Data Set ID:

VIIRS/NPP Ice Surface Temperature 6-Min L2 Swath 750m, Version 1

This data set reports sea ice surface temperature (IST) derived from radiance data acquired by the Visible Infrared Imager Radiometer Suite (VIIRS). Following the approach used by MODIS, the algorithm converts VIIRS calibrated radiances into brightness temperature and computes IST using a split-window technique.

VIIRS flies on board the Suomi National Polar-orbiting Partnership (NPP) satellite.

This is the most recent version of these data.

COMPREHENSIVE Level of Service

Data: Data integrity and usability verified; data customization services available for select data

Documentation: Key metadata and comprehensive user guide available

User Support: Assistance with data access and usage; guidance on use of data in tools and data customization services

See All Level of Service Details

  • Sea Ice > Ice Temperature > ICE TEMPERATURE
Data Format(s):
  • NetCDF
Spatial Coverage:
N: 90, 
S: -90, 
E: 180, 
W: -180
Spatial Resolution:
  • 750 m x 750 m
Temporal Coverage:
  • 19 January 2012
Temporal Resolution6 minuteMetadata XML:View Metadata Record
Data Contributor(s):Mark Tschudi, George Riggs, Dorothy Hall, Miguel Román

Geographic Coverage

Other Access Options

Other Access Options


As a condition of using these data, you must cite the use of this data set using the following citation. For more information, see our Use and Copyright Web page.

Tschudi, M., G. Riggs, D. K. Hall, and M. O. Román. 2017. VIIRS/NPP Ice Surface Temperature 6-Min L2 Swath 750m, Version 1. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: [Date Accessed].

Back to Top

Collapse All / Open All

Detailed Data Description

The VIIRS sea ice surface temperature (IST) algorithm and output data have been designed to be compatible with Version 6 MODIS ISTs from Aqua and Terra, to ensure continuity between the collections and facilitate climate-data records (CDRs) from the three sensors. Differences in the algorithms reflect physical differences between the instruments, for example spatial resolution and the location of spectral bands.

Unlike MODIS, VIIRS swath-level sea ice cover and ice surface temperature (IST) data are provided as separate products: VNP29 (sea ice cover, release pending) and VNP30 (this data set). This decision by the the Science Team allows the data to be produced at the spatial resolution of the underlying VIIRS acquisition bands: 375 m for sea ice cover (I-band) and 750 m for IST (M-band).

Data files are provided in NetCDF-4/HDF5 (.nc) format, following the NetCDF Climate and Forecast (CF) Metadata Conventions (Version 1.6). JPEG browse images are also available.

NetCDF is a set of software libraries and self-describing, machine-independent data formats that are specifically designed to help create, access, and share array-oriented scientific data sets. Note that NetCDF-4 is not a file format. It is a convention for storing data as HDF using the NetCDF data model. For more information, visit the HDF Group's HDF5 Home Page and Unidata's NetCDF Documentation website.

Background color off
File Contents

VNP30 files contain six minutes of swath data (a scene), during which the instrument sweeps out 202 (and occasionally 203) cross-track scans along a 12 km viewing path. VIIRS M-bands are equipped with 16 detectors and thus VNP30 M-band scenes typically contain 3,232 pixels in the along-track direction. The instrument's ±56.28° Earth-view scan width produces 3,200 M-band pixels in the cross-track direction.

Background color off
File Naming Convention

VIIRS file names begin with a product identifier (VNP30) followed by the acquisition date and time. Dates are specified as a 4-digit year and 3-digit day of the year. Acquisition times are specified as HHMM and reflect the start time of the 6-minute scene, beginning with 0000 and ending with 2354. The following section describes the full VIIRS file naming convention:

Example File Name:

  • VNP[PID].A[YYYY][DDD].[HHMM].[VVV].[yyyy][ddd][hhmmss].nc

Refer to Table 1 for descriptions of the file name variables listed above.

Table 1. Variables in the VNP10 File Naming Convention
Variable Description
PID Product ID
A Acquisition date follows
YYYY Acquisition year
DDD Acquisition day of year
HHMM Acquisition hour and minute in Greenwich Mean Time (GMT)
VVV Version (Collection) number
yyyy Production year
ddd Production day of year
hhmmss Production hour/minute/second in GMT
.nc NetCDF-4/HDF5 formatted data file

NetCDF-4/HDF5 data files contain important metadata including global attributes, which store details about the data, and local attributes such as keys to data fields. In addition, each data file has a corresponding XML metadata file. For detailed information about metadata fields and values, consult the NASA S-NPP VIIRS Ice Surface Temperature Products Collection 1 (C1) User Guide.

