The UKESM1 earth system model has been used to run the climate experiments prescribed by the CMIP6 project, including a simulation of the historical period (1850-2014) and a range of projections (2015-2100) which explore ways in which the Earth’s climate could evolve in the future. The output from each simulation has been converted to data in the standard format prescribed by CMIP6 and uploaded to the Earth System Grid Federation (ESGF) for access by climate scientists worldwide.

Partly because of the broadened scope of CMIP6, our investment in the project is much greater than for previous rounds, and the experiments have consumed several person years’ effort and CPU core centuries. More specifically, we expect to upload around 5 PB of data to ESGF, which is more than three times the size of the entire CMIP5 data archive. The scale of this investment is one of the reasons we are keen to take more opportunities to exploit our model data by ensuring it is used not only in contributions to climate research and policy-making, but also in public outreach and dissemination efforts.

For example, results for near-surface air temperature – a variable of interest for climate change studies – from the historical and future projections are plotted in Figure 1. The data is plotted as an anomaly – that is, the difference from the global average mean near-surface temperature between 1850 and 1900 – thereby focusing attention on changes in temperature since that period, which is conventionally used as a pre-industrial reference.

Figure 1: Global average annual mean near surface temperature, as determined by UKESM1, for the CMIP6 historical experiment and four future projections.

Each of the four projections in Figure 1 corresponds to an assumed so-called shared socio-economic pathway (SSP), prescribing how – amongst other things – greenhouse gas emissions and land use could change in the future. They range from SSP126 – a future where emissions are constrained in order to try and limit temperature rise to around 2°C – to SSP585, which assumes a “business as usual” pathway in which the rate of increase in emissions stays constant for many decades, resulting in a very large rise in atmospheric greenhouse gas concentrations. UKESM1 simulates the response of the Earth’s climate to these different conditions, which includes increases in global average near-surface temperature in 2100 which range between circa 2.5°C (in the case of SSP126) to around 7°C (for SSP585).

The temperature data plotted in Figure 1 has been averaged over both time (as an annual mean) and space (as an area-weighted spatial average). Hence, although it provides a compelling illustration of some of the differences between the future projections, it does not contain any information about spatial distribution of temperature change. This can be displayed using a 2D contour plot, but, inspired by our experience at public outreach events where we displayed our contour plots on a 3D spherical projection system, we have opted instead to mimic the physical globe by wrapping 2D temperature contours around the surface of a sphere.

Figure 2: Annual mean near-surface temperature anomaly in the Arctic, as determined by UKESM1, at the end of the four CMIP6 future projections; land areas are represented by yellow coastlines.

Figure 2 shows solid contour plots of the annual mean near-surface temperature anomaly wrapped around a sphere for each of the four future projections in the year 2100 (i.e., at the end of the experiment). The differences between the temperature change for the projections which is a feature of Figure 1 can still be seen be in Figure 2, but this also displays the spatial variation of temperature change. For each future projection, the Arctic region warms most strongly, and this warming is greatest for SSP585 (corresponding to the largest rise in emission levels) – specifically, it shows an increase in temperature of around 25°C for the year 2100 – that is, around three times the global average displayed in Figure 1.

We note in passing that an in-depth investigation of a climate change signal would not be based solely on the annual mean results for one year from a single realization of a climate experiment, as depicted here. Instead, a rolling average of the results for several ensemble members would be used – see, for example, the article from Swaminathan et al. elsewhere in this edition of the Newsletter.

We have also produced animations of our CMIP6 data, reflecting the evolution of climate variables over the course of the experiment. For example, Figure 3 is a dynamic visualization of near-surface temperature, showing how this evolves over the surface of the globe during the time period covered by the future projection experiments (i.e. 2015-2100).

Figure 3. Dynamic visualization of near-surface temperature, as determined by UKESM1, for the four CMIP6 future projections; land areas are represented by yellow coastlines.

We are using images such as Figure 2 and 3 in our dissemination work, and associated efforts to engage with a non-specialist audience. The study of climate change is a scientific activity which – partly because of its connections to human activities and implications for society – excites a degree of interest from the general public which is unusual when compared to other fields of science. The scale of the problem, coupled with the degree of commitment required to mitigate its effects, can be daunting, necessitating a sustained level of engagement and understanding from the public. There is a concomitant requirement for specialists to explain and disseminate their work to a broad audience in an accessible and compelling fashion – such as, for example, Figure 2. Further work in this area will look at the creation of images using other variables of interest produced by the model, including precipitation and wind vectors in the atmosphere, carbon content in the ocean and ice extent on sea and land.

For further information, please contact Jeremy Walton (jeremy.walton@metoffice.gov.uk).