neXtSIM¶

Arctic Ocean Sea Ice Reanalysis (ARCTIC_MULTIYEAR_PHY_ICE_002_016, neXtSIM-F)

Available

At a glance¶

Note on period: According to the Copernicus Marine (STAC) metadata, daily data cover 1993-01-01 to 2026-05-31 (12,204 days) and monthly data January 1993 to May 2026 (401 months), as of the 2026-09-21 update. The PUM gives the period as "1993 to Y-1" with "yearly updates in November after the update of ARCTIC_MULTIYEAR_PHY_002_003", while the QUID says the product is "extended regularly every 6 months", so the documents disagree. The initial state is the TOPAZ4 reanalysis plus a two-year spin-up (PUM). Thickness is assimilated only in winter (October–April) from October 2010 onward.

Overview¶

A stand-alone Arctic sea ice reanalysis produced by NERSC with the neXtSIM-F sea ice model. neXtSIM solves the Brittle-Bingham-Maxwell (BBM) rheology, which treats sea ice as a brittle material, with a finite-element method on an adaptive Lagrangian triangular mesh. It is forced by hourly ERA5 atmospheric fields and daily ocean fields from the TOPAZ4b physical reanalysis (ARCTIC_MULTIYEAR_PHY_002_003). OSI SAF SSMIS sea ice concentration is assimilated daily, and CS2SMOS winter (October–April) thickness from October 2010. Besides concentration, thickness, snow depth and drift, it provides multiyear and young ice fractions, ice age, ridged ice volume fraction and albedo on a 3 km grid, which makes it well suited to studies of sea ice dynamics.

Available variables¶

Names checked against the metadata of the Copernicus Marine daily dataset (cmems_mod_arc_phy_my_nextsim_P1D-m_202411, including originalGrid) and the PUM variable table. The monthly and climatology datasets contain the same 10 variables. Damage, the key state variable of the BBM rheology, and deformation or stress fields are not included in this product.

instantaneous mean accumulated maximum minimum static — instantaneous: value at the time stamp · mean/accumulated/maximum/minimum: over the indicated interval · static: does not change with time

Sea ice and snow state¶

Ice type and age¶

Ice drift and albedo¶

The full variable list is in the official documentation.

How to get the data¶

• Copernicus Marine — ARCTIC_MULTIYEAR_PHY_ICE_002_016 — Copernicus Marine Toolbox (Python, CLI) / web download (Subset, File Browser)
  • A free Copernicus Marine account is required. Dataset IDs: daily mean cmems_mod_arc_phy_my_nextsim_P1D-m and monthly mean cmems_mod_arc_phy_my_nextsim_P1M-m (version tag 202411), monthly climatology cmems_mod_arc_phy_my_3km-climatology_P1M-m (202511). The native 3 km polar stereographic grid is served separately as the originalGrid part of each dataset.
• Copernicus Marine Toolbox documentation — Python / command line (CLI)
  • subset (area and variable extraction) returns the interpolated lat–lon version; get downloads the original NetCDF files unchanged.
• Product User Manual (PUM) and Quality Information Document (QUID) — Web documents (PDF)
  • The QUID summarises the validation of concentration, thickness, age, albedo and drift (Table 1).

Example code¶

Install with pip install copernicusmarine and store your credentials once with login(). open_dataset lazily opens the default lat–lon (0.03°) interpolated version. Open the native 3 km polar stereographic grid with dataset_part="originalGrid" and set the extent with minimum_x etc. (in metres for this product).

import copernicusmarine

# copernicusmarine.login()  # first time only

ds = copernicusmarine.open_dataset(
    dataset_id="cmems_mod_arc_phy_my_nextsim_P1D-m",
    variables=["siconc", "sithick", "sisnthick", "vxsi", "vysi"],
    minimum_latitude=70, maximum_latitude=90,
    minimum_longitude=-180, maximum_longitude=180,
    start_datetime="2024-03-01", end_datetime="2024-03-31",
)

# March mean thickness (average of the daily means)
sit_mar = ds["sithick"].mean("time")

# Ice speed (m/s) — eastward/northward components in the default dataset
speed = (ds["vxsi"] ** 2 + ds["vysi"] ** 2) ** 0.5
print(float(speed.mean()))

# Native 3 km polar stereographic grid (x/y in m, velocities along grid x/y)
ds_pol = copernicusmarine.open_dataset(
    dataset_id="cmems_mod_arc_phy_my_nextsim_P1D-m",
    dataset_part="originalGrid",
    variables=["sithick"],
    minimum_x=-1_500_000, maximum_x=1_500_000,
    minimum_y=-1_500_000, maximum_y=1_500_000,
    start_datetime="2024-03-01", end_datetime="2024-03-31",
)

