4 km NODC/RSMAS AVHRR Pathfinder Version 5 Seasonal and Annual Day-Night Sea Surface Temperature Climatologies for 1982-2009 for the Gulf of Mexico (NODC Accession 0072888)

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Frequently anticipated questions:


What does this data set describe?

Title:
4 km NODC/RSMAS AVHRR Pathfinder Version 5 Seasonal and Annual Day-Night Sea Surface Temperature Climatologies for 1982-2009 for the Gulf of Mexico (NODC Accession 0072888)
Abstract:
The 4 km Pathfinder effort at the National Oceanic and Atmospheric Administration (NOAA) National Oceanographic Data Center (NODC) and the University of Miami's Rosenstiel School of Marine and Atmospheric Science (RSMAS) is an extension of and improvement on the sea surface temperature (SST) fields from the NOAA/NASA AVHRR Oceans 9km Pathfinder dataset. In this 4 km Pathfinder project, some important shortcomings in the original 9 km data have been corrected, and the entire time series has been reprocessed at the 4 km Global Area Coverage (GAC) level, the highest resolution possible globally. These Gulf of Mexico seasonal and annual climatologies were produced from 5-day averaged Pathfinder AVHRR SST data from 1982-2009, which are archived at the National Oceanographic Data Center (<http://www.nodc.noaa.gov/>) under separate accession numbers. The climatologies are available as 32-bit Tagged Image File Format (.TIFF) data files for 1982-2009 and include seasonal and yearly time periods. The climatologies are also included as Arc Grid (.mxd) and .PNG layers with associated legends for user convenience and were assigned projection GCS_WGS_1984. An additional subdirectory contains the annual mean, season 1 (Jan-Mar) mean, season 2 (Apr -June) mean, season 3 (Jul - Sept) mean, and season 4 (Oct-Dec) mean as color-classified .PNG images with a matching shape file that were developed for use in online visualizations.
Supplemental_Information:
The time series of 5-day SST averages used to create these seasonal and annual climatologies was created by averaging original twice-daily Pathfinder data of quality flags 4-7 only into 5-day temporal bins for 1982-2009. The original twice-daily Pathfinder data was computed using the Version 5 Pathfinder algorithm. This algorithm is an improved version of the University of Miami Pathfinder version v4.2 SST algorithm (described fully in Kilpatrick et al., 2001). The v4.2 algorithm offered marked improvement over operational retrieval algorithms such as MCSST and was applied to AVHRR data to maximize accuracy and to minimize artificial fluctuations arising from the sequence of AVHRR instruments flown on NOAA's polar-orbiting satellites during the past 2 decades. The 9 km v4.2 Pathfinder SSTs were shown to be the highest quality product currently available for the construction of global climatologies (Casey and Cornillon, 1999) and longer-term SST trend determination (Casey and Cornillon, 2001), and were demonstrated to be accurate within about 0.3 degrees C under optimal conditions (Kearns et al., 2000). Relative to the older 9 km v4.2 Pathfinder data, the new, ~ 4 km resolution Pathfinder Version 5 global SSTs increase detail by a factor of four simply by virtue of the increased resolution. The increase in detail over widely used but relatively coarse SST data sets such as Optimally Interpolated SST Version 2 (OISSTv2; Reynolds et al., 2002) and the Hadley Centre's Global Sea Ice and SST (HadISST1; Rayner et al., 2003) is far greater. In addition to the increased resolution, significant improvements have been made in the Version 5 which enhance the usefulness of the SST fields. Currently, these enhancements include the use of sea ice in the quality level determination scheme, inclusion of many inland water bodies, and the use of a greatly improved land mask. The greatest improvements are seen in coastal zones, marginal seas, and boundary current regions where SST gradients are often large and their impact on operational or research products is greatest. Separate SST products for daytime and nighttime AVHRR retrievals are made to better understand the differences in skin and bulk temperatures, since mean differences between AVHRR-measured skin temperatures and bulk temperatures of 0.1 to 0.2 degrees C (Schluessel et al., 1990) and locally varying differences of up to 1.8 degrees C (Minnett et al., 2000) have been observed. The following is information to be used when the seasonal climatology geotiff files: Geotiff_Information: Version: 1 Key_Revision: 1.0 Tagged_Information: ModelTiepointTag (2,3):0 0 0-180 90 0 ModelPixelScaleTag (1,3):0.0439453 0.0439453 0 End_Of_Tags. Keyed_Information: GTModelTypeGeoKey (Short,1): ModelTypeGeographic GTRasterTypeGeoKey (Short,1): RasterPixelIsArea GTCitationGeoKey (Ascii,17): 'LONG/LAT E005' GeographicTypeGeoKey (Short,1): GCS_WGS_84 GeogAngularUnitsGeoKey (Short,1): Angular_Degree ProjLinearUnitsGeoKey (Short,1): Linear_Meter End_Of_Keys. End_Of_Geotiff. GCS: 4326/WGS 84 Datum: 6326/World Geodetic System 1984 Ellipsoid: 7030/WGS 84 (6378137.00,6356752.31) Prime Meridian: 8901/Greenwich (0.000000/ 0d 0' 0.00""E) Projection Linear Units: 9001/metre (1.000000m) Corner Coordinates:Upper Left (180d 0' 0.00"W, 90d 0' 0.00"N) Lower Left (180d 0' 0.00"W, 90d 0' 0.00"S) Upper Right (180d 0' 0.00"E, 90d 0' 0.00"N) Lower Right (180d 0' 0.00"E, 90d 0' 0.00"S) Center ( 0d 0' 0.00"E, 0d 0' 0.00"N)

A separate land mask developed from the Global Self-Consistent High-Resolution Shoreline Database (GSHHS v 2.2.0, Wessel and Smith, 2011) is included with the data files. The color-classified versions of the climatologies were developed for use in visual online applications and are annual and seasonal means only.

