## 1 Introduction
In doing so, NRL has developed a maritime lasercomm test facility (LCTF), consisting of facilities 16-km apart on both sides of Chesapeake Bay, equipped with instruments to measure transmission, the scintillation index and angle of arrival of the beam [7; 8; 9; 10; 11; 12; 13]. During another trial (FATMOSE), high resolution images were collected by point sources at a range of 15.7 km, along with turbulence related atmospheric parameters that provided statistical information on the mean and variance of the atmospheric point spread function and the associated modulation transfer function during a series of consecutive frames [14]. An experimental set-up to control and measure the effect of laser beam broadening due to turbulence has been designed [15]. In [16], a weather research and forecasting (WRF) model was used to calculate routine meteorological parameters and the refractive index structure parameter near the ocean surface using Monin-Obukhov similarity theory. In [17], this work has been extended to estimate surface layer \({C_{n}}^{2}\) over snow and ice and gave even better results than estimations over the ocean. In [18], an approach was developed to quantify scintillation by estimating the refractive index structure parameter from surface fluxes that are derived from single-level routine weather data. [PERSON] et al. related the structure functions of the atmospheric variables with spatial structure functions of the numerical weather prediction (NWP) model variables [19]. Atmospheric turbulence and environmental conditions have directly negative effects on an FSO link's performance in terms of its reliability and even its availability. Extensive experimental and theoretical research has been conducted for various communication schemes and performance metrics, both for terrestrial and maritime environments. [PERSON] et al., have studied the weak gamma-distributed turbulence effects on the bit rate of an FSO link over sea [20]. A theoretical work in [21] examined the atmospheric turbulence induced fading modeled by the \(M\)-distribution and the line-of-sight (LOS) blockage of an FSO link. [PERSON] et al. investigated the average symbol error rate (ASEP) of a hybrid RF/FSO link [22]. [PERSON] et al. reported on the modelling of the channel attenuation coefficient for a coastal environment, taking into consideration the air temperature, humidity and dew point by employing an FSO system with 70 m link length [23]. In [24], the signal fluctuations due to atmospheric turbulence and extinction effects was measured in terms of RSSI, using a commercial FSO communication system. The same performance metric (i.e., RSSI) was used in [25] in conjunction with several real-time measured atmospheric properties and resulted in two empirical equations for day and night. [PERSON] et al. simulated the atmospheric effects of a laser beam propagating from an airborne high-speed moving platform, showing that the turbulence effect in a downward slant path is less severe [26]. In [27; 28], a second-order polynomial model is constructed to predict RSSI values for a maritime FSO link based on real-time macroscopic meteorological parameters, and different standard probability distributions were evaluated against the RSSI distribution. This work provides a comprehensive study for the performance prediction of a commercial FSO link over a maritime environment. A large data set of seven macroscopic meteorological parameters, acquired over a period of 12 months, is utilized to predict the received signal strength (i.e., RSSI) by employing regression model analysis. The variance selection of these seven parameters was chosen based on the knowledge that they can strongly affect FSO performance [27; 28]. In doing so, five machine learning algorithms are employed, including the KNN, decision trees (DT), gradient boosting regression (GBR), random forest (RF) and ANN.