Ice Model Research Articles

Application of distributed Xin'anjiang model of melting ice and snow in Bahe River basin

Study regionBahe River basin on the Tibetan Plateau, China. Study focusThe thawing of glaciers and snow in cold regions is critical to the impact of runoff. This study proposes a distributed degree-day Xin'anjiang model (DD-XAJ) considering ice and snow thawing, which added the degree-day module describing snow and ice thawing to the previously distributed Xin'anjiang model. A sensitivity analysis of the main parameters of the improved model was conducted to discuss the effect of snow and glacier melt on the runoff process. The DD-XAJ model was also applied to the Bahe River basin to analyze its runoff change process and identify the composition of runoff components in the basin. New hydrological insightsThe DD-XAJ model was successfully applied to the Bahe River basin, which is located on the Tibetan Plateau, with good daily runoff simulation results. The mean values of the Nash efficiency coefficients were 0.828 and 0.859 in the calibration and validation periods, respectively, and the mean values of the correlation coefficients were 0.917 and 0.941, respectively. The runoff composition of the Bahe River basin is mainly rainfall runoff (76.3 %), snowmelt runoff (16.7 %), and glacier melt runoff (7 %), which indicates that rainfall runoff plays a dominant role in the Bahe River basin. Snowmelt runoff is influenced by rainfall events, while glacier melt runoff is mainly influenced by the seasons. In addition, the contribution of runoff components in different elevation zones differed significantly. The contribution of elevation 4000–5500 m to the total runoff was the largest. This study provides a new understanding of runoff processes and runoff components in the cryosphere basin.

Examining Antarctic sea ice bias sensitivity in the multi-variate parameter space using a global coupled climate modelling system

Coupled global numerical climate models (GCMs) typically underestimate mean Antarctic sea ice area and extent, particularly during the austral summer months, contributing to uncertainties in climate prediction. This study examines the climatological behaviour of Antarctic sea ice in a coupled GCM in the multivariate sea ice model parameter space. Individual parameters dominate the ice response in different seasons and regions, with a compensatory effect in some parameter combinations and an amplified effect in others; however, certain parameter combinations are found to improve aspects of Antarctic sea ice climatology well beyond the limitations of a univariate approach. For example, the disparity between observed and simulated summer sea ice extent and area is halved, and the tendency towards very low-concentration ice (<15 %) reduced in favour of a more compact summer and autumn ice pack. Regardless, clear limitations in the extent to which a coupled GCM can be calibrated with sea-ice model parameters also emerge. Relatively unconsolidated winter ice cover persists and, in some experiments, becomes looser still, exacerbating the already overestimated maximum sea ice extent. Furthermore, the seasonal evolution of sea ice and the exaggerated asymmetry of the seasonal cycle, with the onset of ice advance too slow and maximum sea ice reached too late, sees negligible improvements. We note that, even with the large gains under certain parameter combinations, bias and other deficiencies still remain. Using coupled data assimilation to optimise parameters in both sea-ice and ocean models will likely assist in contributing to further model improvements.

Exceptional sea ice loss leading to anomalously deep winter convection north of Svalbard in 2018

AbstractAn important question is will deep convection sites, where deep waters are ventilated and air-gas exchange into the deep ocean occurs, emerge in the Arctic Ocean with the warming climate. As sea ice retreats northward and as Arctic sea ice becomes younger and thinner, air-sea interactions are strengthening in the high-latitude oceans. This includes new and extreme deep convection events. We investigate the associated physical processes and examine impacts and implications. Focusing on a region near the Arctic gateway of Fram Strait, our study confirms a significant sea ice cover reduction north of Svalbard in 2018 compared to the past decade, shown in observations and several numerical studies. We conduct our study using the regional configuration Arctic and North Hemisphere Atlantic of the ocean/sea ice model NEMO, running at 1/12° resolution (ANHA12). Our numerical study shows that the open water condition during the winter of 2018 allows intense winter convection over the Yermak Plateau, as more oceanic heat is lost to the atmosphere without the insulating sea ice cover, causing the mixed layer depth to reach over 600 m. Anomalous wind prior to the deep convection event forces offshore sea ice movement and contributes to the reduced sea ice cover. The sea ice loss is also attributed to the excess heat brought by the Atlantic Water, which reaches its maximum in the preceding winter in Fram Strait. The deep convection event coincides with enhanced mesoscale eddy activity on the boundary of the Yermak Plateau, especially to the east. The resulting substantial heat loss to the atmosphere also leads to a heat content reduction integrated over the Yermak Plateau region. This event can be linked to the minimum southward sea ice volume flux through Fram Strait in 2018, which is a potential negative freshwater anomaly in the subpolar Atlantic.

