MODIS/Aqua Sea Ice Extent Daily L3 Global 1km EASE-Grid Night (MYD29P1N) data set, new for Version 5 (V005), contains fields for Ice Surface Temperature (IST) and IST Spatial Quality Assessment (QA) in Hierarchical Data Format-Earth Observing System (HDF-EOS) format along with corresponding metadata. MYD29P1N V005, the latest version of the Moderate Resolution Imaging Spectroradiometer (MODIS) data, consists of 951 x 951 km files of 1 km resolution data gridded in the Lambert Azimuth Equal Area map projection.
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.
The following example shows how to cite the use of this data set in a publication. List the principal investigators, year of data set release, data set title and version number, dates of the data you used (for example, December 2003 to March 2004), publisher: NSIDC, and digital media.
Hall, Dorothy K., George A. Riggs, and Vincent V. Salomonson. 2007, updated daily. MODIS/Aqua Sea Ice Extent Daily L3 Global 1km EASE-Grid Night V005, [list the dates of the data used]. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media.
|Data format||HDF-EOS version 2.9. GeoTIFF available through Reverb | ECHO, NASA's Next Generation Earth Science Discovery tool.|
|Spatial coverage and resolution||Coverage is global, but the sea ice algorithm is applied only to ocean pixels. Gridded resolution is 1 km.|
|Temporal coverage and resolution||MODIS data extends from 04 July 2002 to present.
Temporal resolution is daily.
|Tools for accessing and analyzing data||MODIS: MODLAND Tile Calculator
HEG HDF-EOS to GeoTIFF Conversion Tool
NSIDC's Hierarchical Data Format - Earth Observing System (HDF-EOS) site
HDF Java Products: NCSA HDFView
NASA Goddard Space Flight Center: MODIS Land Global Browse Images
Space Science and Engineering Center (SSEC): Aqua orbital tracks GLOBAL
The MODIS Conversion Toolkit (MCTK)
For more information regarding the scaled value descriptions, please see the MOD29P1N and MYD29P1N Local Sea Ice Attributes, Version 5 document.
|Grid type and size||MYD29P1N data are gridded to EASE-Grid tiles, 951 x 951 pixels in size.|
|File naming convention||Example: MYD29P1N.A2000057.h12v07.005.2006252061042.hdf|
|File size||0.05 - 1.5 MB using HDF compression|
|Parameter(s)||Ice Surface Temperature (IST)|
|Procedures for obtaining data|
Dorothy K. Hall
National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC)
Mail stop 614.1
Greenbelt, MD 20771
Vincent V. Salomonson
Room 809 WBB
Department of Meteorology
University of Utah
Salt Lake City, UT 84112
George A. Riggs
Science Systems and Applications, Inc.
Mail stop 614.1
Greenbelt, MD 20771
NSIDC User Services
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO 80309-0449 USA
phone: +1 303.492.6199
fax: +1 303.492.2468
form: Contact NSIDC User Services
The following site can help you select appropriate MODIS data for your study:
Data are available via the following methods:
Reverb: NASA search and order tool for subsetting, reprojecting, and reformatting data.
Subscription Service: Subscribe to have new data automatically sent when the data become available.
The following software tools can help you analyze the data:
Algorithms that generate sea ice products are continually being improved, as limitations become apparent in early versions of data. As a new algorithm becomes available, a new version of data is released. Users are encouraged to work with the latest version available, which is the highest version number. Version 5 (V005) is the most current version of MODIS data available from NSIDC. For V005, the Science Data Sets (SDS) Sea Ice by Ice Surface Temperature and Combined Sea Ice present in Version 4 (V004) were deleted from the product.
Please visit the following sites for more information about the V005 data, known data problems, the production schedule, and future plans:
MODIS sea ice products are archived in compressed HDF-EOS format, which employs point, swath, and grid structures to geolocate the data fields to geographic coordinates. This data compression should be transparent to most users since HDF capable software tools automatically uncompress the data. Various software packages, including several in the public domain, support the HDF-EOS data format. See the Software section for details. Also, see the Hierarchical Data Format - Earth Observing System (HDF-EOS) Web site for more information about the HDF-EOS data format, as well as tutorials in uncompressing the data and converting data to binary format.
