Jong Yul Chung

Spatial and Temporal Scale Variations of Sea Surface Temperature in the East Sea Using NOAA/AVHRR Data

Sea surface temperature fields in the East Sea are composed of various spatial structures such as eddies, fronts, filaments, turbulent-like features and other mesoscale variations associated with the oceanic circulations of the East Sea. These complex SST structures have many spatial scales and evole with time. Semi-monthly averaged SST distributions based on extensive satellite observations of SSTs from 1990 through 1995 were constructed to examine the characteristics of their spatial and temporal scale variations by using statistical methods of multi-dimensional autocorrelation functions and spectral analysis. Two-dimensional autocorrelation functions in the central part of the East Sea revealed that most of the spatial SST structures are anisotropic in the shape of ellipsoids with minor axes of about 90–290 km and major axes of 100–400 km. Two dimensional spatial scale analysis demonstrated a consistent pattern of seasonal variation that the scales appear small in winter and spring, increase gradually to summer, and then decrease again until the spring of the next year. These structures also show great spatial inhomogeneity and rapid temporal change on time scales as short as a semi-month in some cases. The slopes in spectral energy density spectra of SSTs show characteristics quite similar to horizontal and geostrophic turbulence. Temporal spectra at each latitude are demonstrated by predominant peaks of one and two cycles per year in all regions of the East Sea, implying that SSTs present very strong annual and semi-annual variations.

Sea surface temperature retrievals optimized to the East Sea (Sea of Japan) using NOAA/AVHRR data

The accuracy of sea surface temperatures derived by NOAA/NESDIS (National Oceanic and Atmospheric Administration/National Environmental Satellite, Data, and Information Service) equations was tested by comparison with temperatures measured by thirty-four satellite-tracked ARGOS drifters deployed in the East Sea (Sea of Japan) from 1993 to 1997. Using an improved cloud-screening algorithm for the East Sea, we obtained 362 matchup points between the NOAA satellite data (NOAA-11, NOAA-12, and NOAA-14) and the drifter buoy temperatures. The split window technique of linear MCSST, non-linear CPSST and NLSST showed relatively small rms (root mean square) errors in the range of 0.9°C to 1.2°C compared with the other window methods. However, a predominant trend was found that satellite-derived SSTs are underestimated by as much as -2°C in dry atmospheric conditions during winter, and overestimated in very humid conditions in summer by approximately 2°C. The characteristic trend was removed using a regression method, and the rms errors of newly-derived equations for the split window MCSST and the non-linear SST optimized to the East Sea were improved to within 0.3°C ∼ 0.9°C. The locally-optimized SSTs may be more important than the SSTs based on the global database, particularly in the inaccessible regions off North Korea and sea ice regions that are important for the critical research issue of cold water formation in the East Sea.