  1. How should this data set be cited?

    Kenneth S. Casey, National Oceanic and Atmospheric Administration (NOAA) National Oceanographic Data Center (NODC), and Edward J. Kearns, Vicki Halliwell, and Robert Evans, University of Miami, Rosenstiel School of Marine and Atmospheric Science (RSMAS), 20060920, 4 km NODC/RSMAS AVHRR Pathfinder Version 5 Seasonal and Annual Day-Night Sea Surface Temperature Climatologies for 1982-2009 for the Gulf of Mexico (NODC Accession 0072888): not applicable Pathfinder Version 5.0, NOAA National Oceanographic Data Center, Silver Spring, Maryland, USA.

    Online Links:

  2. What geographic area does the data set cover?

    West_Bounding_Coordinate: -98.68
    East_Bounding_Coordinate: -78.9
    North_Bounding_Coordinate: 31.97
    South_Bounding_Coordinate: 17.03

  3. What does it look like?

    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_amax_Climatology.jpg> (JPG)
    1982-2009 maximum SST(Annual)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_amean_Climatology.jpg> (JPG)
    1982-2009 average SST(Annual)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_amin_Climatology.jpg> (JPG)
    1982-2009 minimum SST(Annual)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_aobs_Climatology.jpg> (JPG)
    1982-2009 total number of Observations(Annual)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_astd_Climatology.jpg> (JPG)
    1982-2009 standard deviations(Annual)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s1max_Climatology.jpg> (JPG)
    1982-2009 maximum SST(January to March)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s1mean_Climatology.jpg> (JPG)
    1982-2009 average SST(January to March)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s1min_Climatology.jpg> (JPG)
    1982-2009 minimum SST(January to March)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s1obs_Climatology.jpg> (JPG)
    1982-2009 total number of Observations(January to March)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s1std_Climatology.jpg> (JPG)
    1982-2009 standard deviations(January to March)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s2max_Climatology.jpg> (JPG)
    1982-2009 maximum SST(April to June)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s2mean_Climatology.jpg> (JPG)
    1982-2009 average SST(April to June)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s2min_Climatology.jpg> (JPG)
    1982-2009 minimum SST(April to June)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s2obs_Climatology.jpg> (JPG)
    1982-2009 total number of Observations(April to June)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s2std_Climatology.jpg> (JPG)
    1982-2009 standard deviations(April to June)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s3max_Climatology.jpg> (JPG)
    1982-2009 maximum SST(July to September)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s3mean_Climatology.jpg> (JPG)
    1982-2009 average SST(July to September)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s3min_Climatology.jpg> (JPG)
    1982-2009 minimum SST(July to September)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s3obs_Climatology.jpg> (JPG)
    1982-2009 total number of Observations(July to September)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s3std_Climatology.jpg> (JPG)
    1982-2009 standard deviations(July to September)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s4max_Climatology.jpg> (JPG)
    1982-2009 maximum SST(October to December)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s4mean_Climatology.jpg> (JPG)
    1982-2009 average SST(October to December)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s4min_Climatology.jpg> (JPG)
    1982-2009 minimum SST(October to December)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s4obs_Climatology.jpg> (JPG)
    1982-2009 total number of Observations(October to December)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/JPG_browse_graphics/SST_1982-2009_s4std_Climatology.jpg> (JPG)
    1982-2009 standard deviations(October to December)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/amax.png> (png)
    1982-2009 maximum SST(Annual)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/amean.png> (png)
    1982-2009 average SST(Annual)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/amin.png> (png)
    1982-2009 minimum SST(Annual)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/aobs.png> (png)
    1982-2009 total number of Observations(Annual)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/astd.png> (png)
    1982-2009 standard deviations(Annual)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s1max.png> (png)
    1982-2009 maximum SST(January to March)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s1mean.png> (png)
    1982-2009 average SST(January to March)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s1min.png> (png)
    1982-2009 minimum SST(January to March)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s1obs.png> (png)
    1982-2009 total number of Observations(January to March)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s1std.png> (png)
    1982-2009 standard deviations(January to March)</
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s2max.png> (png)
    1982-2009 maximum SST(April to June)</
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s2mean.png> (png)
    1982-2009 average SST(April to June)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s2min.png> (png)
    1982-2009 minimum SST(April to June)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s2obs.png> (png)
    1982-2009 total number of Observations(April to June)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s2std.png> (png)
    1982-2009 standard deviations(April to June)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s3max.png> (png)
    1982-2009 maximum SST(July to September)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s3mean.png> (png)
    1982-2009 average SST(July to September)</
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s3min.png> (png)
    1982-2009 minimum SST (July to September)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s3obs.png> (png)
    1982-2009 total number of Observations(July to September)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s3std.png> (png)
    1982-2009 standard deviations(July to September)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s4max.png> (png)
    1982-2009 maximum SST(October to December)</
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s4mean.png> (png)
    1982-2009 average SST(October to December)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s4min.png> (png)
    1982-2009 minimum SST(October to December)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s4obs.png> (png)
    1982-2009 total number of Observations(October to December)
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_GOM_PNG/s4std.png> (png)
    1982-2009 standard deviations(October to December)</
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_means_GOM_color_classified_layers/PNG/amean.png> (PNG)
    For these data, in subdirectory SST_means_GOM_color_classified_layers/PNG. File displays Pathfinder v5 GOM climatology as a color classified layer and was developed primarily for online use and visual displays.
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_means_GOM_color_classified_layers/PNG/s1mean.png> (PNG)
    For these data, in subdirectory SST_means_GOM_color_classified_layers/PNG. File displays Pathfinder v5 GOM climatology as a color classified layer and was developed primarily for online use and visual displays.
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_means_GOM_color_classified_layers/PNG/s2mean.png> (PNG)
    For these data, in subdirectory SST_means_GOM_color_classified_layers/PNG. File displays Pathfinder v5 GOM climatology as a color classified layer and was developed primarily for online use and visual displays.
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_means_GOM_color_classified_layers/PNG/s3mean.png> (PNG)
    For these data, in subdirectory SST_means_GOM_color_classified_layers/PNG. File displays Pathfinder v5 GOM climatology as a color classified layer and was developed primarily for online use and visual displays.
    <http://www.nodc.noaa.gov/archive/arc0033/0072888/3.3/data/0-data/SST_means_GOM_color_classified_layers/PNG/s4mean.png> (PNG)
    For these data, in subdirectory SST_means_GOM_color_classified_layers/PNG. File displays Pathfinder v5 GOM climatology as a color classified layer and was developed primarily for online use and visual displays.

