Aim
This module applies the basic knowledge of atmospheric physics and
dynamics gained in the first semester to develop a quantitative
understanding of the mean structure and variability of Earth's climate.
Learning outcomes
On completion of this module, students should be able to:
Resources
Official
module descriptor page
Syllabus
Figures shown in class:
Part I: The basics
[html]
[ppt]
[pdf]
Part II: The tropics
[html]
[ppt]
[pdf]
Part III: The extratropics
[html]
[ppt]
[pdf]
Part IV: The ocean circulation
[html]
[ppt]
[pdf]
Part V: Climate variability
[html]
[ppt]
[pdf]
Part VI: Paleoclimatology
[html]
[ppt]
[pdf]
Exercise sets:
Lab 1
Lab 2 (assessable)
Lab 3
Lab 4
Lab 5
Lab 6 (assessable)
Lab 7
Hartmann
and Michelsen (1993) paper on the sensitivity of the surface energy budget
Trenberth et
al. (2001) paper on implied poleward heat transports
Held and Soden (2000) paper on water vapour feedback
Soden
and Held (2006) paper on climate feedbacks in GCMs
Emanuel
(2003) review paper on tropical cyclones.
Vallis and Gerber
(2007)
paper on the NAO and annular modes.
Pierrehumbert, Principles of Planetary Climate book in prep.
The IPCC AR4 report.
Animation of high-resolution simulation of atmospheric motion.
Animation of gray-gas
radiative-convective equilibration.
RealClimate.org, a site with
high-quality but very accesible articles on climate science (check out
the index)
ISCCP
cloud data viewer
Figure
skater illustrating conservation of angular momentum
Additional Resources
CH 01
CH 02
CH 2.1
CH 03
CH 04
CH 05
CH 06
Ch07 WRF Intro
CH 08
CH 09
CH 10
Run the WRF Model
Lab 1
Assignment 1
Data Set 1
Data Set 2
Assignment 3
Online radiation codes
Diurnal cycle with
fixed temperature
Solve for
temperature that gives top-of-atmosphere radiative equilibrium
Python resources
Python tutorial
Python
notes to go with A First Course in Climate
Dive into
Python,
an online Python text book
Documentation for
the Numeric module (how to generate and manipulate arrays)
Scripts used in class:
OLR.curve.py OLR as function of
surface temperature with gray-gas scheme.
Runaway.py OLR as function of
surface temperature with increasing relative humidity: illustrates
runaway greenhouse.
Insolation.py Seasonal cycle of insolation
Schwarzschild.weighting.function.py
Schwarzschild weighting function and effective emission level
emission.level.py Compute
effective emission level given OLR and temperature profile.
mass.streamfunction.py Compute
meridional mass streamfunction from zonal-mean v.
deformation.py Compute and plot
deformation due to differential advection.
plot.psi.omega.py Plot
streamfunction and vertical velocity, solutions to exercise 6.4 in Holton.