(syllabus)=
# ATSC 301: syllabus


- Instructor:   Dr. Phil Austin
- Email:        paustin@eoas.ubc.ca
- Office:       EOS South 157
- Office hours: TBD
- TA: Luke Brown <lbrown@eoas.ubc.ca>
- Course website: [https://phaustin.github.io/a301_eoas](https://phaustin.github.io/a301_eoas)


## Course objectives

By the end of this course you should have a good understanding of

1. how radiation is emitted, absorbed, transmitted and reflected by
   surfaces, clouds, and the atmosphere  (the "forward problem")
2. how radiometers, radars and lidars are used to infer
   temperature and surface and cloud properties (the "inverse problem")
3. how orbiting radar and climate sensors (MODIS, Cloudsat, Calypso, GOES ABI) are combined with
   global forecast models to study the atmosphere, ocean and land surface
3. how to map spatial remote sensing data the earth's surface using Python's geographic information software  
4. how to write clear, documented and tested code that can ingest, manipulate and display
   data, and how to turn equations into computer algorithms in Python


## Evaluation

|           Assessment            | weight |
| ------------------------------- | ------ |
| Bi-Weekly Assignments/Quizzes   | 45%    |
| Mid-term                        | 15%    |
| Final (including takehome part) | 40%    |


- a reminder about the [UBC code of conduct](https://students.ubc.ca/campus-life/student-code-conduct/)

## Week by week topics (subject to change, see individual weekly topic pages on the course website)

| Week                                               | Topic                                                  |   |
|----------------------------------------------------|--------------------------------------------------------|---|
| **Week 1  1/6 - 1/10**                             | Introduction, course outline, Beer's law, flux         |   |
|                                                    |                                                        |   |
| **Week 2  1/13 - 1/17**                            | Jupyter introduction, satellite data                   |   |
| Assignment 1: Brightness temperatures              |                                                        |   |
| **Week 3  1/20 - 1/24**                            | Reading geotifs                                        |   |
| **Week 4  1/27 - 1/31**                            | Geographic coordinate systems, Schwartzchild equation  |   |
| Assignment 2: Stull Chapter 2 problems             |                                                        |   |
| **Week 5  2/3 - 2/7**                              | Schwartzchild eqn with absorption and emission         |   |
|                                                    | Cartopy mapping and image resampling             |   |
| Assignment 3: Flux from radiance                  |                                                        |   |
| **Week 6  2/10 - 2/14**                            | Pandas, Weighting functions for temperature retrieval  |   |
| Assignment: mid-term review
|                                                        |   |
| **Midterm: Monday Feb. 24**                            |   |   |
| 
|
| **Week 7  2/24 -  2/28**                            | xarray, geotiffs, Landsat and Sentinel data            |   |
|                                                        |   |
| **Week 8  3/3 - 3/7**                             | Reading cloud optimized geotiffs, Landsat channels     |   |
| Assignment 4: NDVI                                 |                                                        |   |
| **Week 9  3/10 - 3/14**                            | Analyzing Cloudsat radar data                          |   |
| **Week 10 3/17 - 3/21**                            | Comparing Cloudsat with the ECMWF model                |   |
| Assignment 5: Cloudsat and Landsat data            |                                                        |   |
| **Week 11 3/24 - 3/28**                            | Heating rates for climate modeling, false color images |   |
| Assignment 6: Radar equation, Hurricane case study |                                                        |   |
| **Week 12 3/31 - 4/4**                              | GIS processing review, final exam guide                |   |
| Assignment 7: Raster/vector overlays and true color              |                                                        |   |
| **Week 13 4/7**                            | Catch-up, review                                       |   |