons are presented. Possibilities for remote sensing of the arctic environment are discussed. [Work supported by ONR.]

Numerical Modeling of Atmospheric Rime Ice Accretion on an Airfoil Using an Eulerian Approach

AbstractThis paper presents an approach to numerically simulate the inherently unsteady rime ice accretion problem on a two-dimensional airfoil and elucidate the associated variations under different icing conditions. The airflow field and the water impingement on the airfoil are obtained based on an Eulerian two-phase model. A dynamic mesh strategy is employed to unsteadily account for the changes in the ice profile and its impact on the air and droplet flow by continuously reconstructing the computational grid at each time-step through smoothing and layering mechanisms. All main icing modules including the airflow field, droplet trajectory, icing thickness profile, and mesh management are fully coupled within the same computational framework without resorting to any external tools. Classical icing theory is employed to model the rime ice roughness, and it is assumed that the ice accretes in a direction normal to the airfoil surface. The governing Reynolds-averaged Navier–Stokes (RANS) conservation equations along with the energy and continuity equations are solved to produce the velocity and temperature fields. A convective film heat transfer coefficient is computed based on the surface heat flux and a recovery temperature which takes into account the dissipative heat release in the boundary layer in the vicinity of the airfoil surface. With the implemented strategy and calculating the convective heat transfer coefficient, the water film thickness is also calculated along with the ice shape. The model is validated by comparing the local collection efficiency distribution and ice shape with experimental data, and the results show that the implemented approach provides acceptable predictions of ice accretion profiles and rates.

Monitoring the Hydrological Activities of Antarctic Subglacial Lakes Using CryoSat-2 and ICESat-2 Altimetry Data

Monitoring the hydrological activities of subglacial lakes is critical to understanding the subglacial hydrological system and evaluating the internal mass changes of the Antarctic ice sheet. Drainage or filling events of active lakes lead to elevation changes in the ice surface. These changes can be observed by satellite altimetry, but the monitoring must be conducted continuously since the water movements in active subglacial lakes may occur frequently. We used CryoSat-2 Baseline-D and ICESat-2 data from 2010 to 2020 to obtain the time series of the ice surface elevation changes for 17 active lakes. We also evaluated the uncertainty of the time series derived from the CryoSat-2 data by cross-validation. The mean and RMS of the biases between the CryoSat-2-based and ICESat-2-based time series are generally less than 0.3 m and 1.0 m, respectively. However, the mean and RMS are greater over the lakes with rough ice surfaces, such as Whillans6, KT1, Mac3, and Slessor23. The drainage and filling events continue exhibiting in the extended period and the hydrological activities of SLW, L12, Whillans6, L78, and Mac1 occurred periodically. Furthermore, we inferred the hydrological connections between the lakes combining simulated water pathways.

PRETTY\xa0\u2013 passive GNSS-Reflectometry for CubeSats

The Passive Reflectometry and Dosimetry (PRETTY) is a small satellite mission developed by a consortium consisting of RUAG Space GmbH (RSA), Graz University of Technology (TUG), and Seibersdorf Laboratories (SL). The primary objective of the passive altimetry within the PRETTY mission is to measure the ice and sea ice surface elevation and roughness in the polar regions.

Modelling and analysis of initial icing roughness with fixed-grid enthalpy method based on DPM-VOF algorithm

Ice particles could form under the continuous impingement of incoming supercooled droplets in icing conditions, which will change the surface roughness to enhance the further heat and mass transfer during icing process. A fixed-grid porous enthalpy method based on the improved Discrete Phase Model (DPM) and Volume of Fluid (VOF) integrated algorithm is developed to solve the multiphase heat transfer problem to give more detailed demonstration of the formation of initial ice roughness. The algorithms to determine the criterion of transformation from DPM to VOF and the allocation of source items during transformation are improved to the general DPM-VOF algorithm. Two verification cases, namely two glycerine-solution droplets impact and single droplet freeze, are conducted to verify the accuracy and reliability of the enthalpy-DPM-VOF method, where the simulation results match well with experiment phenomena. Ice roughness on a NACA0012 airfoil is precisely captured and the effects on convective heat transfer characteristics are preliminarily revealed. The results illustrate that the enthalpy-DPM-VOF method could successfully capture the characteristics of motion and the phase change process of droplet, as well as balance the calculation accuracy and efficiency.

