Education Center | Photo Gallery

Data Advanced Data Search More Data Discovery & Access Easy-to-use Data Products Data Collections Data Software & Programming Tools Data Submission Data News Centers & Programs Antarctic Glaciological Data Center Arctic System Science Data (ARCSS) IARC Frozen Ground Data Center International Polar Year Data & Information Service (IPYDIS) NOAA at NSIDC NASA's Distributed Active Archive Center at NSIDC (NSIDC DAAC) U.S. Antarctic Data Coordination Center World Data Center for Glaciology, Boulder Science Scientists Research Projects Publications NSIDC Notes Glaciological Data Series Special Reports Posters & Presentations Annual Reports Education Resources News & Events Press Room NSIDC In the News Data News Events About Expertise Data & Services NSIDC Sponsors Contacts Jobs Related Organizations

TOVS Pathfinder Path-P Daily Arctic Gridded Atmospheric Parameters

Summary

The TIROS-N Operational Vertical Sounder (TOVS) Polar Pathfinder (Path-P) consists of gridded daily and monthly Arctic atmospheric data derived from various NOAA satellites. TOVS Path-P daily files are available for Northern and Southern Hemispheres (from 60° poleward) at 100 km gridded spatial resolution in an Equal-Area Scalable Earth Grid (EASE-Grid). Daily Northern Hemisphere data are available from July 1979 through December 2005, and Southern Hemisphere data are through December 2001. Monthly Northern Hemisphere data are available from July 1979 through December 2004. Data were created from a modified version of the Improved Initialization Inversion Algorithm (3I) (Chedin et al. 1985), a physical-statistical retrieval method improved for use in identifying geophysical variables in snow- and ice-covered areas (Francis 1994).

Variables retrieved from satellite-observed radiances for this product include atmospheric temperature, water vapor, skin surface temperature, total effective cloud fraction, cloud top pressure and temperature, solar zenith elevation, surface pressure, turning angle between geostrophic wind and surface stress over ice, emissivity, boundary layer stratification and geostrophic drag coefficient. The algorithm used to generate these grids has been validated through comparisons with surface observations from the North Pole drifting meteorological stations (Schweiger et al. 1999).

These data were developed at the University of Washington's Applied Physics Laboratory with funding from Polar Exchange at the Sea Surface (POLES), a NASA EOS interdisciplinary project. For validation updates, or more information on POLES or the TOVS Polar Pathfinder project please see the TOVS Polar Pathfinder Web site (http://psc.apl.washington.edu/pathp/).

The complete TOVS data set in Hierarchical Data Format (HDF) is available via FTP in compressed annual tar files. Users may also order subsets of the data for any of the parameters listed above, or for specific spatial or temporal coverage. Subsetted data are available in binary format only through the Graphical Interface for Subsetting, Mapping, and Ordering (GISMO).

Data users are encouraged to register before accessing the TOVS data. Registered users automatically receive release notes via e-mail containing notification of data manipulation or formatting modifications.

Citing These Data

To broaden awareness of our services, NSIDC requests that you acknowledge the use of data sets distributed by NSIDC. Please refer to the citation below for the suggested form, or contact NSIDC User Services for further information. We also request that you send us one reprint of any publication that cites the use of data received from our Center. This helps us to determine the level of use of the data we distribute. Thank you.

Francis, J., and A. Schweiger. 1999, updated 2008. TOVS Pathfinder Path-P Daily Arctic Gridded Atmospheric Parameters. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media.

Overview Table

Table of Contents

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

1. Contacts and Acknowledgments

Investigator(s) Name and Title

Jennifer Francis
Institute of Marine and Coastal Sciences, Rutgers University
New Brunswick, New Jersey

Axel Schweiger
University of Washington, Applied Physics Laboratory - Polar Science Center
Seattle, Washington

Technical Contact

2. Detailed Data Description

The NOAA/NASA Pathfinder Program was initiated to provide scientists with global-scale remote sensing data ahead of NASA's Earth Observing System satellite launches. The Pathfinder concept involved careful reprocessing of existing data sets which could be made readily available as high quality products for global change research. Because the polar regions hold special significance in the climate system, the Polar Pathfinders have established a cooperation to maximize the scientific potential of their data sets.

