Documentation for MEaSUREs Northern Hemisphere State of Cryosphere Weekly 100km EASE-Grid 2.0, Version 1

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Detailed Data Description

This data set utilizes three variables to represent Northern Hemisphere snow cover and sea ice extent from 2 January 1979 through 31 December 2012. These variables report:

Format

Data files are formatted in Network Common Data Form, Version 4 (NetCDF-4) (.nc) following version 1.6 of the Climate and Forecast (CF) metadata conventions. For more information about working with NetCDF formatted data, visit the UCAR Unidata Network Common Data Form (NetCDF) Web site.

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File and Directory Structure

Data are available on the HTTPS site in the https://n5eil01u.ecs.nsidc.org/MEASURES/NSIDC-0535.001/ directory. Within this there are folders labeled by year that contain all the weekly data files for that year.

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File Naming Convention

This section explains the file naming convention used for this data set with an example.

Example File Name: socw100e2_19790102_19790108_v01r01.nc

socwxxxe2_YYYYMMDD_yyyymmdd_v01r01.nc

Refer to Table 1 for the valid values for the file name variables listed above.

Table 1. File Naming Convention
Variable Description
soc State of Cryosphere
w Weekly
xxx Resolution (km)
e2 EASE-Grid 2.0
YYYYMMDD First day of week (year, month, and day)
yyyymmdd Last day of week (year, month, and day)
v01r01 Version 1.1
.nc netCDF-formatted file
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File Size

Data files are approximately 160 KB. The entire data set is approximately 275 MB.

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Spatial Coverage

Northern Hemisphere

Southernmost Latitude: 0.0°
Northernmost Latitude: 90.0°
Westernmost Longitude: -180.0°
Easternmost Longitude: 180.0°

Spatial Resolution

100 km

Projection and Grid Description

Data are provided in the 100 km Northern Hemisphere Equal Area Scalable Earth Grid 2.0 (EASE-Grid 2.0). Grid dimensions are 180 x 180. For a complete description of EASE-Grid 2.0, visit NSIDC's EASE-Grid 2.0 Format Description page.

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Temporal Coverage

2 January 1979 - 31 December 2012

Temporal Resolution

This data set consists of weekly snow and sea ice cover. Each week runs from Tuesday through the following Monday.

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Parameter or Variable

Snow cover, sea ice cover, and status of melt onset are the primary parameters in this data set. Data files also include latitude and longitude arrays that specify the center of each 100 km EASE-Grid 2.0 cell, coordinate system parameters, and the number of days since the beginning of the data record.

Variable Description

Data files contain the variables listed in Table 2.

Table 2. Variable Names and Descriptions
Variable Name Description Dimensions Data Type
merged_snow_and_sea_ice_extent Merged snow and sea ice cover 180 x 180 byte (signed)
status_of_melt_onset Status of melt onset for Greenland and Arctic sea ice 180 x 180 byte (signed)
snow_agreement_with_cdr Indicates whether MW snow cover agrees with SCE CDR¹ 180 x 180 byte (signed)
latitude Latitude at the center of each 100 km EASE-Grid 2.0 cell 180 x 180 float²
longitude Longitude at the center of each 100 km EASE-Grid 2.0 cell 180 x 180 float²
cols x coordinate, center of 100 km EASE-Grid 2.0 cell (m from origin) 1 x 180 int
rows y coordinate, center of 100 km EASE-Grid 2.0 cell (m from origin) 180 x 1 int
coord_system EASE-Grid 2.0 grid and projection parameters — char
time Days since 12/31/1978 — int
¹Passive microwave (MW) derived snow cover; NOAA/NCDC Northern Hemisphere Snow Cover Extent Climate Data Record (SCE CDR).
²32-bit single precision floating point. Fill value for grid corners = -999.

Parameter Range

The merged_snow_and_sea_ice_extent, status_of_melt_onset, and snow_agreement_with_cdr variables, refer to Table 3 for more information, use coded integers to indicate the location of snow and sea ice, the status of melt onset on the Greenland Ice Sheet and Arctic sea ice, and whether snow cover derived from passive microwave (MW) brightness temperatures agrees with the NOAA/NCDC Northern Hemisphere Snow Cover Extent Climate Data Record (SCE CDR). The merged snow and sea ice extent variable also indicates the location of the pole hole.

The following tables contain keys to the values stored in this data set's snow and sea ice cover variables.

