On Wednesday, January 25 from 9:00 a.m. to 12:00 p.m. (USA Mountain Time) AMSR-E, Aquarius, IceBridge, ICESat/GLAS, MODIS, NISE, and SMAP data will not be available for ordering due to system maintenance.
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MODIS/Terra Snow Cover 8-Day L3 Global 0.05Deg CMG, Version 6
This data set reports the maximum percentage of snow-covered land during an eight-day period in 0.05 degree (approx. 5 km) resolution Climate Modeling Grid (CMG) cells. Percentages are computed from snow cover observations in the MODIS/Terra Snow Cover 8-Day L3 Global 500m Grid (MOD10A2) data set. Persistent cloud cover is also reported.
Changes for Version 6 include:
- Fractional Snow Cover (FSC) previously used as input to this data set has been replaced by Normalized Difference Snow Index (NDSI) snow cover;
- The Eight_Day_CMG_Confidence_Index variable has been replaced with Eight_Day_CMG_Clear_Index.
|Temporal Resolution:||8 day|
|Data Contributor(s):||Miguel Román, Dorothy Hall, George Riggs|
|Metadata XML:||View Metadata Record|
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.Hall, D. K. and G. A. Riggs. 2016. MODIS/Terra Snow Cover 8-Day L3 Global 0.05Deg CMG, Version 6. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/MODIS/MOD10C2.006. [Date Accessed].
Detailed Data Description
This data set is generated from Normalized Difference Snow Index (NDSI) snow cover. Snow covered land typically has a very high reflectance in visible bands and very low reflectance in the shortwave infrared; the NDSI reveals the magnitude of this difference. MOD10A2 eight-day maximum snow extent observations at 500 m resolution are mapped into 0.05 degrees (approx. 5 km) CMG cells, binned by observation type (e.g. snow, snow-free land, cloud, etc.), and tallied. Snow and cloud cover percentages are generated by computing the ratio of snow or cloud observation counts to the total number of land observations mapped into the CMG cell.
Data files are provided in HDF-EOS2 (V2.17). JPEG browse images are also available.
HDF-EOS (Hierarchical Data Format - Earth Observing System) is a self-describing file format based on HDF that was developed specifically for distributing and archiving data collected by NASA EOS satellites. For more information, visit the HDF-EOS Tools and Information Center.
Example File Name:
Refer to Table 1 for descriptions of the file name variables listed above.
|A||Acquisition date follows|
|DDD||Day of year, first day of 8-day compositing period|
|VVV||Version (Collection) number|
|ddd||Production day of year|
|hhmmss||Production hour/minute/second in GMT|
|.hdf||HDF-EOS formatted data file|
Note: Data files contain important metadata including global attributes that are assigned to the file and local attributes like coded integer keys that provide details about the data fields. In addition, each HDF-EOS data file has a corresponding XML metadata file (.xml) which contains some of the same internal metadata as the HDF-EOS file plus additional information regarding user support, archiving, and granule-specific post-production. For detailed information about MODIS metadata fields and values, consult the MODIS Snow Products Collection 6 User Guide.
Data files are approximately 6 MB.
Coverage is global. Terra's sun-synchronous, near-polar circular orbit is timed to cross the equator from north to south (descending node) at approximately 10:30 A.M. local time. Complete global coverage occurs every one to two days (more frequently near the poles). The following sites offer tools that track and predict Terra's orbital path:
- Daily Terra Orbit Tracks, Space Science and Engineering Center, University of Wisconsin-Madison
- NASA LaRC Satellite Overpass Predictor (includes viewing zenith, solar zenith, and ground track distance to specified lat/lon)
MODIS CMG data sets are produced in a Geographic Lat/Lon projection. This simple projection treats geographical longitude and latitude degrees as if they were x- and y-coordinates in a plane. Figure 1 shows the geographical lat/lon projection known as Plate Carrée, which plots longitude and latitude degrees as coordinates on the x and y axes, respectively:
The MODIS CMG consists of 7200 columns by 3600 rows. Each cell has a resolution of 0.05 degrees (approximately 5 km). The upper-left corner of the upper-left cell is -180.00 degrees longitude, 90.00 degrees latitude. The lower-right corner of the lower right cell is -180.00 degrees longitude, -90.00 degrees latitude. For additional details about the MODIS Climate Modeling Grid, see the NASA MODIS Lands | MODIS Grids Web page.
The following resources can help you select and work with gridded MODIS data:
MODIS Terra data are available from 24 February 2000 to present. However, because the NDSI depends on visible light, data are not produced when viewing conditions are too dark. In addition, anomalies over the course of the Terra mission have resulted in minor data outages. If you cannot locate data for a particular date or time, check the MODIS/Terra Data Outages Web page.
