Winter Arctic sea ice state variability

Summary: In this notebook, we highlight key additional sea ice variables: snow depth, ice type, snow density, and sea ice drift. We’ll use cartopy and xarray to generate maps and lineplots of the data to demonstrate methods for visualizing the data statically, as opposed to the interactive plotting functions highlighted in the seperate interactive notebooks (which can be slow to render and push the GitHub file size limits!).

Please take a look at the ‘Data variables’ tab in the book_ds cell below to explore the potential variables for analysis in this notebook.

The dataset also includes a few interpolated/smoothed variables (freeboard_int, snow_depth_int, ice_thickness_int) that can be used instead of the raw monthly means to increase coverage in some regions. See the interp_demo notebook for more information on how they are derived.

The analysis presented here was peer-reviewed in this paper in The Cryosphere.

Version history: Version 1 (01/01/2022)

Import notebook dependencies

# For working with gridded climate data 
import xarray as xr 
# Helper function for reading the data from the bucket
from utils.read_data_utils import read_book_data 
from utils.plotting_utils import static_winter_comparison_lineplot, staticArcticMaps, staticArcticMaps_overlayDrifts, interactiveArcticMaps, compute_gridcell_winter_means # Plotting utils 
import numpy as np
# Plotting dependencies
#%config InlineBackend.figure_format = 'retina'
import matplotlib as mpl
# Sets figure size in the notebook
mpl.rcParams['figure.dpi'] = 150 

# Remove warnings to improve display
import warnings 
warnings.filterwarnings('ignore')