Snow Melt Onset Over Arctic Sea Ice from SMMR and SSM/I Brightness Temperatures
Table of Contents
- Detailed Data Description
- Data Access and Tools
- Data Acquisition and Processing
- References and Related Publications
- Contacts and Acknowledgments
- Document Information
Citing These Data
The following example shows how to cite the use of this data set in a publication. For more information, see our Use and Copyright Web page.
Drobot, S. and M. Anderson. 2001, updated 2009. Snow Melt Onset Over Arctic Sea Ice from SMMR and SSM/I Brightness Temperatures. Version 2.0. [indicate subset used]. Boulder, Colorado USA: National Snow and Ice Data Center.
Overview
Nimbus-7, DMSP-F8, -F11, -F13 | |
SMMR, SSM/I |
|
Arctic |
|
25 km |
|
1978 – 2007 |
|
Yearly |
|
Snow melt onset |
|
Flat binary, GIF |
|
Metadata Access |
|
Current Version |
|
Data Access |
1. Detailed Data Description
Summary
This data set includes yearly snow melt onset dates over Arctic sea ice derived from Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) brightness temperatures. The introduction of liquid water to snow results in a sharp increase in the emissivity and hence brightness temperature of the snowpack. Snow melt onset is defined as the point in time when microwave brightness temperatures increase sharply due to the presence of liquid water in the snowpack. Data span the years 1979 through 2007, and are in a polar stereographic grid at 25 km resolution. Tab-delimited ASCII files and GIF images are accessible via FTP. Several value-added products are also available.
Value-added data sets include the following for each pixel: mean melt onset date; latest (maximum) melt onset date; earliest (minimum) melt onset date; range of melt onset dates (the difference between maximum and minimum -- an index of variability); standard deviation of melt onset date (another index of variability); and a trend analysis. Graphical representations of value-added data are also available.
Applications
Accurate dates of snow melt onset over sea ice contribute to improved simulations of climate during the Arctic snow melt period. Records of the spatial and temporal variability in snow melt can serve as climate proxies in Arctic sea ice zones (Drobot and Anderson 2001).
Snow melt onset affects the Arctic energy balance as surface albedo decreases and energy absorption increases in response to the appearance of liquid water (Drobot and Anderson 2001). Initial locations of sea ice melt vary both spatially and temporally. Melt signatures appear first in lower latitudes and advance northward with time. Along the Asian Arctic coast, snow melt starts in the far eastern (Chukchi Sea) and western (Barents and Kara Seas) regions. Over several weeks, the melt progresses zonally toward the Laptev Sea (Anderson 1987).
Format
Data are in flat binary format, in 304 by 448 pixel grids. A GIF-formatted graphical representation of each data file is also available. Data fields are 1-byte integers with values ranging from 0 to 255, and value-added fields are 4-byte floating point numbers.
File and Directory Structure
Each melt onset data file (granule) represents one year of data. Twenty-nine flat binary files and twenty-nine GIF images make up the time series. Each binary file is approximately 136,192 bytes and each GIF image file is approximately 20,000 bytes.
File Naming Conventions
The file naming convention for all files is listed here and described in Table 1.
melt_YYYY_v02_n.bin
where:
| Variable | Description |
|---|---|
| melt | Snow melt onset |
| yyyy | 4-digit year3 |
| h | Hemisphere (n: Northern, s: Southern) |
| vVV | Version (v02) |
| .bin | Indicates a binary file |
| .gif | Indicates this is a GIF image file |
Example: melt_2007_v02_n.bin
Ancillary, value-added files are named according to the following convention and as described in Table 2.
melt_parameter_1979-YYYY_v02_n.gif
where:
| Variable | Description |
|---|---|
| melt | Snow melt onset |
| parameter | Valid parameter values: earliest, latest, mean, median, range, stdev, trend |
| 1979-yyyy | Temporal coverage: 1979 through 4-digit year |
| h | Hemisphere (n: Northern, s: Southern) |
| vVV | Version (v02) |
| .bin | Indicates a binary file |
| .gif | Indicates this is a GIF image file |
Example: melt_median_1979-2007_v02_n.gif
Spatial Coverage and Resolution
As shown in Figure 1, data cover the Northern Hemisphere, except for circular sectors centered over the pole. Data from the SMMR period (1978-87) have a polar gap 611 km in radius, located poleward of 84.5 degrees North latitude. Data from the SSM/I period (1987 through 2007) have a polar gap 311 km in radius, located poleward of 87.2 degrees North latitude. Spatial resolution is 25 km.
