摘要
Recent discovery of low-dimensional coherent structure in oceanic currents along with a new merged altimeter product called Absolute Dynamic Topography (ADT) makes it possible to derive subsurface ocean information from satellite remote sensing data.An altimetric geostrophic empirical mode (η-GEM) is developed in this study by projecting hydrographic transects onto the ADT sea surface height coordinate,based on which the four-dimensional thermohaline and velocity structures of oceanic currents are reconstructed from satellite surface observations.In the WOCE/SR3 area,the η-GEM fields capture more than 95% of the total thermal variance.The GEM-derived flow has equivalent-barotropic structure and represents the velocity profile better than traditional dynamic modes.Comparison with mooring observations also demonstrates that the η-GEM provides good estimates of the deep thermohaline fields.
Recent discovery of low-dimensional coherent structure in oceanic currents along with a new merged altimeter product called Absolute Dynamic Topography （ADT） makes it possible to derive subsurface ocean information from satellite remote sensing data. An altimetric geostrophic empirical mode （η-GEM） is developed in this study by projecting hydrographic transects onto the ADT sea surface height coordinate, based on which the four-dimensional thermohaline and velocity structures of oceanic currents are reconstructed from satellite surface observations. In the WOCE/SR3 area, the η-GEM fields capture more than 95% of the total thermal variance. The GEM-derived flow has equivalent-barotropic structure and represents the velocity pro- file better than traditional dynamic modes. Comparison with mooring observations also demonstrates that the η-GEM provides good estimates of the deep thermohaline fields.
基金
supported by National Basic Research Program of China(Grant Nos. 2007CB411804 and 2012CB417401)
Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KZCX2-YW-Q11-02)
National Natural Science Foundation of China (Grant No.41006114)
