1. Getting Started

Climate Bars from ShowYourStripes and developed by Ed Hawkins

Introductions

Activity Introductions:

Introduce yourself with

  • preferred name & pronouns
  • major
  • do you prefer cats or dogs (must make a choice). Why?
  • one environmental issue you care most about/ are most curious about

Course Objectives

Let’s have a look at the provisional course objectives from the syllabus:

By the end of this course, our goal will be for you to:

  • Apply principles of open and responsible science to acquire, process, and visualize environmental data
  • Understand different types of models and environmental data and how they can be used to characterize environmental issues
  • Interpret environmental data to characterize causes and effects of environmental problems
  • Evaluate complex environmental systems using computational tools to
    • Understand causes and effects of environmental problems
    • Realize limitations of data and models
    • Effectively communicate scientific and technological information
  • Analyze, present, and defend the results and conclusions from projects that involve environmental data from observations and models

What is this course about?

  • We have a lot of environmental issues that we need to understand and solve

  • There are also a lot of environmental data available to us (and steadily increasing)

    The red area starting to the right of the Fiscal Year 2024 (FY24) dot indicates the enormous volume of data expected from upcoming high-data-volume missions that are projected to grow NASA's Earth science data collection to almost 600 petabytes (PB) by 2030, based on current launch schedules.

    Volume of data archived by NASA; Credit: NASA EMS

Making this data useful to solve problems

  • Challenges

    • Storing and processing this data
    • Finding and accessing the right data to solve problems
    • Understanding the story that the data tells us

  • This requires processes and workflows

    Basic NASA data processing flow. After raw satellite data are downloaded (left box), MDPS elements (center box) facilitate the transformation and processing of instrument data into science data products (right box).

    Basic NASA data processing flow - raw data is transformed into products; Credit: NASA EMS

We will try to model this in class

  • Develop workflows
  • Learn tools that help us do this
  • Explore environmental datasets
  • Explore environmental questions

How do we relate data, models, and questions that we can ask

There is a sequence from raw data to analyzed data and models. Each serves to ask different questions. Models allow for higher complexity questions and are more complex. At the same time there is much more raw data.

The relationship between data and models

Class expectations

Activity: Class Expectations

We will use a board to collect class expectations. Write down on a sticky note (1 idea per note) and place the notes on the board:

  1. What do you hope we learn in this class?
  2. How do we want to work together in this class?

We will review and discuss these at your table and within the group.

Syllabus & Schedule

We will now review the Syllabus and the Schedule.

Class expectations (Follow Up)

Activity: Working together

Discuss on your table: What specific steps can we take to:

  1. best work together in a team?
  2. have good class discussions?

How we work together

  • Collaborative environment
  • No quizzes/ exams
  • Mixture of mini-lectures, code demonstrations, activities, guided coding
  • Team coding:
    • Work in pairs and discuss what you are doing
    • Have at least one laptop as a pair
    • The focus is on learning the process and not the results
    • Ask me questions when you don’t know the Why or What

A note on AI (as team mate)

  • The focus of this class is on learning the process and to understand what you do and why

  • GenAI has become quite good at the basics (i.e. vibe coding)

  • Here is how I see AI

    Good uses of genAI

    • Automate the boring stuff
    • Do things that you know how to do
    • Revise and clarify

    This is the danger zone

    • use AI to learn new things
      • AI can be used as a tutor, but you need to stay in charge
      • cross-check output with reliable sources
      • also do it on your own to make sure you can do it/ you understand
      • make sure things are aligned with the course and the level of learning

    Bad uses of genAI

    • use to deceive (e.g. pass of AI output as your own)
    • use AI to outsource thinking
      • bypasses learning
      • true learning needs friction and moments when you are not sure
      • gives AI power to shape your thinking and personality
      • what are your skills if AI can do it?
    • use AI to shape human interactions
      • …

Evaluation

Learning Journal/ Notes

Let’s review the syllabus portion on evaluation and the guide on crafting learning notes.

Note

What are your questions?

Outlook: Environmental Issues & Data

Review the 3 articles I shared.

Activity: Communicating Environmental Issues

  1. Briefly review the three articles I shared. There is no need to read them in detail.
  2. On your table and discuss (keep a record):
    1. Select a chart/ figure from the article that catches your eye.
    2. What is the environmental issue that the chart is about?
    3. What are the main points being communicated?
    4. What data is likely used to make this chart? Be specific …
    5. Is the chart effective? Why?
  3. We will discuss your charts in the class.

Outlook

Important

I am at a conference this week. We will not be meeting this week, but there will be asynchronous assignments. We will discuss these when I am back in Week 3.

In the next week, you will be working on some foundations including:

  • What is open science and what are the benefits?
  • Get ready to work with the tools of open science/ research
  • Explore an environmental issue you care about (Prep for semester project)

Let’s have a look at the goals for next week: Week 2: Lesson Plan