Figure 1. Spatial Coverage Map
Projection and Grid Description
Projection
Data are in a polar stereographic projection with a plane of tangency at 70 degrees north latitude. Polar stereographic formulae for converting between latitude/longitude and x,y grid coordinates are taken from Snyder (1982). NSIDC chose the Hughes ellipsoid in constructing the polar stereographic grid. The Hughes ellipsoid assumes a radius of 6378.273 km and an eccentricity (e) of 0.081816153 (or e**2 = 0.006693883).
The polar stereographic projection often assumes that the plane (grid) is tangent to the Earth at the pole. Thus, a one-to-one mapping exists between the Earth's surface and grid with no distortion at the pole. Distortion in the grid increases as the latitude decreases because more of the Earth's surface falls into a given grid cell. Surface area is quite significant at the edge of the northern SSM/I grid where distortion reaches 31%. The projection is true at 70 degrees rather than the poles in order to minimize distortion in the marginal ice zone. Distortion increases at the poles and grid boundaries by only 3%.
Grid Description
Grids are the same as those of the DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures; however, only the Northern Hemisphere grid is used in this data set. The grid cell resolution is 25 km true at 70 degrees north latitude. Grid orientation is such that the first data value for the Northern Hemisphere corresponds to 30.98 degrees latitude and 168.35 degrees longitude (see Spatial Coverage Map). The origin of each x, y grid is the pole.
The grids' approximate outer boundaries are defined by corner points in Table 3. Apply values to the polar grids reading clockwise from upper left. Interim rows define boundary midpoints.
| X (km) | Y (km) | Latitude (deg) | Longitude (deg) | Position in Pixel |
|---|---|---|---|---|
| -3850 | 5850 | 30.98 | 168.35 | corner |
| 0 | 5850 | 39.43 | 135.00 | midpoint |
| 3750 | 5850 | 31.37 | 102.34 | corner |
| 3750 | 0 | 56.35 | 45.00 | midpoint |
| 3750 | -5350 | 34.35 | 350.03 | corner |
| 0 | -5350 | 43.28 | 315.00 | midpoint |
| -5850 | -5350 | 33.92 | 279.26 | corner |
| -5850 | 0 | 55.50 | 225.00 | midpoint |
Temporal Coverage and Resolution
Snow melt onset data range from 1978 through 2007, as shown in Table 4. Data are derived from brightness temperatures acquired from multiple platforms. Snow melt onset data are derived once per year for each grid cell.
| Data Type/Sensor | Start Date | End Date |
|---|---|---|
| Nimbus-7 SMMR | 25 October 1978 | 20 August 1987 |
| DMSP F8 SSM/I | 9 July 1987 | 18 December 1991 |
| DMSP F11 SSM/I | 3 December 1991 | 31 December 1996 |
| DMSP F13 SSM/I | 5 May 1995 | 31 December 2007 |
Parameter or Variable
Parameter Description
Each pixel represents the day of the year that melt first began. The introduction of liquid water to snow results in a sharp increase in the emissivity and hence brightness temperature (TB) of the snowpack. Snow melt onset is defined as the point in time when microwave TBs increase sharply due to the presence of liquid water in the snowpack.
Parameter Source
See the Derivation Techniques and Algorithms section of this document for information regarding derivation of snow melt onset values.