Ice roughness estimation via remotely piloted aircraft and photogrammetry

Abstract. The monitoring of fluvial ice covers can be time intensive, dangerous, and costly if detailed data are required. Ice covers on a river surface cause resistance to water flow, which increases upstream water levels. Ice with a higher degree of roughness causes increased flow resistance and therefore even higher upstream water levels. Aerial images collected via remotely piloted aircraft (RPA) were processed with structure from motion photogrammetry to create a digital elevation model (DEM) and then produce quantitative measurements of surface ice roughness. Images and surface ice roughness values were collected over 2 years on the Dauphin River in Manitoba, Canada. It was hypothesized that surface ice roughness would be indicative of subsurface ice roughness. This hypothesis was tested by comparing RPA-measured surface ice roughness values to those predicted by the Nezhikhovskiy equation, wherein subsurface ice roughness is proportional to ice thickness. Various statistical metrics were used to represent the roughness height of the DEMs. Strong trends were identified in the comparison of RPA-measured ice surface roughness to subsurface ice roughness values predicted by the Nezhikhovskiy equation, as well as with comparisons to ice thickness. The standard deviation and interquartile range of roughness heights were determined to be the most representative statistical metrics and several properties of the DEMs of fluvial ice covers were calculated and observed. No DEMs were found to be normally distributed. This first attempt at using RPA-derived measurements of surface ice roughness to estimate river ice flow resistance is shown to have considerable potential and will hopefully be verified and improved upon by subsequent measurements on a wide variety of rivers and ice covers.

Sensitivity to changes in the surface‐layer turbulence parameterization for stable conditions in winter: A case study with a regional climate model over the Arctic

AbstractThe modeling of the atmospheric boundary layer over sea ice is still challenging because of the complex interaction between clouds, radiation and turbulence over the often inhomogeneous sea ice cover. There is still much uncertainty concerning sea ice roughness, near‐surface thermal stability and related processes, and their accurate parameterization. Here, a regional Arctic climate model forced by ERA‐Interim data was used to test the sensitivity of climate simulations to a modified surface flux parameterization for wintertime conditions over the Arctic. The reference parameterization as well as the modified one is based on Monin–Obukhov similarity theory, but different roughness lengths were prescribed and the stability dependence of the transfer coefficients for momentum, heat and moisture differed from each other. The modified parameterization accounts for the most comprehensive observations that are presently available over sea ice in the inner Arctic. Independent of the parameterization used, the model was able to reproduce the two observed dominant winter states with respect to cloud cover and longwave radiation. A stepwise use of the different parameterization assumptions showed that modifications of both surface roughness and stability dependence had a considerable impact on quantities such as air pressure, wind and near‐surface turbulent fluxes. However, the reduction of surface roughness to values agreeing with those observed during the Surface Heat Budget of the Arctic Ocean campaign led to an improvement in the western Arctic, while the modified stability parameterization had only a minor impact. The latter could be traced back to the model's underestimation of the strength of stability over sea ice. Future work should concentrate on possible reasons for this underestimation and on the question of generality of the results for other climate models.

Causes and Consequences of Sea Ice Initialization Shock in Coupled NWP Hindcasts with the GC2 Climate Model

AbstractWe present a coupled retrospective forecast (hindcast) study using the Met Office Global Coupled Model, version 2 (GC2), in which we identify and mitigate causes of initialization shock that lead to rapid error growth in sea ice forecasts. Sea ice state variables and volume budget terms as a function of forecast lead time are evaluated relative to analyses from an uncoupled Met Office ocean–sea ice analysis system [Forecast Ocean Assimilation Model, version 13 (FOAMv13)]. Two sources of initialization shock are highlighted and addressed, both of which are related to effective differences in physics between the analysis system and coupled forecast model. The primary shock to sea ice state variables arises from the use of a salinity-independent freezing temperature for seawater in GC2 as opposed to a salinity-dependent formulation in FOAMv13. A secondary effect arises from differences in the sea ice roughness and hence air–ice drag in the GC2 forecast model compared to the FOAMv13 analysis system. Generalizing from the findings of this study, we suggest that using nonnative analyses as initial conditions for coupled numerical weather prediction (NWP) studies will likely make them prone to initialization shock in some model components, to the detriment of forecast skill. To reduce the undesirable impacts of initialization shock on short-range forecast skill noted in this study we would therefore recommend the use of initial conditions (analyses) physically consistent with the native model components of the coupled forecast model, a native coupled analysis likely being the optimal initialization method.

