Assignment: major features of the atmospheric circulation#

# Import the tools we are going to need today:
import matplotlib.pyplot as plt  # plotting library
import numpy as np  # numerical library
import xarray as xr  # netCDF library
import cartopy  # Map projections libary
import cartopy.crs as ccrs  # Projections list
# Some defaults:
plt.rcParams['figure.figsize'] = (12, 5)  # Default plot size

Sea-level pressure and surface winds#

ds = xr.open_dataset('../data/ERA5_LowRes_MonthlyAvg_uvslp.nc')

Compute \(\left[ \overline{SLP} \right]\) (in hPa), and plot it. With the help of plt.axhline, add the standard atmosphere pressure line to the plot to emphasize high and low pressure regions.

# Your answer here

Repeat with \(\left[ \overline{u_{10}} \right]\) and \(\left[ \overline{v_{10}} \right]\) (in m/s) add a horizontal line at zero windspeed to the plot (to detect surface westerlies from easterlies for example). Analyse the three plots alltogether. How do they fit to the circulation we discussed in the lecture?

# Your answer here

Plot the annual \(\overline{SLP}\) on a map. Choose adequate levels and colormap, so that low pressure and high pressure systems are visible. These are called “semi-permanent highs and lows”. Can you name most of them?

  • Icelandic Low

  • Aleutian Low

  • Subtropical highs: Bermuda High, South/North Pacific High…

  • Siberian High

  • Monsoon Low (or through)

  • …

# Your answer here

Now use the same colors and levels as above, and plot \(\overline{SLP}\) for the months of January and July. Compare the evolution of the major systems. When are they strongest? Weakest? Which systems disappear entirely?

# Your answer here

General circulation of the upper atmopshere#

ds = xr.open_dataset('../data/ERA5_LowRes_MonthlyAvg_4D_zuvw.nc')

Geopotential and zonal winds#

Compute \(\left[ \overline{z_h} \right]\), where \(z_h\) is the geopotential height (unit: m). Plot it (you can use .plot.contourf(levels=18, center=False) for example). Don’t forget to put the y-axis in the right direction!

# Your answer here

What is the approximate average height of the 200hPa level at the poles? At the tropics? Not that easy to see, right? Instead, you can try to compute the anomaly of \(\left[ \overline{z_h} \right]\) with respect to \(\left\{ \left[ \overline{z_h} \right] \right\}\), where \(\left\{ \right\}\) would represent the meridional average. Plot it (this time without the center keyword) and analyse the plot: what altitude difference is there at the 500hPa level between the equator and the poles? And at the 200hPa level? How does that fit into the thermal wind concept we discussed in the lecture?

# Your answer here

Repeat the operation with the month of January and July. Analyse the differences.

# Your answer here

Now plot the zonal temporal average of the zonal wind \(\left[ \overline{u} \right]\), for the annual average and the months of January and July. Analyse the plot: when and where is the zonal wind speed highest? Where is the zonal wind negative?

# Your answer here

Meridional overturning circulation#

Compute the stream function of the meridional overturning circulation of the atmosphere for the annual average and the months of January, April, July, and October. Plot all five with the same colors and levels for comparison. Analyse what you see.

# Your answer here

Stationary waves in the mid- and upper troposphere#

“Stationary waves” or “stationary eddies” are circulations which are absent from the zonal mean, but visible in the temporal average of the wind field (see lecture). A nice way to visualize stationary waves is simply to plot \(\overline{z^{*}}\) (with \(z\) the geopotential). Remember what this is? We computed this anomaly in the “temperature and precipitation data” assignment last week.

Select data in one hemisphere (NH is a bit stronger), for one pressure level and for one month, and plot \(\overline{z^{*}}\) on a map.

# Your answer here