Table of Contents

1. Detailed Data Description
2. Data Access
3. Data Acquisition and Processing
4. References and Related Publications
5. Contacts and Acknowledgments
6. Document Information

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NSIDC encourages you to register as a user of this data product. As a registered user, you will be notified of updates and corrections. Register.

Citing These Data

The following example shows how to cite the use of this data set in a publication.

Meier, W., F. Fetterer, M. Savoie, S. Mallory, R. Duerr, and J. Stroeve. 2011. NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration. Boulder, Colorado USA: National Snow and Ice Data Center. http://dx.doi.org/10.7265/N5B56GN3

Overview

Parameters	Sea Ice Concentration
Spatial Coverage & Resolution	North and south polar regions gridded onto a polar stereographic projection with 25 x 25 km grid cells
Temporal Coverage & Resolution	NOAA/NSIDC CDR: 09 July 1987 - 31 December 2007 at a daily and monthly resolution
Platform	Defense Meteorological Satellite Program (DMSP)
Sensor	Special Sensor Microwave Imager (SSM/I) passive microwave radiometers: F-8, F-11, and F-13
Data Format	NetCDF4 CF-1.5
Metadata Access	View Metadata Record
Data Access	FTP

1. Detailed Data Description

Summary

The NOAA/NSIDC CDR is based on the recommendations from the National Research Council (NRC) (2004). It is produced from gridded brightness temperatures from the Defense Meteorological Satellite Program (DMSP) series of Special Sensor Microwave Imager (SSM/I) passive microwave radiometers: F-8, F-11, and F-13.

The NOAA/NSIDC CDR sea ice concentrations are an estimate of the fraction of ocean area covered by sea ice that is produced by combining concentration estimates created using two algorithms developed at the NASA Goddard Space Flight Center (GSFC): the NASA Team algorithm (Cavalieri et al., 1984) and the Bootstrap algorithm (Comiso, 1986). NSIDC applies the individual algorithms to brightness temperature data from Remote Sensing Systems, Inc. (RSS).

The data are gridded on the NSIDC polar stereographic grid with 25 x 25 km grid cells and are available in netCDF file format. Each file includes four different sea ice concentration variables: a variable with the primary CDR sea ice concentrations created by NSIDC and three variables with sea ice concentrations created by Goddard.

The three Goddard-produced sea ice concentrations are the Goddard NASA Team algorithm sea ice concentrations, the Goddard Bootstrap sea ice concentrations, and a merged version of the two sea ice concentrations. These Goddard-produced sea ice concentrations are included in the data files for a number of reasons. First, the merged Goddard NASA Team/Bootstrap sea ice concentrations are an ancillary data set that is analogous to the NOAA/NSIDC CDR data but that adds late 1978 through mid 1987 data to the record. A different instrument, the Scanning Multichannel Microwave Radiometer (SMMR), was the source for the brightness temperatures from this period. Sea ice concentrations from the extended period are not part of the primary NSIDC-produced CDR record because complete documentation of the SMMR brightness temperature processing method is not available. Second, the separate Goddard NASA Team and Bootstrap sea ice concentrations are provided for reference.

Variables containing standard deviation, quality flags, and projection information are also included in the netCDF files.

Format

These data are provided in netCDF4 file format and are compliant with the Climate and Forecast (CF) Metadata Convention CF-1.5. "The purpose of the CF conventions is to require conforming data sets to contain sufficient metadata that they are self-describing in the sense that each variable in the file has an associated description of what it represents, including physical units if appropriate, and that each value can be located in space (relative to earth-based coordinates) and time" (Eaton B., et al., 2010).

Both the daily and monthly files contain 12 variables that are described in the sections below:

• Daily File Variable Description
• Monthly File Variable Description

Daily File Variable Description

The daily netCDF files contain 12 variables. They are described below.

Monthly File Variable Description

The monthly netCDF files contain 12 variables; they are described below.

File and Directory Structure

The data files are organized on the FTP site into two main directories by hemisphere: north and south. Within each of these, there are two sub-directories: daily and monthly. The daily directory is further sub-divided into directories labeled by the 4-digit year (YYYY) beginning with 1978; the daily files reside within their respective year directory. All of the monthly files reside directly in the monthly directory. Figure 1 shows an image of the directory structure.