The Southern Ocean Freshwater Input from Antarctica (SOFIA) Initiative: scientific objectives and experimental design

Abstract. As the climate warms, the grounded ice sheet and floating ice shelves surrounding Antarctica are melting and releasing additional freshwater into the Southern Ocean. Nonetheless, almost all existing coupled climate models have fixed ice sheets and lack the physics required to represent the dominant sources of Antarctic melt. These missing ice dynamics represent a key uncertainty that is typically unaccounted for in current global climate change projections. Previous modelling studies that have imposed additional Antarctic meltwater have demonstrated regional impacts on Southern Ocean stratification, circulation, and sea ice, as well as remote changes in atmospheric circulation, tropical precipitation, and global temperature. However, these previous studies have used widely varying rates of freshwater forcing, have been conducted using different climate models and configurations, and have reached differing conclusions on the magnitude of meltwater–climate feedbacks. The Southern Ocean Freshwater Input from Antarctica (SOFIA) initiative brings together a team of scientists to quantify the climate system response to Antarctic meltwater input along with key aspects of the uncertainty. In this paper, we summarize the state of knowledge on meltwater discharge from the Antarctic ice sheet and ice shelves to the Southern Ocean and explain the scientific objectives of our initiative. We propose a series of coupled and ocean–sea ice model experiments, including idealized meltwater experiments, historical experiments with observationally consistent meltwater input, and future scenarios driven by meltwater inputs derived from stand-alone ice sheet models. Through coordinating a multi-model ensemble of simulations using a common experimental design, open data archiving, and facilitating scientific collaboration, SOFIA aims to move the community toward better constraining our understanding of the climate system response to Antarctic melt.

Description of FIO-ESM version 2.1 and evaluation of its sea ice simulations

To improve Arctic sea ice simulations by the First Institute of Oceanography–Earth System Model (FIO–ESM), the model version has been updated from FIO–ESM v2.0 to FIO–ESM v2.1 by upgrading its sea ice component from Los Alamos Sea–Ice Model (CICE) version 4.0 (CICE4.0) to CICE6.0, and improving the ice–ocean heat exchange process from a two–equation boundary condition parameterization to a more realistic three–equation boundary condition parameterization. Numerical experiments show that the underestimation of Arctic summer sea ice extent (SIE) in FIO–ESM v2.0 is significantly improved by the model enhancements. The root mean square error of the simulated Arctic September SIE during 1979–2014 is reduced from 2.9 million to 0.7 million km2. Nevertheless, the biases of Antarctic SIE increase following the model version update. FIO–ESM v2.1 performs well for the simulations of surface air temperature, sea surface temperature, Atlantic Meridional Overturning Circulation, and Arctic SIE; however, it overestimates summer SIE in the Antarctic. Furthermore, future projections based on FIO–ESM v2.1 indicate that the first ice–free Arctic summer will occur in the 2050s and the 2040s under SSP2–4.5 and SSP5–8.5, respectively.

Improvements in September Arctic Sea Ice Predictions Via Assimilation of Summer CryoSat‐2 Sea Ice Thickness Observations

AbstractBecause of a spring predictability barrier, the seasonal forecast skill of Arctic summer sea ice is limited by the availability of melt‐season sea ice thickness (SIT) observations. The first year‐round SIT observations, retrieved from CryoSat‐2 from 2011 to 2020, are assimilated into the GFDL ocean–sea ice model. The model's SIT anomaly field is brought into significantly better agreement with the observations, particularly in the Central Arctic. Although the short observational period makes forecast assessment challenging, we find that the addition of May–August SIT assimilation improves September local sea ice concentration (SIC) and extent forecasts similarly to SIC‐only assimilation. Although most regional forecasts are improved by SIT assimilation, the Chukchi Sea forecasts are degraded. This degradation is likely due to the introduction of negative correlations between September SIC and earlier SIT introduced by SIT assimilation, contrary to the increased correlations found in other regions.

