Meeting time and place: Monday, 10:30a-12:00 pm (Tucson time), location TBD.
Instructor: Michael Evans, ph (301) 405-8763. More about the instructor is here.
Office hours and location: via email and teleconference (see below).
Unofficial Course TA: Yolande Serra, ph (520) 621-6619.
Office hours and location: via email and appointment.
Reading and Course Materials: Readings from selected topical, authoritative and/or timely sources will be linked in the Schedule/Syllabus below as password-protected Portable Document Format (pdf) files. Lecture (preview) notes (may/may not include work and exercises performed in class) will be linked as html files and also as downloadable Microsoft PowerPoint-compatible files or pdfs. They may, but not guaranteeably so, be available prior to class meetings, and are subject to change and correction. We will make use of copyrighted materials under academic Fair Use Policy of applicable copyright law.
Readings, pre-session assignment (Prework), and problem sets to be
started in class and completed as homework (Classwork).
Written and oral presentation of a final project applying the
concepts and tools studied in this workshop is required.
Look for Reading and Prework to be posted by Thursday 5pm
the week before it is discussed; Classwork to be posted the day we
attack it in class. If you need to work ahead of time due to
prior commitments, please let me know well ahead of time so I can
try to accomodate you.
Disability resources: Do you have a physical or learning disability? Please speak with me right away about accommodations. You will only need to have the Disability Resource Center send me a confidential documentation letter, and we can make arrangements from there.
OverviewHow are the principal features buried in noisy spatiotemporal datasets routinely identified in meteorological, climatological and paleoclimatological research? This course will provide practical experience in the fundamental concepts, coding, use and abuse of two commonly used tools, empirical orthogonal function analysis and singular spectrum analysis. We will apply these tools to the analysis and interpretation of historical climate data sets. In parallel we will critically assess the strengths and weaknesses of these techniques by examining similar analyses published in the climate dynamics literature.
By the conclusion of this course, you should be able to demonstrate the following skills in pursuit of the following goals, via the following assignments:
||Skills Goals||Assignments (see course structure)
|Understand the strengths and weaknesses of tools which use empirically-derived basis functions.||Develop basic concepts in elementary linear/matrix algebra at the heart of empirical analysis techniques, and code scripts to perform these analyses in a high-level scripting language such as Matlab or GNU/Octave.||Prework, Classwork
|Analyze and interpret the principal features resolvable in climate data (x,y,t)||Perform such analyses on
historical gridded climate data (possibly to include sea
surface temperature, sea level pressure, and surface air
|Critically assess similar analyses in the meteorology and/or climate dynamics literature.||Practice elements of the
Matrix algebra, Linear algebra:
Each week's work will consist of the following cycle:
This is a new course (second offering) and a new approach for me; there are likely to be many "bugs". Your patience may be required often. I will be looking for feedback from you as we go as to how to best tailor this course to your needs. Consequently we may have informal, anonymous, occasional 1-minute teaching evaluations and mid-semester evaluations, in addition to the usual end-of-course evaluations. Your candid and constructive observations are appreciated.
Schedule/Syllabus (subject to change)
Note: Scanned readings are password protected to meet copyright fair use guidelines. If you need the userid and password, email the instructor.
||Introduction and Big Picture; the
||Course overview, logistics; Get set up to compute with Matlab on CLUE Lab PCs||Homework
0 (due Aug. 25th)
Solutions are here.
||The art of programming||Pratap 2002, excerpts (5 Mb pdf)||Prework 1 (due Aug 25th)
A class-compiled webpage of functions you might use for classwork assignments is here.
the MATLAB environment; Elements of programming logic and
||Homework 1 (due Sept. 8th)
My script is here.
||Basic matrix algebra manipulations and implementation in Matlab||Strang, Ch. 1,
pp. 1-9, 19-27, 42-48 (8.4 Mb pdf)
Optional: Elsner and Tsonis (1996) Ch. 1-2 (2.7Mb pdf) and Navy's Matlab quick reference
|Prework 2 (due Sept. 15th)
||Matrix algebra is your friend||Homework 2 (due Sept. 15th)
My script is here.
||Input: gridded historical sea surface temperature dataset||Bottomley et al., (1990) (11Mb pdf)||Prework 3 (due Sept. 13th)
data; covariance estimation
||Homework 3 (due Sept. 22nd)
My script is here.
|Linear algebra review;
EOF analysis (space)
Oort (1992), Appendix B (348k pdf) and
Weare et al. (1976) (686k pdf).
|Prework 4 (due Sept. 22nd). A student response is here. A link to a Mathworks piece on applications of the SVD is here.||EOF
of a covariance matrix (notes).
4 (due Oct. 6th)
Pencil and paper solutions are here; Matlab script is here; plots are here (Q3 plot; SST field evals, evecs, PCs). A student response is here.
Office hours this week are on Tuesday, 2-3pm, not Monday
|Error, stability, truncation and filtering (space)||Overland and
Preisendorfer (1982) (313k pdf); optional: North et al.
(1982) (348k pdf)
||Prework 5 (due Oct 6th). A student response is here.||Signal vs. noise: How many EOFs are
interpretable? How stable are the interpretable
5 (due Oct 13th)
Script to solve HW5 is here; my plots are here (Rule N results; filtering results; stability of eof patterns). A student response is here.
||EOF rotation; Caveats on interpretation of EOF patterns||Wilks (2006) pp.492-500 (3.3Mb pdf); Dommenget and Latif (2002) (641 kb pdf); Optional: A review and discussion of rotation methods by Richman and Jolliffe is here.||Prework 6 (due Oct 13th). A student response is here.||What are the pros and cons
of EOF rotation?
||Homework 6 (due Oct 20th) Script to solve HW6 is here; my plots are here (simple example; SST EOF pattern rotation (fig 1 and fig 2); corresponding PCs). A student response is here.|
Mid semester course evaluation
results are here.
|Ghil et al
pdf), sections 1-2.2 (pp. 3-1 to 3-11)
||Prework 7 (due Oct 18th). A student response is here.||Singular spectrum analysis
algorithm; EOF analysis of a trajectory matrix; RC
calculation. Notes from class are here (updated
||Homework 7 (due Oct 27th) Paper and pencil solutions are here; Matlab script to solve HW7 is here; Plot of results is here. Start thinking about the dataset you wish to analyze for your class project; a broad, searchable database is here. A student response is here.|
||Error, stability, truncation and filtering (time)||Ghil et al
pdf), sections 2.3 (pp. 3-11 to 3-13);
Vautard and Ghil (1991) (522 kb pdf);
Elsner and Tsonis (1991) (297kb pdf)
||Prework 8 (due Oct 27th). A student response is here.||Monte-Carlo error estimates for
eigenvector retention; effect of choice of embedding
||Homework 8 (due Nov. 3rd) Matlab script to solve HW8 is here; plots of results are here and here. A student response is here.|
||Student projects: Introduction||student project consultations
||Student projects: supervised worktime and consultation; Analysis of the covariance between two (or more) spatiotemporal fields||PW9 reading: Wallace et al.
(1992) sections 1-4 (1.5Mb); see
Prework assignment for optional readings.
9 (due Nov. 15th). A student response is here.
||Student projects: supervised worktime and consultation||student project
||Thanksgiving week off
(office hours Monday, Nov. 20th as usual)
presentations are here.
||Independent project presentations and peer evaluations.|
General results, lessons, caveats, future work.