Meteo 810 Syllabus - Spring 2023

Introduction to Weather and Climate Datasets

Please note that I divided the syllabus into several sections. You can read it sequentially by scrolling down the length of this page. Without reservation, it is crucial that you read the entire page (and the material covered on the other pages of the course orientation). Together, they constitute an informal course "contract" between you and me.

---

Instructor

Ben Reppert
Department of Meteorology and Atmospheric Science
John A. Dutton e-Education Institute
The Pennsylvania State University
428 Earth and Engineering Sciences Building
University Park, PA 16802

---

Technical Assistance

If you're studying the course content in Meteo 810 and encounter a lesson page with a typo or broken link, or you have trouble viewing one of the animations or images, feel free to post a question in one of the course discussion forums found in each lesson module. I'll do my best to determine the cause of the problem and get it fixed.

However, if you're having trouble with Canvas (posting to a discussion forum, sending an email, taking a quiz, etc.), please use the Help button located in the left banner of the Canvas environment. You will notice that there are several options. First, I would try the Canvas Guides... they are an excellent resource. However, if you still are stuck, use the "Report a Problem for World Campus Courses" option to contact the Outreach Helpdesk. When describing your issue, try to be as specific as you possibly can. Include information such as:

• the specific part of Canvas you're having trouble with, what you attempted to do when that failed, and the exact language of any error message displayed on your screen,
• the date and time when your problem occurred,
• the type of browser and OS that you are using, and
• any other pertinent information (does the problem happen consistently and always in the same way, etc.).

Alternatively, you can contact the Helpdesk directly in a variety of ways.

The Outreach Helpdesk
wdtechsupport@outreach.psu.edu
http://student.worldcampus.psu.edu/technical-support
(800) 252-3592, option #4
(814) 865-0047

Hours of Operation:

• 08:00 A.M. till 12:00 Midnight ET, Monday through Friday
• 10:00 A.M. till 7:00 P.M. ET, Saturday and Sunday

---

General Course Structure

METEO 810: Weather and Climate Datasets. (3 credits). Fundamental principles of retrieving, parsing, collating, and displaying large environmental data sets. Prerequisites: None

METEO 810 is the first course in a series of online offerings in the Weather and Climate Analytics. Other courses include how to analyze large environment datasets using various methods such as bulk descriptions, descriptive models, time series analytics, and predictive modeling.

Course materials in METEO 810 consist of 7 online lessons for which I've allotted approximately two weeks apiece. Within each lesson, students will complete the assigned reading as well as an extensive data-retrieval and display activity. These activities are meant to improve your skills in data retrieval, analysis, and communication (while developing your proficiency in the use of the R statistical-coding language).

Course Objectives

When you successfully complete this course, you will be prepared to:

• research any given data type so that you understand what exactly that data set is measuring, the technical aspects of its measurement, any assumptions involved in the observation or instrumentation, the site placement of the station or observing platform, and any quality-control issues associated with the data set that might affect your analysis.
• ask the right questions when selecting a data set. These questions might deal with location and times but may also involve issues of resolution versus reliability, or appropriateness of certain data for solving the problem at hand.
• retrieve large data sets from a wide variety of governmental and private sources using a variety of methods. 
• create and display cogent summaries or depictions of large data sets in a manner which addresses a specific problem or need.
• use the R programing language as an analysis and graphical presentation toolset.

What I expect of you

As with most graduate courses, there is a considerably higher onus on you to take responsibility for your own learning. While lessons present guidance on what you need to learn, much of your actual learning will take place as you engage in directed research and experiment with various examples presented in the text. Following through on these examples and exploring various ways to accomplish prescribed, data-procurement tasks are an absolute necessity, not only to be successful on the lesson's assessment activity but to meet your own learning goals as well.

---

Required Course Materials

I emphasize here that all the material contained in the lessons, taken as a whole, will serve as the primary textbook for this course. If you desire a supplement to the online text, I might suggest a manual on the R programming language. There are many different books to choose from, and I would choose one that fits your learning style and background. However, know that most answers to R programming problems can be found in online programming forums. I would give that a try first.

It goes without saying that you'll need an active Penn State Access Account user ID and password to access all the online course resources maintained in Canvas. If you have any questions about obtaining or activating your Penn State Access Account, please contact the Help Desk at your home campus.

---

Assignments and Grading

Two components of assessment will comprise your final grade in METEO 810:

• Weekly Activities     ... 70%
• Culminating Project ... 30%

Detailed information about these assessments is covered in Course Assignments section of the Course Orientation material.

The grading scale will differ from the traditional "points-based" scales that you are familiar with. First, I assume that you are taking this course because you want to learn the material, and thus you will give your maximum effort in doing so. This course, not unlike the real world, has very few "right" answers. Instead, what counts is a good deal of research, thought, and effort behind any project that you take on. I will expect no different in this course. Below is my rubric criteria for letter grades as applied to any assessment (or section thereof) or as an overall grade.

• Grade of A: This grade represents exemplary work, in both thought and effort. As an overall grade, an "A" represents a consistent pattern of diligence, correct analysis, and attention to detail.
• Grade of B: Earning a B means that you completed the assessment as stated, but perhaps displayed some flawed analysis or lackluster presentation. By all means, a "B" is nothing to be ashamed of. On the contrary, this grade represents work that is still quite good, both in effort and execution. However, there are likely areas that the student can improve upon. A final grade of "B" could represent a track record of consistently "good" work or some inconsistency of work, some being excellent while others leaning more to the "poor" end of the spectrum.
• Grade of C: Unlike at the undergraduate level, a "C" grade represents "poor" performance, in either thought or execution of assignments. Typically a "C" grade in graduate work is considered a failing grade (one that requires a repeat of the course). 
• Grade of F: This grade is reserved for students who did not complete a significant portion the work assigned. It represents a failure to complete the course on any level.

---

Course Schedule

See all assignment deadlines on the "Syllabus" page in Canvas or on your Canvas Calendar.
 

---

Course Policies