x4c: Xarray for CESM

x4c is an Xarray extension that aims to support efficient and intuitive CESM output postprocessing, analysis, and visualization:

• Postprocessing features: time series generation, seasonal cycle climatology generation, etc.

• Analysis features: regrid, various of mean calculation, annualization/seasonalization, etc.

• Visualization features: timeseries plots, zonal mean plots, horizontal and vertical 2D spatial plots, etc.

Installation

Installation instructions.

Core Features

x4c as an Xarray extension.

CESM Postprocessing

Timeseries generation using the History class.

CESM Diagnostics

Diagnostics using the Timeseries class and the spell magics.

API Reference

The essential API.

Gallery¶

Every figure below comes from a notebook in this documentation, and every one is reachable in a line or two. Click any to open the notebook that produced it.

Water isotopes, annual mean

da.x.regrid(2,2).x.annualize().mean('time').x.plot(…)

EOFs of sea-surface height

m.x.plot(ax=axd[k], ssv=ssv, cmap='RdBu_r', …)

Ocean and land state

ocean['SST'].x.regrid(2,2).mean('time').x.plot(…)

A whole diagnostics dashboard

case.quickview(timespan=(1, 10))

Native grid to regular lat/lon

ds.x.da.isel(time=0).x.regrid().x.plot(…)

A variable you defined yourself

case.calc('PRECT_MM|regrid(2,2):ann')

Vertical sections, same call

moc.x.plot(levels=np.linspace(-20, 20, 21))

Publication styles, built in

x4c.set_style('journal')

Seasonal averaging, DJF included

da.x.annualize(months=[-12, 1, 2])

Any Cartopy projection

x4c.subplots(1, 3, projs={...})

Hybrid levels to pressure levels

ds.x.get_plev(ps, hyam=..., hybm=...)