Correcting for artificial heat in coupled sea ice perturbation experiments

A common approach to assessing how polar amplification affects lower latitude climate is to perform coupled ocean-atmosphere experiments in which sea ice is perturbed to a future state. Recent work with a simple 1-dimensional energy balance model (EBM) shows that sea ice perturbation experiments impose an artificial heat flux on the climate system. We explore this effect in a broader range of models and suggest a technique to correct for the artificial heat post-hoc. Our technique successfully corrects for artificial heat in the EBM, and a possible generalization of this approach is developed to correct for artificial heat in an albedo modification experiment in a comprehensive earth system model. Generalizing this technique to sea ice perturbation methodologies that employ a ‘ghost flux’ seen only by the sea ice model would require a better understanding of the effect of ghost fluxes on the surface energy budget. Applying the correction to the comprehensive albedo modification experiment, we find stronger artificial warming than in the EBM. Failing to account for the artificial heat also leads to overestimation of the climate response to sea ice loss (SIL), and can suggest false or artificially strong ‘tugs-of-war’ between low latitude warming and SIL over some fields, for example Arctic surface temperature and zonal wind.

JWST Reveals Widespread CO Ice and Gas Absorption in the Galactic Center Cloud G0.253+0.016

We report JWST NIRCam observations of G0.253+0.016, the molecular cloud in the Central Molecular Zone known as “The Brick,” with the F182M, F187N, F212N, F410M, F405N, and F466N filters. We catalog 56,146 stars detected in all six filters using the crowdsource package. Stars within and behind The Brick exhibit prodigious absorption in the F466N filter that is produced by a combination of CO ice and gas. In support of this conclusion, and as a general resource, we present models of CO gas and ice and CO2 ice in the F466N, F470N, and F410M filters. Both CO gas and ice contribute to the observed stellar colors. We show, however, that CO gas does not absorb the Pfβ and Huϵ lines in F466N, but that these lines show excess absorption, indicating that CO ice is present and contributes to observed F466N absorption. The most strongly absorbed stars in F466N are extincted by ∼2 mag, corresponding to >80% flux loss. This high observed absorption requires very high column densities of CO, and thus a total CO column that is in tension with standard CO abundance and/or gas-to-dust ratios. This result suggests the CO/H2 ratio and dust-to-gas ratio are greater in the Galactic Center than in the Galactic disk. Ice and/or gas absorption is observed even in the cloud outskirts, implying that additional caution is needed when interpreting stellar photometry in filters that overlap with ice bands throughout galactic centers.

Interactions between Gravity Waves and Cirrus Clouds: Asymptotic Modeling of Wave-Induced Ice Nucleation

Abstract We present an asymptotic approach for the systematic investigation of the effect of gravity waves (GWs) on ice clouds formed through homogeneous nucleation. In particular, we consider high- and midfrequency GWs in the tropopause region driving the formation of ice clouds, modeled with a double-moment bulk ice microphysics scheme. The asymptotic approach allows for identifying reduced equations for self-consistent description of the ice dynamics forced by GWs including the effects of diffusional growth and nucleation of ice crystals. Further, corresponding analytical solutions for a monochromatic GW are derived under a single-parcel approximation. The results provide a simple expression for the nucleated number of ice crystals in a nucleation event. It is demonstrated that the asymptotic solutions capture the dynamics of the full ice model and accurately predict the nucleated ice crystal number. The present approach is extended to allow for superposition of GWs, as well as for variable ice crystal mean mass in the deposition. Implications of the results for an improved representation of GW variability in cirrus parameterizations are discussed.

A high-resolution physical–biogeochemical model for marine resource applications in the northwest Atlantic (MOM6-COBALT-NWA12 v1.0)