Table 3. Key for merged_snow_and_sea_ice_extent
Value Description

10

Snow covered land

20

Snow free land

30

Sea ice cover

40

Open water

90

Missing

91

Pole hole

-99

Fill value for grid corners

Table 4. Key for status_of_melt_onset
Value Description

0

No melt data

51

Melt onset begins prior to file date

52

Melt onset begins on file date

53

Melt onset begins on a future date

-99

Fill value for grid corners

Table 5. Key for snow_agreement_with_cdr
Value Description

0

MW does not agree with SCE CDR snow cover¹

1

MW agrees with SCE CDR¹

90

No comparison

-99

Fill value for grid corners
¹Passive microwave (MW) derived snow cover; NOAA/NCDC Northern Hemisphere Snow Cover Extent Climate Data Record (SCE CDR).
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Software and Tools

Software and Tools

Unidata at the University Corporation for Atmospheric Research maintains an extensive list of freely available Software for Manipulating or Displaying NetCDF Data.

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Data Acquisition and Processing

The following sections describe how each of the variables in this data set were generated. All variables were reconciled with EASE-Grid 2.0 Land-Ocean-Coast-Ice (LOCI) masks obtained from the EASE-Grid 2.0 Land-Ocean-Coastline-Ice Masks Derived from Boston University MODIS/Terra Land Cover Data data set.

Merged Snow and Sea Ice Cover

Processing Steps

Snow cover was obtained directly from the weekly_climate_data_record_snow_cover_extent variable in the MEaSUREs Northern Hemisphere Terrestrial Snow Cover Extent Weekly 100km EASE-Grid 2.0 data set. Arctic sea ice extent was obtained from the sea_ice_cover variable in MEaSUREs Arctic Sea Ice Characterization Daily 25km EASE-Grid 2.0. When these variables were reconciled with their corresponding 100 km and 25 km EASE-Grid 2.0 LOCI masks, changes to the original data were stored using separate codes. For example, the snow cover extent variable contains different values for "snow covered land" and "ocean converted to snow covered land." These values were combined for the purposes of this data set.

The merged_snow_and_sea_ice_extent variable was generated as follows:

  1. Weekly sea ice maps were created from daily files by selecting Monday's value as the representative value for each cell, each week. If Monday's data was missing, Sunday's was used instead. If neither day was available, the value for that cell was filled as missing. This approach—using data weeks that run from Tuesday through the following Monday—was adopted to match the convention used by snow cover source data.
  2. Weekly sea ice maps were re-gridded from 25 km to 100 km using Mapx and compared with the 100 km EASE-Grid 2.0 LOCI mask. In cases where land mask mismatches converted a pixel from land to ocean, the discrepancy was reconciled by applying a 3x3 moving box filter through several passes. On the first pass, the filter examined the eight cells surrounding the converted cell and assigned it as sea ice cover if more than 50 percent contained ice. Otherwise the cell was assigned the value for open water. Subsequent iterations reassigned pixels if at least 33 percent of the surrounding cells were ice covered. Iterations were continued until no more changes were found.
  3. Values for ocean and land from the 100 km EASE-Grid 2.0 LOCI mask were written to an intermediate array.
  4. Values for snow covered land and ocean converted to snow covered land were written to the array using the coding scheme in Table 3.
  5. Values for sea ice were written to the array using the coding scheme in Table 3.
  6. Data from the intermediate array were written to the merged_snow_and_sea_ice_extent NetCDF variable.

For details about the snow cover source data, refer to the Data Acquisition and Processing section in MEaSUREs Northern Hemisphere Terrestrial Snow Cover Extent Weekly 100km EASE-Grid 2.0. For details about the Arctic sea ice cover source data, refer to the Data Acquisition and Processing section in MEaSUREs Arctic Sea Ice Characterization Daily 25km EASE-Grid 2.0.

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Status of Melt Onset

Processing Steps

Status of melt onset over Arctic sea ice was derived from the status_of_melt_onset variable in MEaSUREs Arctic Sea Ice Characterization Daily 25km EASE-Grid 2.0. Status of melt onset over Greenland was calculated at the University of Georgia using melt onset dates from MEaSUREs Greenland Surface Melt Daily 25km EASE-Grid 2.0. These variables were reconciled with the 25 km EASE-Grid 2.0 LOCI mask when generated for their respective data sets.

Status of melt onset is created by assigning integer values which indicate whether the cell has a melt onset date prior to the current day, on the current day, or later in the year. Cells with no melt onset date are filled with 0 (see Table 5). Melt onset is only calculated for days 61-245 of the year. This range corresponds to 2 March through 2 September in non-leap years and 1 March through 1 September in leap years. Days that lie outside this range are filled with 0.