File Naming Convention

The file naming convention for the daily and monthly files is listed below and described in Table 4:

Daily: seaice_conc_daily_hh_sat_yyyymmdd_vXXrXX.nc
Monthly: seaice_conc_monthly_hh_sat_yyyymm_vXXrXX.nc

Where:

Table 4. File Naming Convention

Variable	Description
seaice_conc	Identifies files containing sea ice concentration data
daily	Identifies files containing daily sea ice concentration
monthly	Identifies files containing monthly sea ice concentration
hh	Hemisphere (nh: North, sh: South)
sat	Satellite the data came from (n07: Nimbus 7, f08: DMSP F8, f11: DMSP F11, f13: DMSP F13)
yyyy	4-digit year
mm	2-digit month
dd	2-digit day of month
vXXrXX	Version and release number of the data file (v01r00: version 01 release 00)
.nc	Identifies a netCDF file

File Size

File sizes are shown in Table 5.

Table 5. File Size

	Northern Hemisphere	Southern Hemisphere
Daily	2.5 MB - 3.5 MB each	1.8 MB - 2.5 MB each
Monthly	3.4 MB each	2.6 MB - 2.7 MB

Spatial Coverage

These data cover both the Northern and Southern polar regions at a 25 x 25 km grid cell size. Note: While resolution and grid cell size are often used interchangeably with regards to satellite data, there is an important difference. Resolution refers more properly to the instantaneous field of view (IFOV) of a particular sensor frequency. That is, resolution is the spot size on the ground that the sensor channel can resolve. The SSM/I channels used are the 19 GHz vertical, the 19 GHz horizontal, and the 37 GHz vertical. The IFOV of the 19 GHz SSM/I passive microwave channel is approximately 70 km x 45 km. See Table 12 for a complete list of IFOVs by channel.

Since these data are gridded onto a 25 x 25 km grid and the IFOV of the sensor is coarser than this, the sensor is obtaining information from up to a 3 x 2 grid cell (~75 km x 45 km) region, but because a simple drop-in-the-bucket gridding method is used, that signature is placed in a single grid cell. This results in a spatial "smearing" across several grid cells. Also, some grid cells do not coincide with the center of the sensor footprint and are thus left as missing even though there is brightness temperature information available at that region. Higher frequency channels have finer resolution, but because the sea ice concentration algorithms use data from the 19 GHz channel, the sea ice concentration estimate is affected by the makeup of the surface over an area considerably larger than the nominal 25 km resolution.

The spatial coordinates for the Northern polar region are the following:

Southernmost Latitude: 31.10° N
Northernmost Latitude: 89.84° N
Westernmost Longitude: 180° W
Easternmost Longitude: 180° E

The spatial coordinates for the Southern polar region are the following:

Southernmost Latitude: 89.84° S
Northernmost Latitude: 39.36° S
Westernmost Longitude: 180° W
Easternmost Longitude: 180° E

Projection and Grid Description

The sea ice concentration data are displayed in a polar stereographic projection. For more information on this projection, see the NSIDC Polar Stereographic Projections and Grids Web page. Note that the polar stereographic grid is not equal area; the latitude of true scale (tangent of the planar grid) is 70 degrees. The grid size varies depending on the region, as shown in Table 6.

Table 6. Polar Stereo Grid Size

Region	Columns	Rows
North	304	448
South	316	332

Temporal Coverage

The primary NOAA/NSIDC CDR sea ice concentrations span 09 July 1987 to 31 December 2007 provided at both a daily resolution and a monthly averaged resolution. The merged Goddard NASA Team/Bootstrap sea ice concentrations that are analogous to the NOAA/NSIDC CDR sea ice concentrations adds 26 October 1978 through 08 July 1987 data to the record. The two reference Goddard NASA Team and Goddard Bootstrap sea ice concentrations are also available for that time period. The three Goddard-produced sea ice concentrations are also provided at a daily resolution from 09 July 1987 to 31 December 2007 but every other day from 1978 to 08 July 1987. Note: Data files for the 1978 to 1987 time period still contain a variable for the primary CDR data (seaice_conc_cdr for daily file, seaice_conc_cdr_monthly for monthly file), but it is populated with a fill value of 255. See Table 7 for a list of the dates that each of the different instruments were used.