This data set is generated from observations acquired during successive eight-day periods. Each year comprises 46 periods; the first period begins on the first day of the year and the last period begins on day 361 and extends either two or three days into the following year (leap years vs non-leap years). Table 3 lists the days covered by each period:
|¹Includes 2 or 3 days from the next year.|
Snow cover percentage, cloud cover percentage, and data quality metrics are written to the HDF-EOS formatted data files as Scientific Data Sets (SDSs) according to the HDF Scientific Data Set Data Model. The SDSs for this data set are described in the following table:
|Scientific Data Set||Description|
Percentage of snow cover observations plus other results. Value = the ratio of MOD10A2, 500 m snow cover observations to the total number of land observations mapped into the CMG cell. Possible values are:
Note: Antarctica deliberately mapped as snow. Snow cover percentage set to 100.
Percentage of input cells obscured by clouds plus other results. Value = the ratio of MOD10A2, 500 m cloud observations to the total number of land observations mapped into the CMG cell. Note: MOD10A2 cells only report cloud if the cell was obscured by clouds on all eight days of the period. Possible values are:
Note: Antarctica deliberately mapped as snow. Value set to 252 (masked).
Percentage of non-cloud input cells plus other results. Value = the ratio of MOD10A1, 500 m non-cloud observations to the total number of land observations mapped into the CMG cell. Low values indicate low confidence in the snow cover fraction due to extensive, persistent cloud cover. Note: the MOD10A2 algorithm infers a surface condition if any clear-sky views are available. Cells are only filled as cloud if they were obscured by clouds on all eight days of the period. A clear index = 0 does not indicate cloud-free conditions, but only that none of the MOD10A2 input cells were completely cloud obscured. Possible values are:
Note: Antarctica deliberately mapped as snow. Clear index set to 100 (clear).
Basic QA plus other results. Value = good or other quality, based on counts of MOD10A2, 500 m basic QA values mapped into the CMG cell. Values of best (0), good (1), and ok (2) are counted as good quality (0); poor (3) and other (4) are counted as other (1). CMG cells report the greater of the two counts. Possible values are:
Software and Tools
The following sites can help you identify the right MODIS data for your study:
- NASA's Earth Observing System Data and Information System | Near Real-Time Data
- NASA Goddard Space Flight Center | MODIS Land Global Browse Images
The following resources are available to help users work with MODIS data:
- The MODIS Reprojection Tool allows users to read data files in HDF-EOS format, specify geographic subsets or science data sets as input to processing, perform geographic transformations to different coordinate systems and cartographic projections, and write output files to formats other than HDF-EOS.
- The HDF-EOS to GeoTIFF Conversion Tool (HEG) can reformat, re-project, and perform stitching/mosaicing and subsetting operations on HDF-EOS objects.
- HDFView is a simple, visual interface for opening, inspecting, and editing HDF files. Users can view file hierarchy in a tree structure, modify the contents of a data set, add, delete and modify attributes, and create new files.
- The MODIS Conversion Toolkit (MCTK) plug-in for ENVI can ingest, process, and georeference every known MODIS data set, including products distributed with EASE-Grid projections. The toolkit includes support for swath projection and grid reprojection and comes with an API for large batch processing jobs.
- NSIDC's Hierarchical Data Format | Earth Observing System (HDF-EOS) Web page contains information about HDF-EOS, plus tools to extract binary and ASCII objects, instructions to uncompress and geolocate HDF-EOS data files, and links to obtain additional HDF-EOS resources.
Data Acquisition and Processing
MODIS is a key instrument onboard NASA's Earth Observing System (EOS) Aqua and Terra satellites. The EOS includes satellites, a data collection system, and the world-wide community of scientists supporting a coordinated series of polar-orbiting and low inclination satellites that provide long-term, global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans. As a whole, EOS is improving our understanding of the Earth as an integrated system. MODIS plays a vital role in developing validated, global, and interactive Earth system models that can predict global change accurately enough to assist policy makers in making sound decisions about how best to protect our environment. For more information, see:
The MODIS sensor contains a system whereby visible light from 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 generated. 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 downlinked to ground receiving stations. 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.
The MODIS science team continually seeks to improve the algorithms used to generate MODIS data sets. Whenever new algorithms become available, the MODIS Adaptive Processing System (MODAPS) reprocesses the entire MODIS collection—atmosphere, land, cryosphere, and ocean data sets—and a new version is released. Version 6 (also known as Collection 6) is the most recent version of MODIS snow cover data available from NSIDC. NSIDC strongly encourages users to work with the most recent version.
Consult the following resources for more information about MODIS Version 6 data, including known problems, production schedules, and future plans:
MOD10C2 is generated using a version of the MOD10C1 algorithm that has been adapted to utilze MOD10A2 eight-day data as input. The algorithm maps 500 m, MOD10A2 observations into 0.05° (approx. 5 km) CMG cells and bins and counts each observation by type, for example snow cover, cloud cover, and snow-free land. Snow and cloud cover percentage are computed as the ratio of the number of snow or cloud observations to the total number of land observations mapped into the CMG cell. These ratios are expressed as percentages in the SDSs. Because MOD10A2 reports snow cover if snow is found in a cell for any day in the period, the MOD10C2 snow map represents the maximum snow cover extent in each CMG cell during the eight-day period.