The TIROS TOVS has flown on NOAA polar-orbiting satellites since 1978 and has generated one of the longest and most complete satellite data records in existence. Radiances from the global TOVS data set have been subsetted and processed for the Arctic region, and the retrieved products are presented on a regular grid in a user-friendly format.

The TOVS Path-P provides users with gridded daily Arctic atmospheric soundings. These data were obtained to identify geophysical parameters in snow- and ice-covered areas (Francis 1994). The data set has been designed to address the particular needs of the polar research community including quantities used to compute surface turbulent fluxes and to drive ocean models.

The modified 3I algorithm (Chedin et al. 1985) is applied to the TOVS high-resolution infrared radiation sounder (HIRS) and the microwave sounding unit (MSU) level-1b radiances to generate daily gridded Arctic atmospheric variables. (Radiances were obtained from the National Environmental Satellite Data Service Division and the National Center for Atmospheric Research.) The grids have a spatial resolution of 100 km, and use observations from areas poleward of 60° N and 60° S. The 3I method combines statistical and physical techniques to estimate these geophysical quantities, which are then averaged over a 24-hour period centered at 12:00 Coordinated Universal Time (UTC) to produce one Arctic-wide field per day. Estimates are then organized onto a rectangular grid using a "drop-in-the-bucket" approach.

The data are gridded to the EASE-Grid (Armstrong and Brodzik 1995) equal-area azimuthal projection centered on the North and South Poles. This facilitates combining TOVS data set with other data sets, and opens the door to studies using data from a variety of sources (such as SSM/I and AVHRR data).

The algorithm used to generate these atmospheric variables has been validated directly through comparisons with surface observations from the Coordinated Eastern Arctic Experiment (CEAREX), North Polar drifting station data, and with radiosonde data from Russian ice stations. Comparisons with other TOVS retrieval algorithms provided further validation.

Format

Data are stored in Hierarchical Data Format (HDF), developed by the National Center for Supercomputing Applications (NCSA), and they follow standards and recommendations outlined in the EOSDIS Version 0 Data Product Implementation Guidelines. TOVS Path-P data can be read by analysis tools capable of reading HDF data or using supplied sample programs.

Daily and monthly TOVS Path-P files are packaged into annual tar files, compressed with gzip. Each daily and monthly file contains a group of 16 HDF Scientific Data Sets. Metadata are implemented as global attributes containing information about the data set dates and times. Much of this information may not be relevant to the user, but it is included for production and archiving purposes. The metadata consist of 25 global attributes.

The grid dimensions of the sixteen Scientific Data Sets are 67 rows by 67 columns. Only two Scientific Data Sets are structured as three-dimensional arrays. The three-dimensional field TEMP has 10 levels in the vertical dimension, while WVAPOR has 5 layers. All data sets are represented as 32-bit floating point values.

TOVS data ordered through GISMO are stored in binary format as 4-byte floating point values. The grid dimensions are 67 rows by 67 columns. There is 1 file per parameter per day.

See Appendix A: Data Dictionary, and Appendix B: Geometry Class, for more information.

File and Directory Structure

Figure 1 displays the directory structure.

Figure 1. FTP Directory Structure

Note: the monthly Southern directory is empty.

File Naming Convention

The data files are named according to the following convention and as described in Table 1.

Where:

For example, tpp_s100_1987294_daily.v3-3.hdf or tpp_n100_200412_monthly.v3-4.hdf.

