Data Description

Parameters

The main parameter for this data set is the Snow Melt Onset Date (SMOD) over Arctic sea ice, or the Day of Year (DOY) when microwave brightness temperatures increase sharply due to the presence of liquid water in the snowpack. This data set also includes statistical analyses of each grid cell's SMOD over the period between 1979 through 2017. Table 1 includes a description of valid SMOD values, while Table 2 contains a description of valid statistical fields.

File Information

Format

Data are provided in netCDF (.nc) file format. 

PNG (.png) browse images and Extensible Markup Language (.xml) files with associated metadata are also provided.

File Contents

NetCDF file contents are described in Table 3.

One browse image is provided for each year of data showing the annual SMOD; Figure 1 contains a sample image. One browse image is also provided for each statistical field, as exemplified by Figure 2. 

Directory Structure

Data are available for download via HTTPS; the link is accessible through the "Download Data" tab on the data set landing page. Within the file directory, browse images are available in the subfolder labeled "Browse."

Naming Convention

The netCDF file name is:
SMOD_1979-2017_v04r00.nc

Browse images showing the annual snow melt onset date are named according to the following convention and as described in Table 4:
melt_<year>_v04r00_n.png

Browse images for statistical fields are named according to the following convention and as described in Table 5:
melt_<field>_1979-2017_v04r00.png

File Size

The netCDF file is approximately 1.9 MB.

Browse images are approximately 345 KB.

Spatial Information

Coverage

Data cover the Northern Hemisphere, except for three circular gaps centered over the pole that correspond to the three satellite records. Data from the SMMR period (1978-87) have a gap with a radius of 611 km, located poleward of 84.5 degrees North. Data from the SSM/I period (1987 through 2007) have a polar gap with a radius of 311 km, located poleward of 87.2 degrees North. Lastly, data from the SSMIS period (2008 through 2017) have a gap poleward of 89.2° North. See the Polar Stereographic Projection and Grid spatial coverage map for details. 

Resolution

25 km

Geolocation

The data are provided on the 25 km Northern Hemisphere Polar Stereographic Grids, as described in Tables 6 and 7. For more information, see the Polar Stereographic Projections and Grid web page.

Temporal Information

Coverage

This data set extends from 1979 through 2017. Snow melt onset dates were derived from brightness temperatures acquired from multiple platforms, as described in Table 8. For all years, only brightness temperatures from DOY 61 (early March) through 245 (early September) were used to calculate snow melt onset dates.

Resolution

Snow melt onset dates were derived once per year for each grid cell.

Data Acquisition and Processing

Background

Accurate snow melt onset dates 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 also serve as climate proxies in Arctic sea ice zones. 

Snow melt onset dates are estimated based on changes in brightness temperature measurements. Microwave emissivity 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 signature. Lower microwave frequencies (e.g. 18.0 GHz and 19.3 GHz) are more responsive to melt onset in ice than are higher frequencies (e.g. 37.0 GHz), primarily due to the change in emission depth associated with melt. Melt therefore causes the difference between low-frequency and high-frequency brightness temperatures to change from positive to near-zero or negative. Furthermore, the increase in brightness temperature associated with melt is polarization-dependent. Horizontal channels reflect a stronger dependence on snow conditions during melt due to the change in dielectric properties at the air-snow interface when snow is wet.

Acquisition

Snow melt onset dates were derived from brightness temperature (T_b) measurements acquired by the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave/Imager (SSM/I), and Special Sensor Microwave Imager/Sounder (SSMIS) instruments. Sea ice extent masks were also used to constrain the melt algorithm. Table 9 describes the input data sources in more detail.

Processing

Snow melt onset dates were estimated using daily average brightness temperature (T_b) data from SMMR, SSM/I (F8, F11, and F13), and SSMIS (F17) satellite radiometers. Changes in 18.0 or 19.3 H-polarization GHz and 37.0 H-polarization GHz T_b were recorded for each grid cell using the Advanced Horizontal Range Algorithm (AHRA). For more details on AHRA, please refer to Anderson 1997. 

1. Ensure consistent input data
   For this data set, SSM/I F8 was used as the standard input sensor. Regression analysis was used to convert SMMR, SSM/I F11 and F13, and SSMIS F17 T_b to SSM/I F8 T_b (after Abdalati et al. 1995). Table 10 provides an overview of the correction coefficients used. These conversions ensure a consistent data record for determining temporal trends in the snow melt onset dates. If data are not consistent, snow melt trends could be attributable to instrument characteristics rather than climate conditions.
2. Created sea ice extent mask
   The goddard_merged_seaice_conc variable from the NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration, Version 3 data set was used as a measure of daily Sea Ice Concentration (SIC). Beginning on Day of Year (DOY) 61 (early March), these SIC estimates were used to determine which pixels had a SIC ≥ 50%. Snow melt onset dates were only calculated at pixel locations that met this criterion.
   • DOY 61 was used because this date roughly corresponds to the time period of maximum annual sea ice extent.
   • Since the SMMR data were collected every other day, in the event of data outages (i.e. a missing swath), a SIC ≥ 50% for any day between DOY 61 and DOY 65 was used to define the sea ice extent.
   • A unique sea ice extent mask was created for each year of data.
3. Run AHRA
   The AHRA calculates the difference between low-frequency (18.0 GHz or 19.3 GHz) and high-frequency (37.0 GHz) T_b measurements. When conditions are dry and frozen, low-frequency T_b measurements are larger than high-frequency T_b measurements. When low-frequency T_b drop below high-frequency T_b measurements, melt has started. Turn points are described below; refer to Drobot and Anderson 2001 for more details.
   • If (18.0 / 19.3 GHz - 37.0 GHz) > 4 K, the AHRA assumes winter conditions and proceeded to the next day with data for that pixel.
   • If (18.0 / 19.3 GHz - 37.0 GHz) ≤ -10 K, the AHRA assumes liquid water was present in the snowpack and classifies that day as the snow melt onset date.
   • If 4 K > (18.0 / 19.3 GHz - 37.0 GHz)  > -10 K, the AHRA determines if snow melt onset occurred based on a 20-day time series of T_b. The algorithm subtracts the minimum and maximum T_b 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 then subtracted from the latter number. If the difference is greater than 7.5 K, the algorithm assigns a snow melt onset date to that particular grid cell because a large difference indicates variability in the 18.0 / 19.3 GHz - 37.0 GHz range after the potential melt onset date. If the difference was less than 7.5 K, then liquid water is unlikely to be in the snowpack, and the algorithm moves on to the next day.
4. Assigned quality flags​
   • Assigned a value of 5 to all pixels that were part of the pole hole.
   • Assigned a value of 10 to all pixels that were over open ocean.
   • Assigned a value of 15 to all pixels that were over land.
   • Assigned a value of 255 to all pixels where melt was not calculated.