Abstract. We present the development and evaluation of MOM6-COBALT-NWA12 version 1.0, a 1/12∘ model of ocean dynamics and biogeochemistry in the northwest Atlantic Ocean. This model is built using the new regional capabilities in the MOM6 ocean model and is coupled with the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALT) biogeochemical model and Sea Ice Simulator version-2 (SIS2) sea ice model. Our goal was to develop a model to provide information to support living-marine-resource applications across management time horizons from seasons to decades. To do this, we struck a balance between a broad, coastwide domain to simulate basin-scale variability and capture cross-boundary issues expected under climate change; a high enough spatial resolution to accurately simulate features like the Gulf Stream separation and advection of water masses through finer-scale coastal features; and the computational economy required to run the long simulations of multiple ensemble members that are needed to quantify prediction uncertainties and produce actionable information. We assess whether MOM6-COBALT-NWA12 is capable of supporting the intended applications by evaluating the model with three categories of metrics: basin-wide indicators of the model's performance, indicators of coastal ecosystem variability and the regional ocean features that drive it, and model run times and computational efficiency. Overall, both the basin-wide and the regional ecosystem-relevant indicators are simulated well by the model. Where notable model biases and errors are present in both types of indicator, they are mainly consistent with the challenges of accurately simulating the Gulf Stream separation, path, and variability: for example, the coastal ocean and shelf north of Cape Hatteras are too warm and salty and have minor biogeochemical biases. During model development, we identified a few model parameters that exerted a notable influence on the model solution, including the horizontal viscosity, mixed-layer restratification, and tidal self-attraction and loading, which we discuss briefly. The computational performance of the model is adequate to support running numerous long simulations, even with the inclusion of coupled biogeochemistry with 40 additional tracers. Overall, these results show that this first version of a regional MOM6 model for the northwest Atlantic Ocean is capable of efficiently and accurately simulating historical basin-wide and regional mean conditions and variability, laying the groundwork for future studies to analyze this variability in detail, develop and improve parameterizations and model components to better capture local ocean features, and develop predictions and projections of future conditions to support living-marine-resource applications across timescales.

Southern Ocean warming and Antarctic ice shelf melting in conditions plausible by late 23rd century in a high-end scenario

Abstract. How much Antarctic ice shelf basal melt rates can increase in response to global warming remains an open question. Here we describe the response of the Southern Ocean and ice shelf cavities to an abrupt change to high-end atmospheric conditions plausible by the late 23rd century under the SSP5-8.5 scenario. To achieve this objective, we first present and evaluate a new 0.25∘ global configuration of the NEMO (Nucleus for European Modelling of the Ocean NEMO System Team, 2019) ocean and sea ice model. Our present-day simulations demonstrate good agreement with observational data for key variables such as temperature, salinity, and ice shelf melt rates, despite the remaining difficulties to simulate the interannual variability in the Amundsen Sea. The ocean response to the high-end atmospheric perturbation includes a strengthening and extension of the Ross and Weddell gyres and a quasi-disappearance of sea ice, with a subsequent decrease in production of High Salinity Shelf Water and increased intrusion of warmer water onto the continental shelves favoured by changes in baroclinic currents at the shelf break. We propose to classify the perturbed continental shelf as a “warm–fresh shelf”. This induces a substantial increase in ice shelf basal melt rates, particularly in the coldest seas, with a total basal mass loss rising from 1180 to 15 700 Gt yr−1 and an Antarctica averaged melt rate increasing from 0.8 to 10.6 m yr−1. In the perturbed simulation, most ice shelves around Antarctica experience conditions that are currently found in the Amundsen Sea, while the Amundsen Sea warms by 2 ∘C. These idealised projections can be used as a base to calibrate basal melt parameterisations used in long-term ice sheet projections.

