Air-Ice-Ocean Coupling During a Strong Mid-Winter Cyclone: Observations

This repository contains code used in the analysis of sea ice motion and storm structure during a pair of winter cyclones observed during the MOSAiC Arctic Expedition in January and February 2020. The results produced here are a portion of a collaborative project funded by the US Department of Energy, Office of Naval Research, and National Science Foundation. Results have been shared in numerous scientific conferences, and will be available in a peer-reviewed journal article in the Journal of Geophysical Research: Atmospheres in the near future. A poster summarizing the results was presented at the American Geophysical Union 2023 Annual Meeting and can be viewed here: Sea Ice and Ocean Response to a Strong Mid-Winter Cyclone in the Arctic Ocean

Setting up a computing environment

The analysis was carried out using open-source libraries for Python 3.9. The computing environment can be recreated using the package list in the file airsea.yml. If you do not already have an installation of the environment manager conda, follow the instructions to download microconda(a minimal installation of the conda environment manager). You can then create an environment with the necessary packages by running this code in a terminal window:

conda env create --file airsea.yml

Preparing data

The data preparation scripts require the following datasets to be downloaded. For ERA5, a download script is included. Using this script requires an account at the Copernicus Data Store. Similarly, a download script for the sigma6 radar product is provided. 1. Drifting buoy dataset: Bliss et al. data paper * prepare_buoy_data.py Applies standard_qc and interpolate_buoy_track funtions from the drifter.py file to the MOSAiC buoy data files to produce quality controlled, hourly-resolution time series with stereographic coordinates and velocity estimates. Trajectories are saved to the folder data/interpolated_tracks/. Data from the Arctic Data Center should be placed in the folder data/adc_dn_tracks.

1. Meteorological data from flux towers and sleds: Cox et al. data paper

   • compile_met_data.py Produces CSV files from the Level 3 Met City and ASFS netCDF datasets. Data must first be downloaded from the Arctic Data Center and the user specifies the location where the data are stored.

2. Meteorological data from ERA5 reanalysis: Single level and pressure level data from the Copernicus Data Store

   • prepare_era_data.py Downloads ERA5 data from 2020-01-25 to 2020-02-05 and saves it locally, then uses xesmf to regrid onto the NSIDC polar stereographic grid. Data is saved to the folder data/era5_regridded.

3. Sea ice concentration from AMSR Unified 12 km: National Snow and Ice Data Center

   • compile_amsr.py Reads in the daily 12 km AMSR data obtained from NSIDC and compiles the files into a single netcdf file. Expects hdf-5 files from NSIDC to be in the folder data/amsr.

4. Sea ice sigma 6 radar: Krumpen et al. (2021), Pangaea Data Repository

Parameter files

• array_info.csv Table containing the buoys used in the deformation arrays, and the color scheme.
• buoy_info.csv. TBD table with the buoy parameters, used to make a table for manuscript.

Utilities

• drifter.py Functions for processing the drifting buoy data

Figures

Figure 1: Map of the MOSAiC drifting buoy array

Produced by plot_maps.py. Requires interpolated buoy tracks.

Figure 2

• plot_multi_storm_overview.py Requires gridded ERA5, AMSR2, and buoy data.

Figure 3

• plot_storm_system.py Requires gridded ERA5 and buoy data.

Figure 6

plot_Lsite_tracks.py Plots the 4 panels showing ERA5 wind, observed wind, and drift speed, and the two motion cusps. Requires companion figure to merge for the final figure.

Figure 7

plot_DN_trajectories.py Shows the curvature of the trajectories and the cusp timing.

Figure 8

plot_velocity_time_series.py Produces the two components of Figure 7 and Figure S1 and merges them.

Figure 9 and 10

plot_deformation_time_series.py Produces the two components of Figure 9 and Figures S1 and S2 and merges them.