Data Set ID:
NSIDC-0726

Daily Lake Ice Phenology Time Series Derived from AMSR-E and AMSR2, Version 1

The Daily Lake Ice Phenology Time Series Derived from AMSR-E and AMSR2 provides 5 km ice phenology retrievals describing daily lake ice conditions (ice-on/ice-off) over the Northern Hemisphere. This satellite-based data set allows for rapid assessment and regional monitoring of seasonal ice coverage over large lakes with resulting accuracy suitable for global change studies. Data are provided in the 5 km Northern Hemisphere Equal-Area Scalable Earth Grid 2.0 (EASE-Grid 2.0).

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Geographic Coverage

Parameter(s):
  • Snow/Ice > Lake Ice
Spatial Coverage:
  • N: 90, S: 0, E: 180, W: -180

Spatial Resolution:
  • 5 km x 5 km
Temporal Coverage:
  • 4 June 2002 to 3 October 2011
  • 24 July 2012 to 31 December 2015
Temporal Resolution: 1 day
Data Format(s):
  • GeoTIFF
Platform(s) AQUA, GCOM-W1
Sensor(s): AMSR-E, AMSR2
Version: V1
Data Contributor(s): Jinyang Du, John Kimball

Data Citation

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.

Du, J. and J. S. Kimball. 2018. Daily Lake Ice Phenology Time Series Derived from AMSR-E and AMSR2, Version 1. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/HT4NQO7ZJF7M. [Date Accessed].

Literature Citation

As a condition of using these data, we request that you acknowledge the author(s) of this data set by referencing the following peer-reviewed publication.

  • Du, J., J. S. Kimball, C. Duguay, Y. Kim, and J. D. Watts. 2017. Satellite microwave assessment of Northern Hemisphere lake ice phenology from 2002 to 2015, The Cryosphere. 11. 47-63. https://doi.org/10.5194/tc-11-47-2017

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Detailed Data Description

Format

All files are in GeoTIFF (.tif) format with Lempel–Ziv–Welch (LZW) lossless compression on a grid of 3600 columns x 3600 rows.

The daily data files contain a 2D array of 16-bit integer-type data (lake coverage ≥50%), showing the lake ice conditions of the 76,671 lake pixels of the Northern Hemisphere.

The ancillary file, Pixel_Water_Percent_v01.tif, contains a 2D array of 8-bit data and describes the percentage of water coverage of each 5-km pixel for the Northern Hemisphere.

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File and Directory Structure

Data are available via HTTPS: https://daacdata.apps.nsidc.org/pub/DATASETS/nsidc0726_AMSRE2_LAKE_ICE_PHEN_v01.

In this directory, there are fourteen folders, one for each year from 2002 to 2015, and the ancillary file. Each year's folder contains a file for each day covered in that year.

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File Naming Convention

This section describes the file naming convention for the data files with an example. Refer to Table 1 for the description of the naming elements.

Example File Name
AMSR_LakeIce_Phen_5KM_2002_155_v01.tif

File Naming Convention
AMSR_LakeIce_Phen_5KM_yyyy_xxx_vxx.tif

Table 1. File Naming Elements
Element Description
AMSR Represents the AMSR-E and AMSR2 instruments
LakeIce_Phen Lake ice phenology
yyyy Indicates the year (2002-2015)
xxx Indicates day of year
vxx Version number
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File Size

Data file sizes range from 928 to 951 KB. The ancillary file, Pixel_Lake_Percent_v01.tif, is 447 KB.

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Volume

The total data set volume is 1.4 GB.

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Spatial Coverage

This data set covers the Northern Hemisphere.

North Latitude: 90.0 N
South Latitude: 0.0 N
East Longitude: 180.0 E
West Longitude: 180.0 W

Spatial Resolution

The spatial resolution is 5 km.

Projection and Grid Description

The data are projected using a polar aspect Lambert azimuthal equal-area projection with the WGS 84 datum (EASE-Grid 2.0 North; Brodzik et al. 2014). The EPSG code for this projection is 6931. Refer to Table 2 for the defining pixel coordinates of the 5-km grid used with this projection. Grid dimensions are 3600 x 3600.

Table 2. Grid Coordinates
Location in Grid Pixel
Upper Left Corner -9,000,000; 9,000,000
Lower left corner -9,000,000; -9,000,000
Upper Right Corner -9,000,000; -9,000,000
Lower Right Corner -9,000,000; -9,000,000
Center 0

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Temporal Coverage

Temporal coverage is from 4 June 2002 to 3 October 2011 and from 24 July 2012 to 31 December 2015.

Temporal Resolution

Temporal resolution is daily.

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Parameter or Variable

Lake ice

Parameter Description

The lake ice data only focus on the pixels with lakes identified by the Global Lakes and Wetlands Database (GLWD) and with water coverage equal to or higher than 50%. If the pixels (including those along the coastline) have no major lakes identified, they are simply assigned as "land" (value -1) or "ocean" (value -999). Table 3 provides descriptions of the data values.

