by Mary J. Brodzik
For more information about Northern Hemisphere EASE-Grid 2.0 Weekly Snow Cover and Sea Ice Extent, Version 4 data, please refer to the complete data set documentation.
Please note that the term EASE-Grid is used throughout this document to refer to the target grid, regardless of the processing version of the data set. This data set was gridded to the original EASE-Grid through Version 3.1, and was changed to EASE-Grid 2.0 beginning beginning with Version 4.
The NSIDC development team encountered four categories of problems during the production of the Northern Hemisphere EASE-Grid Weekly Snow Cover and Sea Ice Extent Version 4 product:
The effects of all four problems can be seen in Figure 1. (Click on the image for a larger version).
Figure 1. Zoomed image of raw, regridded combined data for June 17-23, 1996 |
Neither the Nimbus-7 nor the DMSP satellites pass directly over the pole. To eliminate the resulting "hole" at the North Pole, all regridded ocean pixels above 83 degrees North latitude were reset to sea ice (assigned the byte value for QC sea ice).
For Version 3 processing, one of the main reasons that we switched the input sea ice data to the Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data time series was the improved algorithm for detecting and eliminating coastal contamination and weather, both of which resulted in misclassifications as ice in the earlier version of this data set. Beginning with Version 3, the sea ice data did not suffer from these problems. See Figure 2 for a comparison of Version 2 data and Version 3 data. (Click on the images for larger versions).
Figure 2a. Version 2 data, December 21-27, 1998 |
Figure 2b. Version 3 data, December 21-27, 1998 (Note sea ice improvements in weather filter and along coastlines) |
Figure 2c. Difference image |
However, the sea ice data used for Version 3 and Version 4 still returned "ice" pixels on inland lakes in the summertime (see the coastlines of the Great Lakes in Figure 1). The following monthly sea ice extent climatology was used to reset likely misclassified ice pixels back to open ocean. The sea ice extent climatology represents the monthly maximum extent of sea ice derived from satellite passive microwave sensors (SMMR and SSM/I) from 1978 through 2003. Weekly files that span two months are filtered with the climatology for the month that includes four or more days of the week.
Figure 3. Monthly Sea Ice Climatology Masks (Click on the image for a larger version). |
The input sea ice data land mask classified pixels as coastline, land, or ocean; it differed slightly from the EASE-Grid land-ocean-coastline-ice (LOCI) mask, resulting in consistent open ocean pixels along coastlines within the ice pack. In order to minimize these differences, the sea ice land mask was systematically compared to the EASE-Grid land mask prior to regridding.
Each EASE-Grid ocean pixel location was regridded to the source land mask. The EASE-Grid pixel was identified as a mismatch if the source mask was tagged as either coastline or land, because nearest neighbor regridding would never classify the mismatched pixels as ice. The mismatched pixels were then further categorized.
The resulting mismatched pixels are displayed by category in Figures 4a and 4b. (Click on the image for a larger version).
After visual inspection, we decided that pixels in the first two categories were acceptable coastline errors resulting from three different land masks in two projection/grids derived from various coastline databases and algorithms. The most significant areas in the third category included small lakes (in northwestern Russia and central Canada) that simply were not included in the source masks. Pixels in this category have been assigned a byte value that corresponds to "unclassifiable water."
The pixel classification in the first two categories was used during the actual ice data regridding. Up to seven SMMR or SSM/I daily sea ice concentration grids were combined for each corresponding week of NOAA snow data. A pixel was classified as sea ice if it was at least 15 percent sea ice for at least half of the component days. These interim data were then regridded to the NL EASE-Grid via nearest neighbor interpolation. When the target EASE-Grid pixel mapped to an ice pixel in the source grid, it was set to ice (to retain as much of the original information as possible). However, when the EASE-Grid pixel was in the "one-neighbor category," it was classified as sea ice (assigned the byte value for QC sea ice) if any of the eight adjacent source grid interim pixels were sea ice. Similarly, when the EASE-Grid pixel was in the "two neighbor category," it was classified as sea ice (assigned the byte value for QC sea ice) if any of the 24 adjacent source grid interim pixels were sea ice.