Parameter Range
Values representing snow melt onset dates are in day-of-year integer format, ranging from 60 to 244. Values of 0 represent open ocean. Values of 253 indicate no melt date detected, applicable to points in the ice pack for which the algorithm did not return a melt date, as well as to the missing area around the North Pole. Pixels over land have values of 255, and coastline pixels (for example, land-contaminated pixels within two pixels from the coast) have values of 254.
Sample Data Record
Data are organized in a two-dimensional array. Sample data values are shown below.
...71
97
104
104
104
104
104
104
106
105
71
71
0
0
...
Error Sources
Brightness temperature data may introduce errors related to pixel averaging, sensor errors, and weather effects. See the following temperature documentation for more information regarding errors in the source data:
- DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures
- Nimbus-7 SMMR Polar Radiances and Arctic and Antarctic Sea Ice Concentrations
Known Problems with the Data
Initially, the investigators assigned a value of 0 to all pixels that were open ocean, land, part of the polar gap, or if melt was not that location. NSIDC then added a land mask and reassigned the melt-not-detected pixels to a value other than 0 in order to differentiate among these classes. Other than the circular section over the Northern Hemisphere pole (known as the pole hole), no more than twenty such pixels exist in any given year.
A second iteration of this classification created a two-pixel-wide land-contaminated Lakes and Lake Baikal) were omitted, so that there are no designated land-contaminated pixels within lakes.
NSIDC performed the following steps to identify pixels with melt not detected:
- In all eight directions a pixel was encountered that had either a melt value, land/coast value, or was part of the polar gap AND
- in at least one of the eight directions, a pixel was encountered that had a melt value.
Note that this method may classify some pixels as melt not detected that were previously classified as open water. However, other than the circular section over the Northern Hemisphere pole (known as the pole hole), no more than twenty such pixels exist in any given year.
Limitations of the Data
Given the short data record and the known errors, users are advised against selecting individual pixels without examining surrounding data points. Also, trend analysis at any given pixel should include a study of nearby pixels to confirm that results are locally consistent.
3. Data Access and Tools
Data Access
Data are available via FTP.
Software and Tools
Tools for reading and displaying the snow melt onset files are available via FTP. Included are tools to extract the files; display, extract and export the data; determine geolocation (geocoordinates) of data; and masking tools that limit the influence of non-snow melt data values. Table 5 lists the tools that can be used with this data set. For a comprehensive list of all polar stereographic tools and for more information, see the Polar Stereographic Data Tools Web page.
| Tool Type | Tool File Name |
|---|---|
| Data Display | display_onset_of_melt.pro |
| Geocoordinate | locate.for |
| mapll.for and mapxy.for | |
| psn25lats_v3.dat and pss25lats_v3.dat | |
| psn25lons_v3.dat and pss25lons_v3.dat | |
| Pixel-Area | psn25area_v3.dat and pss25area_v3.dat |
| Land Masks | melt_landmask_v02_n.bin |
4. Data Acquisition and Processing
Theory of Measurements
Microwave emmissivity of snow increases dramatically as the snow melts and liquid water appears. With the presence of liquid water in the snow pack, surface scattering dominates over volume scattering, resulting in a sharp increase in the brightness temperatures (TB) signature. Lower microwave frequencies (19.3 GHz for the SSM/I instrument and 18.0 GHz for the SMMR instrument) are more responsive to melt onset in the firn than are higher frequencies (37.0 GHz for both SSM/I and SMMR), due primarily to the change in emission depth associated with melt. This causes the difference between 19.3 (or 18.0) GHz and 37.0 GHz TBs to change from positive to near-zero or negative (Kunzi et al. 1982). Furthermore, the increase in TB associated with melt is frequency- and polarization-dependent. Horizontal channels reflect a stronger dependence on snow conditions during melt (Anderson 1997) due to the change in dielectric properties at the air-snow interface when snow is wet (Abdalati and Steffen 1995).
Sensor or Instrument Description
See the SSM/I and SMMR instrument documents, which also provide information regarding the Nimbus-7 and DMSP-F8, -F11, and -F13 platforms.
