External resources

General links / resources

IPCC reports:

• Summary for Policymakers, IPCC AR WG2: Impacts, Adaptation and Vulnerability

• Full report, IPCC AR WG2: Impacts, Adaptation and Vulnerability

• Guidance note – The concept of risk in the IPCC Sixth Assessment Report: a summary of cross Working Group discussions — IPCC

• Guidance Note on Uncertainty for IPCC Authors

Climate policy:

• Climate Action Tracker

Books:

• Quantifying Climate Risk and Building Resilience in the UK (Open Access)

Learning python:

Here are my favorites resources for Python beginers in STEM:

• There is an excellent Python tutorial provided by the Software Carpentry. It’s based on a real data analysis and I strongly recommend it.

• Chapter 1 from the Scientific Python lectures is also excellent.

• Finally, my own classes provide some resources as well, but they are more adapted to a classroom than self-study: beginner, advanced.

Learning climate analysis with python:

The excellent resources by Climatematch inspired some of my notes:

• comptools.climatematch.io

Project Pythia contains fantastic resources:

• Foundations

• CookBooks

Interactive climate dashboards:

• PROVIDE Climate Risk Dashboard

• Met Office Climate Data Portal (see local authority risk assessment)

• IPCC Interactive Atlas

• Climate Impact Explorer

Further lecture notes by Fabien:

• 💻 Introduction to Python Programming (undergraduate level)

• 🧑‍💻 Scientific Programming in Python (postgraduate level)

• 🌍 Physics of the Climate System Practicals

Miscellanea

• The excellent episode of “Cautionary Tales” about how risk mitigation measures can go wrong: BBC iPlayer, youtube

• Art: Landscape Of Change by Jill Pelto

By Week

Lecture 1 (Introduction)

• Summary for Policymakers, IPCC AR WG2: Impacts, Adaptation and Vulnerability

• Guidance note – The concept of risk in the IPCC Sixth Assessment Report: a summary of cross Working Group discussions — IPCC

• Guidance Note on Uncertainty for IPCC Authors

Lecture 2 (Climate data)

• Videos

  • “Data Assimilation: The secret to better weather Forecasts”

  • “Reanalysis - from local measurements to global weather reconstructions”

  • “What is reanalysis? ECMWF”

• Web resource about climate datasets, their strengths and limitations: Cimate Data Guide, in particular:

  • Reanalysis data

  • Global temperature from stations datasets: CRU, BEST, GISTEMP

Lecture 3 (Statistical methods)

• Book: Statistical Methods for Climate Scientists, Cambridge University Press
  🔗 https://doi.org/10.1017/9781108659055
  Recommended for their broad coverage, the code examples (need to be translated to Python – easy enough with AI), and the excellent introductions before the heavy statistics. 📘 PDF available from Uni Bristol.

• Book: Statistical Methods in the Atmospheric Sciences, Daniel S. Wilks
  🔗 https://www.sciencedirect.com/book/9780128158234/statistical-methods-in-the-atmospheric-sciences
  Recommended as “the” reference textbook — more complete but also a bit more complex than the above. 📘 PDF available from Uni Bristol.

• Report: Bristol Local Flood Risk Management Strategy
  🔗 https://democracy.bristol.gov.uk/documents/s82208/Bristol%20Local%20Flood%20Risk%20Management%20Strategy%202023.pdf
  A real-world policy view on flood risk management.

(this list will be updated when the notes get written further)