GIOMAS¶

Global Ice-Ocean Modeling and Assimilation System

Update delayed

At a glance¶

Note on period: The official page describes the data as running from January 1979 to the present, but when checked on 2026-10-11 the server held 2026 files only through January. Some 2025 files (heff, area and others) were re-uploaded in March–April 2026, so they may differ from 2025 data downloaded earlier.

Overview¶

GIOMAS provides global sea ice thickness, concentration and upper-ocean fields from the Polar Science Center's coupled ice-ocean model, the same system as PIOMAS (the Thickness and Enthalpy Distribution (TED) sea ice model with the Parallel Ocean Program) run on a global grid. SSM/I sea ice concentration is assimilated by nudging and the model is forced by NCEP/NCAR reanalysis; no thickness observations are assimilated, so thickness is a model estimate, not an observation. It is widely used for Antarctic sea ice thickness and volume, where long-term observations are scarce.

Available variables¶

Each variable comes as yearly headerless single-precision flat binary files (name.H), with 12 months per file. Names and units of the monthly variables follow the table on the PSC GIOMAS page; the daily files are names found in the server directory. heff, area and otemp1 are also available as NetCDF (.nc.gz).

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 (monthly)¶

Ocean surface (monthly, 2.5 m)¶

Daily files (from the server directory)¶

The full variable list is in the official documentation.

How to get the data¶

• PSC GIOMAS data page — Web download / sftp, ssh or rsync (username and password "anonymous") No login needed
  • Variable table, grid and mask files (grid.dat, grid.dat.pop, io.dat_360_276.output) and links to Fortran and IDL readers.
• pscfiles server — Global_seaice directory — HTTPS directory No login needed
  • All variables and years are in one directory. Daily files exceed 100 MB per year, so download only the variables you need.

Example code¶

Download heff.H2020 (uncompressed) and grid.dat from the same directory first.

import numpy as np

nx, ny = 360, 276
# headerless single-precision flat binary, 12 months in sequence (use ">f4" if big-endian)
heff = np.fromfile("heff.H2020", dtype="<f4").reshape(12, ny, nx)
if np.nanmax(np.abs(heff)) > 100:  # values look wrong: re-read with the other byte order
    heff = np.fromfile("heff.H2020", dtype=">f4").reshape(12, ny, nx)
print("September maximum thickness (m):", heff[8].max())

Practical tips¶

• An evaluation of Antarctic sea ice thickness (Liao et al. 2022) found that GIOMAS reproduces the variability of Antarctic sea ice volume well (correlation 0.83) and the trend reversal around 2013, but its volume is on average about 38% lower than Envisat and CryoSat-2, and it is especially thin where deformed ice is common, such as the northwestern Weddell Sea. It is safer to use it for variability and trends than for absolute values.
• Assimilating ice concentration also adjusts thickness, which tends to thin the mean ice. Thickness observations are not assimilated, so do not describe GIOMAS thickness as "observed thickness".
• The citation on the GIOMAS page gives the pages of Zhang and Rothrock (2003) as 681–697, but the paper is in Monthly Weather Review 131(5), 845–861. Use the bibliographic details matching the DOI below.
• Multiplying oflux_ocn by -3.02×10⁸ gives the ocean heat flux to the mixed layer in W/m², and multiplying snow by (water density / snow density) gives the actual snow depth.

Notices and change history¶

References for your paper¶

Reference papers¶

Model paper (citation 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}
}

Application of the global model to Antarctic sea ice (optional) — DOI 10.1175/JCLI4136.1

Evaluation of Antarctic sea ice thickness (optional) — DOI 10.5194/tc-16-1807-2022

Acknowledgements¶

PSC asks GIOMAS users to cite Zhang and Rothrock (2003). There is no dataset DOI, so give the data location (the PSC GIOMAS page) and your download date in the Data availability statement.

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 GIOMAS data page
• PSC PIOMAS page (for the group's notices)
• Liao et al. (2022) — evaluation of GIOMAS Antarctic sea ice thickness
• NOAA PSL — Data Alert, NCEP/NCAR Reanalysis 1 updates to end