Data can also be obtained in GeoTIFF format from Reverb | ECHO, NASA's Next Generation Earth Science Discovery Tool.
Visible data are not acquired when the sensor is observing the surface in darkness; therefore, this night product only contains IST data fields, which are based on thermal data. MYD29P1D consists of 951 x 951 cells of tiled data in the Lambert Azimuth Equal Area Projection.Each data granule contains the following HDF-EOS local attribute fields, which are stored with each SDS:
A separate ASCII text file containing metadata with a .xml file extension accompanies the HDF-EOS file. This ASCII text file contains some of the same metadata as in the HDF-EOS file, but also includes other information regarding archiving, user support, and post production QA relative to the granule ordered. The post-production QA metadata may or may not be present in the .xml file depending on whether or not the data granule was investigated for Quality Assessment. The ASCII text file should be examined to determine if post-production QA was applied to the granule (Riggs, Hall, and Salomonson 2006).
The file naming convention used for the MYD29P1N product is MYD29P1N.A2000057.h12v07.005.2006252061042.hdf. Refer to Table 1 for an explanation of the variables used in the MODIS file naming convention.
|Type of product|
|Year of data acquisition|
|Day of year of data acquisition (day 57)|
|Horizontal tile number and vertical tile number. For further information, see the Grid Description section in this document.|
|Year of production (2006)|
|Day of year of production (day 252)|
|Hour/minute/second of production in GMT (06:10:42)|
|HDF-EOS data format|
Data files are typically between 0.05 -1.5 MB using HDF compression.
Note: New in V005, MYD29P1N data files now use HDF data compression. The extent to which compression reduces the file size varies from image to image, but generally it is a factor of 5 or more.
Coverage is global; however, only ocean granules are produced. A ±55 degree scanning pattern at 705 km altitude achieves a 2330 km swath with global coverage every one to two days. The following resources can help you select and work with MYD29P1N tiles:
The local equatorial crossing time of the Aqua satellite is approximately 1:30 p.m. in an ascending node with a sun-synchronous, near-polar, circular orbit.
Gridded resolution is 1 km.
MYD29P1N data are gridded to the NSIDC EASE-Grid in a Lambert Azimuthal Equal Area projection. Please review the All About EASE-Grid document for general information on the EASE-Grid.
The following Web sites provide links to the software tools that reformat, re-project, and perform stitching/mosaicing, and subsetting operations on HDF-EOS objects:
In the polar aspect of the Lambert Azimuthal Equal Area Projection, all meridians are straight lines and all parallels are circles with either the north or south pole as the center of the projection (Snyder 1987). Areas on the map are shown in true proportion to the same areas on the Earth. Directions are true only from the pole. Scale decreases gradually away from the pole. Distortion of shapes increases away from the pole. Any straight line drawn through the pole is on a great circle. Finally, the map is equal area but neither conformal, perspective, nor equidistant (USGS 2003). Specific parameters are listed in Table 2.
|North (90° latitude, 0° longitude)
South (-90° latitude, 0° longitude)
|North (0° longitude, oriented vertically at bottom)
South (0° longitude, oriented vertically at top)
Upper left corner point (m)
Lower right corner point (m)
True scale (m)
MYD29P1N data are gridded to Polar EASE-Grid tiles, each 951 x 951 pixels in size, which corresponds to approximately 954 km by 954 km at a resolution of 1002.7010 m per pixel.
The following maps show tile locations for MYD29P1N. Click on the thumbnail images to see the full-resolution images.
See the following documents for bounding coordinate information for each tile:
MODIS data extends from 04 July 2002 to present.
Over the course of the Aqua mission, there have been a number of anomalies that have resulted in dropouts in the data. If you are looking for data for a particular date or time and can not find it, please visit the MODIS/Aqua Data Outages Web page.
Temporal resolution is daily. The time between repeat coverage of a given point on the earth depends on latitude with the most frequent coverage occurring near the poles. Areas pole ward of ±30 degrees latitude are observed at least daily.
