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This study addresses the regression of in-water radiometric profile data with the objective of investigating solutions to minimize uncertainties of derived products like subsurface radiance and irradiance (L(u0) and E(d0)) and diffuse attenuation coefficients. Analyses are conducted using radiometric profiles generated through Monte Carlo simulations and field measurements. A nonlinear NL approach is presented as an alternative to the standard linear method LN. Results indicate that the LN method, relying on log-transformed data, tends to underestimate regression results with respect to NL operating on non-transformed data. The log-transformation is thus identified as the source of biases in data products. Observed differences between LN and NL regression results for L(u0) are of the order of 1-2%, that is well below the target uncertainty for data products from in situ measurements (i.e., 5%). For E(d0), instead, differences can easily exceed 5% as a result of more pronounced light focusing and defocusing effects due to wave perturbations. This work also remarks the importance of applying the multi-cast measurement scheme as a mean to increase the precision of data products.

A Monte Carlo code for ocean color simulations has been developed to model in-water radiometric fields of downward and upward irradiance (E(d) and E(u)), and upwelling radiance (L(u)) in a two-dimensional domain with a high spatial resolution. The efficiency of the code has been optimized by applying state-of-the-art computing solutions, while the accuracy of simulation results has been quantified through benchmark with the widely used Hydrolight code for various values of seawater inherent optical properties and different illumination conditions. Considering a seawater single scattering albedo of 0.9, as well as surface waves of 5 m width and 0.5 m height, the study has shown that the number of photons required to quantify uncertainties induced by wave focusing effects on E(d), E(u), and L(u) data products is of the order of 10(6), 10(9), and 10(10), respectively. On this basis, the effects of sea-surface geometries on radiometric quantities have been investigated for different surface gravity waves. Data products from simulated radiometric profiles have finally been analyzed as a function of the deployment speed and sampling frequency of current free-fall systems in view of providing recommendations to improve measurement protocols.