Assignment: CERES data

To solve the following exercises you can copy and paste code from the previous notebook. The code modifications required to solve the exercises are minimal (e.g. changing the name of a variable, add a small computation…): don’t think too “complicated”!

Importing the modules

This one is easy. I’ll do it for you:

# 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

TOA fluxes

Read the TOA dataset we used during the lesson. Do you remember all variables it contains?

# Your answer here

Albedo

Compute the climatological mean of clear-sky planetary albedo \(\overline{\alpha_{P_{clr}}}\) and plot it on a map. Analyse the plot.

# Your answer here

Repeat the operation with all-sky planetary albedo \(\overline{\alpha_{P_{all}}}\). Where are the largest differences? Can you plot the difference between the two on a map, too?

# Your answer here

Now plot the zonal, climatological means \(\left[ \overline{\alpha_{P_{all}}} \right]\) and \(\left[ \overline{\alpha_{P_{clr}}} \right]\) on the same plot. Add a legend to it!

# Your answer here

Compute the global average of \(\overline{\alpha_{P_{all}}}\) and \(\overline{\alpha_{P_{clr}}}\) (remember to weight according to latitude!). Compare the values you obtain with the ones we mentioned in the lecture.

# Your answer here

Longwave outgoing radiation

Repeat the operations above with \(LW_{all} \) and \(LW_{clr}\) (i.e.: maps of \(\overline{LW_{all}}\), \(\overline{LW_{clr}}\), line plots of \(\left[ \overline{LW_{all}} \right]\), \(\left[ \overline{LW_{clr}} \right]\)). What is the global effect of clouds on outgoing longwave radiation?

# Your answer here

Surface fluxes

Now open the EBAF-Surface dataset, available for download from the download page.

# Your answer here

Surface albedo

Compute the all-sky surface albedo \(\overline{\alpha_{S_{all}}}\). Plot it on a map.

# Your answer here

Compute the global average of \(\overline{\alpha_{s}}\).

# Your answer here

Surface energy balance

Now compute the net surface energy intake \(\overline{SEB} = \overline{SW_{in}} - \overline{SW_{out}} + \overline{LW_{in}} - \overline{LW_{out}}\). Plot it on a map and analyse your results. Where does the surface gain most energy? Is the net radiative energy a gain or a loss for the surface of the globe?

# Your answer here

Compute the global averages of each term and compare them to the values we discussed in the lecture (ref). For reference, here is the figure again:

# Your answer here

Discuss the processes that will counterbalance this net radiative energy imbalance, in the oceans and on land! Also discuss the differences between your results and the plot above. (Careful literature search might lead you to more recent estimates of the budget if you are interested).

# Your answer here