Scientists begin building highly accurate digital twin of our planet
rael-science
A
digital twin of our planet is to simulate the Earth system in future.
It is intended to support policy-makers in taking appropriate measures
to better prepare for extreme events. A new strategy paper by European
scientists and ETH Zurich computer scientists shows how this can be
achieved.
To
become climate neutral by 2050, the European Union launched two
ambitious programs: 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.
Information system for decision-making
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-meter 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.
In order to take this big step in the digital revolution, Bauer emphasizes the need for earth sciences to be married to the computer sciences. In a recent publication in Nature Computational Science,
the team of researchers from the earth and computer sciences discusses
which concrete measures they would like to use to advance this "digital
revolution of earth-system sciences," where they see the challenges and what possible solutions can be found.
Weather and climate models as a basis
In
their paper, the researchers look back on the steady development of
weather models since the 1940s, a success story that took place quietly.
Meteorologists pioneered, so to speak, simulations of physical
processes on the world's largest computers. As a physicist and computer
scientist, CSCS's Schulthess is therefore convinced that today's weather
and climate models are ideally suited to identify completely new ways
for many more scientific disciplines how to use supercomputers
efficiently.
In
the past, weather and climate modeling used different approaches to
simulate the Earth system. Whereas climate models represent a very broad
set of physical processes, they typically neglect small-scale
processes, which, however, are essential for the more precise weather
forecasts that in turn, focus on a smaller number of processes. The
digital twin will bring both areas together and enable high-resolution
simulations that depict the complex processes of the entire Earth
system. But in order to achieve this, the codes of the simulation
programs must be adapted to new technologies promising much enhanced
computing power.
With
the computers and algorithms available today, the highly complex
simulations can hardly be carried out at the planned extremely high
resolution of one kilometer because for decades, code development
stagnated from a computer science perspective. Climate research
benefited from being able to gain higher performance by ways of new
generations of processors without having to fundamentally change their
program. This free performance gain with each new processor generation
stopped about 10 years ago. As a result, today's programs can often only
utilize 5 percent of the peak performance of conventional processors
(CPU).
For
achieving the necessary improvements, the authors emphasize the need of
co-design, i.e. developing hardware and algorithms together and
simultaneously, as CSCS successfully demonstrated during the last ten
years. They suggest to pay particular attention to generic data
structures, optimized spatial discretisation of the grid to be
calculated and optimisation of the time step lengths. The scientists
further propose to separate the codes for solving the scientific problem
from the codes that optimally perform the computation on the respective
system architecture. This more flexible program structure would allow a
faster and more efficient switch to future architectures.
Profiting from artificial intelligence
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.
Explore further
A digital twin of Earth for the green transition. Nat. Clim. Chang. 11, 80–83 (2021). DOI: 10.1038/s41558-021-00986-y