Practical tips¶

• Thickness before October 2010, and every May–September, is free-running model output with no thickness assimilation. The QUID reports a 0.28 m RMSD against CS2SMOS during the assimilation period, but compared with PIOMAS the reanalysis is about 0.4 m thinner early in the record and only about 0.1 m thinner once assimilation starts. Allow for a possible discontinuity at October 2010 when computing thickness or volume trends from 1993.
• The default dataset (0.03° lat–lon) and subset output are re-interpolated from the native polar stereographic grid, which slightly smooths the fields and enlarges the land mask (PUM). For small-scale features or area and volume integrals, use the originalGrid (regular 3 km) data. Even the 3 km grid is interpolated from the ~10 km model mesh, so the effective resolution is coarser.
• In originalGrid files, vxsi and vysi are grid x/y components, not eastward/northward. The PUM includes a Python example that rotates the vectors with cartopy. Coordinates are in metres on a spherical projection (R = 6378273 m); treating them as WGS 84 will misplace the data.
• Per the QUID, the assimilated inputs are OSI SAF SSMIS sea ice concentration (CDR v3 for 1993–2020 and ICDR v3 for 2021–2023, obtained from the C3S CDS) and AWI CS2SMOS ("version 2.6"). The SSMIS-based interim record (OSI SAF OSI-430-a, release 3) was suspended on 2025-10-17 and AWI's merged thickness became CS3SMOS (v300) from the 2025/26 winter, so inputs from 2024 onward may differ from the documentation. If you analyse the recent period together with earlier years, ask the Copernicus Marine Service Desk which inputs were used.
• The QUID reports concentration about 4–8% higher than passive microwave estimates, multiyear ice area overestimated by 0.5–1 million km², ice-edge advance in October–December slower than observed, and underestimated magnitude of high-drift events (trajectory error about 4.2 km per day against OSI SAF 24-hour drift). Ice age accumulates from 1993 and is not fully spun up until around 2000. The real-time forecast product from the same neXtSIM-F system is ARCTIC_ANALYSISFORECAST_PHY_ICE_002_011.

Notices and change history¶

References for your paper¶

Dataset citation¶

Copernicus Marine product DOI (ARCTIC_MULTIYEAR_PHY_ICE_002_016) — DOI 10.48670/mds-00336

@misc{cmems_arctic_multiyear_phy_ice_002_016,
  author       = {{E.U. Copernicus Marine Service Information (CMEMS)}},
  title        = {Arctic Ocean Sea Ice Reanalysis ({ARCTIC\_MULTIYEAR\_PHY\_ICE\_002\_016})},
  publisher    = {Marine Data Store (MDS)},
  year         = {2024},
  doi          = {10.48670/mds-00336},
  note         = {Accessed on DD MMM YYYY}
}

Reference papers¶

neXtSIM-F forecasting and assimilation system (product page reference) — DOI 10.5194/tc-15-3207-2021

@article{williams2021nextsimf,
  author  = {Williams, Timothy and Korosov, Anton and Rampal, Pierre and {\'O}lason, Einar},
  title   = {Presentation and evaluation of the {Arctic} sea ice forecasting system {neXtSIM-F}},
  journal = {The Cryosphere},
  volume  = {15},
  number  = {7},
  pages   = {3207--3227},
  year    = {2021},
  doi     = {10.5194/tc-15-3207-2021}
}

BBM rheology (PUM reference) — DOI 10.1029/2021MS002685

@article{olason2022bbm,
  author  = {{\'O}lason, Einar and Boutin, Guillaume and Korosov, Anton and Rampal, Pierre and Williams, Timothy and Kimmritz, Madlen and Dansereau, V{\'e}ronique and Samak{\'e}, Abdoulaye},
  title   = {A New Brittle Rheology and Numerical Framework for Large-Scale Sea-Ice Models},
  journal = {Journal of Advances in Modeling Earth Systems},
  volume  = {14},
  number  = {8},
  pages   = {e2021MS002685},
  year    = {2022},
  doi     = {10.1029/2021MS002685}
}

Acknowledgements¶

As Copernicus Marine data, include the statement "This study has been conducted using E.U. Copernicus Marine Service Information; https://doi.org/10.48670/mds-00336". The product page gives no fixed citation text and refers users to the Copernicus Marine "How to cite" help page.

Information on the datasets used in this study was compiled with the help of the Korean Climate Data Navigator (KCDN) (Sim, 2026; https://doi.org/10.5281/zenodo.23300923).

Links¶

• Product User Manual (PUM) — grid, file names, variables, time conventions
• Quality Information Document (QUID) — assimilated inputs and validation
• Synthesis of Quality Overview (SQO)
• Copernicus Marine product metadata (STAC)
• Copernicus Marine Toolbox — subsetting the original grid (originalGrid)
• OSI SAF — Implications of the end of SSMIS data on OSI SAF products
• neXtSIM version 2 model description (Ólason et al., 2026, GMD — not cited in the product documentation)
• Copernicus Marine User Notification Service