In the IST field, pixels classified as cloud free ocean contain an IST value in kelvins, and pixel values are scaled by 100 for all classes. The IST algorithm was designed for sea ice; however, IST values are provided for all ocean areas that are not classified as cloud.
Refer to the MOD29P1N and MYD29P1N Local Sea Ice Attributes, Version 5 document for a key to the meaning of the scaled values in the Ice Surface Temperature Field, and the Ice Surface Temperature Pixel QA Field.
For information regarding the theory for sea ice mapping and ice suface temperature retrieval, please see the Theory of Measurements section in the MODIS/Terra Sea Ice Extent 5-Min L2 Swath 1km, Version 5 guide document (MOD29).
For more information regarding the processing steps used as the input to this data set, please see the Processing Steps section in the MODIS/Terra Sea Ice Extent 5-Min L2 Swath 1km, Version 5 guide document (MOD29).
MYD29P1N is generated from a temporary product (MYD29PGN) which was created by mapping each night pixel in each of the MYD29 products acquired over a 24 hour period to their earth locations on the Lambert Azimuthal Equal Area projection. As a result, multiple observations are associated with each cell in the grid. For each grid cell, the algorithm that creates the MYD29P1N product, then selects the observation that is nearest nadir and has the greatest coverage of the grid cell using a weighted scoring function. The observation with the highest score is selected as the observation for that grid cell (Riggs, Hall, and Salomonson, 2006).
IST is the primary variable of interest in this data set.
As with any upper level product, the characteristics of or anomalies in input data may carry through to the output data product. The following products are input to MYD29P1N:
Because sea ice varies in concentration from near zero to 100 percent, it can show temperatures within a pixel due to sub-pixel effects. Melt ponds and leads in the summer months affect the emissivity of the ice surface; therefore, affecting the calculation of ice surface temperature (Hall et al. 1998). The presence of even very thin clouds or fog within the field of view prevent obtaining an accurate IST (Hall et al. 2004). Recent studies in the arctic and antarctic have shown that under clear sky conditions the IST are accurate to better than ± 1.5 over the 245-270 K range for all ice types (Hall et al. 2004) (Scambos, Haran, and Massom).
All MODIS/Aqua sea ice products are considered validated or at stage 2 meaning that accuracy has been assessed over a widely distributed set of locations and time periods using several ground-truth and validation campaigns.
Quality indicators for MODIS sea ice data can be found in the following three places:
These quality indicators are generated during production or in post-production scientific and quality checks of the data product. For more information on local and global attributes, go to one of the following links:
The AutomaticQualityFlag is automatically set according to conditions for meeting data criteria in the sea ice algorithm. In most cases, the flag is set to either Passed or Suspect, and in rare instances, it may be set to Failed. Suspect means that a significant percentage of the data were anomalous and that further analysis should be done to determine the source of anomalies. The AutomaticQualityFlagExplanation contains a brief message explaining the reason for the setting of the AutomaticQualityFlag. The ScienceQualityFlag and the ScienceQualityFlagExplanation maybe updated after production, either after an automated QA program is run or after the data product is inspected by a qualified scientist. Content and explanation of this flag are dynamic so it should always be examined if present in the external metadata file. A sampling of products will be inspected. Random sampling or support of specific events, such as field campaigns, may also be conducted.
The IST Spatial QA data field provides additional information on algorithm results for each pixel within a spatial context, and is used as a measure of usefulness for sea ice data. QA data are stored as coded integer values and tells if algorithm results were good or not, or if other defined conditions were encountered (Riggs, Hall, and Salomonson 2003).
See the MODIS Land Quality Assessment Web page for further details.
The MODIS instrument provides 12-bit radiometric sensitivity in 36 spectral bands ranging in wavelength from 0.4 µm to 14.4 µm. Two bands are imaged at a nominal resolution of 250 m at nadir, five bands at 500 m, and the remaining bands at 1000 m. A ±55 degree scanning pattern at a 705 km altitude achieves a 2330 km swath with global coverage every one to two days.
