Smooth Mean Daily Annual Cycle

Note

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Smooth Mean Daily Annual Cycle#

Calculates a smooth mean daily annual cycle.

Before proceeding with all the steps, first import some necessary libraries and packages

import xarray as xr
import easyclimate as ecl
import matplotlib.pyplot as plt

Preprocessed data

Tip

You can download following datasets here:

lats, latn = -20, 20

olr_data = xr.open_dataset('olr-daily_v01r02_19800101_20231231.nc', chunks='auto').sel(lat=slice(lats,latn)).olr
olr_data_daily_annual_cycle_mean = ecl.calc_daily_annual_cycle_mean(olr_data).thin(lat = 2, lon = 5).compute()

olr_data_daily_annual_cycle_mean = ecl.utility.get_compress_xarraydata(olr_data_daily_annual_cycle_mean)
olr_data_daily_annual_cycle_mean.to_netcdf("olr_daily_annual_cycle_mean.nc")

Here, we directly load the data of mean daily annual cycle for outgoing longwave radiation (OLR).

olr_data_daily_annual_cycle_mean = xr.open_dataset("olr_daily_annual_cycle_mean.nc").olr
olr_data_daily_annual_cycle_mean

Simply do a regional average for the tropics

olr_data_ave = olr_data_daily_annual_cycle_mean.mean(dim = ("lon", "lat"))
olr_data_ave.plot()

[<matplotlib.lines.Line2D object at 0x7fd6464a22c0>]

By removing excess noise in the mean daily annual cycle through the way of easyclimate.smooth_daily_annual_cycle, we can plot the following:

olr_data_ave_smoothed = ecl.smooth_daily_annual_cycle(olr_data_daily_annual_cycle_mean).mean(dim = ("lon", "lat"))

olr_data_ave.plot(label = "Daily annual cycle mean")
olr_data_ave_smoothed.plot(label = "Smoothed daily annual cycle mean")
plt.legend()

<matplotlib.legend.Legend object at 0x7fd6462f1390>

Total running time of the script: (0 minutes 4.114 seconds)