Data Set ID: 
AU_SI6

AMSR-E/AMSR2 Unified L3 Daily 6.25 km Polar Gridded 89 GHz Brightness Temperatures, Version 1

The AMSR-E/AMSR2 Unified Level-3 6.25 km product includes brightness temperatures at 89.0 GHz. Data are mapped to a polar stereographic grid at a spatial resolution of 6.25 km for the Northern and Southern Hemispheres. This product uses the Japan Aerospace Exploration Agency (JAXA) AMSR2 Level-1R input brightness temperatures that are calibrated (unified) across the JAXA AMSR-E and AMSR2 Level-1R products.

This is the most recent version of these data.

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Data: Data integrity and usability verified; data customization services available for select data

Documentation: Key metadata and comprehensive user guide available

User Support: Assistance with data access and usage; guidance on use of data in tools and data customization services

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Parameter(s):
  • Microwave > Brightness Temperature
  • Microwave > Microwave Imagery
Data Format(s):
  • HDF-EOS5
Spatial Coverage:
N: -39.23, 
N: 89.24, 
S: -89.24, 
S: 30.98, 
E: 180, 
E: 180, 
W: -180
W: -180
Platform(s):GCOM-W1
Spatial Resolution:
  • 6.25 km x 6.25 km
Sensor(s):AMSR2
Temporal Coverage:
  • 2 July 2012
Version(s):V1
Temporal Resolution1 dayMetadata XML:View Metadata Record
Data Contributor(s):Walter Meier, Josephino 'Joey' Comiso, Thorsten Markus

Geographic Coverage

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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.

Meier, W. N., J. C. Comiso, and T. Markus. 2018. AMSR-E/AMSR2 Unified L3 Daily 6.25 km Polar Gridded 89 GHz Brightness Temperatures, 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/NX1R09ORNOZN. [Date Accessed].
Created: 
9 July 2018
Last modified: 
18 March 2019

Data Description

Parameters

This data set consists of brightness temperature (Tb) observations at 89.0 GHz.  Tables 1 and 2 show the parameters associated with this data set.

Table 1. Northern Hemisphere Parameter Summary

Field Name

Description

SI_06km_NH_89V_ASC 89.0 GHz vertical daily average ascending Tb
SI_06km_NH_89V_DSC 89.0 GHz vertical daily average descending Tb
SI_06km_NH_89V_DAY 89.0 GHz vertical daily average Tb
SI_06km_NH_89H_ASC 89.0 GHz horizontal daily average ascending Tb
SI_06km_NH_89H_DSC 89.0 GHz horizontal daily average descending Tb
SI_06km_NH_89H_DAY 89.0 GHz horizontal daily average Tb
Table 2. Southern Hemisphere Parameter Summary

Field Name

Description

SI_06km_SH_89V_ASC 89.0 GHz vertical daily average ascending Tb
SI_06km_SH_89V_DSC 89.0 GHz vertical daily average descending Tb
SI_06km_SH_89V_DAY 89.0 GHz vertical daily average Tb
SI_06km_SH_89H_ASC 89.0 GHz horizontal daily average ascending Tb
SI_06km_SH_89H_DSC 89.0 GHz horizontal daily average descending Tb
SI_06km_SH_89H_DAY 89.0 GHz horizontal daily average Tb

Parameter Details

Missing or out-of-bounds grid cells have a value of 0. Data have a scale factor of 0.1. Multiply data values by 0.1 to obtain Tb in Kelvin (K). The valid range of Tb is approximately 50 K to 300 K.

File Information

Format

Data are stored in Hierarchical Data Format - Earth Observing System (HDF-EOS5) format.

File and Directory Structure

As shown in Figure 1, each data file includes twelve parameter fields (six Northern Hemisphere and six Southern Hemisphere) and three metadata objects (CoreMetadata, StructMetadata, and Processing_Facility) in 32 bit signed integer format.

Figure 1:  File Structure

Ancillary Data

There are two ancillary text files (.qa and .ph) included with each day of data. The .qa text file provides a quality assessment summary. The .ph text file provides a list of the input data files.

Parameter Naming Convention

Table 3 explains the parameter name variable values using the parameter convention example below.

