PIOMAS¶

Pan-Arctic Ice Ocean Modeling and Assimilation System

Update delayed

At a glance¶

Note on period: In normal operation the data were updated roughly monthly. There have been no updates since the 2026-03-24 notice, and the monthly volume CSV holds missing values (-1) from March 2026 onward.

Overview¶

PIOMAS is a coupled sea ice–ocean model run by the University of Washington Polar Science Center, and its output provides estimates of Arctic sea ice thickness and volume since 1979. It assimilates satellite sea ice concentration and, in ice-free areas, sea surface temperature, but no thickness observations, so the results are model and assimilation estimates rather than direct measurements. Because it has been validated extensively against submarine, ICESat and other thickness observations, it is widely used as the reference record of Arctic sea ice volume change and for evaluating climate models.

Available variables¶

PSC provides the model-grid data as one file per variable per year (name.H), in headerless single-precision flat binary. The names below are the file-name prefixes. Descriptions and units follow the table on the PSC "model grid" page; aiday and uiday are file names found in the server directories (they are not described in the official table, so their meaning is inferred from the naming convention).

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

Ice thickness and concentration (monthly mean)¶

Ice dynamics and thermodynamics (monthly mean)¶

Daily files¶

Pan-Arctic time series (text and CSV)¶

The full variable list is in the official documentation.

How to get the data¶

• PSC PIOMAS volume and thickness time series page — Web download (text and CSV) No login needed
  • Pan-Arctic daily and monthly volume and daily mean thickness time series (version 2.1).
• PSC model-grid data page — Web download / SFTP or rsync (username and password anonymous) No login needed
  • Variable table, grid files (grid.dat etc.), Fortran and IDL reading programs, and links to community Python tools.
• pscfiles server — sea ice thickness (heff) — HTTPS directory No login needed
  • Binary files (heff.H.gz) plus NetCDF versions for 1979–2025 (heff.H.nc.gz).
• pscfiles server — sea ice concentration (area, aiday) — HTTPS directory No login needed
• pscfiles server — other variables (other) — HTTPS directory No login needed
  • Some ocean variables (ssh, tice0, uo1_10, etc.) stop with the 2020 files.

Example code¶

Download and unzip heff.H2025.gz, and also get grid.dat from utilities/ on the same server.

import numpy as np

nx, ny = 360, 120
# Headerless single-precision binary; 12 monthly fields back to back (use ">f4" if big-endian)
heff = np.fromfile("heff.H2025", dtype="<f4").reshape(12, ny, nx)
if np.nanmax(np.abs(heff)) > 100:  # implausible values: re-read with swapped byte order
    heff = np.fromfile("heff.H2025", dtype=">f4").reshape(12, ny, nx)
print("September mean thickness, max (m):", heff[8].max())

Practical tips¶

• PIOMAS is a model estimate that assimilates no thickness observations. In the satellite era it has been reported to overestimate thin ice and underestimate thick ice, so do not call it "observed thickness", and compare with ICESat or CryoSat-2 thickness where possible.
• PSC gives an uncertainty of about ±1.0 × 10³ km³ per decade for the volume trend and about ±0.75 × 10³ km³ for monthly anomalies. Long-term trends also depend on the atmospheric reanalysis used as forcing, so if production resumes with a new forcing after 2026, check the version and forcing before joining new and old data.
• The model's southern boundary excludes parts of the Sea of Okhotsk, the Gulf of St. Lawrence and the Labrador Sea. Match domains when comparing with Northern Hemisphere ice volume from other sources, especially in winter.
• Binary files may need byte-swapping depending on your system. heff and area are also available as NetCDF (.nc.gz), which is easier.

Notices and change history¶

References for your paper¶

Reference papers¶

Volume time series and uncertainty (cited as requested by PSC) — DOI 10.1029/2011JC007084

@article{schweiger2011piomas,
  author  = {Schweiger, Axel and Lindsay, Ron and Zhang, Jinlun and Steele, Mike and Stern, Harry and Kwok, Ron},
  title   = {Uncertainty in modeled {Arctic} sea ice volume},
  journal = {Journal of Geophysical Research},
  volume  = {116},
  pages   = {C00D06},
  year    = {2011},
  doi     = {10.1029/2011JC007084}
}

Model description (cited as requested by PSC) — DOI 10.1175/1520-0493(2003)131<0845:MGSIWA>2.0.CO;2

@article{zhang2003ted,
  author  = {Zhang, Jinlun and Rothrock, D. A.},
  title   = {Modeling Global Sea Ice with a Thickness and Enthalpy Distribution Model in Generalized Curvilinear Coordinates},
  journal = {Monthly Weather Review},
  volume  = {131},
  number  = {5},
  pages   = {845--861},
  year    = {2003},
  doi     = {10.1175/1520-0493(2003)131<0845:MGSIWA>2.0.CO;2}
}

Acknowledgements¶

PSC asks users to cite Schweiger et al. (2011) for the volume time series and uncertainties and Zhang and Rothrock (2003) for model details. Recording the version (currently v2.1) and download date will help distinguish your data from any later reprocessing or forcing change.

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¶

• PSC — PIOMAS Arctic Sea Ice Volume Reanalysis
• PSC — PIOMAS Variables on Model Grid
• NOAA PSL — NCEP/NCAR R1 end-of-updates notice
• NCAR Climate Data Guide — PIOMAS