The SSMIS instrument is a microwave radiometer that senses emitted microwave radiation from the Earth's surface. This radiation is affected by surface and atmospheric conditions, and thus provides a range of geophysical information including sea ice concentration.

The input Near-Real-Time DMSP SSMIS Daily Polar Gridded Brightness Temperatures are gridded onto the NSIDC polar stereographic grid. NSIDC generates sea ice concentrations from these brightness temperature data using the NASA Team Sea Ice Algorithm. The NRTSI data processing is as close as possible to that used for the Goddard Space Flight Center Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I Passive Microwave Data (GSFC data set). These data are updated daily and are retained on the FTP site until the GSFC data set becomes available for the same time period. Roughly the most recent three to six months of near-real-time sea ice concentration data are available.

SSMIS data from the DMSP-F18 satellite are used in the current near-real-time product starting with 4/1/2016 to present. The near-real-time data are intended to facilitate time-sensitive research dependent upon precise detection of seasonal polar sea ice formation and break up and to provide the product within one to two days following data acquisition. These data are primarily meant to provide a best estimate of current ice conditions based on information and algorithms available at the time the data are acquired. 

Note: Near-real-time products are not intended for operational use in assessing sea ice conditions for navigation and should be used with caution in extending the GSFC sea ice time series. For historical SMMR, SSM/I, and SSMIS sea ice concentration data, refer to the Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data data set.

Processing Steps

The NRTSI data are created using the following general steps:

1. Obtain the most recent input brightness temperatures from Near-Real-Time DMSP SSMIS Daily Polar Gridded Brightness Temperatures for both hemispheres.
    
2. Apply the land spillover correction.
    
3. Compute the sea ice concentration from the brightness temperature data using the NASA Team Sea Ice Algorithm.
   
   Note: The differences between the brightness temperatures provided by F17 and F18 are so minimal that the same tie points can be used for both sets of data. Thus, the current sea ice concentration fields are computed using F18 data with F17 tie points.  If further analysis indicates that the tie points should be adjusted, this will be implemented and documented here.
    
4. For the Northern Hemisphere, remove spurious ice caused by residual weather effects by applying the Polar Stereographic Valid Ice Masks Derived from National Ice Center Monthly Sea Ice Climatologies. For the Southern Hemisphere, remove the spurious ice caused by residual weather effects by applying SST climatology masks from AMSR-E data.
    
5. Apply the SSMIS pole hole mask to the Northern Hemisphere.
    
6. Create header.
    
7. Save the data to a binary file and create a browse image of the data. 

Masks

A number of masks are applied to the input brightness temperature data to make the land area consistent with other sea ice concentration data sets, to remove spurious ice, and to remove the section of Earth not imaged by the sensor over the North Pole. The sections below explain the masks applied to these data during the processing of this product at NSIDC.

Valid Ice Masks

Weather effects can cause the passive microwave signature of seawater to appear like that of ice (Cavalieri 1995). Atmospheric water vapor is often the reason behind false ice detection. Most of these false ice signatures are removed with a standard brightness temperature filter, but some are too close to those of real ice. Sea surface temperature (SST) fields that show where water is usually too warm for ice, maximum ice extent fields that show where ice has never been before (in the satellite record), or sea ice climatologies can be used to mask out spurious ice resulting from residual weather effects.

For the Northern Hemisphere, spurious sea ice caused by residual weather effects are removed by applying Polar Stereographic Valid Ice Masks Derived from National Ice Center Monthly Sea Ice Climatologies. The masks have the additional benefit of removing some of the false ice detections that can occur along coasts. No extra manual removal of false ice is done as is done in the GSFC data set. Note: Prior to January 2015, the Northern Hemisphere was masked with the climatology based on the SST masks from AMSR-E. See the Version History section of this document for more information on why these new masks are being applied.

For the Southern Hemisphere, spurious ice caused by residual weather effects are removed by applying a valid ice mask derived from maximum ice climatology masks based on SST masks from AMSR-E data.

SSMIS Pole Hole Mask

The SSMIS Pole Hole mask (gsfc_pole_hole.N17) is a circular mask that symmetrically covers the observed maximum extent of the missing data resulting from the orbit inclination and instrument swath near the North Pole. For SSMIS, the hole is 94 km in radius and is located poleward of 89.18° N with an area of 0.029 million km². This area is masked out to provide the smallest, most consistent missing area we can create from satellite swath data which has a jagged, irregular coverage around the North Pole. See the Version History section of this document for information on the different pole hole masks that have been used for this product.

Land-Spillover Corrections

Ice can be falsely detected along coasts due to contamination of ocean pixels by the passive microwave emission of land. While the nominal grid cell size of the gridded products is 25 km x 25 km, the -3dB footprint of the 19.35 GHz SSM/I and SSMIS passive microwave channel is 72 km x 44 km (Kunkee et al 2008). To remove spurious Northern Hemisphere coastal ice, the NRTSI product processing uses the land spillover correction used in the GSFC data set that is described in NASA Technical Memorandum 104647 (Cavalieri et al, 1997) and in the Sea Ice Concentrations from Nimbus-7 SSMR and DMSP SSM/I-SSMIS Passive Microwave Data guide document. The rational behind this land spillover approach is that ice will have retreated from most coasts in late summer, so that coastal ice observed at this time by passive microwave instruments is probably a false detection. To reduce the chance of removing ice where it really does exist, the method searches for and requires the presence of open water in the vicinity of the grid cell to be corrected. The method uses the monthly data from 1992 as a basis for correcting SSMIS data.

This NRTSI data set is created using brightness temperature data from CLASS in order to provide the product within one to two days following data acquisition.

Additionally, these NRTSI data may:

• be missing swaths
• contain erroneous ice over ocean that was missed by the weather filters.

Error Sources

Through time, the sensor used for this data set has changed from SSM/I on the DMSP F13 and F15 to the SSMIS on the DMSP F17 and F18 satellites. To correct for the sensor differences, NSIDC conducted preliminary inter-calibration between F13 and F15 using an overlap period of 01 January 2007 to 31 December 2007. These data should retain reasonable consistency, though differences of approximately 50,000 sq km may be possible in daily total extents. For the transition to F17 SSMIS data, NSIDC conducted preliminary inter-calibration between F13 and F17 using an overlap period of 01 April 2008 to 31 March 2009. A direct intercomparison of the year of daily sea ice extent (F13-F17) yielded an average daily difference of approximately 2800 sq km with an average magnitude of difference of approximately 28,000 sq km.

On 05 April 2016, the vertically polarized 37GHz (37V) channel of the F17 Special Sensor Microwave Imager and Sounder (SSMIS) began yielding compromised data.  This is a primary channel used to assess sea ice concentration, so NSIDC stopped producing F17 data and started producing with F18 uncalibrated data.

This data set now uses F18 SSMIS beginning 1 April 2016. For the latest transition to F18 SSMIS, NSIDC investigated the calibration of tie point values to best match the sea ice extent from F17 over a 12-month period from 01 March 2015 through 29 February 2016.  No adjustment to the tie points were indicated, and the average difference between F17- and F18-derived sea ice extents were approximately 20,000 sq km.