Classification of surface atmospheric pressure fields in the Laptev and East Siberian seas

The need for classifying surface atmospheric pressure fields over the Arctic seas arose as a method was being developed for predicting the characteristics of discontinuities (leads) in the sea ice cover. Wind, which is determined by the atmospheric pressure field, acts on the ice cover and causes it to drift. Leads are formed in the ice cover due to the irregularity of ice drift. Ice drift can be caused by several factors, such as skewed sea level, tidal waves and currents. However, the main cause of ice drift in the Arctic seas is wind. Each typical field of surface atmospheric pressure corresponds to a certain field of leads in the ice cover. This makes it possible to predict the characteristics of leads in the ice cover by selecting fields similar to predictive fields of atmospheric pressure based on archived data.The variety of atmospheric pressure fields makes it difficult to find an analogue to a given field by simply going through all the corresponding data available in the electronic archive. Classification of atmospheric pressure fields makes it possible to simplify the process of selecting an analogue.To develop the classification, we used daily surface pressure maps at 00 hours GMT for the cold seasons (from mid- October to the end of May) 2016–2021. The atmospheric pressure fields, which were similar in configuration, and hence the wind fields, belonged to the same type. In total, 27 types were identified, applicable both to the Laptev Sea and the East Siberian Sea. Within one type, a division into subtypes was made, depending on the speed of the geostrophic wind.The wind intensity was estimated by the number of isobars multiples of 5 mb on the surface atmospheric pressure map. All the surface pressure fields observed over the waters of the Laptev and East Siberian Seas over the past 5 years have been assigned to one of the types identified using cluster analysis. Each type of atmospheric pressure within the framework of the forecasting method being developed is supposed to correspond to a field of discontinuities in the ice cover.

Partial Shape Recognition for Sea Ice Motion Retrieval in the Marginal Ice Zone from Sentinel-1 and Sentinel-2

We present an algorithm for computing ice drift in the marginal ice zone (MIZ), based on partial shape recognition. With the high spatial resolution of Sentinel-1 and Sentinel-2 images, and the low sensitivity to atmospheric influences of Sentinel-1, a considerable quantity of ice floes is identified using a mathematical morphology method. Hausdorff distance is used to measure the similarity of segmented ice floes. It is tolerant to perturbations and deficiencies of floe shapes, which enhances the density of retrieved sea ice motion vectors. The PHD algorithm can be applied to sequential images from different sensors, and was tested on two combined image mosaics consisting of Sentinel-1 and Sentinel-2 data acquired over the Fram Strait; the PHD algorithm successfully produced pairs of matched ice floes. The matching result has been verified using shape and surface texture similarity of the ice floes. Moreover, the present method can naturally be extended to the problem of multi-source sea ice image registration.

SITool (v1.0) – a new evaluation tool for large-scale sea ice simulations: application to CMIP6 OMIP

The Sea Ice Evaluation Tool (SITool) described in this paper is a performance metrics and diagnostics tool developed to evaluate the skill of Arctic and Antarctic model reconstructions of sea ice concentration, extent, edge location, drift, thickness, and snow depth. It is a Python-based software and consists of well-documented functions used to derive various sea ice metrics and diagnostics. Here, SITool version 1.0 (v1.0) is introduced and documented, and is then used to evaluate the performance of global sea ice reconstructions from nine models that provided sea ice output under the experimental protocols of the Coupled Model Intercomparison Project phase 6 (CMIP6) Ocean Model Intercomparison Project with two different atmospheric forcing datasets: the Coordinated Ocean-ice Reference Experiments version 2 (CORE-II) and the updated Japanese 55-year atmospheric reanalysis (JRA55-do). Two sets of observational references for the sea ice concentration, thickness, snow depth, and ice drift are systematically used to reflect the impact of observational uncertainty on model performance. Based on available model outputs and observational references, the ice concentration, extent, and edge location during 1980–2007, as well as the ice thickness, snow depth, and ice drift during 2003–2007 are evaluated. In general, model biases are larger than observational uncertainties, and model performance is primarily consistent compared to different observational references. By changing the atmospheric forcing from CORE-II to JRA55-do reanalysis data, the overall performance (mean state, interannual variability, and trend) of the simulated sea ice areal properties in both hemispheres, as well as the mean ice thickness simulation in the Antarctic, the mean snow depth, and ice drift simulations in both hemispheres are improved. The simulated sea ice areal properties are also improved in the model with higher spatial resolution. For the cross-metric analysis, there is no link between the performance in one variable and the performance in another. SITool is an open-access version-controlled software that can run on a wide range of CMIP6-compliant sea ice outputs. The current version of SITool (v1.0) is primarily developed to evaluate atmosphere-forced simulations and it could be eventually extended to fully coupled models.

Ice-Associated Amphipods in a Pan-Arctic Scenario of Declining Sea Ice

Sea-ice macrofauna includes ice amphipods and benthic amphipods, as well as mysids. Amphipods are important components of the sympagic food web, which is fuelled by the production of ice algae. Data on the diversity of sea-ice biota have been collected as a part of scientific expeditions over decades, and here we present a pan-Arctic analysis of data on ice-associated amphipods and mysids assimilated over 35 years (1977–2012). The composition of species differed among the 13 locations around the Arctic, with main differences between basins and shelves and also between communities in drift ice and landfast sea ice. The sea ice has been dramatically reduced in extent and thickness during the recorded period, which has resulted in reduced abundance of ice amphipods as well as benthic amphipods in sea ice from the 1980’s to the 2010’s. The decline mainly involved Gammarus wilkitzkii coinciding with the disappearance of much of the multiyear sea ice, which is an important habitat for this long-lived species. Benthic amphipods were most diverse, and also showed a decline over the time-span. They had higher abundance closer to land where they are associated with landfast ice. However, they also occurred in the Central Arctic Ocean, which is likely related to the origin of sea ice over shallow water and subsequent transport in the transpolar ice drift. Recent sampling in the waters east and north of Svalbard has found continued presence of Apherusa glacialis, but almost no G. wilkitzkii. Monitoring by standardized methods is needed to detect further changes in community composition of ice amphipods related to reductions in sea-ice cover and ice type.

Feasibility Study on Estimation of Sea Ice Drift from KOMPSAT-5 and COSMO-SkyMed SAR Images

Estimating the sea ice drift field is of importance in both scientific study and activities in the polar ocean. Ice motion is being tracked at large scale (10 km and larger) on a daily basis; however, a higher resolution product is desirable for more reliable monitoring of rapid changes in sea ice. The use of wide-swath SAR has been extensively studied; yet, recent high-resolution X-band SAR sensors have not been tested enough. We examine the feasibility of KOMPSAT-5 and COSMO-SkyMed for retrieving sea ice motion by using the dataset of the MOSAiC expedition. The ice drift match-ups extracted from consecutive SAR image pairs and buoys for more than seven months in the central Arctic were used for a performance evaluation and validation. In addition to individual tests for KOMPSAT-5 and COSMO-SkyMed, a cross-sensor combination of two sensors was tested to overcome the drawback, a relatively long revisit time of high-resolution SAR. The experimental results show that higher accuracies are achievable from both single- and cross-sensor configurations of high-resolution X-band SARs compared to wide-swath C-band SARs, and that sub-daily monitoring is feasible from the cross-sensor approach.