Basin-scale tracer replacement timescales in a one-degree global OGCM

This study investigates basin-scale tracer replacement timescales of the two polar oceans and the Atlantic, Indian, and Pacific Oceans using a one-degree global ocean-sea ice model that represents oceans under the largest Antarctic ice shelves, the Filchner-Ronne and Ross Ice Shelf (FRIS and RIS). After a long spin-up with present-day surface boundary conditions, we confirm that the model has a typical representation of wind-driven and thermohaline circulations in one-degree ocean models. We use virtual passive tracers placed in the five oceans and examine the behavior of the passive tracers to estimate the tracer replacement timescales and pathways of the basin-scale ocean waters. Replacement timescales in the polar oceans (114 years for the Southern Ocean and 109 years for the Arctic Ocean) are found to be shorter than those in the three oceans (217 years for the Atlantic Ocean, 163 years for the Indian Ocean, and 338 years for the Pacific Ocean). The Southern Ocean tracer has two clear pathways to the Northern Hemisphere: the surface route in the Atlantic Ocean and the bottom route in the Pacific and Indian Oceans. This surface route is a rapid conduit to transport the Southern Ocean signal to the North Atlantic and Arctic Oceans. The Atlantic Ocean tracer is transported to both polar regions along the North Atlantic Current and the Antarctic Circumpolar Current (ACC). The tracer experiments clearly demonstrate that Atlantic Meridional Overturning Circulation (AMOC) plays a vital role in transporting the water masses in the Atlantic and Arctic Oceans to the Southern Ocean. The southward flow of the AMOC at the intermediate depths carries the northern waters to the ACC region, and then the water spreads over the Southern Ocean along the eastward-flowing ACC. The decay timescales of water in the ice-shelf cavities exposed to the water outside the Southern Ocean are estimated to be approximately 150 years for both the FIRS and RIS. The decay timescales in the Antarctic coastal region are short at the surface and long in the deep layers, with a noticeable reduction in the areas where ACC flows southward toward the Antarctic continent.

Disentangling Dynamic from Thermodynamic Summer Ice Area Loss from Observations (1979–2021): A Potential Mechanism for a “First-Time” Ice-Free Arctic

Abstract In recent decades, the Arctic minimum sea ice extent has transitioned from a predominantly thick multiyear ice cover to a thinner seasonal ice cover. We partition the total (observed) Arctic summer area loss into thermodynamic and dynamic (convergence, ridging, and export) sea ice area loss during the satellite era from 1979 to 2021 using a Lagrangian sea ice tracking model driven by satellite-derived sea ice velocities. Results show that the thermodynamic signal dominates the total summer ice area loss and the dynamic signal remains small (∼20%) even in 2007 when dynamic loss was largest. Sea ice loss by compaction (within pack ice convergence) dominates the dynamic area loss, even in years when the export is largest. Results from a simple (Ekman) free-drift sea ice model, supported by results from the Lagrangian model, suggest that nonlinear effects between dynamic and thermodynamic area loss can be important for large negative anomalies in sea ice extent, in accord with previous modeling studies. A detailed analysis of two all-time record minimum years (2007 and 2012)—one with a semipermanent high in the southern Beaufort Sea and the other with a short-lived but extreme storm in the Pacific sector of the Arctic in late summer—shows that compaction by Ekman convergence together with large thermodynamic melt in the marginal ice zone dominated the sea ice area loss in 2007 whereas, in 2012, it was dominated by Ekman divergence amplified by sea–ice albedo feedback—together with an early melt onset. We argue that Ekman divergence from more intense summer storms when the sun is high above the horizon is a more likely mechanism for a “first-time” ice-free Arctic.

Physical Links from Atmospheric Circulation Patterns to Barents–Kara Sea Ice Variability from Synoptic to Seasonal Timescales in the Cold Season

Abstract Previous findings show that large-scale atmospheric circulation plays an important role in driving Arctic sea ice variability from synoptic to seasonal time scales. While some circulation patterns responsible for Barents–Kara sea ice changes have been identified in previous works, the most important patterns and the role of their persistence remain unclear. Our study uses self-organizing maps to identify nine high-latitude circulation patterns responsible for day-to-day Barents–Kara sea ice changes. Circulation patterns with a high pressure center over the Urals (Scandinavia) and a low pressure center over Iceland (Greenland) are found to be the most important for Barents–Kara sea ice loss. Their opposite-phase counterparts are found to be the most important for sea ice growth. The persistence of these circulation patterns helps explain sea ice variability from synoptic to seasonal time scales. We further use sea ice models forced by observed atmospheric fields (including the surface circulation and temperature) to reproduce observed sea ice variability and diagnose the role of atmosphere-driven thermodynamic and dynamic processes. Results show that thermodynamic and dynamic processes similarly contribute to Barents–Kara sea ice concentration changes on synoptic time scales via circulation. On seasonal time scales, thermodynamic processes seem to play a stronger role than dynamic processes. Overall, our study highlights the importance of large-scale atmospheric circulation, its persistence, and varying physical processes in shaping sea ice variability across multiple time scales, which has implications for seasonal sea ice prediction. Significance Statement Understanding what processes lead to Arctic sea ice changes is important due to their significant impacts on the ecosystem, weather, and shipping, and hence our society. A well-known process that causes sea ice changes is atmospheric circulation variability. We further pin down what circulation patterns and underlying mechanisms matter. We identify multiple circulation patterns responsible for sea ice loss and growth to different extents. We find that the circulation can cause sea ice loss by mechanically pushing sea ice northward and bringing warm and moist air to melt sea ice. The two processes are similarly important. Our study advances understanding of the Arctic sea ice variability with important implications for Arctic sea ice prediction.