The snow map also includes lake ice coverage. The number of inland water body observations are counted using the water flag in the MOD10A1
NDSI_Snow_Cover_Algorithm_Flags_QA SDS. If the water body has more lake ice observations than open water, a value of 107 is set in the output.
A CMG-specific, 0.05 degrees land mask is used with the binning algorithm. This land mask was derived from the University of Maryland 1km Land Cover data set. CMG cells which contain 12 percent or greater land are considered land and analyzed; cells with less than 12 percent land are considered ocean. This threshold was selected as a balance between remaining sensitive enough to map snow along coasts and minimizing snow detection errors in these regions.
Persistent cloud cover—eight consecutive days of cloud obscuration—is recorded in the
Eight_Day_CMG_Cloud_Obscured SDS. This array reports the fraction of 500 m, MOD10A2 cloud observations to the total number of land observations mapped into the CMG cell. Because MOD10A2 only reports cloud in cells that were obscured for all eight days of the period, the
Eight_Day_CMG_Cloud_Obscured SDS represents the fraction of 500 m input cells whose surface was unobservable for the entire period.
Viewing conditions in the CMG cell, relative to persistent cloud cover, can be inferred from the eight-day Clear Index (CI). This value reports the percentage of all MOD10A2 land observations mapped into the cell that were not obscured by clouds for eight consecutive days, thus providing an estimate of the amount of land surface that was observable on at least one day of the period. Low values indicate low confidence in the snow cover fraction due to extensive, persistent cloud cover. A high CI indicates that relatively few input cells were completely obscured. Users should note, however, that the MOD10A2 algorithm infers a surface condition if any clear-sky views are available for a cell. A determination of snow or snow-free land, for example, can be based on anywhere from 1 - 8 days of observations, and partial cloud-obscuration is not tracked in this data set. As such, a clear index = 0 does not indicate that clouds were not present, but only that no MOD10A2 input cells were blocked from view by clouds for eight consecutive days. For more details about the MOD10A2 snow cover algorithm, see Derivation Techniques and Algorithms in the MOD10A2 documentation.
Polar darkness extent is based on the latitude of the CMG cell nearest the equator that is full of night observations. All CMG cells poleward of that latitude are filled as night. This approach was adopted so that a neat demarcation of night and day is visible in the CMG.
Antarctica has been masked as 100 percent snow covered to improve the visual quality of data. As such, this data set cannot be used to map snow in Antarctica. For users who wish to evaluate Antarctica, the MOD10_L2 data set offers a higher resolution and contains more data and information about accuracy and error.
See the MODIS | Data Versions page for the history of MODIS snow and sea ice data versions.
The NDSI technique has proven to be a robust indicator of snow cover. Numerous investigators have utilized MODIS snow cover data sets and reported accuracy in the range of 88 percent to 93 percent. The daily CMG offers a synoptic view of maximum snow cover extent during eight-day windows plus persistent cloud cover and optionally the clear index. Snow cover and cloud cover are written to separate data arrays so that users can consider how best to interpret and use the snow cover map and whether to combine it with the cloud cover data.
Snow commission errors, in general the most apparent type of error, are typically associated with cloud cover and may appear on any day in conjunction with clouds. These errors may spread in spatial extent over the course of eight days and manifest as low-percentage, maximum snow fractions. Based on experience, a majority of the most probable snow commission errors can be filtered by interpretting snow cover with a value of NDSI < 20 as snow-free. However, this approach may mask out actual snow along the periphery of snow-covered regions.
The algorithm for this data set does not screen for errors; QA values are only provided to indicate whether the input data were valid or invalid or if a special condition like polar darkness was encountered. Users should analyze the snow cover map and choose for themselves an interpretation that minimizes the most probable errors and yet applies the data in a reasonable manner to track maximum snow cover extent.
Snow errors are ultimately propagated from the first data set in the MODIS snow suite of products, MOD10_L2, into MOD10A1, MOD10A2, and then this data set. For more detail about potential error sources in the input data, see the Derivation Techniques and Algorithms section in the MOD10_L2 documentation and the MODIS Snow Products Collection 6 User Guide.
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 an altitude of 705 km 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, and is 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, short- and mid-wavelength infrared, and long wavelength infrared spectral regions.
The MODIS instruments on the Terra and Aqua space vehicles were built to NASA specifications by Santa Barbara Remote Sensing, a division of Raytheon Electronics Systems. Table 3 contains the instruments' technical specifications:
|Orbit||705 km altitude, 10:30 A.M. descending node (Terra), 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 m x 1.6 m 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||6 years|
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 short wave infrared bands. The Solar Diffuser Stability Monitor 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 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.
For additional details about the MODIS instruments, see NASA's MODIS | About Web page.
References and Related Publications
Contacts and Acknowledgments
Miguel O. Román
NASA Goddard Space Flight Center
Greenbelt , MD 20771
Dorothy K. Hall
NASA Goddard Space Flight Center
Greenbelt, MD 20771
George A. Riggs
NASA Goddard Space Flight Center
Science Systems and Applications, Inc.
Greenbelt, MD 20771
DOCUMENT CREATION DATE
DOCUMENT REVISION DATES