Table 7. Time Period Each Instrument is Used

Platform and Instrument	Time Period
Nimbus-7 SMMR	26 October 1978 - 08 July 1987
DMSP-F8 SSM/I	09 July 1987 - 02 December 1991
DMSP-F11 SSM/I	03 December 1991 - 30 September 1995
DMSP-F13 SSM/I	01 October 1995 - 31 December 2007

Parameter

The parameter of this data set is sea ice concentration which is the fraction of ocean area covered by sea ice. Sea ice concentration represents an areal coverage of sea ice. For a given grid cell, the parameter provides an estimate of the fractional amount of sea ice covering that cell, with the remainder of the area consisting of open ocean. Land areas are coded with a land mask value.

2. Data Access and Tools

Data Access

Data are available via FTP.

Software and Tools

There are a number of netCDF file readers available to read/view netCDF files. For a list of some of these tools, please see the NetCDF Resources at NSIDC: Software and Tools Web page.

3. Data Acquisition and Processing

Data Acquisition Methods

NOAA/NSIDC CDR Sea Ice Concentrations

The input gridded brightness temperatures used for creating the daily NOAA/NSIDC CDR sea ice concentrations (seaice_conc_cdr) come from NSIDC in the DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures data set. These gridded brightness temperatures are produced by NSIDC from swath data obtained from RSS. For a complete description of how NSIDC obtains and processes the input data, see the Data Acquisition Methods section of the DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures data set guide document. The input for the monthly CDR concentration (seaice_conc_cdr_monthly) is the daily CDR variable.

Note that the NOAA/NSIDC CDR does not currently include the SMMR product because full provenance and documentation of the SMMR brightness temperatures and processing methodology (for example, manual filtering of bad grid cells) cannot be assured, and thus, does not fulfill the CDR standards set forth by NRC (2004).

Goddard Sea Ice Concentrations

The data for the Goddard-produced sea ice concentrations are created by Goddard but are archived at NSIDC. NSIDC uses the archived products as input for these variables. The input data for the goddard_nt_seaice_conc and goddard_nt_seaice_conc_monthly variables are the Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data. This data set is also called the NASA Team sea ice concentration data set because the values are computed using the NASA team algorithm. See the NASA Team Algorithm section for a description of this algorithm.

The input data for the goddard_bt_seaice_conc and goddard_bt_seaice_conc_monthly variables are the Bootstrap Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS data. This data set is also called the Bootstrap sea ice concentration data set because the values are computed using the Bootstrap algorithm. See the Bootstrap Algorithm section for a description of this algorithm.

Note: These data are processed almost identically to the intermediate NSIDC-produced NASA Team and Bootstrap sea ice concentrations used in the CDR concentration estimates but are produced at NASA GSFC and include manual quality control. This hand editing removes spurious ice in grid cells that are not removed through automated filtering methods and any other bad data discovered through the manual inspection. However, the hand-editing process has not been documented and, thus, is not traceable, which means that they do not pass the traceability recommendations for CDRs from NRC (2004). In addition, older versions of the RSS brightness temperatures were used as input for some parts of the record, though these differences are small. Therefore, while the Goddard products do not have full traceability, they do result in a better overall quality record. In addition, they also include sea ice estimates from the NASA Nimbus-7 SMMR sensor, which predates DMSP and extends the total time series to late 1978 with every-other-day concentration estimates. The input data for the merged Goddard sea ice concentration variables (goddard_merged_seaice_conc and goddard_merged_seaice_conc_monthly) are the NASA Team and Bootstrap variables mentioned above. For a description of the algorithm used to merge the data, see the CDR Algorithm section of this document.

Derivation Techniques and Algorithms

Overview

NSIDC processes the input brightness temperatures into two different intermediate sea ice concentrations using two Goddard-developed algorithms: NASA Team (Cavalieri et al., 1984) and Bootstrap (Comiso, 1986). The two algorithms are described in the NASA Team Algorithm and Bootstrap Algorithm sections of this document, respectively. These intermediate NSIDC NASA Team and Bootstrap sea ice concentrations are used in the NOAA/NSIDC CDR algorithm described in further detail in the CDR Algorithm section of this document.

