Without traditional knowledge, there is no climate change solution

Traditional indigenous knowledge is the key to solving climate change.

You can’t reach net zero without resource efficiency

Earlier this week, the climate minister, Claire Perry, asked the Committee on Climate Change (CCC) to investigate a pathway for the UK to become a net zero emissions economy. This followed the publication of a major International Panel on Climate Change (IPCC) report warning that the world must make deep cuts in carbon emissions. These, the scientists say, are necessary

Model Independence Day

We hold these truths to be self-evident, that all models are created equal, that they are endowed by their Creators with certain unalienable Rights, that among these are a DOI, Runability and Inclusion in the CMIP ensemble mean. Well, not quite. But it is Independence Day in the US, and coincidentally there is a new discussion paper (Abramowitz et al) (direct link) posted on model independence just posted at Earth System Dynamics

The Alsup Aftermath

The presentations from the Climate Science tutorial last month have all been posted (links below), and Myles Allen (the first presenter for the plaintiffs) gives his impression of the events. Guest Commentary by Myles Allen A few weeks ago, I had an unusual — and challenging — assignment: providing a one-hour “tutorial” on the basic science of human-induced climate change to a Federal District Court in San

1.5ºC: Geophysically impossible or not?

Guest commentary by Ben Sanderson Millar et al’s recent paper in Nature Geoscience has provoked a lot of lively discussion, with the authors of the original paper releasing a statement to clarify that there paper did not suggest that “action to reduce greenhouse gas emissions is no longer urgent“, rather that 1.5ºC (above the pre-industrial) is not “geophysically impossible”. The range of post-2014 allowable emissions for a 66% chance of not passing 1.5ºC in Millar et al of 200-240GtC implies that the planet would exceed the threshold

Comparing models to the satellite datasets

How should one make graphics that appropriately compare models and observations? There are basically two key points (explored in more depth here) – comparisons should be ‘like with like’, and different sources of uncertainty should be clear, whether uncertainties are related to ‘weather’ and/or structural uncertainty in either the observations or the models. There are unfortunately many graphics going around that fail to do this properly, and some prominent ones are

Marvel et al (2015) Part 1: Reconciling estimates of climate sensitivity

This post is related to the substantive results of the new Marvel et al (2015) study. There is a separate post on the media/blog response. The recent paper by Kate Marvel and others (including me) in Nature Climate Change looks at the different forcings and their climate responses over the historical period in more detail than any previous modeling study. The point of the paper was to apply those results to improve calculations of climate sensitivity from the historical record and see if they can be reconciled with other estimates. But there are some broader issues as well – how scientific anomalies are dealt with and how simulation can be used to improve

And the winner is…

Remember the forecast of a temporary global cooling which made headlines around the world in 2008? We didn’t think it was reliable and offered a bet. The forecast period is now over: we were right, the forecast was not skillful. Back around 2007/8, two high-profile papers claimed to produce, for the first time, skilful predictions of decadal climate change, based on new techniques of ocean state initialization in climate models. Both papers made forecasts of the future evolution of global mean and regional temperatures. The first paper, Smith et al. (2007), predicted “that internal variability will

Global warming and unforced variability: Clarifications on recent Duke study

Guest Commentary from Patrick Brown and Wenhong Li, Duke University We recently published a study in Scientific Reports titled Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise. Our study seemed to generated a lot of interest and we have received many inquires regarding its findings. We were pleased with some of coverage of our study (e.g., here) but we were disappointed that some outlets published particularly misleading articles (e.g, here, here, and here). Since

Debate in the noise

Last week there was an international media debate on climate data which appeared to be rather surreal to me. It was claimed that the global temperature data had so far shown a “hiatus” of global warming from 1998-2012, which was now suddenly gone after a data correction. So what happened? One of the data centers that compile the data on global surface temperatures – NOAA – reported in the journal Science on an update of their data. Some artifacts due to changed measurement methods (especially for sea surface temperatures) were corrected and additional data of previously not included weather stations were

Reflections on Ringberg

As previewed last weekend, I spent most of last week at a workshop on Climate Sensitivity hosted by the Max Planck Institute at Schloss Ringberg. It was undoubtedly one of the better workshops I’ve attended – it was focussed, deep and with much new information to digest (some feel for the discussion can be seen from the #ringberg15 tweets). I’ll give a brief overview of my impressions below. As we’ve discussed previously, there are multiple classes of observational data that could provide