You’ve heard of climate change, but what does that actually mean for the weather in the region where you live? Could it be that you are going to see an increase in the number of damaging weather events? Or could the weather actually be getting nicer? The weather@home experiment hopes to answer these questions, with your help.
For experiments which look at climate globally, Global Climate Models (GCMs) are used, as they have a coarse resolution and thus give an overall picture of climate. In this case, however, a Regional Climate Model (RCM) needs to be used so as to provide specific information about certain regions. RCMs increase the resolution of areas of interest, allowing scientists to make predictions regarding the local impact of climate change. Such models are also supplied with climate information such as temperature, winds and humidity, around the edges, so that the influence of the weather in other parts of the world is still taken under consideration. Essentially, this is achieved through the embedding of the regional model within a ‘driving’ global model.
Initially, three target regions are now available for download: the Western US, Southern Africa and Europe. These were chosen because the majority of climateprediction.net participants (to date) live in Europe and the US, and because Southern Africa is a region thought to be particularly vulnerable to climate change.
The overall experiment design is in five parts:
First, a large number of different versions of the global and regional models will be used to simulate the period from 1960 to 2010 using observed changes in sea surface temperatures, sea ice, atmospheric greenhouse gases and aerosols. The simulated climates and patterns of change in weather events from the models will then be compared with observations over the same period to select a range of realistic model versions and document their behaviour. If, for example, we find that a particular version of the model tends to over-do the number of storms, we can take account of this when using this model to forecast future changes in storminess.
The second experiment is to produce a forecast of changes in weather events by the 2020s and 2030s. Using output from many different models with evolving oceans to provide the forecast sea surface temperatures up to this time, the regional model will tell us about the potential changes to patterns of weather events through the next three decades in unprecedented detail. Features such as changes in the likelihood of drought, flood and extreme heat or cold are likely to be of particular interest.
The third experiment returns to changes seen over the last 50 years, and attempts to quantify to what degree these changes can be attributed to the effects of human interference in the climate system. The driving conditions fed into the models are modified to reflect what they would have been like if we had not produced the greenhouse gas and aerosol emissions that we have over the past century. The difference between these simulations and the initial `baseline’ runs will provide the basis for assessing the human contribution to recent weather trends.
The fourth experiment returns to forecast mode but runs beyond the timeline of the second experiment, providing detailed information about changes in weather features in a world 2, 3 and 4 degrees warmer than global temperatures today, representing a range of climates that might be encountered towards the end of this century or beyond. This experiment will provide some of the most detailed information to date on regional weather in such possible future worlds, which is essential to assess the range of potential impacts of climate change.
Finally, the fifth experiment looks back into the past – looking at snapshots of the weather at intervals over the past 10,000 years, a period of Earth’s history called the ‘Holocene.’ This is the first time large numbers of regional models have been applied to such ‘paleoclimate’ (past climates) simulation: an unprecedented opportunity to explore the evolution of the weather over recent Earth history.
Please note: The project team aims to run as many of these experiments as possible, but not all experiments will necessarily be performed for all regions.
Myles Allen, Neil Massey, Andy Bowery, Jonathan Miller, Hiro Yamazaki, Cameron Rye, Friederike Otto, Juan Añel, Jara Imbers, Niel Bowerman, Suzanne Rosier (Oxford University), Richard Jones, Simon Wilson (Met. Office), Daithi Stone, Bruce Hewitson (University of Cape Town), Philip Mote (Oregon State University).