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.