  4. Does the data set describe conditions during a particular time period?

    Beginning_Date: 01-Jan-1982
    Beginning_Time: Unknown
    Ending_Date: 31-Dec-2009
    Ending_Time: Unknown
    Currentness_Reference: publication date

  5. What is the general form of this data set?

    Geospatial_Data_Presentation_Form: GeoTIFF version 2.4

  6. How does the data set represent geographic features?

    1. How are geographic features stored in the data set?

      This is a Raster data set. It contains the following raster data types:

      • Dimensions 340 x 450 x 1, type Grid Cell

    2. What coordinate system is used to represent geographic features?

      Horizontal positions are specified in geographic coordinates, that is, latitude and longitude. Latitudes are given to the nearest 0.0439453125. Longitudes are given to the nearest 0.0439453125. Latitude and longitude values are specified in Decimal Degrees.

      The horizontal datum used is WGS84.
      The ellipsoid used is WGS84.
      The semi-major axis of the ellipsoid used is 6378137.
      The flattening of the ellipsoid used is 1/298.257223563.

  7. How does the data set describe geographic features?

    1982-2009 SST Day-Night Climatologies for the Gulf of Mexico
    1982-2009 seasonal and yearly day-night sea surface temperature climatologies for the periods of Jan-Mar, Apr-Jun, Jul-Sep, and Oct-Dec, and (for yearly), Jan-Dec. (Source: NOAA National Oceanographic Data Center/Satellite Oceanography Group)

    Latitude
    The angular distance between an imaginary line around the earth parallel to its equator and the equator itself; North latitude values range from 0-90 degrees, South latitude values range from 0 to -(-)90 degrees (Source: <http://www.cogsci.princeton.edu>)

    Range of values
    Minimum:17.03
    Maximum:31.97
    Units:decimal degrees
    Resolution:0.000000001

    Longitude
    Longitude is measured from the Prime Meridian (the longitude that runs through Greenwich, England), with positive values going east (0-180 degrees) and negative values going west (0-(-)180 degrees. (Source: <http://jwocky.gsfc.nasa.gov/>)

    Range of values
    Minimum:-98.68
    Maximum:-78.9
    Units:decimal degrees
    Resolution:0.0000000001