Example parameter convention: 
SI_6km_HE_PARAM_TIME
Table 3. Parameter Name Variables
Variable Values
SI Indicates sea ice.
6km Indicates a nominal spatial resolution of 6 km.
HE Indicates the observation hemisphere; NH: Northern Hemisphere, SH Southern Hemisphere.
PARAM Indicates the measured parameter; 6 GHz, 10 GHz, 18 GHz Tbs, 23 GHz Tbs, 36 GHz Tbs, and 89 GHz Tbs. Brightness Temperature parameters also include a polarization identifier; V: Vertical and H: Horizontal.
TIME Indicates the observation time period; ASC: 12 hour ascending orbit, DSC: 12 hour decending orbit, DAY: Full orbit daily average
Example parameter name: 
SI_6km_NH_89H_ASC

File Naming Convention

Table 4 explains the file name variable values using the file name convention example below.

Example file convention: 
AMSR_U2_L3_SeaIce6km_X##_yyyymmdd.he5
Table 4. Variable Values for the File Name
Variable Description
AMSR Advanced Microwave Sounding Radiometer
U Unified
2 AMSR2
L3 Level 3
X Product Maturity Code (Refer to Table 5)
## File version number
yyyy Four-digit year
mm Two-digit month
dd Two-digit day
he5
Hierarchical Data Format (HDF-EOS5)
Example file name: 
AMSR_U2_L3_SeaIce6km_B02_20180509.he5

Table 5 provides the meaning for the product maturity code variable values.

Table 5. Variable Values for the Product Maturity Code
Variables Description
B Beta: indicates a developing algorithm with updates anticipated.
T Transitional: period between Beta and Validated when the product is past the beta stage, but not quite ready for validation while the algorithm matures and stabilizes.
V Validated: products are upgraded to Validated once the algorithm is verified by the algorithm team and validated by the validation team.  Validated products have an associated validation stage. Refer to Table 2 in the Naming Conventions section of the AMSR Unified Data Versions page for a description of the stages.

File Size

The average file size for this data set is 88.3 MB.

Spatial Information

Coverage

Figure 2. Northern Hemisphere Coverage Extent
Figure 3. Southern Hemisphere Coverage Extent

A small gap in coverage exists at the poles due to the path of the ascending and descending orbits. Known as the pole hole, this gap is consistent for both AMSR2 and AMSR-E data sets. For additional information see the AMSR-E Pole Hole page.

Resolution

The nominal spatial resolution of the 89.0 GHz brightness temperature polar grids is 6.25 km.  However, because the polar grids are not equal area, the actual resolution varies by latitude.

Geolocation

Tables 6 and 9 provide projection and grid details for this data set.

Table 6. Projection Properties
Northern Hemisphere Southern Hemisphere
Geographic coordinate system Unspecified (Based on Hughes 1980 ellipsoid) Unspecified (Based on Hughes 1980 ellipsoid)
Projected coordinate system NSIDC Sea Ice Polar Stereographic North NSIDC Sea Ice Polar Stereographic South
Longitude of true origin 0 0
Latitude of true origin 70° N 70° S
Scale factor at longitude of true origin 1 1
Datum Unspecified (Based on Hughes 1980 ellipsoid) Unspecified (Based on Hughes 1980 ellipsoid)
Ellipsoid/spheroid Hughes 1980 Hughes 1980
Units Meter Meter
False easting 0 0
False northing 0 0
EPSG code 3411 3412
PROJ4 string

+proj=stere +lat_0=90 +lat_ts=70 +lon_0=-45 +k=1 +x_0=0 +y_0=0 +a=6378273 +b=6356889.449 +units=m +no_defs

+proj=stere +lat_0=-90 +lat_ts=-70 +lon_0=0 +k=1 +x_0=0 +y_0=0 +a=6378273 +b=6356889.449 +units=m +no_defs 

Reference http://epsg.io/3411 http://epsg.io/3412

Table 7. Grid Properties
Northern Hemisphere Southern Hemisphere
Grid cell size (x, y pixel dimensions) 6.25 km 6.25 km
Number of rows 1792 1328
Number of columns 1216 1264
Geolocated lower left point in grid -3850 E, -5350 S -3950 E, -3950 S
Nominal gridded resolution 6.25 km 6.25 km
ulxmap – x-axis map coordinate of the center of the upper-left pixel (XLLCORNER for ASCII data) -3850 -3950
ulymap – y-axis map coordinate of the center of the upper-left pixel (YLLCORNER for ASCII data) 5850 4350

The origin of each x, y grid is the pole.  Tables 7 and 8 show the approximate outer boundaries for the Arctic and Antarctic grids.  Corner points are listed starting from the upper left corner and progress clockwise. Interim rows define boundary midpoints.

