Seasonal attribution experiment

The climateprediction.net Seasonal Attribution Project used computing time donated by the general public to run state-of-the-art high-resolution model simulations of the world’s climate. These simulations are used to determine the extent to which the risk of occurrence of extreme weather events is attributable to human-induced climate change.

The focus was on extreme weather events that occur on a seasonal timescale, and specifically on the United Kingdom floods of Autumn 2000 which occurred during the wettest autumn ever recorded, causing widespread damage and an estimated insured loss of £1.3 billion.

  • Half of the climate model simulations that were run for this project were for the Autumn 2000 period, specifically including the effects of human-induced climate change caused by the emission of greenhouse gases. These are termed the “Industrial Autumn 2000″ simulations.
  • The other half simulated a representation of the the Autumn 2000 climate had there not been any human-induced emissions of greenhouse gases over the last century. These are termed “Non-Industrial Autumn 2000″ simulations.
  • By then comparing the results of these Industrial and Non-industrial simulated climates, and recording the occurrence of floods like that of Autumn 2000 in each of them, the change in the frequency of occurrence (or ‘risk’) of such a flood was determined, and therefore how much risk is attributable to human-induced emissions of greenhouse gases over the last century.

We are also collaborating with other research groups who are interested in using our simulations to perform similar attribution studies, for snowmelt in western North America, and heatwaves in South Africa and India.

Recent extreme weather events having large societal and economic impacts have prompted the debate about effects of human activity on the world’s climate. One way to answer this question is to compare the world’s current climate with what it would look like had it not been for human activity – similar to the way an epidemiologist might compare samples of smokers and non-smokers to attribute the effects of smoking to lung cancer. The problem is that we cannot observe what a climate without the presence of human activity looks like, since we can only observe the current state of the climate. Hence we have to resort to simulations of such a climate using state-of-the-art climate models.Furthermore, small differences in how we initialize these simulations can have a significant impact on the end results – reflecting the fact that we do not have completely perfect models and that in the real world small differences in what is going on now can have significant effects on what happens in the future (to quote a famous statement, ‘The flap of a butterfly’s wings in Brazil can set off a tornado in Texas’), the so called ’butterfly effect’.

To account for this uncertainty a large number of simulations of each climate were run, similar to how an epidimiologist might study a large number of patients to have confidence in his results. Also, because the Autumn 2000 flood event was in itself extreme this further necessitates running a large number of simulations before we might expect to reproduce an event of that magnitude. A larger number of simulations for each of the Industrial and Non-Industrial Autumn 2000 climates were completed.The focus was particularly on the United Kingdom Autumn 2000 floods because, aside from causing widespread damage, they occurred during the wettest autumn since records began in 1766. Thus we might have expected any signal of such an event in the simulations to be more prominent and easier to detect than if we had investigated less severe and/or shorter lived weather phenomena. Also, it is only relatively recently that models have been developed with the required resolution to sufficiently capture the storms and weather patterns associated with the Autumn 2000 floods.Attributing the risk of extreme weather events to climate change in this way also has very interesting implications for liability for such events. For our simulations we used the state-of-the-art HadAM3-N144 climate model, which was developed at the Hadley Centre for Climate Prediction and Research. It is a high spatial resolution version of the standard Unified Model used by the UK Met Office.

At the earth’s surface it has a horizontal resolution of approximately 100km2 at mid-latitudes enabling it to reasonably capture the storms and weather patterns associated with the Autumn 2000 floods flooding. Specifically, in the simulations we record daily surface temperature, precipitation, 500hPa geopotential height and surface winds over the Atlantic-European region. Monthly temperature, precipitation, 500hPa geopotential height, mean sea-level pressure and soil moisture over the entire globe are also output to assess larger scale weather systems. Furthermore, daily temperatures and precipitation over the Northwest US, India and South Africa are recorded for related attribution projects investigating snowmelt and heatwaves.

Funding

World Wildlife Fund for Nature (WWF) International
Natural Environment Research Council

Lead scientists

Pardeep Pall, Myles Allen and Dáithí Stone

Published papers

Pall, P., Aina, T., Stone, D.A., Stott, P.A., Nozawa, T., Hilberts, A.G.J., Lohmann, D., and Allen, M.R., (2011) Anthropogenic greenhouse gas contribution to flood risk in England and Wales in Autumn 2000, Nature, 470, 382-385.

Kay, A. L., S. M. Crooks, P. Pall, and Stone, D. A. (2011) Attribution of Autumn/Winter 2000 flood risk in England to anthropogenic climate change: a catchment-based study, Journal of Hydrology, 406, 97-112.

  • Lead scientists: Pardeep Pall, Myles Allen & Dáithí Stone
  • Finish: Led to weather@home project