Daily and monthly data are packaged into annual tar files that are compressed with gzip for distribution and are named according to the following convention and as described in Table 2.

yyyy_Nss_H100.tar.gz

Where:

Note: 1991 data are from both N10 and N11 satellites; their file names are 1991_N10N11_H100.tar.gz., where H is the hemisphere.

For a binary subset of the data there is one file per day per parameter. The binary file names are prefixed with subset_ and end with an extension that reflects the parameter. For example, the file containing (version 3-3) northern, daily cloud fraction data for 10 April 1996 (day 100) is named subset_tpp_n100_1996100_daily.v3-3.FCLD., where the extension .FCLD indicates the cloud fraction parameter.

File Size

Northern Hemisphere daily files: 506,437 KB uncompressed
Southern Hemisphere daily files: 778,864 KB uncompressed
Northern Hemisphere monthly files: 506,443 KB uncompressed

Spatial Coverage

Northern Hemisphere files: 60° N to 90° N
Southern Hemisphere files: 60° S to 90° S

Spatial Resolution

Nominal grid spacing of the TOVS Path-P products is 100.2701 km. The TOVS EASE-Grid spacing is not exactly 100 km because the grid, originally designed for the 25 km Special Sensing Microwave/Imager (SSM/I), required a slightly larger actual cell size (C=25.067525 km) to exactly span the equator. For sake of data product consistency, this cell size was used for all other EASE-Grid products. Of course, few cells actually have these dimensions, but they all have the same area.

Projection

The north and south EASE-Grids are based on an equal area azimuthal projection, centered on the North and South Poles, respectively. Grid spacing of the TOVS products is 100.2701 km, resulting in a 67-row by 67-column grid size.

The grid coordinates, r and s, are defined with axes parallel to the rows (s) and columns (r) of the grid and units equal to the sampling interval. The grid sample locations (grid-cell centers) are then the integer coordinate points. The coordinate system starts at the top left corner with r increasing to the right, and s increasing downward. A grid cell (j,i) in the r,s coordinate system is defined as the area between grid coordinates i-0.5 and i+0.5, and j-0.5 and j+0.5. The lower bound is included in the grid cell, while the upper bound is not; i and j are zero-based array indices for this grid cell. This definition means that the grid cells are referenced in r and s by their grid cell center coordinate.

Figure 2 shows the equations to convert between latitude and longitude coordinates and r,s grid coordinates.

Figure 2. Equations to convert between latitude and longitude coordinates and r,s grid coordinates

Note: Latitude and longitude coordinates for each of the Path-P grid cells are included with the data set as well as elevation information and a land mask in an ancillary data file (tpp_n100_9999999_ancil.hdf).

Grid Description

The TOVS Path-P EASE-Grids are based on an azimuthal equal-area projection for the Northern and Southern Hemispheres, with a grid resolution of 100 km. Please see All about EASE-Grid for more information on the EASE-Grid projection parameters and grid definitions. For a better understanding of the relationship between the various Polar Pathfinder grids, please see the Summary of NOAA/NASA Polar Pathfinder Grid Relationships.

Temporal Coverage

This data set begins in July 1979 and continues through current processing. See the Overview Table at the top of this document for specific dates.

For some days, TOVS Level 1b data were either unavailable or of insufficient quality to ingest into the Path-P processing algorithm. When this occurred, files are available for these days but contain no data. As data become available from alternate satellites, these files will be updated. See Appendix C: Missing Data Files for a list of the missing data files.

Temporal Resolution

Daily data are linear averages of retrievals from all orbits for a single day, defined from 00:00:00 UTC to (excluding) 00:00:00 UTC of the following day. Users will also find files that are very small in size. Data were not available from NOAA for certain orbits but to maintain chronological integrity, files have been added as placeholders to complete the time series.

Parameter or Variable

Parameter Description

Table 3 summarizes the parameters in this data set.

WVAPOR
The weighting functions of the CO₂ absorption bands used by the TOVS retrieval algorithms limit the vertical resolution of the water vapor retrievals to 5 layers between the surface and 300 mb.

