DOI: 10.1594/pangaea.975054
title: Arctic PASSION - High Resolution Synthetic Aperture Radar based Risk Index Outcome (AP-RIO)

description: The Risk Index Outcome (RIO) is a critical component of the Polar Operational Limit Assessment Risk Indexing System (POLARIS) developed by the International Maritime Organization (IMO, 2016). RIO evaluates the operational risks for ships navigating in ice-infested waters by evaluating ice conditions and offers a quantifiable measure of risk that aids in decision-making for safe navigation in polar regions based on ship ice class, sea ice type/stage of development (SOD) and sea ice concentration (SIC). The DMI-led Automated Sea Ice Products (DMI-ASIP; Wulf et al., 2024, dataset) provides daily maps of SOD and SIC based on Sentinel-1 SAR imagery, AMSR-2 Passive Microwave and Ice Charts from the Greenland and Canadian Ice Services, combined with novel AI retrieval and processing techniques. In the framework of EU funded Arctic PASSION project, we produced 10 years of satellite observation based weekly RIO maps referred as the Arctic PASSION-RIO (AP-RIO) by leveraging DMI-ASIP datasets. The AP-RIO dataset will provide weekly risk assessment maps for the given ship classes and will support the establishment of a 10 year climatology thereby enabling the assessment of RIO variability in the years covered by the input DMI-ASIP products. The AP-RIO dataset will enhance the safety and efficiency of maritime operations in the polar seas, providing a robust reference for evaluating normal and extreme ice conditions. AP-RIO is produced in the framework of the Arctic PASSION project (European Union's Horizon 2020 research and innovation program under grant agreement No. 101003472) and supported by the DMI-ASIP development team.Algorithm and Processing Scheme:SIC and SOD from ASIP are processed (by taking the mean and mode respectively) into a weekly field based on the daily files for that week. This is done for the time period of 3 Oct. 2014 - 3 Oct. 2024. The weekly SOD is used to find the Risk Value (RV) by looking at the lookup table (Dybkjær et al. 2025a). Risk Index Outcome (RIO) values are computed for each pixel in the field based on the RIO formula (RIO = SIC x RV) using the SIC from ASIP and the found RV. The meaning of the computed RIO values can be interpreted using the table in (Dybkjær et al. 2025b). The RIO field is finally saved to weekly NetCDF files.
description: NetCDF file example of the AP-RIO data set:netcdf RIO_Lthick_new_PC2_PC7_1C_mean_20150109_20150115 { dimensions:time = UNLIMITED ; // (1 currently)yc = 15100 ;xc = 10400 ;shipclass = 3 ;variables:float lon(yc, xc) ;lon:_FillValue = NaNf ;lon:least_significant_digit = 3LL ;lon:standard_name = longitude ;lon:long_name = longitude coordinate ;lon:units = degrees_east ;lon:grid_mapping = crs ;lon:coordinates = lon lat ;float lat(yc, xc) ;lat:_FillValue = NaNf ;lat:least_significant_digit = 3LL ;lat:long_name = latitude coordinate ;lat:standard_name = latitude ;lat:units = degrees_north ;lat:grid_mapping = crs ;lat:coordinates = lon lat ;double time(time) ;time:_FillValue = NaN ;time:standard_name = time ;time:units = days since 1970-01-01 ;time:calendar = proleptic_gregorian ;double xc(xc) ;xc:_FillValue = NaN ;xc:axis = X ;xc:standard_name = projection_x_coordinate ;xc:long_name = x-coordinate in cartesian system ;xc:units = m ;double yc(yc) ;yc:_FillValue = NaN ;yc:axis = Y ;yc:standard_name = projection_y_coordinate ;yc:long_name = y-coordinate in cartesian system ;yc:units = m ;byte shipclass(shipclass) ;double RIO(time, shipclass, yc, xc) ;RIO:_FillValue = NaN ;RIO:long_name = Risk Index Outcome (POLARIS) ;RIO:units = [] ;RIO:comment = Ship classes included in this file: PC2, PC7, 1C ;RIO:comment2 = Meaning of shipclass-dimension: 1:PC1, 2:PC2, 3:PC3, 4:PC4, 5:PC5, 6:PC6, 7:PC7, 10:1ASuper, 11:1A, 12:1B, 13:1C, 20:noclass ;RIO:coordinates = lat lon ;// global attributes::title = Risk Index Outcome (RIO) calculated from DMI\'s ASIP data ;:history = Created by RIOengine_ASIP.py on 2024-12-05 ;: acknowledgement = Used RIO calculation method: Lthick_new. This dataset has been funded by the European Union's Horizon 2020 research and innovation programme through the project Arctic PASSION under grant agreement No. 101003472. ;:institution = Danish Meteorological Institute, DMI ;:Contact = gd@dmi.dk or msu@dmi.dk ;