Establishment of Near-Real Time Monthly Gridded Dataset from Global Temperature and Salinity Profile Program (GTSPP) Using Optimal Spectral Decomposition

To fully understand the variability in ocean thermohaline structure and then its effects on climate variability needs a sufficient resolution in space and, especially, in time, gridded ocean temperature and salinity (T, S) dataset. We analyzed observational profiles from the Global Temperature and Salinity Profile Program (GTSPP) and produced a T-S data set to meet the above need. GTSPP is a joint programme of the International Oceanographic Data and Information Exchange committee (IODE) and the Joint Commission on Oceanography and Marine Meteorology (JCOMM). IODE and JCOMM are technical committees of the Intergovernmental Oceanographic Commission and the World Meteorological Organization. The quality control procedures used in GTSPP were developed by the Marine Environmental Data Service (MEDS), now the Integrated Science Data Management (ISDM), of Canada. The GTSPP handles all temperature and salinity profile data. This includes observations collected using water samplers, continuous profiling instruments such as CTDs, thermistor chain data and observations acquired using thermosalinographs. These data will reach data processing centres of the Program through the real-time channels of the IGOSS program or in delayed mode through the IODE system. Real-time data in GTSPP are acquired from the Global Telecommunications System in the bathythermal (BATHY) and temperature, salinity & current (TESAC) codes forms supported by the WMO. Delayed mode data are contributed directly by member states of IOC. Any variable (temperature, salinity, or velocity) can be decomposed into generalized Fourier series using the recently developed optimal spectral decomposition (OSD) method (Chu et al., 2003 a, b). The three dimensional field is then represented by linear combination of the products of basis functions (or called modes) and corresponding Fourier coefficients. If a rectangular closed ocean basin is considered, the basis functions are sinusoidal functions. If a realistic ocean basin is considered, the basis functions are the eigen-values of the three-dimensional Laplace operator with real topography. One major benefit of using the OSD method is that the boundary conditions for the ocean variables (temperature, salinity, velocity) are always satisfied. Near-real time gridded (T, S) dataset was established using the OSD method from GTSPP since 1990 with horizontal resolution of (1o×1o) and temporal increment of 1 month. With this new dataset, a new phenomenon, global ocean tripole, was discovered. Its features and connection to climate variability is also discussed.