    Sea Surface Temperature (SST)
    SST is a difficult parameter to define exactly because the upper ocean (~10 m) has a complex and variable vertical temperature structure that is related to ocean turbulence and the air-sea fluxes of heat, moisture and momentum. Definitions of SST provide a necessary theoretical framework that can be used to understand the information content and relationships between measurements of SST made by different instruments. The following explanatory statements attempt to provide this framework and encapsulate the effects of the dominant heat transport processes and time scale of variability associated with distinct vertical and volume regimes within a vertical element of the water column (horizontal and temporal variability is implicitly assumed):-The interface SST, SSTint, is the temperature of an infinitely thin layer at the exact air-sea interface. It represents the temperature at the top of the SSTskin temperature gradient (layer) and cannot be measured using current technology. It is important to note that it is the SSTint that interacts with the atmosphere.-The skin SST, SSTskin, is a temperature measured within a thin water layer (<500 micrometer) adjacent to the air-sea interface. It is where conductive, diffusive and molecular heat transfer processes dominate. A strong vertical temperature gradient is characteristically maintained in this thin layer sustained by the magnitude and direction of the ocean-atmosphere heat flux. Thus, SSTskin varies according to the actual measurement depth within the layer. This layer provides the connectivity between a turbulent ocean and a turbulent atmosphere.-The sub-skin SST, SSTsub-skin, is representative of the SST at the bottom of the surface layer where the dominance of molecular and conductive processes gives way to turbulent heat transfer. It varies on a time scale of minutes and is influenced by solar warming in a manner strongly dependent on the turbulent energy density in the layer below.-The ne (Source: Modified from <http://podaac.jpl.nasa.gov/ghrsst/SST-definitions.html>)

    ValueDefinition
    sea surface temperatureThe .HDF files are 16-bit files, and pixel values can range from 0 to 65535 (2 to the 16th power). However,realistic pixel values for SST will always be less than 600 or so. SST in degrees C = (0.075 *pixel value) - 3.0, so a pixel value of 600 equals 42 degrees C, a temperature which exceedsnormal SST limits. Temperatures are represented in 0.075 degree C increments

    Entity_and_Attribute_Overview:
    Climatologies are created from a 4 km-resolution time series of cloudscreened day-night combined 5-day sea surface temperatures computed from 1982-2009. The time series used to generate the climatologies include (a) SST day-nit average values, (b) overall SST quality flag (from the lowest quality of 4 to the highest quality of 7). The resulting climatologies include only SST values.
    Entity_and_Attribute_Detail_Citation:
    4 km Pathfinder Version 5.0 User Guide (<http://www.nodc.noaa.gov/sog/pathfinder4km/userguide.html>)


Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)

  2. Who also contributed to the data set?

    Kenneth S. Casey, National Oceanographic Data Center (NODC), and Edward J. Kearns, Vicki Halliwell, and Robert Evans, University of Miami, Rosenstiel School of Marine and Atmospheric Science (RSMAS)

  3. To whom should users address questions about the data?

    Yuanjie Li
    NOAA National Oceanographic Data Center
    Data Analyst
    SSMC3, 4th Floor, Room 4839, Route: E/OC1, 1315 East-West Highway
    Silver Spring, Maryland 20910
    USA

    (301)713-3272 x197 (voice)
    FAX:(301)713-3300 (FAX)
    Yuanjie.li@noaa.gov

    Hours_of_Service: 9:00 AM-4:00 PM, EST
    Contact_Instructions: Phone/FAX/E-mail/letter


Why was the data set created?

To provide high resolution climatologies of SST with high accuracy and spatial resolution for climate change and ecological studies.


How was the data set created?

  1. From what previous works were the data drawn?

    NODC Accession numbers 001763, 001764, 001765, 001766, 001767, 001768, 001769, 001770, 001771, 001772, 001773, 001774, 001775, 001776, 001777, 001778, 001779, 0043733, 0043739, 0043745, 0043750, 0043756 (source 1 of 1)
    Kenneth S. Casey, National Oceanic and Atmospheric Administration (NOAA) National Oceanographic Data Center (NODC), and Edward J. Kearns, Vicki Halliwell, and Robert Evans, University of Miami, Rosenstiel School of Marine and Atmospheric Science (RSMAS), 20060920, Pathfinder Version 5 5-day Sea Surface Temperature day/night cloudscreened SST data 1982-2009: not applicable Pathfinder Version 5, NOAA National Oceanographic Data Center, Silver Spring, Maryland.

    Online Links:

    Other_Citation_Details:
    The 5-day cloudscreened day/night files used to generate the climatologies are contained under data sets archived by individual NODC accession numbers. NODC Accession numbers: 001763, 001764, 001765, 001766, 001767, 001768, 001769, 001770, 001771, 001772, 001773, 001774, 001775, 001776, 001777, 001778, 001779, 0043733, 0043739, 0043745, 0043750, 0043756
    Type_of_Source_Media: online
    Source_Contribution:
    Paththfinder cloudscreened 5-day day/night combined data were utilized to generate the climatologies described in this metadata record.