The passive microwave channels employed for the sea ice concentration product are the 19 GHz, 22 GHz, and 37 GHz frequencies. Table 8 lists the channels used for each algorithm and the channels used for the weather filters. For a complete description of the weather filters, see the Climate Algorithm Theoretical Basis Document (C-ATBD): Passive Microwave Sea Ice Concentration document (Meier, W. N., et al., 2011a).
 

Table 8. NASA Team and Bootstrap Algorithm Channels

	NASA Team	Bootstrap
Algorithm Channels	19H, 19V, and 37V	37H, 37V, and 19V
Weather Filters	22V and 19V	22V

 

Since this data set uses multiple sensors over time, the sea ice algorithms are intercalibrated at the product (concentration) level by NASA Goddard. Thus, the brightness temperature source is less important because the intercalibration adjustment includes any necessary changes due to differences in brightness temperature across them. Both the NASA Team and Bootstrap algorithms employ varying tie-points to account for changes in sensors and spacecraft. These tie-point adjustments are derived from regressions of brightness

temperatures during overlap periods. The adjustments are made at the product level by adjusting the algorithm coefficients so that the derived sea ice fields are as consistent as possible.

The NASA Team approach uses sensor-specific hemispheric tie-points for each transition (Cavalieri et al., 1999; Cavalieri et al., 2011). Tie-points were originally derived for the SMMR sensor and subsequent transitions to the different SSM/I instruments adjusted the tie-points to be consistent with the original SMMR record. The Bootstrap algorithm uses daily varying hemispheric tie-points, derived via linear regression analysis on clusters of brightness temperature values of the relevant channels (Comiso, 2009; Comiso and Nishio, 2008). Also, in contrast to the NASA Team, Bootstrap tie-points for SMMR and SSM/I are derived from matching fields from the AMSR-E sensor, which is newer and more accurate.

Automated Quality Control

Automated quality control measures are implemented independently on the intermediate NASA Team and Bootstrap outputs. Two weather filters, based on ratios of channels sensitive to enhanced emission over open water, are used to filter weather effects. Separate land-spillover corrections are used for each of the algorithms to filter out much of the error due to mixed land/ocean grid cells. Finally, climatological ocean masks are applied to screen out errant retrievals of ice in regions where sea ice never occurs.

For a complete description of the automated filters and masks, see the C-ATBD (Meier, W. N., et al., 2011a)

NASA Team Algorithm

The NASA Team algorithm uses brightness temperatures from the 19 GHz V, 19 GHz H, and 37 GHz V channels. The methodology is based on two brightness temperature ratios, the polarization ratio (PR) of the 19 GHz V and H channels (Equation 1) and the spectral gradient ratio (GR) of the 19 GHz V and 37 GHz V channels (Equation 2).

PR(19) = [TB(19V) - TB(19H))]/[TB(19V) + TB(19H)]	(Equation 1)
GR(37V/19V) = [TB(37V) - TB(19V)]/[TB(37V) + TB(19V)]	(Equation 2)

Where

Table 9. NASA Team Algorithm Variable Descriptions

Variable	Description
PR(19)	Polarization ratio of the 19 GHz vertical and horizontal channels
TB(19V)	Brightness temperature at the 19 GHz vertical channel
TB(19H)	Brightness temperature at the 19 GHz horizontal channel
GR(37V/19V)	Gradient ratio of the 37 GHz vertical channel and the 19 GHz vertical channel
TB(37V)	Brightness temperature at the 37 GHz vertical channel

 

When PR and GR are plotted against each other, brightness temperature values tend to cluster in two locations, an open water (0% ice) point and a line representing 100% ice concentration, roughly forming a triangle. The concentration of a grid cell with a given GR and PR value is calculated by a linear interpolation between the open water point and the 100% line segment. See Figure 2.

For a detailed description of the NASA Team algorithm, please see the NASA Team Sea Ice Algorithm Web page, the NASA Technical Memorandum 104647 (Cavalieri, D. J., et al., 1997) that includes information about differences (for example, tie points) between the original algorithm and the revised NASA Team algorithm, and the NASA Team Algorithm section of the C-ATBD (Meier, W. N., et al., 2011a) for a table of tie-point values.
 

