Objective Determination of Feature Resolution in Two Sea Surface Temperature Analyses

• Published in: Journal of climate 2013-04, Vol.26 (8), p.2514-2533
• Main Authors: Reynolds, Richard W., Chelton, Dudley B., Roberts-Jones, Jonah, Martin, Matthew J., Menemenlis, Dimitris, Merchant, Christopher John
• Format: Article
• Language: English
• Subjects: Advanced very high resolution radiometers; Climatology. Bioclimatology. Climate change; Cloud cover; Computer centers; Computer simulation; Data analysis; Data models; Datasets; Earth, ocean, space; Exact sciences and technology; External geophysics; Fields; General circulation models; Geophysics. Techniques, methods, instrumentation and models; High resolution; Information retrieval noise; Infrared; Marine; Meteorology; Missing data; Modeling; Noise; Noise reduction; Ocean models; Oceans; Procedures; Resolution; Salinity; Sampling; Sampling error; Satellite data; Satellites; Sea surface; Sea surface temperature; Signal noise; Simulation; Simulations; Spectral analysis; Spectrum analysis; Standard deviation; Statistical variance; Studies; Surface temperature; Temperature; Variance analysis; Wavelengths; Wavenumber
• ISSN: 0894-8755; 1520-0442
• DOI: 10.1175/JCLI-D-12-00787.1

Considerable effort is presently being devoted to producing high-resolution sea surface temperature (SST) analyses with a goal of spatial grid resolutions as low as 1 km. Because grid resolution is not the same as feature resolution, a method is needed to objectively determine the resolution capability and accuracy of SST analysis products. Ocean model SST fields are used in this study as simulated “true” SST data and subsampled based on actual infrared andmicrowave satellite data coverage. The subsampled data are used to simulate sampling errors due to missing data. Two different SST analyses are considered and run using both the full and the subsampled model SST fields, with and without additional noise. The results are compared as a function of spatial scales of variability using wavenumber auto- and cross-spectral analysis. The spectral variance at high wavenumbers (smallest wavelengths) is shown to be attenuated relative to the true SST because of smoothing that is inherent to both analysis procedures. Comparisons of the two analyses (both having grid sizes of roughly 1 20 0 ) show important differences. One analysis tends to reproduce small-scale features more accurately when the high-resolution data coverage is good but produces more spurious smallscale noise when the high-resolution data coverage is poor. Analysis procedures can thus generate small-scale features with and without data, but the small-scale features in an SST analysis may be just noise when high-resolution data are sparse. Users must therefore be skeptical of high-resolution SST products, especially in regions where high-resolution (∼5 km) infrared satellite data are limited because of cloud cover.