The FaIR DECK

A figure showing the idealised CMIP6 DECK reference experiments carried out using the constrained FaIR probabilistic ensemble.

Historical contributions to warming: what, who, where?

Reasonably recently, I noticed a tweet (it’s always twitter…) asking for an estimate of the contribution of agriculture to global warming. There were a few responses, but they had quite a wide spread and in general seemed inconclusive. I decided, quite some time after seeing the tweet, to see if I could give my own estimate of this using the probabilistic simple climate model ensemble I used in my previous post. As is the way with these “straightforward” projects, it naturally turned into something a bit more comprehensive than intended. This post is the result - my attempt to estimate what (specific forcing drivers), who (sectors) and where (countries) is causing anthropogenic global warming.

Climate modelling in Excel...

You can download the implementation of the FaIRv2.0 model in Excel described in this post here.

This is a brief post that introduces an Excel version of the FaIRv2.0 model¹ that I’ve created. I go through some of the key features, suggest some experiments that you can do, and provide recipes for how to carry out a few different types of analyses with the model.

How long left?

A recent CarbonBrief analysis estimated when two key global temperature targets (1.5 and 2.0 °C) would be exceeded using an ensemble of climate models from CMIP6. Inspired by this, I thought I’d try and carry out something similar, but using a large probabilistic simple climate model ensemble rather than the complex CMIP6 model ensemble in the original article.