Bootstrap Algorithm

Like the NASA Team algorithm, the Bootstrap algorithm is empirically derived based on relationships of brightness temperatures at different channels. The Bootstrap method uses the fact that scatter plots of different sets of channels show distinct clusters that correspond to two pure surface types: 100% sea ice or open water.

Figure 3 shows a schematic of the general relationship between two channels. Points that fall along line segment AD represent 100% ice cover. Points that cluster around point O represent open water (0% ice). Concentration for a point B is determined by a linear interpolation along the distance from O to I where I is the intersection of segment OB and segment AD. This is described by Equation 3.
 

C = (TB - TO)/(TI - TO)

(Equation 3)

Where:

Table 10. Bootstrap Algorithm Variable Descriptions

Variable	Description
C	Sea ice concentration
TB	Observed brightness temperature
TO	Reference brightness temperatures for open water
TI	Reference brightness temperatures for sea ice

 

The Bootstrap algorithm uses two such combinations, 37 GHz H versus 37 GHz V and 19 GHz V versus 37 GHz V, denoted as HV37 and V1937, respectively. Points that fall within 5 K of the AD segment in a HV37 plot, corresponding roughly to concentrations greater than 90 percent, use this approach. Points that fall below the AD-5 line, use the V1937 relationship to derive the concentration. Slope and offset values for line segment AD were originally derived for each hemisphere for different seasonal conditions (Table 2 in Comiso et al, 1997). However, a newer formulation, employed in this CDR, was developed where slope and offsets are derived for each daily field based on the clustering within the daily brightness temperatures (Comiso and Nishio, 2008). For a detailed description of the Bootstrap algorithm, please see the Bootstrap Algorithm Web page.

CDR Algorithm

The NSIDC sea ice concentration CDR algorithm uses sea ice concentrations produced with the NASA Team and Bootstrap algorithms as input and merges them into a combined single concentration estimate based on the known characteristics of the NASA Team and Bootstrap algorithms. First, the Bootstrap 10 percent concentration threshold is used as a cutoff to define the limit of the ice edge. In other words, any grid cell showing a concentration of less than 10 percent is set to open water. Second, at each sea ice grid cell, the concentration value given by the NASA Team algorithm and that given by the Bootstrap algorithm are compared; whichever value is greater is selected as the CDR value. Both algorithms tend to underestimate concentration, but the source of this bias or error differs between algorithms.

The NASA Team algorithm, because it uses a ratio of brightness temperatures, tends to cancel out any physical temperature effects. The Bootstrap algorithm uses relationships between two brightness temperatures that are dependent on physical temperature. Thus, physical temperature changes can affect Bootstrap estimates. Errors occur primarily in regimes with very low temperatures: winter in the high Arctic and near the Antarctic coast (Comiso et al., 1997), where the Bootstrap algorithm can underestimate concentration and give a lower value than the NASA Team algorithm.

During winter conditions with more moderate temperatures, NASA Team concentrations also tend to have more of a low bias (Kwok, 2002; Meier, 2005). During melt conditions, both algorithms tend to underestimate concentration; but the effect is more pronounced in the NASA Team algorithm (Comiso et al., 1997; Meier, 2005; Andersen et. al, 2007).

While these characteristics of the algorithm are true in an overall general sense, ice conditions and algorithm performance can vary from grid cell to grid cell; and in some cases, this approach of choosing the larger value will result in an overestimation of concentration (Meier, 2005). However, using the higher concentration between the two algorithms will tend to reduce the overall underestimation of the CDR estimate. For a more in-depth discussion on the reasoning behind the algorithm, see the C-ATBD (Meier, W. N., et al., 2011a).

Data Processing Steps

Error Sources

Several studies over the years have assessed sea ice concentration estimates from the NASA Team and Bootstrap algorithms. These assessments have typically used coincident airborne or satellite remote sensing data from optical, thermal, or radar sensors, generally at a higher spatial resolution than the SSM/I instrument but with only local or regional coverage. Several assessments indicate an accuracy of approximately five percent during mid-winter conditions away from the coast and the ice edge (Steffen et al., 1992; Gloersen et al., 1993; Comiso et al., 1997; Meier et al., 2005; Andersen et al., 2007, Belchansky and Douglas, 2002). Other assessments suggest concentration estimates are less accurate. Kwok (2002) found that passive microwave overestimates open water by three to five times in winter. Partington et al. (2003) found a difference with operational charts that was relatively low in the winter, but rose to more than 20 percent in summer.