ISICE
Surface classifications may differ from orbit to orbit resulting in examples of daily averaged ice warmer than 273.15 K and water colder than 271.3 K.

SOLZEN
The solar zenith angle is the integral from sunrise to sunset divided by the time from sunrise to sunset. This integral is not just a function of solar zenith angle but also a function of day length.

PBLSTRAT
the bulk stratification parameter is defined as the difference in potential temperature between the 1000 and 900 mb levels. It provides a measure of the boundary layer stability. This value tends to be more negative during the winter when surface inversions are common in the Arctic, than in warmer months.

PBLSTRAT is used to compute the geostrophic drag coefficient and a surface stress turning angle based on the parameterization developed by Overland and Davidson (1992) and Overland and Colony (1994). These parameters are useful for estimating near-surface winds, surface stress, and turbulent fluxes.

PBLSTRAT describes the difference in potential temperature between the 1000 and 900 mb levels, and provides a bulk measure of the stratification in the atmospheric boundary layer. In grid boxes with a sea-ice surface, this value is used to compute Cg, the geostrophic drag coefficient, and ALPHA, the turning angle between the geostrophic wind and the surface stress, using an empirically derived relationship.

Cg
The geostrophic drag coefficient can vary in space and time by a factor of 2 owing to differences in the strength of near-surface temperature inversion. Thus, large spatial variations in Cg may occur and correspond to surface pressure features.

SKTEMP
Surface skin temperature is the radiating temperature of the surface, which may differ from the actual surface temperature if the surface emissivity is less than unity. For more information see Francis and Schweiger 1999.

HIRS_CLDY and FCLD
Two measures of cloud fraction are available within a grid box. The first, FCLD or the effective cloud fraction, is the product of the cloud cover in a grid box and cloud emissivity. Although useful for some studies, it proves difficult to validate with surface observations when clouds are not optically thick in the infrared spectral region. Thin clouds are common in the Arctic, thus FCLD and HIRS_CLDY, the fraction of HIRS fields-of-view within a grid box that are identified as cloudy, can be significantly different from each other.

Most of the products listed above are standard atmospheric variables, but a few, surface skin temperature, cloud fraction and the potential temperature between 1000 and 900 mb, were added specifically for polar research and require some explanation.

Additional Note

Designed so that all parameters are filtered by elevation, the modified 3I algorithm (Chedin et al. 1985) causes footprints with surface elevations of 1000 meters or more to be marked as missing for all parameters. (Consequently, most of Greenland's ice appears as missing.) For elevations less than 1000 m, a daily average is computed across all footprints and orbits for that grid cell. The footprint location changes with each scan, for each pass, although all footprint locations fall within the same grid box. As such, elevations appear to vary greatly from day to day. Users may apply the elevation mask provided to ensure the same area is masked every day.

The reason the retrieval is limited to elevations less than 1000 m is that the weighting functions for some of the channels that peak low in the atmosphere become window channels over high elevations (peak of weighting function at the surface), and the algorithm doesn't take this into account, especially over the high ice sheets of Greenland and Antarctica. Thus, to be on the safe side, retrievals above 1000m were excluded.

The sample file below is composed of sensor data from nine satellite orbits. Each orbit is composed of up to 2500 individual sensor scans, along the orbital track. Each scan contains parameter values and location information for the footprint. Throughout the day, a particular grid cell may be passed over a number of times. For example, four passes occurred in the sample below. Choosing a grid cell location of column 17 and row 45, the following are orbital data for this day, per orbit:

               lat  long  column   row   elevation   orbit   scan number 
               72   -53     17      45     597        2       604 
               72   -54     17      45     428        3       498 
               72   -52     17      45     993        4       143 
               72   -52     17      45     858        5       477 

Sample Data Record

Figure 3 shows sample images for the available data parameters and sample data values from 10 April 1996 (tpp_n100_1996100_daily.v3-3.hdf). For the binary subset version there is one file per day per parameter. The binary file names are prefixed with subset_ and end with an extension that reflects the parameter. For example, the file containing cloud fraction data for 10 April 1996 (day 100) is named: subset_tpp_n100_1996100_daily.v3-3.FCLD.

