Climate science primer: Physics, reanalysis, CMIP, emulators & risk assessments
SPARKLE Session 1 on climate data in infectious disease modelling
Presenter: Dr Vassili Kitsios
Session 1 is delivered remotely as a slide-based presentation. This page exists to give participants a landing point: the slides, a short orientation to what the session covers, and a couple of prompts to carry into Session 2. There is no code in this session.
Overview
This session is an introduction to the climate science that underpins the rest of the course. It sets up the concepts and data products that Session 2 then uses hands-on. It covers, at a high level:
- the physics of the climate system, and how the climate is observed and modelled;
- reanalysis: how past weather is reconstructed into gridded, physically consistent datasets (e.g. ERA5), which we use to learn climate relationships;
- CMIP projections: how multi-model ensembles project future climate under different emissions scenarios, which we use to apply those relationships;
- emulators: fast approximations of expensive climate models; and
- how these feed into risk assessments for climate-sensitive outcomes such as malaria.
Survey
Before we get started with the materials, please fill out the pre-survey available at this link: https://redcap.unimelb.edu.au/surveys/?s=YCTD38YC4NPDX3DP
Slides
The presentation slides are provided as a PDF:
📄 Climate science primer: slides (PDF)
If the embedded viewer above does not display (some browsers block embedded PDFs), use the download link.
Reflection questions
1.1 In your own words, what is the difference between reanalysis and a climate projection, and why does the malaria workflow use one to learn a relationship and the other to look forward?
1.2 What does an emissions scenario (e.g. SSP1-2.6 vs SSP5-8.5) represent, and why do we look at more than one?
Contributors
- Dr Vassili Kitsios