SIO 221B:  2002 Homework

Problem set 1: due Friday October 11, 2002.

• Problem Set 1
• Data rcm00001.str
• Solution Problem Set 1 solutions
• Bonus
  • Liz Douglass (1) Liz Douglass (2)
  • Shane Elipot
  • Jessica Kleiss (1) Jessica Kleiss (2)
  • Takuro Kobashi (1) Takuro Kobashi (2)
  • Andy Thompson (1) Andy Thompson (2)
  • Sarah Zedler

Problem set 2: due Friday October 18, 2002.

• Problem Set 2
• Problem Set 2 solutions

Midterm: due Friday October 25, 2002.

• Midterm
• Midterm solutions
• Clarification 1: question 2b. Compute 4 moments.
• Clarification 2: question 3. Assume that x's are uncorrelated.
• Clarification 3: question 4. Compute a single covariance matrix for all of the data.
• qs875S.dat (data file 1: winds at 177.5 E, 8.75 S)
• qs625S.dat (data file 2: winds at 177.5 E, 6.25 S)
• qs375S.dat (data file 3: winds at 177.5 E, 3.75 S)
• Data is arranged as follows: column 1: latitude. column 2: longitude, column 3: u component of wind. column 4: v component of wind. column 5: local time of day. column 6: number of measurements averaged for this wind value
• QuikSCAT measures at roughly 6 am and 6 pm every day. These observations are spaced 12 hours apart, starting in July 1999 and running for 3 years through July 2002. (That's 365*2 + 366*2 +365*2 observations.)

Problem set 3: due Friday November 1, 2002.

• Problem Set 3
• Problem Set 3 solutions

Problem set 4: due Friday November 8, 2002.

• Problem Set 4
• ps4_profile.dat
• Problem Set 4 solutions

Problem set 5: due Friday, November 15, 2002.

• Problem Set 5
• Problem Set 5 solutions
• Bonus
  • Jessica Kleiss (text) Figure 1 Figure 2 Figure 3 Figure 4 Figure 5
  • Takuro Kobashi
  • Sarah Zedler (1) Sarah Zedler (2)

Problem set 6: due Wednesday, November 27, 2002.

• Problem Set 6
• Matlab file containing both data arrays: hw6.mat
• Zonal velocity on the equator at 22 m depth: ueq.dat
• Longitudes of zonal velocities: loneq.dat
• Problem Set 6 solutions

Problem set 7: due Friday, December 6, 2002.

• Problem Set 7
• amsterdam_brp.dat. Amsterdam Island bottom pressure record for this assignment. Note that bottom pressure shows substantial drift for the first few hundred values, so you may have clearer results if you start your analysis around data point 900. Column 2 indicates flagged data.
• Solutions available for those who have handed in the problem set.
• Problem Set 7 solutions

Final: take-home due Friday, December 13, 2002.

• Final
• Question 2 Clarification: Here by mean flux, I mean "mean eddy flux".
• Question 3 Clarification: sigma_T is the a priori data noise for each measurement.
• Question 4 Clarification: Assume that your hydrographic stations provide temperature, salinity, and pressure. If other things seem useful, you may comment on them as well.
• Question 5 Clarification: The desert island where you are stranded has no internet access. To be specific, temporal fluctuations of temperature above the thermocline at 60 N and 40 N are inversely correlated. XBTs measure temperature as a function of depth. The PDO is a single index time series that represents fluctuations throughout the Pacific Ocean---it's actually a mode 1 EOF. See http://tao.atmos.washington.edu/pdo/ for more information.
• Final Exam solutions/model answers