Geostrophic Wind	Geostrophic Drag Coefficient	Cloudtop Pressure	Cloudtop Temperature	Surface Emissivity	Cloud Fraction
HIRS Pixel	Surface Type	Boundary Layer Stratification	Temperature at 50 Mb	Temperature at 70 Mb	Temperature at 100 Mb
Temperature at 300 Mb	Temperature at 400 Mb	Temperature at 500 Mb	Temperature at 600 Mb	Temperature at 700 Mb	Temperature at 850 Mb
Temperature at 900 Mb	Water Vapor at 300 Mb	Water Vapor at 400 Mb	Water Vapor at 500 Mb	Water Vapor at 700 Mb	Water Vapor at 850 Mb
Figure 3. Sample Images for Available Data Parameters and Sample Data Values from 10 April 1996 (tpp_n100_1996100_daily.v3-3.hdf)

Sample Values from HDF or Binary Data Files -
(Row 32, Column 28 for IDL or C programs;
 Row 33, Column 29 for Fortran programs)

TEMP-50        226.683
TEMP-70        225.740
TEMP-100        224.263
TEMP-300        219.452
TEMP-400        230.288
TEMP-500        240.738
TEMP-600        248.602
TEMP-700        254.337
TEMP-850        258.343
TEMP-900        258.722
WVAPOR-300      0.0600000
WVAPOR-400      0.190000
WVAPOR-500      1.30500
WVAPOR-700        1.63000
WVAPOR-850        1.61500
SKTEMP        251.050
HIRS_CLDY        55.3333
FCLD        106.750
CLPRESS        568.750
CLTEMP        247.292
EMISS       0.751667
ISICE        1.00000
SOLZEN        82.3043
PRESS        1024.21
PBLSTRAT       -16.3351
Cg      0.0265637
ALPHA        26.2023

Error Sources

Users should be aware of potential inter-satellite calibration problems. Removal of such systematic biases required the development of an automatic correction scheme. The correction procedure used satellite and radiosonde data sets from NOAA/NESDIS as inputs to the forward model to accurately account for and eliminate biases caused by the radiative transfer model, the instrument or unexpected events, such as the Mt. Pinatubo eruption. However, this method may not fully address all of the inter-satellite calibration problems.

Some of the files provided contain no data when data from the chosen satellite could not be supplied. These files remain as placeholders to be filled using data from alternate satellites as it becomes available. See Appendix C: Missing Data Files for a list of the missing data files.

Other Known Problems

• Elevation and surface type may vary from orbit to orbit, as reported by the satellites. Because surface classifications may differ from orbit to orbit, grid cells classified as ice may have temperatures warmer than freezing, and grid cells classified as water may have temperatures colder than freezing. Examples:

  Ice temperature warmer than freezing (272°K):
  
    Date          Row       Column      ISICE       SKTEMP
  -------         ---       ------     -------      -------
  1997172          11         37       1.00000      280.900
  1997190          23         49       1.00000      289.900
  1998199          37         52       1.00000      292.500
  
  Water temperature colder than freezing (272°K):
    Date          Row       Column      ISICE        SKTEMP
  -------         ---       ------     -------      -------
  1997021          37          26      0.00000      248.700
  1997318          27          20      0.00000      252.040
  1998294          54          21      0.00000      257.500
  

• The cloud parameter value (FCLD) may be unrealistically high because no upper bound is imposed to ensure that the data are not artificially biased when averaged. Values of 199 have been observed, which may indicate the occurrence of only one retrieval with a value of 199 percent, or that all retrievals had values near 200 percent.
   