  2. How were the data generated, processed, and modified?

    Date: 31-May-2011 (process 1 of 1)
    The Version 5 Pathfinder SSTs require several important pieces of information. This information is categorized below by the four overall steps in the Pathfinder processing system (steps A-D); in addition, several more steps are required to produce the climatologies (step E).AVHRR Pathfinder SST Processing StepsA. Ingestion, calibration, and navigation of Global Area Coverage (GAC) dataa. Calibrate and convert AVHRR digital counts for channels 1 through 5 to radiancesi. Obtain AVHRR channels 1 through 5 radiometer count data.ii. Channels 1 and 2 require pre-launch calibration coefficients for linear counts-to-radiance conversion, followed by a correction for temporal changes using sensor decay rate data and then a correction for inter-satellite differences using inter-satellite standardization data to the NOAA-9 reference, both of which use Libyan desert target area data.iii. Channels 3, 4, and 5 require both the above pre-launch calibration data and onboard blackbody (space view and sensor base plate) data for non-linear counts-to-radiance conversion.b. Navigation, Clock, and Attitude Correctionsi. Satellite clock corrections need Earth time offset data based on RSMAS High-Resolution Picture Transmission data.ii. Altitude corrections are made using coastline comparison data.iii. At this point, navigated, calibrated albedos/brightness temperatures are available for all five channels. Note that channels 1-2 are not used in the Pathfinder SST algorithm, and channel 3 is used only in assignment of a quality indicator (see step B.d.i.).B. SST Calculationa. Channel 4 and 5 brightness temperatures are converted to SST in degrees C using the Pathfinder algorithm, which requires a set of monthly coefficients.b. These coefficients are derived using the Pathfinder Buoy Matchup Database. This is a set of in situ buoy SST observations and collocated AVHRR data.c. In addition, a first-guess SST field is needed by the algorithm. This first-guess field is the Reynolds Weekly Global Optimally Interpolated SST version 2 (OISSTv2) product. Note: the older 9km Pathfinder used OISST version 1.d. Quality Flag Assignmenti. A Channel 3, 4, and 5 brightness temperature test is performed. These data are already available from step A.a.iii.ii. The viewing angle is evaluated using a satellite zenith angle check.iii. A reference field comparison check is made against the Reynolds OISST used in step B.c.iv. A stray sunlight test is performed which requires information on whether the data in question are to left or right of nadir.v. An edge test is performed which checks the location of the pixel within a scan line and the location of the scan line within the processing piece (a piece is a subset of an entire orbit file).vi. A glint test is performed which requires a glint index calculated according to the Cox and Munk (1954) formulation.vii. A sea ice mask is used to identify pixels falling on areas of sea ice. The ice mask is based on weekly SSM/I data and the ice information contained in the Reynolds OISSTv2. (Note: this step was not present in the 9 km Pathfinder reprocessing and is used only in the 4km Version 5 Pathfinder product.)viii. These steps are all combined into an overall quality flag assignment for each pixel.C. Spatial Binninga. An equal-area is grid is defined into which GAC pixels are binned. No external data are needed, only information on the equal-area binning strategy itself.b. A data-day is defined following a spatial data-day definition. See <http://www.nodc.noaa.gov/sog/pathfinder4km/Data-day.pdf> for a description of the spatial data-day definition, written by Guillermo Podesta, University of Miami RSMAS.c. A land mask is applied to the dataset, identifying pixels that fall on land. This land mask was based on an old CIA database in the 9 km Pathfinder (no citation or further information is known). In the 4 km Version 5 Pathfinder, a new and improved land mask based on a 1 km resolution MODIS dataset derived by the USGS Land Processes Distributed Active Archive Center is used (see <http://edcdaac.usgs.gov/modis/mod12q1.html> for more info.)D. Temporal Binninga. The spatially binned pieces from step C are accumulated into a single ascending (daytime) or descending (nighttime) file for each day. In case of overlapping satellite passes, only the best pixels of equivalent quality are binned. No external information is needed, only information about the accumulation procedure itself. Note: the new 4 km Version 5 Pathfinder also generates temporal averages on 5-day, 7-day, 8-day, monthly, and yearly periods.b. A final comparison is made to an internal 3-week Pathfinder comparison field. No external data are required, only knowledge of the Pathfinder reference check.c. Fields are reformatted from equal-area to equal-angle for distribution in HDF format. Note: the old 9 km Pathfinder data were distributed in HDF4 Raster format, while the new 4 km Version 5 Pathfinder data are distributed in HDF4-SDS format, with tiling (internally compressed chunks) enabled.d. The result of all these steps is the high-level Pathfinder SST product.

    To create the "cloud-screened" 5-day files used to create the seasonal and annual climatologies in this collection, original Pathfinder Version 5 day and night data of quality flags 4-7 were averaged to create global daily SST files, which were then averaged into 5day temporal bins. Version 5.1 data were used for 1982-1984, and Version 5.0 data were used for 1985-2009. The main difference between the 5.0 and 5.1 algorithms is that 5.1 uses a higher resolution data set, the Reynolds Optimum Interpolation 1/4-degree Daily SST Analysis Version 2, as both a first guess SST and in the quality control procedures. The primary effect of this change is to retain more data in the coastal and high gradient regions and in regions where meandering or feature advection is present.

    E. Additional processes required for SST climatologies: 1.The individual 5-day day-night cloudscreened files generated as part of the Version 5 Pathfinder Project for 1982-2009 were averaged into 3-month periods, or "seasons," to create a set of initial climatologies. For example, Season 1 of 1982, Season 1 of 1983, ...., Season 1 of 2009 were averaged to create a climatology for Season 1. In addition to the pre-screening of any data with a quality flag of less than 4, data with pixel values less than 16 were masked as NoData. This is because a pixel value translates to -1.8 degrees C, which is the coldest sea surface temperature possible. 2. Then, the temperature value was converted into degrees Celsius (Using the function New value = original value * 0.075 -3.0). 3. The time series maximum, minimum, average, number of observations and standard deviation were used for the final climatology data. 4. The final climatology maximum/minimum/average SST was the average of the time series maximum/minimum/average SST; the final climatology standard deviation was the standard deviation based on the seasonal average time series data; the final climatology number of observations was the total number of observations for all the seasonal time series data. Similar procedures were used for the annual climatology products. Color classified images were developed for use online. For the color classified .PNG images, 1) a land mask was applied, 2) a an ArcGIS filtering and smoothing filter was utilized, and 3) the classification was done with a 0.5 degree interval starting from 16 to 32 celsius.

