Abstract

Abstract The mechanism of initial and transient perturbations of symmetric instability (SI) in a hydrostatic flow with lateral shear is analyzed by applying the generalized stability analysis. It is well known that the SI’s most rapidly growing motion is along isopycnals, and the growth rates consist of growing, neutral, and decaying modes. The eigenvectors of these three modes are not orthogonal to each other, hence the initial and transient perturbations bear little resemblance to the normal mode. Our findings indicate that the emergence of normal modes occurs within a time span of 1–3 inertial periods, which we refer to as the transient state. The overall growth of perturbation energy is divided into three components: geostrophic shear production (GSP), lateral shear production (LSP), and meridional buoyancy flux (MB). During the transient state, the perturbation energy is partly driven by MB, contrary to the normal mode which has zero MB. The relative energy contribution is evaluated through the ratio to GSP. While the MB-to-GSP ratio of the initial mode is higher than that of the normal mode, the LSP-to-GSP ratio remains constant. In the absence of the fastest-growing normal mode, MB can serve as the predominant initial energy source. The precise transition in the energy regime is contingent upon the geostrophic Richardson number and Rossby number. Significance Statement Fronts can be unstable to instabilities, which generate disturbance growth and lead to the mixing of water masses. We wanted to understand the initial and transient development of disturbance growth leading to the well-known exponentially growing state. While the exponentially growing disturbance is dominant in the long run, the disturbance growth may not have enough time to achieve the exponentially growing state. We find that the initial disturbance growth bears little resemblance to the exponentially growing state. Capturing the complete spectrum of front evolution remains challenging, and observations have thus far been limited to short-term records. The insights learned from this study can aid in better characterizing the disturbance growth captured in these short-term records.

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