Pixels set to sea ice via simple nearest neighbor regridding are distinguished from pixels set during the QC processing by the value for sea ice vs. QC sea ice.
Source snow chart pixels ranged in size from 125 x 125 km to 205 x 205 km. EASE-Grid pixels were 25 x 25 km. This regridding resolution difference, combined with the NOAA ocean mask, resulted in consistent open land pixels above the "snow line" (Fig. 1). In order to minimize these differences, the NOAA ocean mask was systematically compared to the EASE-Grid mask prior to regridding.
Each EASE-Grid land pixel location was regridded to the NOAA mask and identified as a mismatch if the NOAA mask was classified as ocean. If the source snow data only occurred in pixels identified as NOAA mask land, nearest neighbor regridding would never classify the mismatched pixels as snow. To retain as much of the actual data as possible, these mismatched pixels were further classified.
The resulting mismatched pixels are displayed by category in Figures 5a and 5b. (Click on the image for a larger version).
The NOAA mismatched pixel classification was then used during the actual snow data regridding. The NOAA snow chart data were regridded to the NL EASE-Grid via nearest neighbor interpolation. When the EASE-Grid pixel mapped to a NOAA pixel that was classified as snow, it was simply set to snow (to retain as much of the original information as possible).
When the EASE-Grid pixel was not classified snow via nearest neighbor regridding, but was in the "lower latitude snow neighbor" category, it was classified as snow (assigned the byte value for QC snow) if any of its adjacent lower-latitude pixels were snow. This test for lower-latitude snow neighbors (rather than "any" snow neighbor) was introduced to avoid erroneously "growing" the southernmost edge of the snow line. EASE-Grid pixels not classified snow via nearest neighbor regridding, but in the "any neighbor snow category," were classified snow (assigned the byte value for QC snow) if any of the eight adjacent source grid pixels were snow.
Some fixed pixel classifications were also introduced. This data set is designed to represent seasonal fluctuations in snow cover. The Greenland ice sheet and other areas classified as permanent snow or ice in the BU-MODIS mask are always masked as snow covered (assigned the byte values for QC snow). These fixed pixels are indicated in the land mask file EASE2_N25km_loci_land50_coast0km.720x720.bin that is included in the tools directory of the data set distribution.
Finally, there were some land areas (at sub-pixel resolution with respect to the NOAA grid) that failed the snow mismatches test, and resulted in year-round "snow-free" areas, even when the surroundings were classified snow or QC snow. Through visual inspection, we identified the area of Coat's Island (in Hudson's Bay, Canada) to be reset to QC snow if the nearby higher-latitude land was snow or QC snow.
The object of the QC algorithms was to create the most realistic snow and ice maps by reasonably compensating for the differences in resolution and source grid projections. However, we have noted an unfortunate side effect in Iceland during the summer months. The Vatnajökull Glacier in southeast Iceland is large enough to be classified snow in the NOAA snow maps. Our QC procedures will therefore set the adjoining higher latitude pixels in Iceland to QC snow. This is obviously incorrect, since the rest of Iceland does experience a snow-free summer. By way of this example, users should be made aware of the overall limitation of the snow classification in this data set, and note that this data set is not intended for such small, relatively sub-resolution area studies, but rather for continental-scale studies of snow cover over time.
The combination of all quality control algorithms is shown in Figure 6. Figure 6a is post-quality control version of Figure 1, with the various QC pixels indicated separately. Figure 6b is of the same data, with the various QC pixels displayed as the new classification (QC snow pixels are displayed as snow, etc). After visual inspection of the entire time series, we are confident that the majority of gross errors due to regridding and algorithm misclassifications have been corrected.
The EASE-Grid land-ocean-coastline-ice (LOCI) mask used for Version 3 was derived from the K. Knowles (2004). The version of the LOCI mask used for this data set was derived with no coastlines, so pixels were classified land, ocean (water), or permanent ice. Version 4 was derived from M. J. Brodzik (2012). EASE-Grid 2.0 Land Cover Data Resampled from Boston University Version of Global 1 km Land Cover from MODIS 2001, Version 4. Boulder, Colorado USA: National Snow and Ice Data Center.
Go to the complete data set documentation.