Improving strategies with constraints regarding non-Gaussian statistics in a three-dimensional variational assimilation method

作者：Usui Norihisa^*; Ishizaki Shiro; Fujii Yosuke; Kamachi Masafumi

来源：Journal of Oceanography, 2011, 67(3): 253-262.

DOI：10.1007/s10872-011-0024-5

• Data assimilation
• Variational method
• Non-Gaussian
• Mixed water region
• Temperature front

We assess validity of a Gaussian error assumption, the basic assumption in data assimilation theory, and propose two kinds of constraints regarding non-Gaussian statistics. In the mixed water region (MWR) off the east coast of Japan exhibiting complicated frontal structures, a probability density PDF) of subsurface temperature shows double peaks corresponding to the Kuroshio and Oyashio waters. The complicated frontal structures characterized by the temperature PDF sometimes cause large innovations, bringing about a non-Gaussianity of errors. It is also revealed that assimilated results with a standard three-dimensional variational (3DVAR) scheme have some issues in MWR, arising from the non-Gaussianity of errors. The Oyashio water sometimes becomes unrealistically cold. The double peaks seen in the observed temperature PDF are too smoothed. To improve the assimilated field in MWR, we introduce two kinds of constraints, J (c1) and J (c2), which model the observed temperature PDF. The constraint J (c1) prevents the unrealistically cold Oyashio water, and J (c2) intends to reproduce the double peaks. The assimilated fields are significantly improved by using these constraints. The constraint J (c1) effectively reduces the unrealistically cold Oyashio water. The double peaks in the observed temperature PDF are successfully reproduced by J (c2). In addition, not only subsurface temperature but also whole level temperature and salinity (T-S) fields are improved by adopting J (c1) and J (c2) to a multivariate 3DVAR scheme with vertical coupled T-S empirical orthogonal function modes.

• 出版日期2011-6
• 单位中国气象科学研究院