In order to satisfy the demand of key sea ice parameters, including melt pond depth H_p and underlying ice thickness H_i, in studies of Arctic sea ice change in summer, four algorithms of retrieving H_p and H_i were compared and validated by using optical data of melt ponds from field observations. The Malinka18 algorithm stood out as the most accurate algorithm for the retrieval of H_p. For the retrieval of H_i, Malinka18 and Zhang21 algorithms could also provide reasonable results and both can be applied under clear and overcast sky conditions, while retrievals under clear sky conditions are more accurate. The retrieval results of H_i for Lu18 agreed better with field measurements for thin ice (H_i < 1 m) than that for thick ice, but those results of H_p were not satisfactory. The König20 algorithm was only suitable for clear sky conditions, and underestimated H_p, while showing a good agreement with H_p < 0.15 m. For Arctic applications, Malinka18 and Zhang21 algorithms provided a basis and reference for the satellite optical data such as WoeldView2 to retrieve H_p and H_i. Malimka18 also showed the ability to retrieve H_i, except for the Lu18 algorithm if pond color captured by helicopters and unmanned aerial vehicles were available. This study identifies the optimal algorithm for retrieval of H_p and H_i under different conditions, which have the potential to provide necessary data for numerical simulations of Arctic sea ice changes in summer.

In this paper, based on high-resolution satellite images near an ice bridge in the Canadian Basin, we extracted floe size parameters and analyzed the temporal and spatial variations in the parameters through image processing techniques. The floe area shows a decreasing trend over time, while the perimeter and mean clamped diameter (MCD) exhibit no obvious pattern of change. In addition, the roundness of floes, reflected by shape parameters, generally decreases initially and then increases, and the average roundness of small floes is smaller than that of large floes. To correct the deviations from power law behaviour when assessing the floe size distribution (FSD) with the traditional power law function, the upper-truncated power law distribution function and the Weibull function are selected. The four parameters of the two functions are important parameters for describing the floe size distribution, and Lr and L0 are roughly equal to the maximum calliper diameter and the average calliper diameter of the floes in the region. D in the upper-truncated power law distribution function represents the fractal dimension of the floes, and r in the Weibull function represents the shape parameter of the floes, both of which increase and then decrease with time. In this paper, we investigate the response of the rate of change in the FSD parameter to the differences in the monthly average temperature and find that D, r and air temperature are positively correlated, which verifies the influence of air temperature on the floe size distribution.