While climate change is controversial in the media, the scientific basis is relatively simple (much simpler than many of the concepts we apply in our everyday lives) and has been long understood. The recent litigation in New York that attempted to hold big oil accountable for health care costs raises several important issues. We use the long-term Moana Loa CO2 data to examine the evidence, and we consider recent modeling studies on its impacts.
Timeline for vignette
day 1: Course overview, form working groups, install Rstudio, introduce R vignette
day 2: Discussion of science and media issues on greenhouse warming; Gain experience with R using Mauna Loa C02 data
Activities today
- Discussion of science and media issues on greenhouse warming
- Gain experience with R using Mauna Loa C02 data
Discussion
The meeting will begin with discussion within working groups, followed by group reports from the coordinator, and a discussion in plenary. Students posted their responses to Sakai/Resources/class files before class.
In your group, draft a consensus statement on each question and post it to Sakai/Resources/class files/myGroup/day2statement.pdf.
The coordinator will summarize the consensus answers for the class. Plenary discussion will follow.
Recall the discussion papers from last time:
In the media:
The world is missing its lofty climate targets. Time for some realism (The Economist). Argues that it’s too late for mitigation, decarbonization is the only choice.
New York’s Global Warming Suit Against Oil Companies Tossed (Bloomberg News). An argument similar to that made by tobacco companies does not work this time.
Why Big Data Could Be a Big Fail (Spectrum IEEE), Jordan on potential and limitations of Big Data (misleading title).
Science resources:
Exceeding 1.5°C global warming could trigger multiple climate tipping points. Armstrong-McKay et al. argue that we’ve already passed some important tipping points, and there are more to come.
Estimating economic damage from climate change in the United States (Science). Hsiang et al. estimate the potential economic damage from severe weather related to climate change. The Supplement to this article is included here
The questions for today were:
- Is Jordan an optimist or a pessimist on the advances and prospects for ‘big data’? Why?
- What sources of uncertainty are included in the projections from Hsiang et al?
- Locate a state of interest to you on Hsiang et al’s figure S2:
- Summarize two big changes that are projected and why.
- From Armstong-McKay et al., which tipping points are likely to affect this state first and most?
- Identify two similarities and two differences between the roles of big tobacco in cancer risk and big oil in climate change.
Help session on the R intro
For next class
Identify a coordinator for next time, who will post to Sakai a bullet list of questions encountered by group members during implementation of R code. Recall that the Mauna Loa data is at this link. These will be reviewed next class period.