    Person who carried out this activity:

    Yuanjie Li
    NOAA National Oceanographic Data Center
    Data Analyst
    SSMC3, 4th Floor, Room 4839, Route: E/OC1, 1315 East-West Highway
    Silver Spring, Maryland 20910
    USA

    (301)713-3272 x197 (voice)
    FAX:(301)713-3300 (FAX)
    Yuanjie.li@noaa.gov

    Hours_of_Service: 9:00 AM-4:00 PM, EST
    Contact_Instructions: Phone/FAX/E-mail/letter
    Data sources used in this process:
    • NODC Accession numbers 001763, 001764, 001765, 001766, 001767, 001768, 001769, 001770, 001771, 001772, 001773, 001774, 001775, 001776, 001777, 001778, 001779, 0043733, 0043739, 0043745, 0043750, 0043756

  3. What similar or related data should the user be aware of?

    University of Miami Rosenstiel School of Marine and Atmospheric Science, 20010630, AVHRR Pathfinder Oceans: Remote Sensing Group, RSMAS, Miami, FL.

    Online Links:

    NOAA National Environmental, Satellite, Data, and Information Services (NESDIS)/National Climatic Data Center (NCDC), 19981130, NOAA Polar Orbiter Data User's Guide: NOAA National Climatic Data Center, Asheville, North Carolina.

    Online Links:

    NASA/Jet Propulsion Laboratory Physical Oceanography, 20031107, NASA/Jet Propulsion Laboratory Physical Oceanography Distributed Active Archive Center (DAAC): NASA/Jet Propulsion Laboratory, Pasadena, CA.

    Online Links:

    Casey, K.S., and P. Cornillon, 19990630, A comparison of satellite and in situ-based sea surface temperature climatologies: none J. Climate, Volume 12, No. 6, American Meteorological Society, Boston, MA.

    Online Links:

    Other_Citation_Details: in pp. 1848-1862
    This is part of the following larger work.

    Society, American Meteorological , 19990630, Journal of Climate, Vol. 12: None Vol. 12, No. 6, American Meteorological Society, Boston, MA.

    Online Links:

    Casey, K.S., and P. Cornillon, 20010930, Global and regional sea surface temperature trends: None J. Climate, Volume 14, No. 18, American Meteorological Society, Boston, MA.

    Online Links:

    Other_Citation_Details: pp. 3801-3818
    This is part of the following larger work.

    Society, American Meteorological , 20010930, Journal of Climate, Vol. 14: None Volume 14, No. 18, American Meteorological Society, Boston, MA.

    Online Links:

    Reynolds, R. W., N. A. Rayner, T. M. Smith, D. C. Stokes, and W.Wang, 20020730, An improved in-situ and satellite SST analysis for climate: None J. Climate, Volume 15, No. 13, American Meteorological Society, Boston, MA.

    Online Links:

    Other_Citation_Details: pp. 1609-1625
    This is part of the following larger work.

    Society, American Meteorological , 20020730, Journal of Climate, Vol. 15: None Volume 15, No.13, American Meteorological Society, Boston, MA.

    Online Links:

    Kearns, E. J., Hanafin, J. A., Evans, R. H., Minnett, P. J., and Brown, O.B., 20000730, An independent assessment of Pathfinder AVHRR sea surface temperature accuracy using the Marine-Atmosphere Emitted Radiance Interferometer: None Bull. Amer. Met. Soc. 81, No. 7, American Meteorological Society, Boston, Ma.

    Online Links:

    Other_Citation_Details: pp. 1525-1536
    This is part of the following larger work.

    Society, American Meteorological , 20000730, Bulletin of the American Meteorological Society: None Volume 81, No. 7, American Meteorological Society, Boston, MA.

    Online Links:

    Barton, I. J., 19950530, Satellite-derived sea surface temperatures: Current status: None J. Geophys. Res., Volume 100, No. C5, American Geophysical Union, Washington, DC.

    Online Links:

    Other_Citation_Details: pp. 8777-8790
    This is part of the following larger work.

    Union, American Geophysical , 19950530, Journal of Geophysical Research, Vol. 100: None Volume 100, No. C5, American Geophysical Union, Washington, DC.

    Online Links:

    Kilpatrick, K. A., Podesta, G. P., and Evans, R., 20010515, Overview of the NOAA/NASA Pathfinder algorithm for sea surface temperature and associated matchup database: None Jour. Geophys. Res., Volume 106, No. C5, American Geophysical Union, Washington, DC.

    Online Links:

    Other_Citation_Details: pp. 9179-9197
    This is part of the following larger work.