• The boundary layer stratification (PBLSTRAT) data may have unrealistically large values. Most, but not all, of these values were filtered out.
   
• A few instances have been noticed where the cloud top pressure (CLPRESS) is greater than the surface pressure, sometimes by more than 5mb. Example:

  Surface Pressure less than cloud pressure:
   Date           Row       Column     CLDPRS       SURFACE PRESS
  -------         ---       ------     -------      -------
  1997010          47          46      976.750      969.586
  1998087          64          24      984.000      982.692
  1998351          61          23      984.000      974.951
  

• The Southern Hemisphere grids reveal some false sea ice, which is likely caused by poor weather/cloud filtering.

Quality Assessment

The algorithm used to generate these grids has been validated directly through comparisons with surface observations from the CEAREX experiment and with radiosonde data from Soviet ice stations. Comparisons with other TOVS retrieval algorithms provided further validation. Additionally, Schweiger et al. (1999) found a strong correlation between the TOVS Path-P data and surface cloud observations obtained from the North Polar drifting meteorological stations, which indicates that the TOVS data effectively represent annual cloud cover. Table 4 provides an initial assessment of the accuracy of some variables included in the Path-P products. Not all variables could be verified and validation of the following Path-P variables has been performed only for sea level.

Validation of TOVS data is ongoing. For validation updates or more information please visit the TOVS Polar Pathfinder Web site at the University of Washington's Applied Physics Laboratory.

3. Data Access and Tools

Data Access

Data are available via FTP. Data users are encouraged to register before accessing the TOVS data. Users can also order TOVS data through a subsetting tool, GISMO.

Software and Tools

To accompany the recently released Polar Pathfinder Product, NSIDC created an Interactive Data Language (IDL) tutorial that may also be used to browse TOVS Path-P data files. (The IDL tools have been tested in unix-based environments but have not been tested on PCs.) Additionally, Fortran and C programs for reading Path-P daily data files have been provided by the University of Washington. Both the IDL tutorial and the software programs are available on the FTP site. A static ancillary HDF data file, tpp_n100_9999999_ancil.hdf (in the TOOLS directory on the FTP site) provides elevation, latitude, longitude, and land mask data.

Users preferring to extract the TOVS Path-P data from HDF will find tools at the NCSA Web site.

Related Data Collections

Polar Pathfinder Sampler: Combined AVHRR, SMMR-SSM/I, and TOVS Time Series and Full-Resolution Samples

4. Data Acquisition and Processing

Source or Platform Description

The TOVS scanner was flown aboard several NOAA Polar Operational Environmental Satellites (POES), as shown in Table 5.

Sensor or Instrument Description

The TOVS scanner aboard the NOAA polar orbiters includes three sensors, the HIRS/2, MSU and Stratospheric Sounding Unit (SSU). The MSU is a scanning microwave radiometer with four channels in the 50 to 60 GHz oxygen region. The MSU sensors consist of two four-inch diameter antennas, each having an instantaneous field of view (IFOV) of 7.5 degrees.

The 109-km IFOV resolution at nadir creates an underlap, or gap, of approximately 115 km between adjacent scan lines. The MSU data output represents uncorrected brightness temperatures after a 1.84 second integration period (i.e., how long the instrument collects signal from a given position) per step of the scanning antenna.

The MSU has no special calibration sequence to interrupt normal scanning. Calibration data are included in a scan line of data. Each MSU data set normally contains an individual satellite recorder playback. Data with each MSU data set are in chronological order with one record for each MSU scan.

HIRS is a 20 channel scanning radiometer with channels in the 15 micrometer and four micrometer regions. The data are recorded onboard satellite for readout on command. TOVS data are used operationally by NESDIS to produce vertical profiles of temperature and moisture, and to derive other atmospheric variables.

SSU data are not used for this data set.

