Archive of announcements (most recent at top)

• Assignment 4 (15%, due 28 March). Review of a classic paper.

• Feedback on Assignment 3.

• Prairie and Arctic Storm Prediction Centre of Environment Canada... interested in hiring up to 4 summer students (2 in Edmonton, 2 in Winnipeg) as severe weather assistants for the period from April 29th to August 30th. These students will be working in Edmonton or Winnipeg and assisting us in the forecast operations area and in other areas of statistics, data mining, air quality, and/ or other programs that we are involved in. Their primary job will be helping us to track and warn for severe thunderstorms... (18 March 2013)

• Assignment 3 (12.5%, due 19 March). A typo has been corrected: the symbol n_n should have been n_j , i.e. F_j=n_j / N. Here is a table giving area under the "normal curve" (second column). Here the random variable is standardized, i.e. it has zero mean and unit variance; the interval -0.43 ≤ (x-μ)/σ ≤ 0.43 has area 0.3328, close enough to 1/3, so the 33rd and 66th percentiles for (x-μ)/σ (or for any standardized Gaussian variable) are -0.43 and 0.43. To get the values for your (non-standardized) distributions, multiply by your std. deviation and add your mean.

  Data as tab-separated text files: Vancouver.csv, Whitehorse.csv, Yellowknife.csv, Calgary.csv, Edmonton.csv, Regina.csv, Winipeg.csv, Toronto.csv, Montreal.csv, Halifax.csv

  Data as Excel (.xls) files: Vancouver.xls, Whitehorse.xls, Yellowknife.xls, Calgary.xls, Edmonton.xls, Regina.xls, Winipeg.xls, Toronto.xls, Montreal.xls, Halifax.xls

• Collective feedback on Assignment 1. Students did demonstrate that their data reveal the expected correlation between "q" and "⟨T⟩". It would have been appropriate to use exactly the same axis to plot q (in dam) and ⟨T⟩, because the hypsometric equation tells us a unit change in the one must go along with a unit change in the other. Most students, however, used different and arbitrary scales for q and ⟨T⟩. The correlation remained apparent. The meteorological side of the task was adequately done at the level of calculation, though not all gave evidence they saw the significance of what had been done: there is a big difference between knowing something, and demonstrating that you know. Being able to calculate is only the beginning, and anyway, that's a given: if you're a student of meteorology, you can calculate, or so we assume. In most cases, writing precision and effectiveness would be the key area for improvement. Guidance had been given (see the file below), but perhaps it was not read?

• It might be useful for students to skim one or two scientific papers to get a sense of the style, structure and organization of modern technical writing. I've chosen Charney (1947) and Rossby et al. (1939), because these individuals are gods in the field of meteorology and so the content may also be of some passing interest (Rossby et al. number their equations on the left, a pattern that is nowadays quite rare, at least in meteorology). These references are not provided because I wish you to study them. Please do, however, note the use of headings; of captions; the layout of equations, and their systematic numbering.

• Final exam 09:00-11:00 Thurs 11 April.

• Setting a date & time for the final exam: by default, according to the UA calendar the exam would be 9:00 am Monday 22 April (whereas our final class period is Thurs 11 April). JDW would like to hold the exam closer to 11 April, perhaps 09:00-11:00 or 09:30-11:30 that day. We'll discuss this and find a date & time that suits all students

• Assignment 2 is an assessment of the skill of public weather forecasts. Please begin collecting your data on 27 Jan. Station assignments: Chris = Vancouver, Tara = Whitehorse, Ambrose = Yellowknife, Jean-Michel = Calgary, Toby = Edmonton, Darren = Regina, Danielle = Winnipeg, Jennifer = Toronto, Allen = Montreal, Brett = Halifax. You may swap stations (by mutual agreement) with another student if you wish.

• As it appears we are going to have a big variation in temperature over the next week or so, it will be interesting to get going with Assignment 1 right away.

• Course Organization. To sustained our focus on practicalities of weather analysis and forecasting, most classes will involve exercises relating to weather of the moment, the immediate past, and the (skillfully) predictable future (i.e. out to a maximum of a couple of weeks; more often the following few days).

  Assigned background readings are intended to ensure you are familiar (or become familiar) with the primary concepts, vocabulary, symbols and equations standing behind informed weather discussion. No deadline for this will be imposed, and no marks are assigned specifically to these readings; however questions on the final exam may explore your mastery of the assigned material.

  Sometimes you will be asked to submit an item of work or the outcome of a calculation or computation for the instructor's perusal, so that he can provide suggestions and monitor progress (this is in addition to the formal assignments). Except in the case that this item is a weather forecast, no deadline will apply (i.e. you may finish the task after class if needbe). Such work will not be graded, but its completion is mandatory: a total of (no more than) five marks from the "assignments" category (i.e. 5 of 50) could potentially be withheld for failure to complete such tasks.

  You may use whichever software you prefer for computations (e.g. to complete assignments). MATLAB and R are available in our classroom (ESB 1-39).

  It is assumed that you will be constantly monitoring weather evolution this term, i.e. visiting the web to peruse analyses, forecasts, satellite images etc. on a daily basis. Your familiarity with the primary sources of information will be tested by a "live web weather data" component on the final exam. (8 Jan. 2013)

Link to Earth & Atmospheric Sciences home page.

Last Modified: 2 Apr., 2013