ClimatePlots is the plotting library that supports ClimateTools.jl.

Documentation for ClimateTools can be found here.

Visualization

Maps

Mapping a ClimGrid is done by using the contourf, contour and pcolormesh functions from the package ClimatePlots.

using ClimateTools # to load the netcdf file
using ClimatePlots # which exports the `contourf` function.
C = ClimateTools.load(filenc, "pr", data_units="mm")
contourf(C)

Note that the functions plots the climatological mean of the provided ClimGrid. Multiple options are available for region: World, Canada, Quebec, WorldAz, WorldEck4, ..., and the default auto which use the maximum and minimum of the lat-long coordinates inside the ClimGrid structure (see the documentation of contourf for all region options).

Timeseries

Plotting timeseries of a given ClimGrid C is simply done by calling plot. This returns the spatial average throughout the time dimension.

using ClimateTools
using ClimatePlots
poly_reg = [[NaN -65 -80 -80 -65 -65];[NaN 42 42 52 52 42]]
# Extract tasmax variable over specified polygon, between January 1st 1950 and December 31st 2005
C_hist = ClimateTools.load("historical.nc", "tasmax", data_units="Celsius", poly=poly_reg, start_date=Date(1950, 01, 01), end_date=Date(2005, 12, 31)))
# Extract tasmax variable over specified polygon, between January 1st 2006 and December 31st 2090 for emission scenario RCP8.5
C_future85 = ClimateTools.load("futureRCP85.nc", "tasmax", data_units="Celsius", poly=poly_reg, start_date=Date(2006, 01, 01), end_date=Date(2090, 12, 31)))
C = merge(C_hist, C_future)
ind = ClimateTools.annualmax(C) # compute annual maximum
plot(ind)

Note. Time labels ticks should be improved!

The timeserie represent the spatial average of the annual maximum temperature over the following region.

contourf(ind, region = "Quebec")

The map represent the time average over 1950-2090 of the annual maximum temperature.