Table 8. Grid Boundary Details - Arctic

X (km)

Y (km)

Latitude (deg)

Longitude (deg)

Pixel Location

-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
-3850 -5350 33.92 279.26 corner
-3850 0 55.50 225.00 midpoint

Table 9. Grid Boundary Details - Antarctic

X (km)

Y (km)

Latitude (deg)

Longitude (deg)

Pixel Location

-3950 4350 -39.23 317.76 corner
0 4350 -51.32 0.00 midpoint
3950 4350 -39.23 42.24 corner
3950 0 -54.66 90.00 midpoint
3950 -3950 -41.45 135.00 corner
0 -3950 -54.66 180.00 midpoint
-3950 -3950 -41.45 225.00 corner
-3950 0 -54.66 270.00 midpoint

Geolocation Tools

NSIDC provides geolocation tools for polar stereographic data sets. The first two tools in the list below enable users to obtain latitude/longitude coordinates from (i,j) oordinates and vice versa. The last tool in the list enables users to identify pixel areas.

Land Masks

A 6.25 km Northern Hemisphere land mask (amsr_gsfc_6n.hdf) and a 6.25 km Southern Hemisphere land mask (amsr_nic_6s.hdf) are available for use with these data.

Temporal Information

Coverage

02 July 2012 to the present.

Resolution

Brightness temperatures are provided in three daily-averaged composites: daily-averaged ascending orbits, daily-averaged descending orbits and a daily average of all orbits.

Sample Data Images

                                                       LANCE AMSR2 - NH - 6KM 89V
                                      AMSR_2_L3_SeaIce6km_P00_20160705_N_89V.png

                                                    LANCE AMSR2 - SH - 6KM 89V
                                      AMSR_2_L3_SeaIce6km_P00_20160705_S_89V.png

Data Acquisition and Processing

Acquisition

Source

This product uses the JAXA AMSR2 Level-1R input Tb observations that are calibrated (unified) across the JAXA AMSR-E and AMSR2 Level-1R products. Note that the AMSR-E products at NSIDC currently only use the Level-2A Tb observations provided by Remote Sensing Systems.  In the future, AMSR-E Tb observations may be reprocessed with the unified JAXA Level-1R Tb observations and archived at NSIDC.

The Level-1R input data consist of resampled brightness temperatures. The brightness temperature sensor footprints (instantaneous fields of view) vary with frequency.  The resampling remaps the brightness temperatures to sets of consistent footprint sizes using a Backus-Gilbert method.  Each resampled set corresponds to the footprint of one frequency and contains that frequency plus all higher-resolution frequencies. Therefore, the number of channels in each resampled set of brightness temperatures varies. In the AU_SI6 product, only 89 GHz data is included, so there is only one resampled set of brightness temperatures. See JAXA Level 1R documentation or Maeda et al. (2016) for more information.

Processing

Processing Steps

Swath data from the 89 GHz channel are mapped onto the 6.25 km polar stereographic grid by converting the geodetic latitude and longitude for the center of each scene station, such as the observation footprint, into AMSR2 map grid coordinates. Scene station map grid coordinates determine grid cell assignments. Observations that fall outside the AMSR2 polar grid are ignored. For each grid cell, brightness temperatures observed over a 24-hour period (midnight to midnight GMT) are summed and then divided by the total number of observations to obtain a daily-averaged brightness temperature value. If no observations fall within a grid cell for a given day, the average brightness temperature is labeled 'missing'. The 24-hour averaging is done three ways: for all ascending orbits; all descending orbits; and a daily average of all orbits.

The daily average is not simply an average of ascending and descending orbits, because a given pixel could have, for example, three measurements from ascending orbits and two from descending orbits. Instead, the algorithm computes the daily average for that grid cell from daily ascending and descending averages. For example, if A = ascending and B = descending:

((A1 + A2)/2 + (B1 + B2 + B3)/3)/2  (Equation 1)

However, this approach biases daytime (ascending) orbits over nighttime (descending) orbits.