The scan mirror assembly uses a continuously rotating double-sided scan mirror to scan ±55 degrees, driven by a motor encoder built to operate 100 percent of the time throughout the six year instrument design life. The optical system consists of a two-mirror off-axis afocal telescope which directs energy to four refractive objective assemblies: one each for the visible, near-infrared, shortwave-infrared, and longwave-infrared spectral regions (MODIS Web 2003).
|Orbit||705 km, 1:30 p.m. ascending node (Aqua), sun-synchronous, near-polar, circular|
|Scan Rate||20.3 rpm, cross track|
|Swath Dimensions||2330 km (cross track) by 10 km (along track at nadir)|
|Telescope||17.78 cm diameter off-axis, afocal (collimated) with intermediate field stop|
|Size||1.0 x 1.6 x 1.0 m|
|Power||162.5 W (single orbit average)|
|Data Rate||10.6 Mbps (peak daytime); 6.1 Mbps (orbital average)|
|Spatial Resolution||250 m (bands 1-2)
500 m (bands 3-7)
1000 m (bands 8-36)
|Design Life||Six years|
For information on the 36 spectral bands provided by the MODIS instrument, see the Spectral Bands Table.
The MODIS scan mirror assembly uses a continuously rotating double-sided scan mirror to scan ±55 degrees with a 20.3 rpm cross track. The viewing swath is 10 km along track at nadir, and 2330 km cross track at ±55 degrees.
MODIS instruments were built to NASA specifications by Santa Barbara Remote Sensing, a division of Raytheon Electronics Systems.
MODIS has a series of on-board calibrators that provide radiometric, spectral, and spatial calibration of the MODIS instrument. The blackbody calibrator is the primary calibration source for thermal bands between 3.5 µm and 14.4 µm, while the Solar Diffuser (SD) provides a diffuse, solar-illuminated calibration source for visible, near-infrared, and shortwave-infrared bands. The Solar Diffuser Stability Monitor (SDSM) tracks changes in the reflectance of the SD with reference to the sun so that potential instrument changes are not incorrectly attributed to changes in this calibration source. The Spectroradiometric Calibration Assembly (SRCA) provides additional spectral, radiometric, and spatial calibration.
MODIS uses the moon as an additional calibration technique and for tracking degradation of the SD, by referencing the illumination of the moon since the moon's brightness is approximately the same as that of the Earth. Finally, MODIS deep space views provide a photon input signal of zero, which is used as a point of reference for calibration (MODIS Web 2003).
MODIS is a key instrument aboard the Aqua satellite, one component of NASA's Earth Observing System (EOS). The EOS includes a series of satellites, a data system, and the world-wide community of scientists supporting a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans that together enable an improved understanding of the Earth as an integrated system. MODIS is playing a vital role in the development of validated, global, and interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment. (NASA's MODIS Web Site 2006), (NASA's Aqua Web Site 2006), and (NASA's EOS Web Site 2006)
Within this overall context, the objectives of the MODIS snow and ice team are to develop and implement algorithms that map snow and ice on a daily basis, and provide statistics of the extent and persistence of snow and ice over eight-day periods. Data at 500 m resolution enables sub-pixel snow mapping for use in regional and global climate models. A study of sub grid-scale snow-cover variability is expected to improve features of a model that simulates Earth radiation balance and land-surface hydrology (Hall et al. 1998).
The MODIS sensor contains a system whereby visible light from the earth passes through a scan aperture and into a scan cavity to a scan mirror. The double-sided scan mirror reflects incoming light onto an internal telescope, which in turn focuses the light onto four different detector assemblies. Before the light reaches the detector assemblies, it passes through beam splitters and spectral filters that divide the light into four broad wavelength ranges. Each time a photon strikes a detector assembly, an electron is created. Electrons are collected in a capacitor where they are eventually transferred into the preamplifier. Electrons are converted from an analog signal to digital data, and down linked to ground receiving stations (MODIS Web 2003).
The EOS Ground System (EGS) consists of facilities, networks, and systems that archive, process, and distribute EOS and other NASA earth science data to the science and user community. For example, ground stations provide space to ground communication. The EOS Data and Operations System (EDOS) processes telemetry from EOS spacecraft and instruments to generate Level-0 products, and maintains a backup archive of Level-0 products (ESDIS 1996). The NASA Goddard Space Flight Center: MODIS Adaptive Processing System (MODAPS) Services is currently responsible for generation of Level-1A data from Level-0 instrument packet data. These data are then used to generate higher level MODIS data products, including MYD29. MODIS snow and ice products are archived at the NSIDC Distributed Active Archive Center (DAAC) and distributed to EOS investigators and other users via external networks and interfaces (MODIS Web 2003). Data are available to the public through a variety of interfaces.
