The government has been using so-called “social simulations” to predict the reactions of people for a long time. They enter in all of the data that people give them through social media, polling data, along with existing behavioral response data, etc., etc., etc. They can effectively predict human responses to events, such as the coronavirus or Black Lives Matter riots.
They don’t talk much about these models, however.
What they are probably going to start talking about is simulations that predict “climate change.” The graphs have gotten a lot of flak.
To become climate neutral by 2050, the European Union launched two ambitious programmes: “Green Deal” and “DigitalStrategy”. As a key component of their successful implementation, climate scientists and computer scientists launched the “Destination Earth” initiative, which will start in mid-2021 and is expected to run for up to ten years. During this period, a highly accurate digital model of the Earth is to be created, a digital twin of the Earth, to map climate development and extreme events as accurately as possible in space and time.
Observational data will be continuously incorporated into the digital twin in order to make the digital Earth model more accurate for monitoring the evolution and predict possible future trajectories. But in addition to the observation data conventionally used for weather and climate simulations, the researchers also want to integrate new data on relevant human activities into the model. The new “Earth system model” will represent virtually all processes on the Earth’s surface as realistically as possible, including the influence of humans on water, food and energy management, and the processes in the physical Earth system.
The digital twin of the Earth is intended to be an information system that develops and tests scenarios that show more sustainable development and thus better inform policies. “If you are planning a two-metre high dike in The Netherlands, for example, I can run through the data in my digital twin and check whether the dike will in all likelihood still protect against expected extreme events in 2050,” says Peter Bauer, deputy director for Research at the European Centre for Medium-Range Weather Forecasts (ECMWF) and co-initiator of Destination Earth. The digital twin will also be used for strategic planning of fresh water and food supplies or wind farms and solar plants.
The driving forces behind Destination Earth are the ECMWF, the European Space Agency (ESA), and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). Together with other scientists, Bauer is driving the climate science and meteorological aspects of the Earth’s digital twin, but they also rely on the know-how of computer scientists from ETH Zurich and the Swiss National Supercomputing Centre (CSCS), namely ETH professors Torsten Hoefler, from the Institute for High Performance Computing Systems, and Thomas Schulthess, Director of CSCS.
The authors also see great potential in artificial intelligence (AI). It can be used, for example, for data assimilation or the processing of observation data, the representation of uncertain physical processes in the models and data compression. AI thus makes it possible to speed up the simulations and filter out the most important information from large amounts of data. Additionally, the researchers assume that the use of machine learning not only makes the calculations more efficient, but also can help describing the physical processes more accurately.
The scientists see their strategy paper as a starting point on the path to a digital twin of the Earth. Among the computer architectures available today and those expected in the near future, supercomputers based on graphics processing units (GPU) appear to be the most promising option. The researchers estimate that operating a digital twin at full scale would require a system with about 20,000 GPUs, consuming an estimated 20MW of power. For both economic and ecological reasons, such a computer should be operated at a location where CO2-neutral generated electricity is available in sufficient quantities.
Oh, you think GPUs are the most promising for processing simulation data?
You think maybe you can put a bunch of GPUs together and process huge amounts of data at once?
Who wrote this?