Data Acquisition Methods
Brightness temperature data were acquired by the SMMR and SSM/I instruments. Refer to the SMMR and SSM/I instrument descriptions for sensor information.
Derivation Techniques and Algorithms
Drobot and Anderson calculate snow melt onset dates using daily-averaged brightness temperature (TB) data from SMMR and SSM/I (F8, F11, and F13) satellite radiometers. (See Nimbus-7 SMMR Polar Radiances and Arctic and Antarctic Sea Ice Concentrations and DMSP SSM/I Daily Polar Gridded TBs for more information on the source data.) The investigators record changes in 19H GHz and 37H GHz TBs for each data point on each day within a 20-day window using the Advanced Horizontal Range Algorithm (AHRA, Anderson 1997
Processing Steps
Version History
Table 6 outlines the processing and algorithm history for this product.
| Version | Date | Description of Changes |
|---|---|---|
| V02 | Nov 2009 |
|
| V01 | Dec 2001 | Original version of data. |
Version 2 Processing Steps
The processing steps for Version 02 snow melt onset data were the same as for Version 01 with the exception of step 6 listed below.
Regarding further differences between the two versions, V01 processing had several problems with spurious brightness temperature values resulting in erroneous melt dates. Because the algorithm uses a threshold, it is particularly susceptible to the effects of spurious TBs. In V01, these spurious dates were corrected using a 9-point median filter. The cause of the spurious TBs was traced to an error in the input TB fields where bad scanlines of data were not properly flagged. The input TBs were reprocessed with the proper bad-data flags. The V02 melt product uses these reprocessed brightness temperatures. Because the spurious TBs were eliminated, the 9-point median filter was not needed and thus not implemented for the V02 melt product.
Version 1 Processing Steps
- To ensure a consistent data set, regression analysis was used to convert SMMR and SSM/I F11 and F13 TBs to SSM/I F8 TBs during overlap periods. This ensures a consistent data record for determining temporal trends in the snow melt onset dates. If data are not consistent, snow melt trends could be attributed to instrument characteristics rather than climate conditions. With this in mind, the investigators processed TBs as follows:
- Converted SMMR TBs to SSM/I F8 TBs using slope and intercept values from Jezek et al. (1991)
- Converted SSM/I F13 TBs to SSM/I F11 TBs using slope and intercept values from Stroeve et al. (1998)
- Converted SSM/I F11 TBs to SSM/I F8 TBs using slope and intercept values from Abdalati et al. (1995)
- Applied a two pixel buffer zone to the SSM/I F13 land mask to eliminate land-to-ocean spillover (Cavalieri et al. 1999)
- Determined which pixels have ice concentrations greater than or equal to 50% in winter throughout the time series (based on the NASA Team algorithm, Cavalieri 1994). (Note: The AHRA melt algorithm is only applied to pixels meeting this criterion.)
- Used an ocean mask to eliminate pixels affected by weather and variations in the annual melt ice extent. Pixels that did not satisfy #3 for all 20 years were removed from consideration of melt onset.
- Implemented the melt algorithm (AHRA).
- If the difference between 19H GHz and 37H GHz is greater than 4 K at a given point, the AHRA assumes winter conditions and proceeds to the next day for that point.
- If the difference between 19H GHz and 37H GHz is -10 K or less, then the AHRA assumes liquid water is present in the snowpack and classifies that day as the snow melt onset date.
- If the difference between 19H GHz and 37H GHz is less than 4 K but greater than -10 K, the AHRA determines if snow melt onset occurred based on a 20-day time series of TBs. The algorithm subtracts the minimum and maximum values for the ten days prior to the potential melt onset date, and again for the period from the potential melt onset date to nine days later. The former number is subtracted from the latter number. If the difference is greater than 7.5 K, the algorithm assigns melt to that particular pixel. A large difference indicates variability in the 19H - 37H range after the potential melt onset date. If the difference is less than 7.5 K, then liquid water is unlikely to be in the snowpack, and the algorithm moves on to the next day (Drobot and Anderson 2001).