Researchers can assess and improve a CDR by comparing it with operational products — real-time products that help ships cross the sea ice. Absolute error can be approximated via comparison to operational sea ice products, such as those produced by the U.S. National Ice Center (NIC) or the Canadian Ice Service, but it is important to keep in mind that such products have an operational focus different from the climate focus of the CDR, and the two are not expected to be consistent with each other. The documentation for the daily Multi-sensor Analyzed Sea Ice Extent (MASIE), distributed by NSIDC in cooperation with NIC, gives a summary of how satellite passive microwave CDRs differ from operational products.

Errors can come from problems with the sensor, from weather effects, and from inadequacies in the algorithm. A satellite's orbit may drift over time, for example, which may degrade the data quality of an instrument. Most SSM/I instruments were used long past their designed lifetime expectancy. Atmospheric water vapor is a weather effect that can modulate the passive microwave signature of the surface, particularly at the 19 GHz frequency, causing ice concentration to be overestimated. The emissivity of sea water is generally stable, except under strong winds that cause waves to form. The emissivity of sea ice varies considerably depending on many factors including age, thickness, and surface roughness. When one considers that algorithms must arrive at a single number for ice concentration, taking into account the varying brightness temperatures of all the different surface types that may fill the footprints of the 19 GHz and 37 GHz channels, and that those footprints differ in size and shape across the instrument swath, one can appreciate the difficulty of the problem. Microwave Remote Sensing of Sea Ice, edited F. Carsey, provides a comprehensive overview of the subject (Carsey, 1992).

Another potential sensor error results from the transition between sensors on different platforms. The brightness temperature regression and tie-point adjustment corrects for this, though small artifacts remain (Cavalieri et al., 1999; Comiso and Nishio, 2008). Comparison of ice extent estimates from sensor overlap periods indicate that the adjustments yield agreements that are on the order of 0.05% or less and about 0.5% for sea ice area (Cavalieri et al., 1999; Cavalieri et al., 2011). Short overlap periods of early sensor transitions (SMMR to F-8 and F-8 to F-11) may not account for the full seasonal variability (Meier et al., 2011b; Cavalieri et al., 2011) and differences may be higher in some cases. However, differences appear to be well below the sensitivity of the instrument, thus, providing confidence in the robustness of the intercalibrated algorithms through the time series.

When melt ponds form on the surface of ice floes in the summer, the ice concentration appears to decline when in fact the true concentration may not have changed (Fetterer and Untersteiner, 1998). Melt state is a surface effect that may in itself contain a climate trend, which could influence sea ice concentration trend estimates. This and other concentration error sources have been examined to some extent in Andersen et al. (2007), and their influence appears to be small compared to the estimated sea ice trends, but such effects should be kept in mind when using these data.

The netCDF files contain a variable called qa_of_seaice_conc_cdr to help data users assess the quality of a given data value. Table 6 gives a list of the flags, their values, and their meaning. Values less than eight indicate that conditions for high error are not present — though errors could still be high — and also denotes the algorithm source (NASA Team or Bootstrap) or area covered by a climatological ocean mask. Values greater than or equal to eight indicate that conditions exist that could increase error, with higher values generally indicating greater uncertainty and hence less confidence in the CDR concentration estimate. Note: Grid cells that meet multiple conditions will have a value that is the sum of the values of each individual condition.

For a more complete description of error sources and assessments, see the C-ATBD (Meier, W., et al., 2011a).

Sensor or Instrument Description

For the NOAA/NSIDC CDR data (seaice_conc_cdr), NSIDC uses brightness temperatures from SSM/I sensors on the DMSP F-8, F-11, and F-13 platforms. See Table 11 for a description of orbital parameters of the different platforms. The rationale for using only these satellites was made to keep the equatorial crossing times as consistent as possible to minimize potential diurnal effects of data from sun-synchronous orbits of the DMSP satellites. Note that the SMMR sensor on the Nimbus-7 platform is used for the merged Goddard NASA Team/Bootstrap data (goddard_merged_seaice_conc), the Goddard NASA Team data (goddard_nt_seaice_conc), and the Goddard Bootstrap data (goddard_nt_seaice_conc) from 1978 to 1987.

