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Class Information
Instructor:
Dan Vimont
1123 AO&SS Building
Phone: 263-3420
email: dvimont@wisc.edu
Course Website:
http://www.aos.wisc.edu/~dvimont/aos575
Meeting Time and Location:
Class meets MWF at 9:55-10:45 a.m., in AO&SS 811
Office Hours:
By appointment
Course
Syllabus: (PDF)
Course Schedule: (PDF)
Paper Discussions: (PDF)
Final
Project Description: (PDF)
Lecture
Notes
We will be using lecture notes
provided
courtesy of Profs. Dennis Hartmann and John M. Wallace (Department of
Atmospheric Sciences, Unversity of Washington). All chapters are
in PDF format.
Chapter 1: Review of Basic
Statistics
Bivariate Normal
Distribution Notes
T-test notes
Chapter 2: Composite
Analysis
Chapter 3: Linear Regression
Chapter 4: Multivariate
Analysis
Chapter 6: Time Series
Analysis
Chapter 6a: Time series
analysis, Part 1
Chapter 6b: Time series
analysis, Part 2
Chapter 6c: Cross-spectral
analysis
Chapter 6d: Other spectral
techniques (SST, Multi-Taper, Maximum Entropy, etc.)
Homework
Chance,
2000:
Due: 1/25/2008
Read Chance, 2000, and answer the questions posted here
Chance,
2000 may be found here
Homework
1: Due 2/13/2008
Homework
1: PDF version
Sample MATLAB scripts
madison_temperature.txt
madison_precip.txt
Paper 1: Discussion / Due
2/8/2008
Paper Reading #1 Handout: PDF
version
Brier
and Bradley, 1964
Reed
and Recker, 1971
Homework
2: Due 2/27/2008
Homework
3: PDF version
Table with Problem 1 data: HW2_prob1_data.txt
Sample MATLAB Script: composite_ENSO.m
(Note: you'll need cti.djf... and
tsfc.NA.19... below for this routine)
cti.djf.1950.2005.mat
hgt.500mb.NA.1950.2005.mat
tsfc.NA.1950.2005.mat
amm.data.mat
Other routines that you may find useful:
wysiwyg.m
corr.m
worldlo.mat
worldlo.m
Paper
2: Discussion Friday 2/29/2008
PDF version of assignment
Lindzen
et al., 2001
Hartmann
and Michelsen, 2002
Homework
3: Due 3/12/2008
Homework 3: PDF version
regression_example.m
co2.maunaloa.1959.2005.txt
hw3_prob2_data.mat
CTI_regmaps.m
THE FOLLOWING TWO FILES ARE BIG! Right click on them, and
download them to an appropriate directory.
CTI_monthly_data.mat
CTI_winter_data.mat
Paper 3: Discussion Friday 3/7/2008
PDF version of assignment
Quadrelli
and Wallace, 2004
Hare and Mantua, 2000
Homework 4: Due 4/9/2008
Homework 4: PDF version
hw4_example1.m
nhem_slp_1979-2006.mat
eof_routine.m
cosweight.m
hw4_prob3_dat.mat
Sample code for setting up a map axis to plot a polar-stereographic
plot:
plot_polar_stereo.m
Paper 4: Discussion Friday 4/4/2008
PDF version of assignment
Chiang
and Vimont, 2004
Deser and Timlin, 1997
Homework 5: Due 4/23/2008
Homework 5: PDF version
olr1_pentad_data.mat
olr2_pentad_data.mat
spectral_analysis.m
Paper 5: Discussion Friday 4/18/2008
(3 pm)
PDF version of assignment
Other Lecture Materials
MATLAB
Demos
I also have a lot of matlab
functions,
including my matlab libraries, here:
http://www.aos.wisc.edu/~dvimont/matlab
EOF Analysis
eof_routine.m
cosweight.m
Suppose you want to perform EOF analysis on tropical Pacific SST from
the NCEP reanalysis. Here's a quick way to do that, assuming
you've downloaded my matlab libraries, above:
lims = [120 285 -30 30];
tim = get_time(1948,2002,1948);
[sst, lat, lon] = getnc2('skt.mon.mean.nc', 'skt', lims, 1, tim);
land = getnc2('land.sfc.gauss.nc', 'land', lims, 1, 1);
sst = remove_anncyc(sst);
sst = cosweight(sst, lat);
[lam, lds, pcs, per] = eof_routine(sst(:,land==0));
% Get a scaled map of the leading EOF
eof1 = repmat(NaN, [length(lat) length(lon)]);
eof1(land == 0) = lds(:,1)*sqrt(lam(1));
eof1 = uncosweight(eof1, lat);
chi2example.m:
1. A demo for using the Chi2 distribution to determine confidence
limits on variance
2. Shows how to construct an AR1 time series, compute its power
spectrum, and compare the spectrum to a theoretical AR1 power spectrum
with confidence limits derived from the chi2 distribution.
Example1_16_Feb.m:
This
example demonstrates univariate and multivariate linear regression in
MATLAB. Regression is used to predict summer ozone concentrations
along the Gulf Coast from meteorological variables. More
information about this data set can be found from "Case Studies
in Environmental Statistics", from the Geophysical Statistics
Project, through NCAR. This example should provide enough
information to solve problem 1 on HW2.
This routine uses: Regression_example.mat
Example2_16_Feb.m:
This
example demonstrates how to generate regression maps of SST or 500mb
height onto the CTI. This requires accounts on the 14th floor
computer to access the data. This example demonstrates how you
might solve Problem 2 from HW2 (2005)
HW2_prob3_code.m:
This
example demonstrates how you would go about solving problem 3 on HW2
(2005).
eof_example.m:
This
example demonstrates EOF/PC analysis on a simple matrix. This
calculates the EOF's in two ways: by eigenanalysis of the
covariance matrix, and by singular value decomposition of the data
matrix.
define_pdo.m:
This
is the code used to calculate the PDO time series in Homework 3.
Note that it uses a bunch of routines from my MATLAB libraries, at:
http://www.aos.wisc.edu/~dvimont/matlab
define_aleutianlow.m:
This
is the code used to calculate the Aleutian Low time series in Homework
3. Note
that it uses a bunch of routines from my MATLAB libraries, at:
http://www.aos.wisc.edu/~dvimont/matlab
weekly_extremes.m:
This
routine generates an AR(1) time series, then calculates extreme values
in that time series relative to the rest of the week.
These two routines can be used in Homework 4:
autocorr.m
partial_autocorr.m
spectral_analysis.m:
Fun with
spectral analysis, including generating AR1 and AR2 null
hypotheses. There's also a routine for calculating alph1 and
alph2 for the AR2 null hypothesis. Hey, check out the similarity
between calculating alph1 and alph2 herein, and "partial_autocorr.m",
above. You can do this using either.
filter_nr.m:
Non-recursive
filtering routine.
freq_stuff.m:
This routine calculates the frequency response function for a couple of
filters. Also, the IRF, etc...
tutorial.m:
This
is the companion to the tutorial handed out in class.
EOF analysis example scripts: EOF analysis applied to the
following image:
First, download the image to your ~/matlab/Data directory. Then,
download the following scripts to an appropriate directory:
eof_pics.m
plot_island_demo.m
subplot2.m
global_axes.m
figure_tall.m
The EOF analysis example is in 'eof_pics.m', and the plotting routine
is in 'plot_island_demo.m'. The other routines are used in the
plotting routines.
Here are some other routines that might be useful:
wysiwyg.m
worldlo.m
worldlo.mat
corr.m
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