The combined Arctic-Greenland status of melt onset variable for this data set was generated as follows:

  1. Weekly maps were created from daily files by selecting Monday's value as the representative value for each cell, each week. If Monday's data was missing, Sunday's was used instead. If neither day was available, the value for that cell was filled as missing. This approach—using data weeks that run from Tuesday through the following Monday—was adopted to match the merged snow and sea ice cover variable described in the preceding section.
  2. Weekly status of melt onset maps over Arctic sea ice and Greenland were regridded to 100 km EASE-Grid 2.0 using Mapx.
  3. Values for status of melt onset over Arctic sea ice and Greenland were written to an intermediate array using the coding scheme in Table 4.
  4. The data were written to the status_of_melt_onset NetCDF variable.

For details about the Arctic Sea Ice and Greenland source data were derived, refer to the Data Acquisition and Processing section in MEaSUREs Arctic Sea Ice Characterization Daily 25km EASE-Grid 2.0 and MEaSUREs Greenland Surface Melt Daily 25km EASE-Grid 2.0.

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Snow Agreement with SCE CDR

Processing Steps

The snow_agreement_with_cdr variable was calculated from the MEaSUREs Northern Hemisphere Terrestrial Snow Cover Extent Weekly 100km EASE-Grid 2.0 data set, which contains both SCE CDR and MW-derived snow cover. This data set also contains the variable merged_snow_cover_extent, which specifies for each cell whether the SCE CDR, MW-derived snow cover, or both indicate snow.

The snow_agreement_with_cdr variable offers a different representation of snow cover in that it reports whether MW-derived snow cover agrees with the SCE CDR. snow_agreement_with_cdr was generated from merged_snow_cover_extent as follows:

MW agreement was calculated and written to an intermediate array using the coding scheme in Table 5.

Areas where no comparison was performed due to missing data and areas covered by permanent ice in the 100 km EASE-Grid 2.0 LOCI mask were written to the array using the coding scheme in Table 5.

Data from the intermediate array were written to the snow_agreement_with_cdr NetCDF variable.

For details about the SCE CDR, MW-derived snow cover, and merged_snow_cover_extent variable, refer to the Data Acquisition and Processing section MEaSUREs Northern Hemisphere Terrestrial Snow Cover Extent Weekly 100km EASE-Grid 2.0 for more information.

Version History

Version 1.1 was released in July, 2015. Refer to Table 6 for this data set's version history.

Table 6. Version History
Version Description
V1.1 (Jul, 2015)
  • Added 1D arrays named cols and rows that contain x and y coordinates (meters from origin) of the projection.
  • v01r01 appended to data file names.
V1 (Feb, 2015) Initial version

Error Sources

Missing data represents the biggest impact to overall data quality, as all the input products lack some daily files during the period of record.

The SCE CDR snow cover maps are not constructed according to a formal algorithm, but instead rely on the expertise of trained analysts. Furthermore, because these maps agenerated from workstation software that is continually being evaluated and improved, changes in mapping methodologies have occurred over time. Passive microwave derived snow and sea ice cover is subject to errors carrying through from the input data to the output. For details about potential errors in snow and sea ice cover derived from passive microwave brightness temperatures, refer to the Error Sources section in MEaSUREs Greenland Surface Melt Daily 25km EASE-Grid 2.0 and MEaSUREs Arctic Sea Ice Characterization Daily 25 km EASE-Grid 2.0 for more information.

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References and Related Publications

Abdalati, W., K. Steffen, C. Otto, and K. C. Jezek. 1995. Comparison of Brightness Temperatures from SSMI Instruments on the DMSP F8 and F11 Satellites for Antarctica and the Greenland Ice Sheet. International Journal of Remote Sensing, 16, 1223-1229. doi:10.1080/01431169508954473

Brodzik, M. J., B. Billingsley, T. Haran, B. Raup, and M. H. Savoie. 2012. EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets. ISPRS International Journal of Geo-Information, 1(1):32-45, doi:10.3390/ijgi1010032

Brodzik, M. J., B. Billingsley, T. Haran, B. Raup, and M. H. Savoie. 2014. Correction: Brodzik, M. J. et al. EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets. ISPRS International Journal of Geo-Information 2012, 1, 32-45. ISPRS International Journal of Geo-Information, 3(3):1154-1156, doi:10.3390/ijgi3031154

Chang, Alfred T. C., and Albert Rango. 2000. Algorithm Theoretical Basis Document for the AMSR-E Snow Water Equivalent Algorithm, Version 3.1. Greenbelt, Maryland USA: NASA Goddard Space Flight Center. (PDF, 300 KB)

Dewey, F. and R. Heim, Jr. 1982. A Digital Archive of Northern Hemisphere Snow Cover. Bulletin of the American Meteorological Society, 63:1132-1141.