Table 3. Data Value Descriptions
Data Value Description
0 ice-on
1 ice-off
3 unidentified ice state with no retrieval process performed
4 no satellite Tb observations for the date
10 ice-on condition assumed for the entire year with no ice-on/ice-off events detected
11 ice-off condition assumed for the entire year with no ice-on/ice-off events detected
12 not retrievable
254 no satellite observations available for the given pixel
-1 land pixels or lake pixels with water coverage <50%
-999 ocean pixels

The data values of the Pixel_Water_Percent_v01.tif file range from 50 to 100 representing water coverage from 50% to 100%. The value 0 is assigned to pixels with water coverage < 50%.

Sample Data Record

lake ice day60 year 2014
Figure 1. Lake ice coverage on 01 March 2014.
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Software and Tools

GeoTIFF files may be viewed with ESRI ArcGIS, QGIS, or similar Geographical Information System (GIS) software.

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Data Acquisition and Processing

This section contains a brief description of the processing steps performed for this data set.  For an in-depth discussion of the processing methods, refer to Du et al. 2017.

Data Sources

This data set was created using Version 7 brightness temperature (Tb) observations from Remote Sensing System (RSS), and JAXA L1R orbital swath Tb observations from the Advanced Microwave Scanning Radiometer 2 (AMSR2). Other data used for this data set were from EASE-Grid 2.0 Land Cover Classifications Derived from Boston University MODIS/Terra Land Cover Data, Version 1.

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Processing Steps

To choose the lake pixels used for the data set, lakes were identified by the GLWD (Lehner and Döll, 2004). From those identified, only lakes with water coverage of 50% or higher per pixel were used in this data set. The data are projected onto a 5 km global EASE-Grid 2.0 grid.

For the Pixel_Lake_Percent.tif file, the MODIS 250m land–water mask (MOD44W) data (Carroll et al., 2009) were used to calculate the proportional water coverage of 5 km resolution pixels within lake areas identified by the GLWD. 

The data set was produced by a "moving t test" method (MTT) using AMSR-E/AMSR2 36.5 GHz orbital swath Tb data, which were spatially resampled to a 5 km resolution polar EASE-Grid 2.0 grid using an inverse distance squared weighting method. The MTT-based retrieval process was carried out in three steps:

  1. Using MTT to detect abrupt changing point
  2. Determining reference Tb values for lake ice conditions
  3. Deriving lake ice status

Data Accuracy

For a detailed accuracy and performance assessment of lake ice phenology, refer to Du et al. 2017. Below is a summary of data performance.

Lake ice conditions derived from lake ice phenology are more accurate for pixels with higher lake coverage, so the information in the ancillary file represents the retrieval reliability.

For the pixels with lake coverage ≥ 90%, the resulting ice phenology record shows a 95.4 % temporal agreement with available ground-based observations from the Global Lake and River Ice Phenology Database (GLRIPD) available at NSIDC (Benson and Magnuson, 2000). There are favorable correlations (R) with alternative ice phenology records from the Interactive Multisensor Snow and Ice Mapping System (IMS) (R = 0.84 for water clear of ice (WCI) dates; R = 0.41 for complete freeze over (CFO) dates) (Helfrich et al., 2007; http://www.natice.noaa.gov/ims/) and Canadian Ice Service (CIS) (R = 0.86 for WCI dates; R = 0.69 for CFO dates) (Howell et al.,2009). Differences between these three ice phenology records were attributed to the different data sources and methods used to construct the different products, including differences in spatial and temporal resolutions of observations, and distinct nature of optical and microwave remote sensing.

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Sensor or Instrument Description

AMSR-E

For detailed information on the AMSR-E instrument, refer to AMSR-E Instrument Description web page.

AMSR2

For information on the AMSR2 instrument, refer to the About AMSR2 - Observing System on the GCOM-W1 Web site.

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References and Related Publications

Contacts and Acknowledgments

Jinyang Du
Numerical Terradynamic Simulation Group (NTSG)
The University of Montana
Missoula, MT 59812

Dr. John Kimball, PI
Numerical Terradynamic Simulation Group (NTSG)
The University of Montana
Missoula, MT 59812

Acknowledgments: 

AMSR-E data are produced by RSS and sponsored by the NASA Earth Science MEaSUREs DISCOVER Project and the AMSR-E Science Team. Data are available at http://www.remss.com.

The AMSR2 L1R Tb data used for this study were provided courtesy of JAXA. The Global Lakes and Wetlands Database is provided by the World Wildlife Organization and created by the Center for Environmental Systems Research, University of Kassel, Germany. This work was conducted at the University of Montana with funding from NASA (NNX15AT74A).

Document Information

DOCUMENT CREATION DATE

November 2017

No technical references available for this data set.
No FAQs or How Tos available for this data set.

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