Table 11. Comparison of Orbital Parameters

Parameter	Nimbus-7	DMSP-F8	DMSP-F11	DMSP-F13
Nominal Altitude*	955 km	860 km	830 km	850 km
Inclination Angle	99.1 degrees	98.8 degrees	98.8 degrees	98.8 degrees
Orbital Period	104 minutes	102 minutes	101 minutes	102 minutes
Ascending Node Equatorial Crossing (local time)	~ 12:00 p.m.	~ 6:00 a.m.	~ 5:00 p.m.	~ 5:43 p.m.
Algorithm Frequencies*	18.0, 37.0 GHz	19.4, 37.0 GHz	19.4, 37.0 GHz	19.4, 37.0 GHz
Earth Incidence Angle*	50.2	53.1	52.8	53.4
3 dB Beam Width (degrees)*	1.6, 0.8	1.9, 1.1	1.9, 1.1	1.9, 1.1

*Indicates sensor and spacecraft orbital characteristics of the three sensors used in generating the sea ice concentrations.

Table 12 lists the footprint size of the SSM/I instrument.

Table 12. SSM/I Footprint Size

Frequency (GHz)	SSM/I IFOV (km)
19.350	70 x 45
22.235	60 x 40
37.000	38 x 30

For a complete description of the SSM/I instrument see the NSIDC Special Sensor Microwave Imager (SSM/I) Web page. For a complete description of the different DMSP platforms, see the NSIDC DMSP Satellite F-8, F-11, and F-13 Web pages.

4. References and Related Publications

Andersen, S., R. Tonboe, L. Kaleschke, G. Heygster, and L. T. Pedersen. 2007. Intercomparison of Passive Microwave Sea Ice Concentration Retrievals over the High-Concentration Arctic Sea Ice. J. Geophys. Res., 112, C08004, doi:10.1029/2006JC003543.

Belchansky, G. I., and D. C. Douglas. 2002. Seasonal Comparisons of Sea Ice Concentration Estimates Derived from SSM/I, OKEAN, and RADARSAT Data. Rem. Sens. Environ., 81: 67-81.

Carsey, F. D. (Ed.). 1992. Microwave Remote Sensing of Sea Ice. American Geophysical Union, 462 pp.

Cavalieri, D. J., C. L. Parkinson. Arctic and Antarctic Sea Ice Concentrations from Multichannel Passive-Microwave Satellite Data Sets: October 1978 - September 1995 - User's Guide. NASA Technical Memorandum 104647. NASA Goddard Space Flight Center, Greenbelt, Maryland.

Cavalieri, D. J., P. Gloersen, and W. J. Campbell. 1984. Determination of Sea Ice Parameters with the NIMBUS-7 SMMR. J. Geophys. Res., 89(D4): 5355-5369.

Comiso, J. C., and F. Nishio. 2008. Trends in the Sea Ice Cover Using Enhanced and Compatible AMSR-E, SSM/I, and SMMR Data. J. of Geophys. Res., 113, C02S07, doi:10.1029/2007JC0043257.

Comiso, J. C., D. Cavalieri, C. Parkinson, and P. Gloersen. 1997. Passive Microwave Algorithms for Sea Ice Concentrations: A Comparison of Two Techniques. Rem. Sens. of the Environ., 60(3):357-384.

Comiso, J. C. 1986. Characteristics of Arctic Winter Sea Ice from Satellite Multispectral Microwave Observations. J. Geophys. Res., 91(C1): 975-994.

Eaton B., J. Gregory, H. Centre, B. Drach, K. Taylor, and S. Hankin. 2010. NetCDF Climate and Forecast (CF) Metadata Conventions Version 1.5. Programs for Climate Model Diagnosis and Intercomparison. 81 pp. http://cf-pcmdi.llnl.gov/documents/cf-conventions/1.5/cf-conventions.pdf. Accessed Sep. 2011.

Fetterer, F., and N. Untersteiner. 1998. Observations of Melt Ponds on Arctic Sea Ice. J. Geophys. Res., 103(C11): 24, 821-24, 835.