A summary of the HIRS and MSU instruments' parameters is given in Table 6.

For more instrument information see the NOAA Polar Orbiter Data Users Guide.

Data Source

TOVS level 1b radiances for the regions poleward of 60° N and 60° S were obtained from the Satellite Data Services Division (SDSD) of the National Oceanographic and Atmospheric Administration (NOAA) and from the National Center for Atmospheric Research (NCAR). Level 1b data files contain raw, quality-controlled radiances as well as calibration and navigation information (Francis 1994).

Derivation Techniques and Algorithms

"The 3I algorithm uses HIRS and MSU measurements to deduce the three-dimensional thermal structure of the atmosphere through inversion of the radiative transfer equation. Physical inversion methods consist of solving the radiative transfer equation iteratively until agreement is found between observed and calculated radiances. The 3I algorithm improves upon other iterative methods by including more physics than do purely statistical models. For this application distinctly polar characteristics and the unique physical aspects of snow and ice have been considered. The 3I algorithm also makes use of a library (called TIGR, TOVS Initial Guess Retrieval) of some 1800 atmospheric profiles culled from a global set of more than 150,000 radiosonde measurements. The library acts as a "look-up" table, speeding the computational process. To build the library, a forward radiative transfer model was developed for each of the 1800 profiles and used to calculate brightness temperatures for each HIRS and MSU channel, the Jacobians of the partial derivatives of the radiances B with respect to temperature T and moisture q at each level, and the temperature and radiance means and covariance matrices. Calculations were performed for 10 viewing angles, 19 surface pressures, and two surface emissivities." (Francis 1994)

Processing Steps

Below are the steps used in the data retrieval process:

• Navigate and calibrate the radiances.
• Detect clouds and remove their effects.
• Select the first-guess profile from TIGR and retrieve final temperature profile.
• Retrieve cloud-top pressure and cloud fraction.
• Retrieve relative humidity, surface temperature, and total precipitable water.

For elevations greater than 1000 meters, all parameters are marked as bad for that orbit. Since each orbital footprint has a unique position, and though several orbits may fall into the same 100 x 100 grid cell, their elevation information is coming from different parts of that cell, and therefore giving different elevations. Thus, regions defined as being higher than 1000 meters vary from day to day due to varying satellite input data.

5. References and Related Publications

Armstrong, R. L. and M. J. Brodzik. 1995. An Earth-gridded SSM/I data set for cryospheric studies and global change monitoring. Adv. Space Res. 16:155-63.

Brodzik, M. J. 1998. The EASE-Grid, A Versatile Set of Equal-Area Projections and Grids. Special report to the National Snow and Ice Data Center, Boulder, CO.

Brodzik, M. J. 1998. Summary of NOAA/NASA Polar Pathfinder Grid Relationships. Special report to the National Snow and Ice Data Center, Boulder, CO.

Chedin, A., N. A. Scott, C. Wahiche, P. Moulineier. 1985. The Improved Initialization Inversion Method: A high resolution physical method for temperature retrievals from satellites of the TIROS-N series. Journal of Climate and Applied Meteorology pp. 62-65.

Chiaachio, M., J. Francis, and P. W. Stackhouse, Jr. 1998. Evaluation and development of nighttime Arctic cloud base algorithms for CERES. American Meteorological Society 5th Conference on Polar Meteorology and Oceans. pp. 300-05.

Francis, J., A. Munchow, and R. Cermak. 1998. Analyses of long-term 10-meter winds over the Arctic Basin. American Meteorological Society 5th Conference on Polar Meteorology and Oceans. pp. 66-68.

Francis, J. and A. Schweiger. 1999. A new window to the Arctic. Journal of Climate 12(8) (August): 2189-2213, Part I.

Francis, J. A. 1994. Improvements to TOVS retrievals over sea ice and applications to estimating Arctic energy fluxes. Journal of Geophysical Research 99(D5):10,395-408.