    Union, American Geophysical , 20010530, Journal of Geophysical Research, Vol. 106: None Volume 106, No. C5, American Geophysical Union, Washington, DC.

    Online Links:

    Rayner, N. A., D. E. Parker, E. B. Horton, C. K. Folland, L. V. Alexander, D. P. Rowell, E. C. Kent and A. Kaplan, 20030730, Global Analyses of SST, Sea Ice and Night Marine Air Temperature Since the Late 19th Century: None Jour. Geophys. Res., Vol. 108 (No. D14),4407,10.1029/2002JD002670, American Geophysical Union, Washington, DC.

    Online Links:

    This is part of the following larger work.

    Union, American Geophysical , 20030730, Journal of Geophysical Research, Vol. 108: None Vol. 108 (No. D14),4407,10.1029/2002JD002670, American Geophysical Union, Washington, DC.

    Online Links:

    Schluessel, P., W. J. Emery, H. Grassl, and T. Mammen, 19900815, On the skin-bulk temperature difference and its impact on satellite remote sensing of sea surface temperature: None Jour. Geophys. Res., Vol. 95, No. C8, American Geophysical Union, Washington, DC.

    Other_Citation_Details: pp. 13,341-13,356.
    This is part of the following larger work.

    Union, American Geophysical , 19900815, Journal of Geophysical Research, Vol. 95: None Vol. 95, No. C8, American Geophysical Union, Washington, DC.

    Minnett, P.J. and B. Ward, 20001230, Measurements of near-surface ocean temperature variability - consequences on the validation of AATSR on Envisat: European Space Agency, The Netherlands.

    This is part of the following larger work.

    Agency, European Space , 20001230, Proceedings of the ERS-ENVISAT Symposium, 2000: European Space Agency, The Netherlands.

    Online Links:

    Other_Citation_Details:
    For copies of proceedings, contact:ESA Publications DivisionESTEC-Finance Division (ADM-FT)P.O. Box 299-2200 AG Noordwijk The Netherlands FAX +31 (0)71 565 5433
    Wessel, P., and W. H. F. Smith, National Geophysical Data Center, 20110715, A Global Self-consistent, Hierarchical, High-resolution Shoreline Database (GSHHS): National Geophysical Data Center, Boulder, Colorado, U.S.A.

    Online Links:

    Other_Citation_Details:
    The land mask for the GOM for this NODC accession was developed from the GSHHS product.

    GSHHS is a high-resolution shoreline data set amalgamated from two databases in the public domain. The data have undergone extensive processing and are free of internal inconsistencies such as erratic points and crossing segments. The shorelines are constructed entirely from hierarchically arranged closed polygons. The data can be used to simplify data searches and data selections, or to study the statistical characteristics of shorelines and land-masses. It comes with access software and routines to facilitate decimation based on a standard line-reduction algorithm. See: Wessel, P., and W. H. F. Smith, A Global Self-consistent, Hierarchical, High-resolution Shoreline Database, J. Geophys. Res., 101, #B4, pp. 8741-8743, 1996


How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?

    Source Pathfinder data used have quality flags 4-7, which indicate good data that are free of clouds. For more information on quality flag attribution, see <http://yyy.rsmas.miami.edu/groups/rrsl/pathfinder/Processing/proc_index.html>. Day and night data of quality flags 4-7 were averaged to create global daily SST files, which were then averaged into 5day temporal bins. These 5day files were used to build up seasonal and annual time series, which were then used to calculate seasonal and annual climatologies, respectively. All SST climatology data layers have corresponding standard deviation and pixel count information to indicate data quality and variability.

  2. How accurate are the geographic locations?

    The major sources of error in geo-locating AVHRR data are (a) drift in the spacecraft clock (which causes errors in the estimated along-track position), and (b) uncertainty errors in spacecraft and sensor attitude.(a) Clock CorrectionTo minimize error in the along track position estimated by the orbital model, a satellite a clock correction factor is applied to the time code imbedded in each piece. The method used to determine these clock correction factors is presented below. The clock aboard a given satellite drifts continually at a relatively constant rate (e.g., for NOAA-14, ~9msday-1) compared to the reference clock on Earth. Because of this drift, the NOAA/NESDIS Satellite Operation Control Center periodically sends a command to the satellite to reset the on-board clock to a new baseline thereby eliminating the accumulation of a large time offset error between the Earth and satellite clocks. To correct for clock drift between these resets, correction factors were determined from a database of satellite clock time and Earth time offsets collected at the RSMAS High Resolution Picture Transmission (HRPT) receiving station. During HRPT transmission, both the satellite clock (used to create the embedded time code in each piece) and the Earth clock are simultaneously available. The clock correction bias was determined by (1) visual examination of the Earth/satellite clock differences collected in the database to locate the precise magnitude and timing of clock resets performed by the Satellite Operation Control Center and (2) recorded time differences between the identified reset periods were then filtered to remove spurious noise, and regressed against the corresponding satellite time to determine the clock drift correction. These drift corrections were then applied to all data time-stamped during a given reset period. Refer to Sea Surface Temperature Global Area Coverage (GAC) Processing Appendix A: Calibration and Navigation Correction Factors for a list of clock offsets for each NOAA spacecraft (<http://www.rsmas.miami.edu/groups/rrsl/pathfinder/Processing/proc_app_a.html>).(b) Attitude CorrectionsAfter clock correction, a nominal attitude correction is then applied to minimize the uncertainty in regard to the direction in which the spacecraft is pointing. The nominal attitude correction applied was determined by averaging the absolute attitude of the spacecraft over many geographic locations and times along the orbital track. The method used to determine the absolute attitude of the spacecraft involves matching a digital coastal outline to a given image and recording the amount of pitch, yaw, and roll required to make the outline and land coincide. This method has the advantage that it can be performed over small geographical distances and is similar to other techniques which rely on widely separated geographical control points to anchor the navigation. The resultant navigation information, output by the SECTOR procedure for each piece, provides the mapping parameters needed to convert between the satellite perspective of pixel and scan line, and Earth-based latitude and longitude coordinates. Refer to Sea Surface Temperature Global Area Coverage (GAC) Processing Appendix A: Calibration and Navigation Correction Factors for attitude correction factors for each NOAA spacecraft (<http://www.rsmas.miami.edu/groups/rrsl/pathfinder/Processing/proc_app_a.html>).