Background color off
File Size

Data files are typically 70–80 MB.

Background color off
Spatial Coverage

Coverage is global, however IST values are only valid for polar oceans (pixels poleward of 55°).

To locate the VIIRS sensor at a given time, the following sites offer tools that track and predict NPP's orbital path:

Spatial Resolution

VIIRS M-bands have a spatial resolution of 750 m at nadir.

Background color off
Temporal Coverage

Data are available from 19 January 2012 to present. IST is calculated for both daytime and nighttime scenes. If you cannot locate data for a particular date or time, check the VIIRS Data Outages Web page.

Temporal Resolution

VIIRS scans the entire globe every one to two days. As such, most locations on Earth are imaged at least once per day and more frequently where swaths overlap, for example near the poles. Suomi NPP's sun-synchronous, near-circular polar orbit is timed to cross the equator from south to north (ascending node) at approximately 1:30 P.M. local time. The repeat cycle is 16 days (quasi 8-day).

Background color off

VNP30 data files contain two NetCDF-4/HDF5 groups: IST_Data and Geolocation_Data. The following sections describe the data sets that are stored within these groups.

IST_Data Group


This data set contains ice surface temperatures with no cloud mask applied. It is provided for users who wish to determine or interpret cloud cover from either the ancillary QA data or from a cloud data product of their choosing. Users should note, however, that the IST algorithm is only valid under clear sky conditions. When clouds are present, IST estimates can contain significant errors.


This data set contains IST data with the cloud mask overlaid to provide a view of the cloud conditions in the scene. See Cloud Masking for details.


The basic QA value provides users with a general quality assessment (best, good, or poor) for each pixel that was processed for IST. The approach is similar to the MODIS IST products, but expanded to include day vs. night and cloud cover. Mask values for land, inland water, and bow tie trim are also included.


For Version 1, QA_Flags is a placeholder with all pixels set to the fill value 255. Future versions will utilize data screens to test for conditions that confound the IST algorithm and store the results as bit flags.

Geolocation_Data Group

Latitude, Longitude

Separate latitude and longitude data sets at 750 m resolution are provided to geolocate observations in the IST data sets. Each latitude/longitude pair corresponds to the center of a pixel (M-band sensor) in the data arrays.

In addition to the data sets above, data files include two HDF5 dimension scales—number_of_lines and number_of_pixels—as defined by Version 1.6 of the NetCDF Climate and Forecast (CF) Metadata Conventions. These data sets allow GIS programs like HDFView, Panoply, and GDAL (versions 2.1.2 and higher) to properly map data arrays from index space to geographic coordinate space.

At this time, ArcGIS and QGIS do not properly geolocate VIIRS swath-level data because they utilize Geospatial Data Abstraction Library (GDAL) libraries which are older than Version 2.1.2. Please contact the vendors for more information. Still have questions? Email NSIDC User Services.

The following table contains additional details about the variables described above, including coded integer keys, data types, and scaling factors:

Table 2. VNP30 Variable Names and Descriptions
Variable Name Description
IST Data

IST plus other results (16-bit unsigned integers). Valid IST range is 21,000 – 31,000; scale factor to recover IST in kelvins = 0.01. Valid values are:

  • 0: missing
  • 100: no decision
  • 1100: night
  • 2500: land
  • 3700: inland water
  • 3900: open ocean
  • 65535: fill

IST with cloud mask applied (16-bit unsigned integers). Valid range is 21,000 – 31,000; scale factor to recover IST in kelvins = 0.01. Valid values are:

  • 0: missing
  • 100: no decision
  • 1100: night
  • 2500: land
  • 3700: inland water
  • 3900: open ocean
  • 5000: cloud
  • 65535: fill
IST_Basic_QA General quality assessment (best, good, poor, or cloud) for pixels processed for IST (8-bit unsigned integers). Separate values are provided for day and night. Mask values indicate land, inland water, and bow tie trim. Valid values are:
  • 0: best
  • 1: day good
  • 2: day cloud
  • 3: night good
  • 4: night cloud
  • 5: other
  • 6: poor
  • 237: inland water
  • 253: land mask
  • 254: bow tie trim

Placeholder for a future version. All array locations set to the fill value 255.

Geolocation Data
latitude 750 m resolution (3232 x 3200) latitude array.
longitude 750 m resolution (3232 x 3200) longitude array.