Estilow, T. W., A. H. Young, and D. A. Robinson. 2014. A Long-Term Northern Hemisphere Snow Cover Extent Data Record for Climate Studies and Monitoring. Earth System Science Data Discussion, 7:669-691. doi: http://dx.doi.org/10.5194/essdd-7-669-2014

Foster, J., A. Chang, D. Hall, and A. Rango. 1991. Derivation of Snow Water Equivalent in Boreal Forests using Microwave Radiometry, Arctic, 44 (Supp. 1), 147-152.

Helfrich, S. R., D. McNamara, B.H. Ramsay, T. Baldwin, and T. Kasheta. 2007. Enhancements to, and Forthcoming Developments in the Interactive Multisensor Snow and Ice Mapping System (IMS). Hydrological Processes, 21:1576-1586. doi:10.1002/hyp.6720

Jezek, K. C., C. Merry, D. Cavalieri, S. Grace, J. Bedner, D. Wilson, and D. Lampkin. 1991. Comparison Between SMMR and SSM/I Passive Microwave Data Collected Over the Antarctic Ice Sheet. Byrd Polar Research Center Technical Report, no. 91-03. The Ohio State University.

Meier, Walt N., Siri Jodha Singh Khalsa, and Matt Savoie. 2011. Intersensor Calibration between F-13 SSM/I and F-17 SSMIS Near-Real-Time Sea Ice Estimates. IEEE Trans. Geosci. Rem. Sens. 49(9), 3343-3349.

Ramsay, B. H. 1998. The Interactive Multisensor Snow and Ice Mapping System. Hydrological Processes, 12:1537-1546. doi:10.1002/(SICI)1099-1085(199808/09)12:10/11<1537::AID-HYP679>3.0.CO;2-A

Robinson, D. A., and G. Kukla. 1985. Maximum Surface Albedo of Seasonally Snow-Covered Lands in the Northern Hemisphere. Journal of Climate and Applied Meteorology, 24, 402-411.

Robinson, D. A., F. Dewey, and R. Heim, Jr. 1993. Global Snow Cover Monitoring: An Update. Bulletin of the American Meteorological Society, 74:1689-1696.

Robinson, D. A. and A. Frei. 2000. Seasonal variability of Northern Hemisphere snow extent using visible satellite data. Professional Geographer, 52(2):307-315.

Robinson, D. A., T. W. Estilow, and NOAA CDR Program. 2012. NOAA Climate Date Record (CDR) of Northern Hemisphere (NH) Snow Cover Extent (SCE), Version 1. Oct 1966–Dec 2012. NOAA National Climatic Data Center. doi: http://dx.doi.org/10.7289/V5N014G9. Accessed: Jan 2013.

Robinson, D. A. 2013. Climate Data Record Program (CDRP): Climate Algorithm Theoretical Basis Document (C-ATBD) Northern Hemisphere Snow Cover Extent, CDRP-ATBD-0156. Asheville, North Carolina, USA, 28 pp.

Savoie, M., R. Armstrong, M. Brodzik, and J. Wang. 2009. Atmospheric Corrections for Improved Satellite Passive Microwave Snow Cover Retrievals over the Tibet Plateau. Remote Sensing of Environment, 113, 2661-2669. doi:10.1016/j.rse.2009.08.006

Stroeve, J., J. Maslanik, and L. Xiaoming. 1998. An Intercomparison of DMSP F11- and F13-Derived Sea Ice Products. Remote Sensing of Environment, 64, 132-152. doi:10.1016/S0034-4257(97)00174-0

RELATED DATA COLLECTIONS

RELATED WEB SITES

Contacts and Acknowledgments

Investigator(s) Name and Title

David A. Robinson
Rutgers University
Department of Geography
54 Joyce Kilmer Avenue
Piscataway, NJ 08854

Mark R. Anderson
University of Nebraska-Lincoln
Department of Earth and Atmospheric Sciences
214 Bessey Hall
Lincoln, NE 68588

Thomas W. Estilow
Rutgers University
Department of Geography
54 Joyce Kilmer Avenue
Piscataway, NJ 08854

Thomas L. Mote
University of Georgia
Department of Geography
210 Field Street
Athens, GA 30602

Acknowledgments: 

These data were generated with support from Award NNX08AP34A from the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program.

The investigators wish to thank:

  • Mary Jo Brodzik at NSIDC for technical assistance, gridding and software support, and for advice regarding the EASE Grid-2.0 format
  • Donna Scott at NSIDC for technical support, documentation and metadata support, and for serving as this project's liaison
  • Members of the Northern Hemisphere Snow and Ice MEaSUREs team, including Angela Bliss, Gina Henderson, and Mark Tschudi

Document Information

DOCUMENT CREATION DATE

February 2015

DOCUMENT REVISION DATE

July 2015