## 1 Introduction
In another related study, experimental characterization was conducted on turbulent motion within a sphere wake collapsing under buoyancy in a linearly stable brine stratification environment [19]. [PERSON] [20] investigated the mean flow and turbulence characteristics of buoyant jets evolving in linearly stratified environments with varying stratified strengths. This was achieved through simultaneous particle image velocimetry and planar laser-induced fluorescence techniques, capturing the jet velocity and density fields under the experimental conditions. [PERSON] [21] conducted an experimental investigation into the thermal jet characteristics under steady stratified conditions. [PERSON] [22] observed the jet mixing process with ambient fluid using a high-speed camera, laser imaging, and ultrasonic velocimetry. The jet mixing process was categorized into fully turbulent and semi-turbulent regions, with the semi-turbulent region further classified into momentum-dominated and buoyancy-dominated regions. It was concluded that the fluid flow was controlled by interactions between fluid inertia, viscosity, and buoyancy. It can be found from the above literature that PIV technology is mainly used to carry out relevant research on jet problems, and PIV combined with PLIF technology is rarely used. There are also few studies on jet flow in strong stratification environment. In addition to the experimental research, some scholars use the simulation method to carry out computational research on the jet problem. [PERSON] conducted an analysis of the flow state of a unilateral discharging thermal jet in a cross-flow environment using computational fluid dynamics (CFD). The results indicated that the ratio of the jet velocity to the ambient water flow velocity affects the initial temperature of the jet [23]. [PERSON] [24] compared the simulation effectiveness of several low Reynolds number k-\(\epsilon\) turbulence models and found that the Myong-Kasagi model (one of the low Reynolds number turbulence models) can better represent strongly buoyant flow states generated by walls compared with DNS and RANS. [PERSON] [25] investigated mesh non-orthogonality in numerical computational solutions for thermal jet flow by comparing divisions with hexahedral and prismatic grid cells. The results showed that prismatic grid cells increase computational instability compared to hexahedral grid cells; although, utilizing a non-orthogonal correction method improves computational stability, it also increases convergence computation time. [PERSON] [26] proposed a unified formulation for addressing mesh variability in thermal jet flows by deriving pressure correction equations from energy equations and simplifying [PERSON]'s equation into continuity constraints which can better simulate flows involving large density variations. [PERSON] [27] discussed the average flow mixing characteristics of vertical circular thermal jets in weak cross-flows using an integral method and established Reynolds mean partial differential equations with continuous tracer mass and momentum conservation under curvilinear column coordinate systems to describe the thermal jet phenomena effectively. In the simulation calculation, the selection of the turbulence model and the setting of grid calculation conditions have obvious effects on the jet calculation results, and the temperature stratification setting in the fluid calculation domain lacks attention. There are few comparative studies with experiments. In this paper, the characteristics of the underwater thermal jet flow field are investigated, with a specific focus on the temperature diffusion region of the jet. The PIV and PLIF techniques are employed to measure both the temperature and velocity fields of the jet motion, allowing for a comparison with simulation calculations. The jet experiment is carried out in a water tank, and PIV and PLIF technologies are used to carry out fine measurement of the velocity and temperature characteristics of the jet field.