- NSIDC staff added a land mask in which ocean pixels adjacent to land, or
one pixel removed from land, are designated as land-contaminated. The melt
algorithm was not run for pixels adjacent to land in order to avoid mixed land/ocean
pixels.
- NSIDC assigned a no-melt-detected pixel value to qualifying pixels for which no melt was detected during the year.
Value-Added Products
Value-added products are 4-byte floating point binary arrays and include the following:
mean: Mean melt onset date for the years 1979 through 2007 at each pixel in the 304 by 448 pixel grid is computed in IDL with the following subset of code:
for i=0,303 do begin
for j=0,447 do begin
mean(i,j)=mean(z(where(z gt 0.)))
endfor
endfor
Where z is a vector of the melt dates from 1979 through 2007 for a given i and j pixel.
Note that the where command eliminates any 0 values (such as for pixels over open water or with no melt detected) that would complicate computation of the mean.
median: Median value of melt onset for the period of record at each pixel, as above
latest: The latest melt onset date observed during the period of record at each pixel
earliest: The earliest melt onset date (excluding 0) observed during the period of record at each pixel
range: Latest minus earliest, an index of variability in melt onset at each pixel. Larger ranges at lower latitudes reflect greater variability in weather conditions farther from the pole
stdev: Standard deviation in melt onset over the period of record at each pixel
trend: A regression of the melt dates at each pixel versus the year (1979 to 2007). The values are multiplied by 10 to obtain decadal values. Thus a value of -3.0 indicates that melt onset dates are occurring earlier at a rate of 3.0 days/decade. Note that these trend lines are exceptionally sensitive to melt onset dates in 1979, 1980, 1997, and 1998.
Calculated Variables
The calculated variables were the annual mean onset dates of snow melt over sea ice.
5. References and Related Publications
Abdalati, W. and K. Steffen. 1997. Snowmelt on the Greenland Ice Sheet as Derived from Passive Microwave Satellite Data. Journal of Climate 10(2):165-175.
Abdalati, W. and K. Steffen. 1995. Passive Microwave-defined Snow Melt Regions on the Greenland Ice Sheet. Geophysical Research Letters 22(7):787-790.
Abdalati, W., K. Steffen, C. Otto and K. Jezek. 1995. Comparison of TBs from SSM/I Instruments on the DMSP F8 and F11 Satellites for Antarctica and the Greenland Ice Sheet. International Journal of Remote Sensing 16:1223-1229.
Anderson, M. 1997. Determination of a Melt Onset Date for Arctic Sea Ice Regions Using Passive Microwave Data. Annals of Glaciology 25:382-387.
Anderson, M. 1987. The Onset of Spring Melt in First-year Ice Regions of the Arctic as Determined from Scanning Multichannel Microwave Radiometer Data for 1979 and 1980. Journal of Geophysical Research 92(C12):13,153-13,163.
Cavalieri, D., C. Parkinson, P. Gloersen, J. Comiso, and H. J. Zwally. 1999. Deriving Long-term Time Series of Sea Ice Cover from Satellite Passive-microwave Multisensor Data Sets. Journal of Geophysical Research 104(C7):15,803-15,814.
Cavalieri, D. 1994. A Microwave Technique for Mapping Thin Sea Ice. Journal of Geophysical Research 99(C6):12,561-12,572.
Drobot, S. and M. Anderson. 2001. Comparison of Interannual Snowmelt Onset Dates with Atmospheric Conditions. Annals of Glaciology 33: 79-84.
Dubach L. and C. Ng. 1988. NSSDC's Compendium of Meteorological Space Programs, Satellites, and Experiments.
Gloersen, P. and F. Barath. 1977. A Scanning Multichannel Microwave Radiometer for Nimbus-G and SeaSat-A. IEEE Journal of Oceanic Engineering 2:172-178.
