Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, Version 1

Data set id:

NSIDC-0051

DOI: 10.5067/8GQ8LZQVL0VL

Data Citation and Acknowledgment
As a condition of using these data, you must cite the use of this data set. Such a practice gives credit to data set producers and advances principles of transparency and reproducibility.

Cavalieri, D. J., Parkinson, C. L., Gloersen, P. & Zwally, H. J. (1996). Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data. (NSIDC-0051, Version 1). [Data Set]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/8GQ8LZQVL0VL. [describe subset used if applicable]. Date Accessed 04-30-2025.

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There is a more recent version of these data.
Version Summary

Initial release

Overview

This data set is retired and no longer available for download. We recommend using the newest version of Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data (NSIDC-0051) data set as an alternative.

This data set is generated from brightness temperature data and is designed to provide a consistent time series of sea ice concentrations spanning the coverage of several passive microwave instruments.The data are provided in the polar stereographic projection at a grid cell size of 25 x 25 km.

Parameter(s):

SEA ICE CONCENTRATION

Platform(s):

DMSP 5D-2/F11, DMSP 5D-2/F13, DMSP 5D-2/F8, DMSP 5D-3/F17, Nimbus-7

Sensor(s):

SMMR, SSM/I, SSMIS

Data Format(s):

PNG, Binary

Temporal Coverage:

26 October 1978 to 31 December 2021

Temporal Resolution:

1 day
1 month

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:

N:

90

S:

30.98

E:

180

W:

-180

N:

-39.23

S:

-90

E:

180

W:

-180

Blue outlined yellow areas on the map below indicate the spatial coverage for this data set.

View Metadata Record

Strengths and Limitations

Strengths

Long-term continuous record, with complete daily coverage of the Antarctic and the Arctic (excluding the “pole-hole”) since August 1987, preceded by every-other-day coverage since late October 1978. This makes it useful for tracking climate trends and variability and as a large-scale climate indicator (Parkinson et al., 1999; Zwally et al., 2002; Parkinson, 2019).
Thorough inter-calibration between sensors for consistency throughout the record (Cavalieri et al., 1999; Cavalieri et al., 2012)
Manual corrections and spatial and temporal interpolation to remove errors and fill in data gaps (Cavalieri et al., 1999)
Less sensitive to temperature variations because it uses ratios instead of differences (Comiso et al., 1997)
Concentrations are generally reliable within the ice pack (away from the ice edge) during cold (non-melt) conditions (Comiso et al., 1997)
Microwave observations provide surface snow and ice coverage during cloudy and night-time (including polar night) conditions (Cavalieri et al., 1999)
Useful input/validation of climate model simulations (National Center for Atmospheric Research Staff, 2017)

Limitations

Low spatial resolution (25 km gridded) limits detail on concentration and precision of ice edge (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)

Data Access & Tools

This data set has been retired. There is a more recent version of these data.

Documentation

Help Articles

General Questions & FAQs

Descriptions of and differences between the NASA Team and Bootstrap algorithms

NSIDC currently archives passive microwave sea ice concentration products based on two algorithms: the NASA Team algorithm and the Bootstrap algorithm. Both algorithms were developed by researchers at the NASA Goddard Space Flight Center in the 1980s.

How to Articles

Filter and order from a data set web page using the Data Access Tool

Many NSIDC DAAC data sets can be accessed using NSIDC DAAC's Data Access Tool. This tool provides the ability to search and filter data with spatial and temporal constraints using a map-based interface.Users have the option to:

The NSIDC Data Map Services Application Programming Interface (API) provides HTTP URLs for requesting geo-registered map images from NSIDC's geospatial database. A WMS request defines the geographic layer(s) and area of interest to be processed.

The NSIDC provides Python scripts for reformatting specific NSIDC SMMR-SSM/I-SSMIS data products in polar stereographic projections from NetCDF to binary.

The NSIDC Python Reformatting and Subsetting (PyRS) tool is a command line tool which prompts the user to specify data reformatting and subsetting preferences. Output formats available are native, GeoTIFF, and NetCDF.