# Estimating Underwater Light Regime under Spatially Heterogeneous Sea Ice in the Arctic
## 5 Conclusions  
Our results show that under spatially heterogeneous sea ice at the surface (and for a homogeneous water column), the average irradiance profile, \(\overline{E_{d}}(z)\), is well reproduced by a single exponential function. We also showed that propagating \(E_{d}(0^{-})\) using \(K_{Lu}\) is a better choice compared to \(K_{d}\) under heterogeneous sea ice. Nowadays, radiance measurements are becoming more routinely performed during field campaigns, so we argue that one should use \(K_{Lu}\) when available to propagate \(E_{d}(0^{-})\) through the water column under sea ice. The main difficulty remains in finding good estimates of averaged \(E_{d}(0^{-})\). In recent years, this has become easier with the development of remotely operated vehicles [3, 4, 25], remote sensing techniques, and drone imagery. In this study, we used a Monte Carlo approach to model an idealized surface with a single melt pond (Figures 1 and 6). Figure 11 shows that the effect of a melt pond with diameter 5 m is minimized at a horizontal distance of approximately 20 m or more. Therefore, when many melt ponds are characterizing an area, if one has to perform a single profile, measuring an upward radiance profile under bare ice as far away as possible from any melt pond would minimize the error in estimating the area-averaged downward irradiance profile using \(K_{Lu}\). Although not representative of a complex Arctic sea ice surface, our simple surface geometry allowed to study the transition from a high to a low transmission sea ice. Further 3D Monte Carlo work could include a more complex geometry of heterogeneous surfaces.  
Conceptualization, P.M., G.B., S.L.-G., E.L. and M.B.; methodology, P.M., G.B., S.L.-G., E.L. and M.B.; field work, G.B., S.L.-G., and M.B.; writing--original draft preparation, P.M.; writing--review and editing, P.M., G.B., S.L.-G., E.L. and M.B.; supervision, M.B.; funding acquisition, M.B. The GreenEdge project is funded by the following French and Canadian programs and agencies: ANR (contract #111112), CNES (project #131425), PHEV (project #1164), CSA, Fondation Total, ArcticNet, LEFE and the French Arctic Initiative (GreenEdge project). This project would not have been possible without the support of the Hamlet of Qikidaruqa and the members of the community as well as the Inuksuit School and its principal, [PERSON]. The project is conducted under the scientific coordination of the Canada Excellence Research Chair on Remote Sensing of Canada's New Arctic Frontier and the CNRS and Universite Laval Takuvik Joint International laboratory (UMI3376). The field campaign was successful thanks to the contributions of [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] from the Takuvik laboratory, [PERSON] and [PERSON] from University of Manitoba, and [PERSON] and [PERSON] Vagabond. We also thank [PERSON], Quebec-Ocean, the CCCS Amundsen and the Polar Continental Shelf Program for their in-kind contribution in polar logistics and scientific equipment. We thank [PERSON], [PERSON] and [PERSON] for their contribution to radiometry measurements in 2016. This research was enabled in part by support provided by Calcul Quebec (www.calculquebec.ca) and Compute Canada (www.computecanada.ca). [PERSON] was supported by a postdoctoral fellowship from the Natural Sciences and Engineering Research Council of Canada (NSERC). We also acknowledge the Canada First Research Excellence Fund and the Sentinel North Strategy for their financial support. We thank [PERSON] and one anonymous reviewer for their valuable comments which helped to greatly improve the manuscript.  
The authors declare no conflict of interest.