CryoSat-2 data wrangling#

Summary This notebook loads the different CryoSat-2 datasets used in our ICESat-2/CryoSat-2 comparison analysis into a single NETCDF4 file, with descriptive attributes maintained for each dataset. Each dataset is regridded to the ICESat2 grid shape [304, 448] (x,y). The datasets used in this notebook are listed below.

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

Details on the CryoSat-2 datasets#

NASA GSFC CryoSat-2 monthly mean winter Arctic sea ice thickness#

CPOM CryoSat-2 monthly mean winter Arctic sea ice thickness#

  • Download link:

  • Reference: Laxon, S. W. et al. CryoSat-2 estimates of Arctic sea ice thickness and volume. Geophysical Research Letters 40, 732-737 (2013).

  • Notes: data are posted on a higher-res grid than the other datasets.

AWI CS-2/SMOS CryoSat-2 monthly mean winter Arctic sea ice thickness#

University of Bristol CryoSat-2 monthly mean all-season Arctic sea ice thickness#

JPL ICESat-2/CryoSat-2 monthly mean winter Arctic sea ice thickness#

  • Download link:

  • Reference: Kacimi, S., Kwok, R. (2022), Arctic snow depth, ice thickness and volume from ICESat-2 and CryoSat-2: 2018-2021, Geophysical Research Letters, doi: 10.1029/2021GL097448.

  • Notes: no projection information but was told it’s on the NSIDC EPSG 3411 projection


Although you’ll see an option to run this notebook in Binder, this notebook is NOT configured to run in Binder. If you want to wrangle the data yourself, each dataset used to compile the final data product can be downloaded from the links above. The final data product produced by this notebook can be downloaded from the google storage bucket associated with this jupyter book.

Import notebook dependencies#

import xarray as xr # For working with gridded climate data 
import pandas as pd
import numpy as np
import itertools
import pyproj 
from netCDF4 import Dataset
import scipy.interpolate 
from utils.read_data_utils import read_book_data # Helper function for reading the data from the bucket
from utils.plotting_utils import compute_gridcell_winter_means, interactiveArcticMaps, interactive_winter_mean_maps, interactive_winter_comparison_lineplot # Plotting

# Plotting dependencies
import as ccrs
from textwrap import wrap
import hvplot.xarray
import holoviews as hv
import matplotlib.pyplot as plt
from matplotlib.axes import Axes
from cartopy.mpl.geoaxes import GeoAxes
GeoAxes._pcolormesh_patched = Axes.pcolormesh # Helps avoid some weird issues with the polar projection 
%config InlineBackend.figure_format = 'retina'
import matplotlib as mpl
mpl.rcParams['figure.dpi'] = 150 # Sets figure size in the notebook

# Remove warnings to improve display
import warnings