Satellite Observations for Detecting and Forecasting Sea-Ice Conditions: A Summary of Advances Made in the SPICES Project by the EU’s Horizon 2020 Programme

Abstract

The detection, monitoring, and forecasting of sea-ice conditions, including their extremes, is very important for ship navigation and offshore activities, and for monitoring of sea-ice processes and trends. We summarize here recent advances in the monitoring of sea-ice conditions and their extremes from satellite data as well as the development of sea-ice seasonal forecasting capabilities. Our results are the outcome of the three-year (2015–2018) SPICES (Space-borne Observations for Detecting and Forecasting Sea-Ice Cover Extremes) project funded by the EU’s Horizon 2020 programme. New SPICES sea-ice products include pancake ice thickness and degree of ice ridging based on synthetic aperture radar imagery, Arctic sea-ice volume and export derived from multisensor satellite data, and melt pond fraction and sea-ice concentration using Soil Moisture and Ocean Salinity (SMOS) radiometer data. Forecasts of July sea-ice conditions from initial conditions in May showed substantial improvement in some Arctic regions after adding sea-ice thickness (SIT) data to the model initialization. The SIT initialization also improved seasonal forecasts for years with extremely low summer sea-ice extent. New SPICES sea-ice products have a demonstrable level of maturity, and with a reasonable amount of further work they can be integrated into various operational sea-ice services.

Revisiting Trans-Arctic Maritime Navigability in 2011–2016 from the Perspective of Sea Ice Thickness

“…For instance, the M'Clintock Channel located to the west of the Prince of Wales Island was blocked in 2014; the Prince of Wales Strait and the Dolphin and Union Strait located in the west of the Victoria Island were occluded in 2011. For more accurate estimation of navigability, especially in these key straits and seas, higher spatial and temporal resolution in sea ice monitoring are required in future studies [13]. Meanwhile, the ability to simulate heavily deformed and ridged sea ice in the MYI regions (e.g., the CAA) still needs improvements in numerical simulations and forecasts [23].…”

“…However, Arctic shipping is still usually hindered by pack sea ice, including multiyear ice (MYI), the thickness of which can be >5 m. For example, navigation in the NWP is severely hampered by local accumulations of MYI, caused by old ice drifting and deforming within the tight Canadian Arctic passages. Recent advances in satellite-based Arctic sea ice monitoring can provide reliable sea ice thickness (SIT) observations that reveal the possible risk for Arctic shipping but are still restricted to freezing season [13]. Recent studies focus on estimating the future potential of Arctic shipping with the primary consideration of sea ice conditions [9][10][11][14][15][16][17][18].…”

Supplementing Remote Sensing of Ice: Deep Learning-Based Image Segmentation System for Automatic Detection and Localization of Sea-ice Formations From Close-Range Optical Images

“…For example, the results from the automated algorithm proposed in [2] were compared to digitized ice charts provided by the Finnish ice service (FIS). Sea ice charts from the Arctic and Antarctic Research Institute (AARI) were used for the evaluation of sea ice types, and the corresponding operational limits were calculated in [5], [6]. Other examples of comparisons between satellite data and sea ice charts can be found in [15]- [18].…”

Should Sea-Ice Modeling Tools Designed for Climate Research Be Used for Short-Term Forecasting?

“…Most of these modeling systems assimilate satellite-derived sea ice concentration, among other ocean properties such as ocean temperature and salinity. Only the ArcIOPS modeling system assimilates ice thickness in an operational mode [31], although approaches using this and other sea ice variables such as ice surface temperature are being explored (e.g., [32][33][34][35]).…”