Quality

Assessment

Each HDF-EOS5 data file contains core metadata with quality assessment (QA) metadata flags.  These flags are set by the operational processing code run by the AMSR Science Investigator-led Processing System (SIPS) prior to delivery to NSIDC. A separate metadata file in XML format is also delivered to NSIDC with the HDF-EOS5 file.  This file contains the same quality assessment (QA) metadata flags as the core metadata contained in the HDF-EOS5 file. Three levels of QA are applied to AMSR2 files: automatic, operational, and science.  Please note that if a granule passes automatic QA and operational QA, the granule is forwarded to NSIDC for archive and distribution.  If not, the issue is resolved and the granule is reprocessed.  Science QA is performed automatically during nominal processing but only reviewed closely after the fact in conjunction with questions that arise post-processing.

Automatic QA

Out-of-bounds Level-1R brightness temperatures are screened out before brightness temperatures are interpolated to the 6.25 km grid.

Operational QA

AMSR2 L1R data are subject to operational QA by JAXA prior to arriving at the AMSR SIPS for processing to higher level products. Operational QA varies by product, but it typically checks for the following criteria in a given file (Conway 2002):

  • File is correctly named and sized
  • File contains all expected elements
  • File is in the expected format
  • Required EOS fields of time, latitude, and longitude are present and populated
  • Structural metadata are correct and complete
  • File is not a duplicate
  • HDF-EOS5 version number is provided in the global attributes
  • Correct number of input files were available and processed

Science QA

In the SIPS environment, as part of the processing code, the science QA includes checking the maximum and minimum variable values, and percent of missing data and out-of-bounds data per variable value. At the Science Computing Facility (SCF), co-located with the SIPS, post-processing science QA involves reviewing the operational QA files and browse images, and performing the following additional QA procedures (Conway 2002):

  • Comparisons with historical data
  • Detection of errors in geolocation
  • Verification of calibration data
  • Detection of trends in calibration data
  • Detection of large scatter among data points that should be consistent.

Several tools have been developed to aid in the QA process of the Level 3 AMSR2 products.  The AMSR SIPS provides software that creates a QA browse image in Portable Network Graphics (PNG) format that can be used for visual QA.  The team lead SCF (TLSCF) provides metadata and QA software specific to each product that generate the metadata files discussed above and a QA summary report in text format. The products of these tools are provided to NSIDC along with each data granule.

Accuracy and Precision

Refer to the Algorithm Theoretical Basis Document for information about data used to check the accuracy and precision of AMSR2 observations.

Anomalies

Refer to the AMSR2 LANCE Anomalies Page for information regarding data anomalies or gaps in coverage. 

Instrument Description

For a detailed description of the AMSR2 instrument, refer to the AMSR2 Channel Specification and Products page.

Software and Tools

For general tools that work with HDF-EOS data, see the NSIDC HDF-EOS web page.

Contacts and Acknowledgments

Josefino Comiso
Laboratory for Hydrospheric Processes
NASA Goddard Space Flight Center
Greenbelt, MD 20771

Thorsten Markus
Laboratory for Hydrospheric Processes
NASA Goddard Space Flight Center
Greenbelt, MD 20771

References

Meier, W.N., and A. Ivanoff, 2017. Intercalibration of AMSR2 NASA Team 2 algorithm sea ice concentrations with AMSR-E slow rotation data, IEEE J. Spec. Topics Appl. Earth Obs. & Rem. Sens., 10(8), doi:10.1109/JSTARS.2017.2719624.

Comiso, J. C. 2009. Enhanced sea ice concentration and ice extent from AMSR-E Data. J. Remote Sensing Soc. of Japan 29(1): 199-215.

Markus, T., and D. J. Cavalieri. 2009. "The AMSR-E NT2 sea ice concentration algorithm: its basis and implementation." Journal of The Remote Sensing Society of Japan, 29 (1): 216-225

Comiso, J., D. Cavalieri, and T. Markus. 2003. Sea Ice Concentration, Ice Temperature, and Snow Depth using AMSR-E data. IEEE Transactions on Geoscience and Remote Sensing 41(2): 243-252.

Markus, T. and D. Cavalieri. 2000. An Enhancement of the NASA Team Sea Ice Algorithm. IEEE Transactions on Geoscience and Remote Sensing 38: 1387-1398.

How To

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