Gloersen, P., W. J. Campbell, D. J. Cavalieri, J. C. Comiso, C. L. Parkinson, and H. J. Zwally. 1993. Arctic and Antarctic Sea Ice, 1978-1987: Satellite Passive-Microwave Observations and Analysis. NASA Spec. Publ. 511, 290 pp.

Kwok, R. 2002. Sea Ice Concentration Estimates from Satellite Passive Microwave Radiometry and Openings from SAR Ice Motion. Geophys. Res. Lett., 29(9), 1311, doi:10.1029/2002GL014787.

Meier, W. N., M. Savoie, and S. Mallory. 2011a. CDR Climate Algorithm and Theoretical Basis Document: Passive Microwave Sea Ice Concentration. NOAA NCDC CDR Program.

Meier, W. N., and S. J. S. Khalsa. 2011b. Intersensor Calibration between F-13 SSM/I and F-17 SSMIS Near-Real-Time Sea Ice Estimates. Geoscience and Remote Sensing 49(9): 3343-3349.

Meier, W. N. 2005. Comparison of Passive Microwave Ice Concentration Algorithm Retrievals with AVHRR Imagery in Arctic Peripheral Seas. IEEE Trans. Geosci. Remote Sens., 43(6): 1324-1337.

Partington, K., T. Flynn, D. Lamb, C. Bertoia, and K. Dedrick. 2003. Late Twentieth Century Northern Hemisphere Sea-Ice Record from U.S. National Ice Center Ice Charts. J. Geophys. Res. 108(C11): 3343. doi:10.1029/2002JC001623.

Steffen, K., J. Key, D. J. Cavalieri, J. Comiso, P. Gloersen, K. St. Germain, and I. Rubinstein. 1992. The Estimation of Geophysical Parameters using Passive Microwave Algorithms, in "Microwave Remote Sensing of Sea Ice." F.D. Carsey, ed., American Geophysical Union Monograph 68, Washington, DC:201-231.

National Research Council of the National Academies. 2004. Climate Data Records from Environmental Satellites: Interim Report. National Academies Press, Washington, D.C., 150 pp.

Related NSIDC Data Collections

• DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures
• Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I Passive Microwave Data
• Bootstrap Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I
• Multi-sensor Analyzed Sea Ice Extent (MASIE)
• Sea Ice Index
• AMSR-E/Aqua Daily L3 12.5 km Brightness Temperatures, Sea Ice Concentration, & Snow Depth Polar Grids
• AMSR-E/Aqua Daily L3 25 km Brightness Temperatures & Sea Ice Concentration Polar Grids

Related Web Sites

• NOAA's National Climatic Data Center (NCDC) Climate Data Record (CDR) program
• EUMETSAT Ocean & Sea Ice Satellite Application Facility

6. Document Information

Acronyms and Abbreviations

Table 13 lists the acronyms used in this document.

Table 13. Acronyms

Acronym	Description
AMSR-E	Advanced Microwave Scanning Radiometer - Earth Observing System
C-ATBD	Climate Algorithm Theoretical Basis Document
CDR	Climate Data Record
CF	Climate and Forecast
DMSP	Defense Meteorological Satellite Program
FTP	File Transfer Protocol
GSFC	Goddard Space Flight Center
H	Horizontal
IDL	Interactive Data Language
MASIE	Multi-sensor Analyzed Sea Ice Extent
NAS	National Academy of Sciences
NASA	National Aeronautics and Space Administration
NCDC	National Climatic Data Center
NetCDF	Network Common Data Format
NIC	National Ice Center
NOAA	National Oceanic and Atmospheric Administration
NRC	National Research Council
NSIDC	National Snow and Ice Data Center
RSS	Remote Sensing Systems, Inc.
SMMR	Scanning Multichannel Microwave Radiometer
SSM/I	Special Sensor Microwave Imager
TB	Brightness Temperature
URL	Uniform Resource Locator
V	Vertical

Document Creation Date

July 2011

Document Revision Date

May 2012: A. Windnagel added the monthly file information and put the document into the new guide doc style.

Document URL

http://nsidc.org/data/docs/noaa/g02202_ice_conc_cdr/index.html