Variable Name Description
Table 3. VNP30 Dimension Scale Data Sets
number_of_lines HDF5 scalar data set/NetCDF shared dimension. 32-bit floating point (3232,1)
number_of_pixels HDF5 scalar data set/NetCDF shared dimension, 32-bit floating point (3200,1)

Background color off

Software and Tools

VIIRS NetCDF4/HDF5 data files can be accessed using either NetCDF4 or HDF5 tools. In addition, NASA has two online tools that can help you find the right data for your project. Worldview offers users an interactive interface to view full-resolution, global, near real-time satellite imagery projected on Earth. EarthData allows users to search for and order NASA data sets.

Background color off

Data Acquisition and Processing

Derivation Techniques and Algorithms

As with MODIS, the VIIRS sea IST algorithm is based on the work of Key et al., 1997, who demonstrated that a split window technique is accurate enough for most climate process studies. One major caveat, however, is that this approach requires clear skies. Cloud contaminated pixels can result in significant IST errors. The method in Key et al. expands upon Key and Haefliger, 1992 and has been validated in Key et al., 2013; Yu et al., 1995; Lindsay and Rothrock, 1994; and Massom and Comiso, 1994.

The following table lists the products that are input to the VIIRS IST algorithm:

Table 4. Input products to the VIIRS IST algorithm
Product Data Arrays Spatial Resolution Descriptor
NPP_VMAES_L1 BrightnessTemperature_M15 750 m BT
QF1_VIIRSMBANDSDR_M15 Poor quality flag
BrightnessTemperature_M16 BT
QF1_VIIRSMBANDSDR_M16 Poor quality flag
SolarZenithAngle Solar zenith angle
SatelliteZenithAngle Satellite zenith angle
VNP35_L2 QF1_VIIRSCMIP (bits 2-3) 750 m Cloud mask confidence
QF2_VIIRSCMIP (bits 0-2) Land/water mask

IST Algorithm

VIIRS IST is computed from band M15 (10.763 µm) and M16 (12.013 µm) brightness temperatures in the NPP_VMAES_L1 product, using the split-window method of Yu et al., 1995 updated for VIIRS as follows:

IST = a + b·T11 + c·(T11 - T12) + d·[(T11 - T12)·(sec(q)-1)] (1)

In Equation 1, T11 and T12 are the brightness temperatures (K) for VIIRS bands M15 and M16, respectively; q is the scan angle from nadir. The coefficients a, b, c, and d compensate for atmospheric effects, primarily humidity, and are empirically determined.¹ The algorithm utilizes separate coefficient sets for the Arctic and Antarctic in three different temperature ranges: < 240; 240K — 260 K; and > 260 K. IST is calculated for all polar ocean water bodies in daylight and nighttime.

¹Obtained via personal communication from J. Key, NOAA-NESDIS, and Y. Liu, University of Wisconsin Madison.

Cloud Masking

Clouds are masked using the 750 m Cloud Detection Results & Confidence Indicator flag in the VIIRS Cloud Mask product (VNP35_L2). When that flag is set to “confident cloudy” or “probably cloudy,” the pixel is labeled as cloud obscured in the IST map.

Data Screens

The algorithm checks the M15 and M16 quality flag (QF), and if the flag has any value other than good the IST_basic_QA value is set to poor. Subsequent versions of the algorithm will incorporate additional data screens and store the results as bit flags in the QA_Flags data field. However, at this time the QA_Flags data field is a placeholder; all pixels contain the fill value 255.

Bow Tie Effect

VIIRS M bands have 16 rectangular detectors in the along-track direction, oriented with the smaller dimension along-scan. The detector size and scan timing are designed to produce a scan width at nadir that matches the ground-track distance traveled by satellite during one scan period, thus leaving no gap between adjacent scans. However, the along-track width of the VIIRS scan at Earth's surface increases from 11.7 km at nadir to 25.8 km at ±56.28°, due primarily to the increasing distance between the sensor and the ground and Earth's curvature. As a result, the scan footprint has the shape of a bow tie (see Figure 1).

Adjacent scans thus begin to visibly overlap at angles greater than approximately 19°, and in M bands by more than 1 pixel at angles greater than 32°. To save transmission bandwidth, VIIRS removes duplicated pixels in off-nadir portions of scans; however, this introduces visual artifacts in the raw swath images. Users who wish may remove these artifacts via interpolation when images are displayed. Note, however, that the artifacts do not appear in higher-level products in which the scans have been projected and gridded onto Earth’s surface.

Figure 1. Illustration of the bow tie effect. Increasing scan width away from nadir leads to pixel overlap in adjacent scans.

Quality Assessment

The IST algorithm is accurate to approximately ±1 K (Key et al., 2013). The Science Team is continuing to assess this product's accuracy via comparison with the MODIS IST swath product and NASA Operation IceBridge airborne IST data.

