Southern Ocean Sea Ice Predictability

CGSN: Southern Ocean Sea Ice Forecasting Antarctic sea ice conditions, including specifics Predictability such as the position of the ice edge in the Southern Ocean, are substantial challenges. As a part of the Polar Prediction

Project (https://www.polarprediction.net), there is a focus on improving coupled air-sea-ice prediction models and determining key sources of forecast errors. In a recent study, Cerovecki et al. (2022) show that sea ice forecast skill is linked to the accuracy of the surface forcing, and in particular, the net surface radiation. The goal of the study was to quantify errors that degrade the skill of Southern

Ocean sea ice forecasts during the freezing season. They conclude that accurately modeling the surface downward longwave radiation (DLW) component of the net surface radiation is critical to sea ice prediction over the Southern

Ocean.

The authors review prior results indicating that climate models have different behaviors in different seasons relative to ground truth. In spring and summer, the models overestimate the net surface radiation whereas in winter the models under-estimate the net longwave radiation.

Recognizing that these issues relate to representations of cloud cover, which can be diagnosed using DLW, the authors also note that some models showed DLW biases of up to 100 W/m2 compared to ground truth. These results were based on comparisons at McMurdo Station, Antarctica, whereas the authors were interested in processes occurring near the ice edge where few direct observations are available.

The OOI Southern Ocean surface mooring provided a rare source of in-situ air-sea flux data for comparison. The study 6 used DLW from the METBK instrument package on the OOI

Southern Ocean buoy to compare with results from the

averaged together to create the observational record. Comparison of the observed monthly mean DLW with reanalysis output showed systematic underestimates by the models relative to the observations. The nature of the offsets is shown in Figure 28 – the reanalysis models do a relatively good job of capturing month to month variability, but with a consistent low bias. The mean offsets range from -13 W/m2 for ERAI to -28 W/m2 for NCEP1. These biases are comparable to those diagnosed at McMurdo Station, and suggest that the ERA5 DLW radiation underestimate is of the order of 20–50 W/m2. This is consistent with the finding that coupled model forecast systems over-estimate sea ice growth. The authors conclude that a significant deficit in reanalysis DLW, related to the accuracy of cloud representation in the models, is a common problem over the Southern Ocean and impacts the skill of sea ice cover prediction. In particular, the ERA5 reanalysis may underestimate DLW by up to 50 W/m^2 during the during the freezing season. The OOI Southern Ocean data, from the furthest south sustained airsea flux mooring, proved uniquely valuable in codifying these results.

Cerovecki, I, R. Sun, D.H. Bromwich, X. Zou, M.R. Mazloff and S -H.Wang (2022). Impact of downward longwave radiative deficits on Antarctic sea-ice extent predictability during the sea ice growth period. Environ. Res. Lett. 17 084008. DOI: /10.1088/1748-9326/ac7d66

EA : Particle trajectories in an eastern boundary current using a regional ocean model at two

To study the transport and dispersal of marine organisms horizontal resolutions during spawning, Wong-Ala et al. developed and applied a Lagrangian particle tracking (LPT) model to compare and contrast particle drift patterns during the spring transition off the Oregon coast. The studied the Oregon coast as it has distinct upwelling and downwelling regimes and variable shelf width. They contrasted years (2016–18) using Regional Ocean Modeling System (ROMS) with different horizontal spatial resolutions (2 km, 250 m). They found the finer spatial resolution model significantly increased retention along the Oregon coast. Particles in the 250 m ROMS were advected to depth at specific times and locations for each simulated year, coinciding with the location and timing of a strong and shallow alongshore undercurrent that is not present in the 2 km ROMS. Additionally, ageostrophic dynamics close to shore, in the bottom boundary layer, and around headlands not present in the coarser model emerged in the 250 m resolution model. They concluded that the higher horizontal model resolution and bathymetry generated well-resolved mesoscale and submesoscale features (e.g., surface, subsurface, and nearshore jet) that vary annually. These results have implications for modeling the dispersal, growth, and development of coastal organisms with dispersing early life stages. The model applied by Wong Ala assimilates satellite sea surface temperature and along-track altimetry. Model 8 atmospheric forcing is from the NOAA North American Mesoscale Model (NAM). To validate their model, Wong-Ala

month of April in each year when they ran their model (Figure 29). They found the modeled currents and temperature from the 250 m ROMS model closely follow the observed data from inshore and shelf moorings compared to the 2 km ROMS. The 250 m ROMS modeled currents and observed currents at the inshore mooring are similar for all three years (Figure 29). They also found that the 250 m ROMS modeled temperature and observed data are similar in 2017 at the inshore and shelf location. In April 2017 and 2018, the modeled temperature from the 250 m ROMS is about 1 °C cooler than the observed temperatures.

*Wong-Ala is a PhD student at Oregon State University. She is a Pacific Islander.

J. A. T. K. Wong-Ala, Ciannelli, L., Durski, S. M., and Spitz, Y., Particle trajectories in an eastern boundary current using a regional ocean model at two horizontal resolutions, Journal of Marine Systems, vol. 233, p. 103757, 2022. https://doi.org/10.1016/j.jmarsys.2022.103757.