Hall, Dorothy K., J. L. Foster, D. L. Verbyla, A. G. Klein, and C. S. Benson. 1998. Assessment of Snow Cover Mapping Accuracy in a Variety of Vegetation Cover Densities in Central Alaska. Remote Sensing of the Environment 66:129-137.
Hall, Dorothy K., Jeffrey R. Key, Kimberly A. Casey, George A. Riggs, and Donald Cavalieri. May 2004. Sea Ice Surface Temperature Product From MODIS. IEEE Transactions on Geoscience and Remote Sensing 42:5.
Hall, Dorothy K., George A. Riggs, and Vincent V. Salomonson. 1995. Development of Methods for Mapping Global Snow Cover Using Moderate Resolution Imaging Spectroradiometer (MODIS). Remote Sensing of the Environment 54(2):127-140.
Hall, Dorothy K., George A. Riggs, and Vincent V. Salomonson. September 2001. Algorithm Theoretical Basis Document (ATBD) for the MODIS Snow-, Lake Ice- and Sea Ice-Mapping Algorithms. Greenbelt, MD: Goddard Space Flight Center. <http://modis-snow-ice.gsfc.nasa.gov/?c=atbd&t=atbd> .
Markham, B. L. and J. L. Barker. 1986. Landsat MSS and TM Post-Calibration Dynamic Ranges, Exoatmospheric Reflectances and At-Satellite Temperatures. EOSAT Technical Notes 1:3-8.
MODIS Science and Instrument Team. MODIS Web. July 2003. <http://modis.gsfc.nasa.gov/> Accessed October 2000.
Riggs, George A., Dorothy K. Hall, and Vincent V. Salomonson. December 2006. MODIS Sea Ice Products User Guide to Collection 5. http://nsidc.org/data/docs/daac/modis_v5/dorothy_ice_doc.pdf
Riggs, George A., Dorothy K. Hall, and S. A. Ackerman. 1999. Sea Ice Extent and Classification Mapping With the Moderate Resolution Imaging Spectroradiometer Airborne Simulator. Remote Sensing of the Environment 68:152-163.
United States Geological Survey. 2003. Lambert Azimuthal Equal Area Map Projections. http://erg.usgs.gov/isb/pubs/MapProjections/projections.html#lambert. Accessed April 2007.
Wiscombe, W. J. and S. G. Warren. 1980. A Model for the Spectral Albedo of Snow I: Pure Snow. Journal of the Atmospheric Sciences 37:2712-2733.
The following acronyms and abbreviations are used in this document:
|ATBD||Algorithm Theoretical Basis Document|
|AVHRR||Advanced Very High Resolution Radiometer|
|DAAC||Distributed Active Archive Center|
|EASE-Grid||Equal Area Scalable Earth Grid|
|EDOS||EOS Data and Operations System|
|EGS||EOS Ground System|
|EOS||Earth Observing System|
|EOSDIS||Earth Observing System Data and Information System|
|ESDIS||Earth Science Data and Information System|
|FTP||File Transfer Protocol|
|GMT||Greenwich Mean Time|
|GSFC||Goddard Space Flight Center|
|HDF-EOS||Hierarchical Data Format - Earth Observing System|
|IST||Ice Surface Temperature|
|LP DAAC||Land Processes Distributive Active Archive Center|
|MCST||MODIS Characterization Support Team|
|MODIS||Moderate Resolution Imaging Spectroradiometer|
|MODLAND||MODIS Land Discipline Group|
|NASA||National Aeronautics and Space Administration|
|NCSA||National Center for Supercomputing Applications|
|NSIDC||National Snow and Ice Data Center|
|SDP||Science Data Processing|
|SDS||Science Data Set|
|SDSM||Solar Diffuser Stability Monitor|
|SRCA||Spectroradiometric Calibration Assembly|