Additional information is available in the NASA S-NPP VIIRS Ice Surface Temperature Products Collection 1 (C1) User Guide and the Suomi-NPP VIIRS Ice Surface Temperature Algorithm Theoretical Basis Document (ATBD).

Background color off
Error Sources

Because sea ice can vary in concentration from near zero to 100 percent within a 750 m pixel, computed ISTs can vary across a scene due to mixed-pixel effects. In addition, the presence of melt ponds and leads in the summer months affects the emissivity of the surface and therefore IST calculations.

The targeted uncertainty of the NASA VIIRS IST product is ±1 K over a measurement range of 213 K – 275 K. Previous estimates based on comparisons with the MODIS IST product approach this value overall, but show generally higher uncertainty (2 K - 3 K) for ISTs above 250 K (Key et al., 2013), with VIIRS cooler than MODIS. Measurement uncertainty is defined as the root-mean-square of the measurement errors.

VIIRS geolocation accuracy is very high, resulting in consistent, high-accuracy mapping of VIIRS data products.

Background color on
Instrument Description

The VIIRS instrument is a whiskbroom scanning radiometer with 22 bands (see VIIRS Bands and Bandwidths) covering the spectrum between 0.412 μm and 12.01 μm. Sixteen moderate resolution bands (M-bands), five imaging resolution bands (I-bands), and one panchromatic day-night band (DNB) acquire spatial resolutions at nadir of 750 m, 375 m, and 750 m, respectively. M-bands include 11 Reflective Solar Bands (RSB) and 5 Thermal Emissive Bands (TEBs). I-bands include 3 RSBs and 2 TEBs. More details about the VIIRS instrument are available in the Visible Infrared Imaging Radiometer Suite (VIIRS) Sensor Data Record (SDR) User’s Guide and the Joint Polar Satellite System (JPSS) VIIRS Radiometric Calibration Algorithm Theoretical Basis Document (ATBD).

The following table lists select technical specifications for the VIIRS instrument:

Table 4. VIIRS Specifications
Variable Description
Orbit 829 km (nominal) altitude, 1:30 P.M. ascending node, sun-synchronous, near-polar, circular
Scan Rate 1.779 sec/rev, 202.3 deg/sec
Scan Width ±56.28° (Earth view)
Imaging Optics 19.1 cm aperture, 114 cm focal length
Swath Dimensions 3060 km cross-track, 12 km along track at nadir
Samples per Band
  • M-bands: 6304 samples at 0.312 mrad/sample (3200 aggregated pixels)
  • I-bands: 12608 samples at 0.156 mrad/sample (6400 aggregated pixels)
  • DNB: 4064 pixels at 0.149 to 0.894 mrad/pixel
Weight 275 kg
Power 200 W (single orbit average)
Data Rate 10.5 Mbps (max)
Quantization 12 bit –14 bit A/D converters for lower noise
Launch date 28 October, 2011
Design Life 7 years (5 year mission)
Background color on

References and Related Publications

How To

Programmatic Data Access Guide
Data from the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) can be accessed directly from our HTTPS file system or through our Application Programming Interface (API). Our API offers you the ability to order data using specific temporal and spatial filters... read more
Search, order, and customize NSIDC DAAC data with NASA Earthdata Search
NASA Earthdata Search is a map-based interface where a user can search for Earth science data, filter results based on spatial and temporal constraints, and order data with customizations including re-formatting, re-projecting, and spatial and parameter subsetting. Thousands of Earth science data... read more
Filter and order from a data set web page
Many NSIDC data set web pages provide the ability to search and filter data with spatial and temporal contstraints using a map-based interface. This article outlines how to order NSIDC DAAC data using advanced searching and filtering.  Step 1: Go to a data set web page This article will use the... read more


What data subsetting, reformatting, and reprojection services are available for VIIRS data?
The following table describes the data subsetting, reformatting, and reprojection services that are currently available for VIIRS data via the NASA Earthdata Search tool. Short Name Title Parameter Subsetting Spatial Subsetting  *... read more
How does VIIRS snow and sea ice data compare to MODIS
Data products from VIIRS are being created that are similar to MODIS data products to ensure the continuity needed for the development of snow and sea ice climate records beyond the life expectancy of MODIS. The temporal resolution and spatial extent are identical in MODIS and VIIRS. A benefit of ... read more
Missing and delayed VIIRS data
The lag time between observations and availability of VIIRS products is only a few days. Lag time may be extended due to satellite maneuvers and extra quality assurance required for the geolocation data after the maneuver. The... read more