About

Background

David is a physicist by training and has many years’ experience of climate modelling.

While a researcher at Oxford University, he co-founded and was chief scientist of the climateprediction.net project, the world’s largest climate modelling experiment.

David has been both a NERC Research Fellow and a Tyndall Research Fellow at Oxford University.

Research interests

  • How we can extract robust and useful information about future climate, and climate related phenomena, from modelling experiments;
  • Issues of how to design climate modelling experiments and how to link climate science to real-world decision making in such a way as to be of value to industry, policymakers and wider society.

Research

Research - 2023

Research - 2022

The authors of this paper define a model selection parameter, which switches on one of a suite of proposed climate nonlinearities and multidecadal climate feedbacks. find that a model with a temperature-dependent climate feedback is most consistent with global mean surface temperature observations, but that the sign of the temperature-dependence is opposite of what Earth system models suggest. Read more

Copyright University Corporation for Atmospheric Research licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License

Research - 2021

Our complementary approach exploits the correspondence between Hasselmann’s EBM and the original mean-reverting stochastic model in physics, Langevin’s equation of 1908. We propose mapping a model well known in statistical mechanics, the Mori-Kubo Generalised Langevin Equation (GLE) to generalise the Hasselmann EBM. Read more

Research - 2020

Research - 2019

Research - 2018

Research - 2016

Research - 2015

Research - 2014

We expose the benefits and limitations of the Bayesian Network approach, weather index insurance as an adaptation measure and climate simulations as a source of quantitative predictive information. Current climate model output is shown to be of limited value and difficult to use by index insurance practitioners. The method presented, however, is shown to be an effective tool for testing pricing assumptions and could feasibly be employed in the future to incorporate multiple sources of climate data. Read more

Research - 2013

Research - 2010

Policy

Policy - 2019

Economic assessments of the potential future risks of climate change have been omitting or grossly underestimating many of the most serious consequences for lives and livelihoods because these risks are difficult to quantify precisely and lie outside of human experience. This policy insight identifies and draws attention to these 'missing risks' and discusses how populations might fare in light of their potential to adapt in the face of these risks. Read more

Books

Books - 2023

Books - 2021

Our complementary approach exploits the correspondence between Hasselmann’s EBM and the original mean-reverting stochastic model in physics, Langevin’s equation of 1908. We propose mapping a model well known in statistical mechanics, the Mori-Kubo Generalised Langevin Equation (GLE) to generalise the Hasselmann EBM. Read more

Events

Events - 2024

Events - 2022

Events - 2020

Events - 2016

Events - 2015

Events - 2014

News

News - 2023

News - 2021

News - 2013

News - 2011

This exhibit, from 5-10 July, aims to explore how predictions are made and communicated, how and when probabilities can be deduced, and the role of computer models in these processes. It will involve interactive computer-based probability games and hands-on physical games to do so. Dr David Stainforth is leading its preparation. Read more

News - 2010

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