The data set is referred to as the "GSSTF 2.0 Global Ocean Gridded Data Set." GSSTF stands for Goddard Satellite-Based Surface Turbulent Fluxes.
The data set currently contains a suite of 3 products. The ... first two products provide (i) daily and (ii) monthly-mean, global ocean 1-degree latitude by 1-degree longitude gridded values of surface fluxes and some related quantities based mainly on SSM/I data (Special Sensor Microwave/ Imager; onboard F8, F10, F11, F13, and F14 satellites) over the 13.5-year period of July 1987 through December 2000. Note that monthly-mean data were produced using at least 10 available daily values.
The third product provides (iii) the 1988-2000 monthly-mean and annual-mean climatology data for the same parameters. The monthly-mean climatology data were produced using the interpolated (grids with missing value being interpolated from their neighboring 8 grids by a distance weight) individual monthly-mean data. An aggressive interpolation scheme was used, with newly-interpolated grid boxes serving as input for filling in additional grid boxes, in order to maximize the number of grid boxes with data. The climatology files thus have more grid boxes with non-missing data values than the individual monthly and daily files. The annual-mean climatology was then generated based on those 12 monthly-mean climatologies.
The daily, monthly-mean, and annual- and monthly-mean climatology products all include eight variables:
WB is retrieved from the SSM/I radiances using the method of Schulz et al. (1993), while U is an SSM/I product derived by Wentz (1997). Q is derived from WB and water vapor amount in the entire atmospheric column of Wentz (1997) using the method developed by Chou et al. (1995, 1997). DQ is derived from Q and sea surface temperature (SST) of the NCEP reanalysis (Kalnay et al. 1996), including a 2% reduction in saturation specific humidity at SST due to salinity effect. The turbulent fluxes (wind stress, E, and H) are then computed from U, DQ, and sea-air temperature difference of NCEP reanalysis based on surface layer similarity (Chou 1993; with the flux-profile relationships of Dyer (1974) but changing the von Karman constant from 0.41 to 0.4). Wind stress direction is taken from 10-m wind direction derived from SSM/I 10-m wind speed (Wentz 1997), 10-m wind field of NCEP reanalysis, and wind measurements from ships and buoys (see Atlas et al. 1996) produced at NASA GMAO by Atlas' group.
The main refereed citation for the data set is Chou et al. (2003) (all references are listed in section 10).
NASA Goddard Space Flight Center
Global Change Master Directory
City:
Greenbelt
Province or State:
Maryland
Postal Code:
20771
Country:
USA
Publications/References
Atlas, R., R.N. Hoffman, S.C. Bloom, J.C. Jusem, and J. Ardizzone, 1996: A multiyear global surface wind velocity dataset using SSM/I wind obser-vations. Bull. Amer. Meteor. Soc., 77, 869-882.
Chou, S.-H., 1993: A comparison of airborne eddy correlation and bulk aerodynamic methods for ocean-air turbulent fluxes during cold-air outbreaks. Bound.-Layer Meteor., ... 64, 75-100.
Chou, S.-H., R.M. Atlas, C.-L. Shie, and J. Ardizzone, 1995: Estimates of surface humidity and latent heat fluxes over oceans from SSM/I data. Mon. Wea. Rev., 123, 2405-2425.
Chou, S.-H., C.-L. Shie, R.M. Atlas, and J. Ardizzone, 1997: Air-sea fluxes retrieved from special sensor microwave imager data. J. Geophys. Res., 102, 12705-12726.
Chou, S.-H., E. Nelkin, J. Ardizzone, R. Atlas, and C.-L. Shie, 2003: Surface turbulent heat and momentum fluxes over global oceans based on the Goddard satellite retrievals, version 2 (GSSTF2). J. Climate, 16, 3256-3273.
Dyer, A.J., 1974: A review of flux-profile relationships. Bound.-Layer Meteor., 7, 363-372.
Kalnay, E. and coauthors, 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77, 437-471.
Schulz, J., P. Schluessel, and H. Grassl, 1993: Water vapor in the atmospheric boundary layer over oceans from SSM/I measurements. Int. J. Remote Sens., 14, 2773-2789.
Wentz, F.J., 1997: A well calibrated ocean algorithm for SSM/I. J. Geophys. Res., 102, 8703-8718.