  3. How accurate are the heights or depths?

    Refer to the Horizontal Positional Accuracy Report for a discussion of sources of error in geo-locating AVHRR data.

  4. Where are the gaps in the data? What is missing?

    These DAY_NIGHT SST climatologies are very nearly globally complete, especially between 60 N and 60 S latitude. However, the AVHRR instrument used to collect the base SST measurements cannot "see" through clouds, so some data gaps exist. The pathfinder GeoTIFF climatology product for GOM used the most updated 5-day day-night average pathfinder cloud-screened data available as of March 2011. Although the data are represented using 16-bit in the .HDF files, 32-bit GeoTIFF files were developed for these day-night seasonal and annual climatologies to facilitate access and use of these data by the widest variety of users. The original .HDF files are 16-bit files, and pixel values can range from 0 to 65535 (2 to the 16th power). However, realistic pixel values for SST will always be less than 600 or so. SST in degC = 0.075 x pixel value - 3. Temperatures are represented in 0.075 degC increments. Land has a value of 1. The Pathfinder Version 5 land mask was derived from a 1km MODIS data set developed by the USGS Land Processes Distributed Active Archive Center (see <http://www-modis.bu.edu/landcover/userguidelc/> for more information).

  5. How consistent are the relationships among the observations, including topology?

    Files are run against the program (algorithm) MD5 to verify data integrity which generates a code, called an MD5 checksum. After files are transferred from one place to another, the program can be run on the file again and a new code generated. The old MD5 checksum code should be identical to the new MD5 checksum code. If not, the file was somehow corrupted during transfer (see original MD5 documentation at <http://www.isi.edu/in-notes/rfc1321.txt>). Completed climatology files in GeoTIFF format were compared against climatology layers created using similar methodology in Matlab for validation.


How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?

Access_Constraints: None
Use_Constraints:
Please acknowledge the use of these data with - The Pathfinder Version 5 SST Data were provided by the NOAA/National Oceanographic Data Center at URL: <http://pathfinder.nodc.noaa.gov>

  1. Who distributes the data set? (Distributor 1 of 1)

    NOAA National Oceanographic Data Center
    oceanographer
    SSMC3, 4th Floor, E/OC1, 1315 East-West Highway
    Silver Spring, MD 20910
    U.S.A

    301-713-3277 or 301-713-3280 (voice)
    301-713-3301 (FAX)
    nodc.services@noaa.gov

    Hours_of_Service: 8:00 - 6:00 PM, EST
    Contact_Instructions: Phone/FAX/E-mail/letter during business hours
  2. What's the catalog number I need to order this data set?

    Downloadable Data

  3. What legal disclaimers am I supposed to read?

    NOAA makes no warranty regarding these data, expressed or implied, nor does the fact of distribution constitute such a warranty. NOAA and NODC cannot assume liability for any damages caused by any errors or omissions in these data, nor as a result of the failure of these data to function on a particular system.

  4. How can I download or order the data?

  5. Is there some other way to get the data?

    Contact the NODC User Services Group via phone/FAX/E-mail: nodc.services@noaa.gov

  6. What hardware or software do I need in order to use the data set?

    PC. Mac or other server (Unix, Linux), standard Internet browser. FTP capability


Who wrote the metadata?

Dates:
Last modified: 06-Mar-2014
Last Reviewed: 05-Aug-2011
To be reviewed: 30-Sep-2012
Metadata author:
Sheri Phillips
NOAA/NODC
Oceanographer
1315 East-West Highway, E/OC1, SSMC3, 4th Floor
Silver Spring, MD 20910
U.S.A.

301-713-3280 x127 (voice)
301-713-3302 (FAX)
sheri.phillips@noaa.gov

Hours_of_Service: 9:30 AM - 6 PM Monday-Thursday
Contact_Instructions: E-mail, phone, FAX, mail
Metadata standard:
FGDC Content Standards for Digital Geospatial Metadata (FGDC-STD-001-1998)


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