Near-Real-Time DMSP SSMIS Daily Polar Gridded Sea Ice Concentrations, Version 2
Data set id:
NSIDC-0081
DOI: 10.5067/YTTHO2FJQ97K
This data set has been retired.
Version Summary
Version update reflects the conversion of the data set from binary to netCDF.

Overview

This data set provides a Near-Real-Time (NRT) map of sea ice concentrations for both the Northern and Southern Hemispheres. As of 18 June 2026, this data set is retired and no longer available for download. Forward processing for this product ceased in January 2026. We recommend using the research quality AMSR2 Daily Polar Gridded Sea Ice Concentrations (https://doi.org/10.5067/W13AO54SS7CW) or Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data (https://doi.org/10.5067/MPYG15WAA4WX) data sets as an alternative.
Parameter(s):
SEA ICE CONCENTRATION
Platform(s):
DMSP 5D-3/F16
DMSP 5D-3/F17
DMSP 5D-3/F18
Sensor(s):
SSMIS
Data Format(s):
PNG
netCDF-4
Temporal Coverage:
  • 1 January 2024 to 14 January 2026
Temporal Resolution:
  • 1 day
Spatial Resolution:
  • 25 km
  • 25 km
Spatial Reference System(s):
  • NSIDC Sea Ice Polar Stereographic North
    EPSG:3411
  • NSIDC Sea Ice Polar Stereographic South
    EPSG:3412
Spatial Coverage:
  • Northern latitude
    90
    Southern latitude
    30.98
    Eastern longitude
    180
    Western longitude
    -180
  • Northern latitude
    -39.23
    Southern latitude
    -90
    Eastern longitude
    180
    Western longitude
    -180
Blue outlined yellow areas on the map below indicate the spatial coverage for this data set.
Strengths and Limitations

Strengths

Limitations

  • Low spatial resolution (25 km gridded) limits detail on concentration and precision of sea ice edge; is unsuitable for operational/navigational support (Cavalieri et al., 1999)
  • Underestimates sea ice concentration during melt season (Kern et al., 2020) and/or when the ice is thin (Ivanova et al., 2015)
  • Higher uncertainties in Antarctica due to flooded snow and other ice characteristics (Comiso et al., 1997)
  • Algorithm coefficients are fixed for a given sensor, so biases can occur if characteristic surface conditions change (Cavalieri et al., 1999)
  • False coastal ice can occur due to mixed land and ocean within a sensor footprint (Cavalieri et al., 1999)
  • Near-real-time product with no planned reprocessing for long-term consistency; should not be used to derive long-term trends in sea ice or snow (Cavalieri et al., 1999)

 

Data Access & Tools

This data set has been retired. Please contact user services if you have questions.

Help Articles

General Questions & FAQs

This article covers frequently asked questions about the NASA NSIDC DAAC's Earthdata cloud migration project and what it means to data users.