weather@home—development and validation of a very large ensemble modelling system for probabilistic event attribution

Abstract

Demonstrating the effect that climate change is having on regional weather is a subject which occupies climate scientists, government policy makers and the media. After an extreme weather event occurs, the question is often posed, 'Was the event caused by anthropogenic climate change?' Recently, a new branch of climate science (known as attribution) has sought to quantify how much the risk of extreme events occurring has increased or decreased due to climate change. One method of attribution uses very large ensembles of climate models computed via volunteer distributed computing. A recent advancement is the ability to run both a global climate model and a higher resolution regional climate model on a volunteer's home computer. Such a set-up allows the simulation of weather on a scale that is of most use to studies of the attribution of extreme events. This article introduces a global climate model that has been developed to simulate the climatology of all major land regions with reasonable accuracy. This then provides the boundary conditions to a regional climate model (which uses the same formulation but at higher resolution) to ensure that it can produce realistic climate and weather over any region of choice. The development process is documented and a comparison to previous coupled climate models and atmosphere-only climate models is made. The system (known as weather@home) by which the global model is coupled to a regional climate model and run on volunteers' home computers is then detailed. Finally, a validation of the whole system is performed, with a particular emphasis on how accurately the distributions of daily mean temperature and daily mean precipitation are modelled in a particular application over Europe. This builds confidence in the applicability of the weather@home system for event attribution studies.

Explaining Extreme Events of 2014 from a Climate Perspective

“…8.1d, lower panel). The 2014/15 SEB deficit is similar to previous events, with dry episodes around 1963, 1970, and 1954 (ii) We use the distributed computing frameworkweather@home-to run the Met Office Hadley Centre atmosphere-only general circulation model HAD-AM3P (Massey et al 2015) to simulate precipitation and P − E in two different model ensembles representing: 1) observed climate conditions of 2014/15, and 2) counterfactual conditions under pre-industrial greenhouse gas forcings and 11 different estimates of SSTs without human influence . The empirical SEB total precipitation return periods (Fig.…”

A large set of potential past, present and future hydro-meteorological time series for the UK

“…Weather@home (Massey et al, 2015) consists of an atmospheric global climate model, HadAM3P, and its regional counterpart, the regional climate model HadRM3P, which dynamically downscales the GCM to a higher resolution over a limited domain. As part of the climateprediction.net project (Allen, 1999), weather@home takes advantage of computing time donated by volunteers around the world to run very large numbers of climate model simulations, of the order of tens of thousands.…”

Regional climate engineering by radiation management: Prerequisites and prospects

“…This can be based on a large model ensemble [Massey et al, 2015]. In attributing a climate event to anthropogenic activity, it is important to assess both the likelihood and the magnitude [Otto et al, 2012].…”