Francis, J. and A. Schweiger. 1998. The NASA/NOAA TOVS Polar Pathfinder: 18 Years of Arctic data. American Meteorological Society 5th Conference on Polar Meteorology and Oceans. 24:128-43.

Francis, J. A. 1994. Improvements to TOVS retrievals over sea ice and applications to estimating Arctic energy fluxes. Journal of Geophysical Research 99(D5):10,395-408.

Goddard Space Flight Center. 1994. EOSDIS Version 0 Data Product Implementation Guidelines. Draft Version 1.0 (March 1, 1994). GSFC 50-003-04. GSFC. Greenbelt, MD.

Groves, D. G. 1998. A new moisture budget of the Arctic atmosphere derived from 19 years of daily TOVS satellite moisture retrievals and NCEP reanalysis winds. American Meteorological Society 5th Conference on Polar Meteorology and Oceans. pp. 107-12.

Groves, D. G. 1998. Temporal variability of Arctic atmospheric moisture budget quantities derived from daily TOVS satellite moisture retrievals and NCEP reanalysis winds. American Meteorological Society 5th Conference on Polar Meteorology and Oceans. pp. 380-82.

Key, J., D. Slayback, C. Xu, and A. Schweiger. 1998. New climatologies of polar clouds and radiation based on the ISCCP "D" products. American Meteorological Society 5th Conference on Polar Meteorology and Oceans. pp. 227-32.

National Center for Supercomputing Applications. 1994. HDF Reference Manual. Version 3.3. University of Illinois at Urbana-Champaign.

National Oceanic and Atmospheric Administration. 1991. NOAA polar orbiter data users guide. Washington, D.C.: National Environmental Satellite, Data and Information Service, National Climatic Data Center Satellite Data Services Division.

Overland, J. E., and R. L. Colony. 1994. Geostrophic drag coefficients over the central Arctic derived from Soviet drifting station data. Tellus. 46(A):75-85.

Overland, J. E., and K. L. Davidson. 1992. Geostrophic drag coefficients over sea ice. Tellus. 44(A):54-66.

Schweiger, A. J., R. W. Lindsay, J. R. Key, and J. A. Francis. 1999. Arctic clouds in multiyear satellite data sets. Geophysical Research Letters 26(13):1,845-48. Document is also available online at http://www.agu.org/GRL/articles/1999GL900479/GL841W01.pdf .

Schweiger A., C. Fowler, J. Key, J. Maslanik, J. Francis, R. Armstrong, M. J. Brodzik, T. Scambos, T. Haran, M. Ortmeyer, S. Khalsa, D. Rothrock, R. Weaver. 1998. P-Cube: A multi-sensor data set for polar climate research. American Meteorological Society 5th Conference on Polar Meteorology and Oceans. pp. 136-141.

Schweiger, A., Francis, J. 1994. TOVS Pathfinder Path-P Gridded Daily and Monthly Arctic Atmospheric Data from TOVS User's Guide. Draft version 0.1. University of Washington, Seattle.

Schweiger, A. J., R. W. Lindsay, J. A. Francis, J. R. Key, J. Intrieri, M. Shupe. Validation of TOVS Path-P data during SHEBA. Submitted to Journal of Geophysical Research, May 2000. (http://psc.apl.washington.edu/pathp/html/publications/papers_list.html#S2000)

Stubenrauch, C. J, W. B. Rossow, F. Cheruy, A. Chedin and N. A. Scott. 1999. Clouds as seen by satellite sounders (3) and imagers (ISCCP), Part I. Evaluation of Cloud Parameters. Journal of Climate 12 (8) (August): 2189-2213.

6. Document Information

Acronyms and Abbreviations

Table 7 lists acronyms used in this document.

Document Creation Date

September 1999

Document Revision History

July 2008
August 2006

Document URL

http://nsidc.org/data/docs/daac/nsidc0027_tovs.gd.html