Mapping the aerodynamic roughness of the Greenland Ice Sheet surface using ICESat-2: evaluation over the K-transect

Abstract. The aerodynamic roughness of heat, moisture, and momentum of a natural surface are important parameters in atmospheric models, as they co-determine the intensity of turbulent transfer between the atmosphere and the surface. Unfortunately this parameter is often poorly known, especially in remote areas where neither high-resolution elevation models nor eddy-covariance measurements are available. In this study we adapt a bulk drag partitioning model to estimate the aerodynamic roughness length (z0m) such that it can be applied to 1D (i.e. unidirectional) elevation profiles, typically measured by laser altimeters. We apply the model to a rough ice surface on the K-transect (west Greenland Ice Sheet) using UAV photogrammetry, and we evaluate the modelled roughness against in situ eddy-covariance observations. We then present a method to estimate the topography at 1 m horizontal resolution using the ICESat-2 satellite laser altimeter, and we demonstrate the high precision of the satellite elevation profiles against UAV photogrammetry. The currently available satellite profiles are used to map the aerodynamic roughness during different time periods along the K-transect, that is compared to an extensive dataset of in situ observations. We find a considerable spatio-temporal variability in z0m, ranging between 10−4 m for a smooth snow surface and 10−1 m for rough crevassed areas, which confirms the need to incorporate a variable aerodynamic roughness in atmospheric models over ice sheets.

Description and Demonstration of the Coupled Community Earth System Model v2 - Community Ice Sheet Model v2 (CESM2-CISM2).

Earth system/ice‐sheet coupling is an area of recent, major Earth System Model (ESM) development. This work occurs at the intersection of glaciology and climate science and is motivated by a need for robust projections of sea‐level rise. The Community Ice Sheet Model version 2 (CISM2) is the newest component model of the Community Earth System Model version 2 (CESM2). This study describes the coupling and novel capabilities of the model, including: (1) an advanced energy‐balance‐based surface mass balance calculation in the land component with downscaling via elevation classes; (2) a closed freshwater budget from ice sheet to the ocean from surface runoff, basal melting, and ice discharge; (3) dynamic land surface types; and (4) dynamic atmospheric topography. The Earth system/ice‐sheet coupling is demonstrated in a simulation with an evolving Greenland Ice Sheet (GrIS) under an idealized high CO2 scenario. The model simulates a large expansion of ablation areas (where surface ablation exceeds snow accumulation) and a large increase in surface runoff. This results in an elevated freshwater flux to the ocean, as well as thinning of the ice sheet and area retreat. These GrIS changes result in reduced Greenland surface albedo, changes in the sign and magnitude of sensible and latent heat fluxes, and modified surface roughness and overall ice sheet topography. Representation of these couplings between climate and ice sheets is key for the simulation of ice and climate interactions.

The Effect of Sea Ice on Tidal Propagation in the Kitikmeot Sea, Canadian Arctic Archipelago

AbstractThe tides in the Kitikmeot Sea, in the southern Canadian Arctic Archipelago, are found to be heavily influenced by seasonal sea‐ice formation and blocking in a strait. Data from a moored current profiler in Dease Strait exhibit strong tidal damping during wintertime seasonal sea‐ice cover, with 50%–60% reduction in tidal elevation and 65% reduction in tidal velocities. We used a 3D unstratified barotropic numerical tidal model of the region to show that the observed wintertime tidal damping likely requires both high sea‐ice friction and a partial sea‐ice blockage in Victoria Strait (VS), the eastern gateway of the Kitikmeot Sea, where tidal‐induced ridging causes thick, rough ice to accumulate over its shallow sill. Our analysis of the model shows different dynamics for the M2 and K1 tides. Both tidal constituents are dominated by the Atlantic tides entering through VS. Overall, ∼90% of the M2 tidal energy entering VS does not reach Dease Strait because, in addition to dissipation in VS (∼25%), it is significantly diverted into adjoining bays and around an amphidrome in eastern Queen Maud Gulf (∼65%). In contrast, the smaller K1 tide is less diverted into the subsidiary channels, after ∼20% dissipation in VS and only ∼25% in adjoining bays, it propagates far into the region and is amplified due to resonance in Dease Strait and Coronation Gulf, resulting in larger tidal height than the M2 tide in Coronation Gulf.