Chromophoric dissolved organic matter (CDOM) is an important component controlling the propagation of light in coastal and open sea areas, and it constitutes the largest organic carbon pool in the ocean, playing a significant role in the global carbon cycle. The laser induced fluorescence (LIF) technique is a well-known analytical method for rapid water environment monitoring. By measuring the emission spectrum of laser-induced seawater, we can quickly and in real-time obtain qualitative and quantitative information about CDOM in the ocean. Previous simulation models for marine LIF detection often ignore the influence of sea breeze and treat the sea surface as an ideal stationary interface. In reality, affected by a sea breeze, the sea surface fluctuates during LIF system operations for marine remote sensing detection. The fluctuating rough sea surface affects the laser and fluorescence, thereby influencing the fluorescence information detected by the receiving system. Therefore, based on the Monte Carlo method and a sea surface simulation model, we construct a simulation model of CDOM fluorescence characteristics under a rough sea surface and use this model to obtain the fluorescence distribution of CDOM received under an ideal stable sea surface and analyze the influence of different wind directions and wind speeds on the fluorescence signal of the rough sea surface.

We use the Monte Carlo method to simulate the transmission of photons through the sea surface in seawater. When the weight of the photon drops below the threshold, we introduce a new photon to continue the simulation. Throughout the simulation process, we record the position, weight, and direction of motion of each photon until it is finally emitted from the sea surface, and we collect and analyze the outgoing fluorescence information. The motion direction of the photon after refraction is determined based on the refraction law and relevant optical theory. We achieve the simulation of a rough sea surface by inverting the Pierson-Moscowitz wave spectrum using a linear superposition method, assuming that the rough sea surface results from the superposition of several triangular waves with varying frequencies, amplitudes, and random phases. We analyze the influence of sea surface fluctuation on CDOM detection by simulating the distribution of CDOM fluorescence under ideal smooth and rough sea surfaces. We then analyze the fluctuation of ocean CDOM fluorescence received under different wind speeds and wind directions. Finally, we validate the reasons for the fluctuations of the received fluorescence signal under the rough sea surface due to changes in the slope of the sea surface through experiments.

The simulation results show that due to the isotropy of fluorescence and the differing transmission distances of outgoing fluorescence at various zenith angles in seawater, the overall fluorescence distribution of received CDOM under an ideal and stable sea surface presents a center-symmetric hemispherical shape (Fig. 1). This indicates that the fluorescence receiving intensity is negatively correlated with the received zenith angle, and is independent of the received azimuth angle. In actual detection, due to sea breeze influences, the sea surface is not ideally stable and fluctuates (Fig. 2). The fluctuating sea surface causes variations in the fluorescence transmission distances along different azimuth angles, leading to an asymmetric fluorescence distribution (Fig. 3). Additionally, the total reflection phenomenon may diminish due to changes in the slope of the sea surface. The fluorescence intensity received at a 90° zenith angle may no longer be zero at certain azimuth angles. The overall fluctuation direction of the sea surface aligns with the wind direction (Fig. 4), with greater wind speeds resulting in larger changes in sea surface height (Fig. 7). As sea surface height and slope change significantly in the downwind and upwind directions, remote sensing detection in these directions will experience stronger fluorescence fluctuations, whereas detection along the vertical wind direction will yield more stable results (Figs. 5 and 6). The stronger the gradient change of the ocean surface with wind speed, the greater the influence on photon refraction, leading to more stable fluorescence signals detected at lower wind speeds. Experimental designs indirectly verify that changes in sea surface slope in different directions affect fluorescence reception intensity.

We establish a fluorescence simulation model of marine CDOM based on the Monte Carlo method, incorporating a rough sea surface generated by the Pierson-Moscowitz wave spectrum. The simulation results reveal how CDOM fluorescence characteristics vary with different wind directions and speeds. Finally, we validate through experiments the changes in fluorescence signals caused by sea surface tilt. The simulation results show that without considering sea breeze influences, the fluorescence signal of marine CDOM is independent of the azimuth angle and inversely proportional to the zenith angle. Therefore, during actual detection, the setting of the receiving zenith angle should not be too large. Compared with a calm sea surface, CDOM fluorescence distribution fluctuates under a rough sea surface, with received fluorescence values fluctuating more sharply downwind or upwind due to the influence of sea surface fluctuations in different wind directions. Wind speed affects the degree of fluorescence fluctuation; as wind speed increases, larger sea surface dip angles occur, leading to greater fluctuations in the received CDOM fluorescence. In remote sensing detection, the fluorescence signal measured by CDOM is relatively more stable in the direction of vertical wind. Choosing a time of lower wind speed also enhances detection stability.