A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images

Abstract. In combination with observations from visible satellite channels, near-infrared channels can provide valuable additional cloud information, e.g. on cloud phase and particle sizes, which is also complementary to the information content of thermal infrared channels. Exploiting near-infrared channels for operational data assimilation and model evaluation requires a sufficiently fast and accurate forward operator. This study presents an extension to the method for fast satellite image synthesis (MFASIS) that allows for simulating reflectances of the 1.6 µm near-infrared channel based on a computationally efficient neural network with the same accuracy that has already been achieved for visible channels. For this purpose, it is important to better represent vertical variations in effective cloud particle radii, as well as mixed-phase clouds and molecular absorption in the idealized profiles used to train the neural network. A new approach employing a two-layer model of water, ice and mixed-phase clouds is described, and the relative importance of the different input parameters characterizing the idealized profiles is analysed. A comprehensive data set sampled from Integrated Forecasting System (IFS) forecasts together with different parameterizations of the effective water and ice particle radii is used for the development and evaluation of the method. Further evaluation uses a month of ICOsahedral Non-hydrostatic development based on version 2.6.1 (ICON-D2) hindcasts with effective radii directly determined by the two-moment microphysics scheme of the model. In all cases, the mean absolute reflectance error achieved is about 0.01 or smaller, which is an order of magnitude smaller than typical differences between reflectance observations and corresponding model values. The errors related to the imperfect training of the neural networks present only a small contribution to the total error, and evaluating the networks takes less than a microsecond per column on standard CPUs. The method is also applicable for many other visible and near-infrared channels with weak water vapour sensitivity.

Computational models of amorphous ice for accurate simulation of cryo-EM images of biological samples

Simulations of cryo-electron microscopy (cryo-EM) images of biological samples can be used to produce test datasets to support the development of instrumentation, methods, and software, as well as to assess data acquisition and analysis strategies. To be useful, these simulations need to be based on physically realistic models which include large volumes of amorphous ice. The gold standard model for EM image simulation is a physical atom-based ice model produced using molecular dynamics simulations. Although practical for small sample volumes; for simulation of cryo-EM data from large sample volumes, this can be too computationally expensive. We have evaluated a Gaussian Random Field (GRF) ice model which is shown to be more computationally efficient for large sample volumes. The simulated EM images are compared with the gold standard atom-based ice model approach and shown to be directly comparable. Comparison with experimentally acquired data shows the Gaussian random field ice model produces realistic simulations. The software required has been implemented in the Parakeet software package and the underlying atomic models are available online for use by the wider community.

Analysis of ice and snow tourism service quality improvement strategy based on grey correlation model in the perspective of sharing economy

Abstract The evaluation model and index system of ice and snow tourism service quality are derived from this paper’s perceived evaluation of ice and snow tourism service quality. The TOPSIS ideal solution ranking method is improved using the entropy power method, and the entropy-TOPSIS-grey correlation model is jointly constructed to evaluate the ice and snow tourism service quality by introducing the grey correlation model. To verify the validity of the evaluation model, a quantitative analysis of the data was conducted through examples. The results show that the perception evaluation scores of transportation, tour, catering, shopping, accommodation and service are around 4, and the comprehensive posting progress of transportation, tour and catering are 0.623, 0.584 and 0.557, respectively. Thus, it indicates that the service quality of ice and snow tourism needs to be improved in various aspects, such as transportation, tours, and catering.