Quality, Errors, and Limitations

Differences between V3 and V4 Data

The differences between the Version 3 (V3) and Version 4 (V4) snow melt onset dates (SMOD) are illustrated for two years in Figure 3. Differences are limited to the sea ice edge and around the pole hole. Along the ice edge, blue pixels indicate grid cells where SMOD was computed in V4 but not V3. Conversely, red pixels along the ice edge indicate grid cells where SMOD was computed in V3 but not in V4. These differences are due to slight variations in the V2 and V3 NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration data sets, which were used to create the sea ice masks in V3 and V4 of this data set, respectively.

The biggest differences between V3 and V4 SMOD occur at the pole hole in the years 2008 - 2012. In the previous SIC data version, a larger pole hole was used to mask SICs obtained using SSMIS; thus, no SMOD could be computed within this region. However, the updated SIC data now use a smaller pole hole mask for these years, which allows SMOD to be computed. These new SMOD are shown as the dark blue ring in Figure 3 (right panel) surrounding the North Pole. Note that almost differences exist between V3 and V4 SMOD for the bulk of the sea ice area because no changes have bene made to the AHRA algorithm since publication by Bliss and Anderson (2014).

Error Sources

Brightness temperature data may have errors related to pixel averaging, sensor errors, and weather effects. See the following brightness 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

Limitations

Given 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.

Instrumentation

Brightness temperature input data were acquired from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave/Imager (SSM/I), and Special Sensor Microwave Imager/Sounder (SSMIS) instruments. For more details, refer to the SMMR, SSM/I, and SSMIS Sensors page.

Software and Tools

For a comprehensive list of all polar stereographic tools, see the Polar Stereographic Data Tools Web page.

Version History

Table 11 outlines the processing and algorithm history for this product.

Related Data Sets

• MEaSUREs Arctic Sea Ice Characterization Daily 25km EASE-Grid 2.0
• 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
• NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration

Contacts and Acknowledgments

Mark Anderson
Meteorology/Climatology Program
Department of Geosciences
University of Nebraska
Lincoln, NE 68588-0340 USA

Corvallis, OR, 97331-5503 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

References

Abdalati, W., K. Steffen, C. Otto and K. Jezek. 1995. Comparison of brightness temperatures 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. DOI: https://doi.org/10.1080/01431169508954473

Anderson, M. 1997. Determination of a Melt Onset Date for Arctic Sea Ice Regions Using Passive Microwave Data. Annals of Glaciology 25:382-387. DOI: https://doi.org/10.3189/s0260305500014324

Bliss, A. C. and M. R. Anderson. 2014. Arctic sea ice melt onset from passive microwave satellite data: 1979 - 2012. The Crysophere 8:2089-2100. DOI: https://doi.org/10.5194/tc-8-2089-2014

Drobot, S. and M. Anderson. 2001b. Comparison of Interannual Snowmelt Onset Dates with Atmospheric Conditions. Annals of Glaciology 33: 79-84. DOI: https://doi.org/10.3189/172756401781818851

Gloersen, P. 2006. Nimbus-7 SMMR Polar Gridded Radiances and Sea Ice Concentrations, Version 1. [1979-1987]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. DOI: https://doi.org/10.5067/QOZIVYV3V9JP.

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.

Maslanik, J. and J. Stroeve. 2004. DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures, Version 4. [1988-2017]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. DOI: https://doi.org/10.5067/AN9AI8EO7PX0.

Meier, W. N., Khalsa, S. J. S., and M. H. Savoie. 2011. Intersensor calibration between F-13 SSM/I and F-17 SSMIs near-real-time sea ice estimates. IEEE Trans. Geosci. Remote Sens. 49:3343–3349. DOI: 10.1109/TGRS.2011.2117433

Meier, W., F. Fetterer, M. Savoie, S. Mallory, R. Duerr, and J. Stroeve. 2017. NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration, Version 3. [1979-2017]. Boulder, Colorado USA: National Snow and Ice Data Center. DOI: https://doi.org/10.7265/N59P2ZTG.

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. DOI: https://doi.org/10.1175/1520-0442(2004)017<0067:DOTASI>2.0.CO;2