Gloersen, P., W. Campbell, D. Cavalieri, J. Comiso, C. Parkinson, and H. J. Zwally. 1992. Arctic and Antarctic Sea Ice, 1978-1987: Satellite Passive-microwave Observations and Analysis. National Aeronautics and Space Administration Scientific and Technical Information Program. Washington, D.C.
Gloersen, P. and L. Hardis. 1978. The Scanning Multichannel Microwave Radiometer (SMMR) Experiment, in The Nimbus 7 Users' Guide. C. R. Madrid, editor. National Aeronautics and Space Administration. Greenbelt, MD: Goddard Space Flight Center.
Jezek, K., 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, Columbus, Ohio, 62 pp.
Kramer, H. 1994. Observation of the Earth and Its Environment - Survey of Missions and Sensors, 2nd Edition. Heidelberg: Springer-Verlag.
Kunzi, K., S. Patil, and H. Rott. 1982. Snow-cover Parameters Derived from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) data. IEEE Transactions on Geosciences and Remote Sensing GE-20:57-66.
Livingstone, C., K. Singh, and L. Gray. 1987. Seasonal and Regional Variations of Active/Passive Microwave Signatures of Sea Ice. IEEE Transactions on Geosciences and Remote Sensing GE-25:159-172.
National Aeronautics and Space Administration. 1978. The Nimbus 7 Users' Guide. C.R. Madrid, editor. Goddard Space Flight Center.
Snyder, J. P. 1982. Map Projections Used by the U.S. Geological Survey. U.S. Geological Survey Bulletin 1532.
Stroeve, J., L. Xiaoming, and J. Maslanik. 1998. An Intercomparison of DMSP F11- and F13-derived Sea Ice Products. Remote Sensing of the Environment 64:132-152.
Swanson, P. and A. Riley. 1980. The Seasat Scanning Multichannel Microwave Radiometer (SMMR): Radiometric Calibration Algorithm Development and Performance. IEEE Journal of Oceanic Engineering OE-5:116-124.
Related Data Collections
- DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures
- Nimbus-7 SMMR Polar Radiances and Arctic and Antarctic Sea Ice Concentrations
- ESMR Polar Gridded Brightness Temperatures and Sea Ice Concentrations
- Near-Real-Time DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures
- Near-Real-Time DMSP SSM/I-SSMIS Daily Polar Gridded Sea Ice Concentrations
- DMSP SSM/I-SSMIS Pathfinder Daily EASE-Grid Brightness Temperatures
- Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data
- Bootstrap Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I
- Sea Ice Trends and Climatologies from SMMR and SSM/I-SSMIS
5. Contacts and Acknowledgments
Investigator(s) Name and Title
Mark Anderson
Meteorology/Climatology Program
Department of Geosciences
University of Nebraska
Lincoln, NE 68588-0340 USA
Sheldon Drobot
Research Applications Lab
National Center for Atmospheric Research (NCAR)
University Corporation for Atmospheric Research (UCAR)
P.O. Box 3000
Boulder, CO 80307-3000 USA
Technical Contact
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
e-mail: nsidc@nsidc.org
6. Document Information
Acronyms and Abbreviations
Table 7 lists acronyms used in this document.
| Acronym | Description |
|---|---|
| ASCII | American Standard Code fo Information Interchange |
| AHRA | Advanced Horizontal Range Algorthim |
| DSMP | Defense Meteorlogical Satellite Program |
| ESMR | Electronically Scanning Microwave Radiometer |
| NASA | National Aeronautics and Space Administration |
| NOAA | National Oceanic and Atmospheric Administration |
| NSIDC | Naational Snow and Ice Data Center |
| SMMR | Scanning Multichannel Microwave Radiometer |
| SSM/I | Special Sensor for Microwave Imaging |
Document Creation Date
December 2001
Document Revision Date
September 2009
May 2008
August 2003
Document URL
nsidc.org/data/docs/daac/nsidc0105_arctic_snowmelt_onset_dates.gd.html