Evaluation of Slope Correction Methods to Improve Surface Elevation Change Estimation over Antarctic Ice Sheet using SARAL/AltiKa

Antarctic Ice Sheet (AIS) surface elevation change plays a crucial role in understanding the ice sheet mass balance. The present study focuses on improving AIS surface elevation estimations by incorporating slope correction methods called Direct Method (DM) using SARAL/AltiKa 40 Hz geophysical data record for 2013 (Exact Repeat Mission) and 2020 (Drifting Phase) with terrain slope ranges from 0° to 0.85°. The NASA's Ice, Cloud, and land Elevation Satellite (ICESat) Digital Elevation Model (DEM) has been utilized as a priori topography model to retrieve slope of the AIS terrain. While comparing the two direct methods (DM1 &amp; DM2) based slope corrected elevations with Operation Ice Bridge (OIB) elevation data of November 2013, the RMSE resulted in 0.35 and 0.37 m and biases of the order of 0.26 m and 0.28 m for DM1 and DM2 respectively. Moreover, comparison with ICESat DEM showed the RMSE of the order of 1.81 and 2.09 m, and biases of the order of 0.95 and 0.99 m for DM1 and DM2, respectively. It has been observed that DM1 is the most suitable method for correcting terrain slope with the lowest RMSE and bias. Moreover, the slope induced error correction methods show utmost importance in estimating accurate elevation, especially over undulating terrain of AIS.

Local analytical optimal nudging for assimilating AMSR2 sea ice concentration in a high-resolution pan-Arctic coupled ocean (HYCOM 2.2.98) and sea ice (CICE 5.1.2) model

Abstract. Local analytical optimal nudging (LAON) is introduced and thoroughly evaluated for assimilating the Advanced Microwave Scanning Radiometer 2 (AMSR2) sea ice concentration (SIC) in the Norwegian High-resolution pan-Arctic ocean and sea ice Prediction System (NorHAPS). NorHAPS is a developing high-resolution (3–5 km) pan-Arctic coupled ocean and sea ice modeling and prediction system based on the HYbrid Coordinate Ocean Model (HYCOM version 2.2.98) and the Los Alamos multi-category sea ice model (CICE version 5.1.2), with the LAON for data assimilation. In this study, our focus is on the LAON assimilation of AMSR2 SIC, which is designed to update the model SIC in every time step such that the analysis will eventually reach the optimal estimate. The SIC innovation (observation minus model) is designed to be proportionally distributed to the multiple sea ice categories. A hindcast experiment is performed with and without the LAON assimilation for the period 1 January 2021 to 30 April 2022, in which the extra computational cost for the LAON assimilation is about 5 % of the free run without assimilation. The results show that the LAON assimilation greatly improves the simulated sea ice concentration, extent, area, thickness, and volume, as well as the sea surface temperature (SST). It also produces significantly more accurate sea ice edge and marginal zone (MIZ) than the observed AMSR2 SIC that is assimilated when evaluated against the Norwegian Ice Service (NIS) ice chart. The results are also compared with the Copernicus Marine Environment Monitoring Service (CMEMS) operational SIC analyses from NEMO, TOPAZ4, and neXtSIM, which use ensemble Kalman filters and direct insertion for data assimilation. It is shown that the LAON assimilation produces significantly lower integrated ice edge error (IIEE) and integrated MIZ error (IME) than the CMEMS SIC analyses when evaluated against the NIS ice chart. LAON also produces a continuous and smooth evolution of sub-daily SIC, which avoids abrupt jumps often seen in other assimilated products. This efficient and accurate method is promising for data assimilation in global and high-resolution models.

Simulation of Sea Ice Fragmentation Based on an Improved Voronoi Diagram Algorithm in an Ice Zone Navigation Simulator

In order to reduce the cost of navigation training in the waters of ice zones and improve the effectiveness of the training process, a method for simulating sea ice fragmentation in an ice zone navigation simulator is proposed. The Voronoi diagram algorithm, which takes the ice thickness into account and affects the degree of fragmentation, was used to preprocess the sea ice model so that the number and sizes of the ice model fragmentations would be related to the ice thickness. According to the position of the preprocessed sub-blocks of the ice model, the collision bodies of the Mesh Collider and Sphere Collider were set up to realize the effect of the conduction of ice cracking as a result of the ship’s hull colliding with the ice surface. Based on the positional relationship between mesh triangle elements and the water surface, the volume of an ice floe that should have been underwater when it reached equilibrium was calculated to achieve the sea-floating effect of the broken ice floe. The quadtree method for the management of sea ice scenes was improved to improve the timeliness of the replacement of the ice model. The experiments show that this method improved the realism of simulations of sea ice breaking in ice zones and can be used for simulations in ice zone navigation simulators.