ALBERT

Description: Any use of observational data for data assimilation requires adequate information of their representativeness in space and time. This is particularly important for sparse, non-synoptic data, which comprise the bulk of oceanic in situ observations in the Arctic. To quantify spatial and temporal scales of temperature and salinity variations, we estimate the autocorrelation function and associated decorrelation scales for the Amerasian Basin of the Arctic Ocean. For this purpose, we compile historical measurements from 1980 to 2015. Assuming spatial and temporal homogeneity of the decorrelation scale in the basin interior (abyssal plain area), we calculate autocorrelations as a function of spatial distance and temporal lag. The examination of the functional form of autocorrelation in each depth range reveals that the autocorrelation is well described by a Gaussian function in space and time. We derive decorrelation scales of 150–200 km in space and 100–300 days in time. These scales are directly applicable to quantify the representation error, which is essential for use of ocean in situ measurements in data assimilation. We also describe how the estimated autocorrelation function and decorrelation scale should be applied for cost function calculation in a data assimilation system.

Description: Two types of optimization methods were applied to a parameter optimization problem in a coupled ocean--sea ice model of the Arctic, and applicability and efficiency of the respective methods were examined. One optimization utilizes a finite difference (FD) method based on a traditional gradient descent approach, while the other adopts a micro-genetic algorithm (\unit{\mu}GA) as an example of a stochastic approach. The opt\imizations were performed by minimizing a cost function composed of model--data misfit of ice concentration, ice drift velocity and ice thickness. A series of optimizations were conducted that differ in the model formulation (``smoothed code'' versus standard code) with respect to the FD method and in the population size and number of possibilities with respect to the \unit{\mu}GA method. The FD method fails to estimate optimal parameters due to the ill-shaped nature of the cost function caused by the strong non-linearity of the system, whereas the genetic algorithms can effectively estimate near optimal parameters. The results of the study indicate that the sophisticated stochastic approach (\unit{\mu}GA) is of practical use for parameter optimization of a coupled ocean--sea ice model with a medium-sized horizontal resolution of 50\,km\,$\times$\,50\,km as used in this study.

Description: The Arctic is no longer a region dominated by thick multi-year ice (MYI), but by thinner, more dynamic, first-year-ice (FYI). This shift towards a seasonal ice cover has consequences for the under-ice light field, as sea-ice and its snow cover are a major factor influencing radiative transfer and thus, biological activity within- and under the ice. This work describes in situ measurements of light transmission through different types of sea-ice (MYI and FYI) performed during two expeditions to the Chukchi sea in August 2018 and 2019, as well as a simple characterisation of the biological state of the ice microbial system. Our analysis shows that, in late summer, two different states of FYI exist in this region: 1) FYI in an enhanced state of decay, and 2) robust FYI, more likely to survive the melt season. The two FYI types have different average ice thicknesses: 0.74 ± 0.07 m (N = 9) and 0.93 ± 0.11m (N = 9), different average values of transmittance: 0.15 ± 0.04 compared to 0.09 ± 0.02, and different ice extinction coefficients: 1.49 ± 0.28 and 1.12 ± 0.19 m -1. The measurements performed over MYI present different characteristics with a higher average ice thickness of 1.56 ± 0.12 m, lower transmittance (0.05 ± 0.01) with ice extinction coefficients of 1.24 ± 0.26 m-1 (N = 12). All ice types show consistently low salinity, chlorophyll a concentrations and nutrients, which may be linked to the timing of the measurements and the flushing of melt-water through the ice. With continued Arctic warming, the summer ice will continue to retreat, and the decayed variant of FYI, with a higher scattering of light, but a reduced thickness, leading to an overall higher light transmittance, may become a more relevant ice type. Our results suggest that in this scenario, more light would reach the ice interior and the upper-ocean.