Protecting Earth from space storms

Date:
August 11, 2021
Source:
University of Texas at Austin, Texas Advanced Computing Center
Summary:
A major space weather event could have a catastrophic impact on
Earth, disabling communications and electrical systems. Researchers
are using the Frontera supercomputer to develop new geomagnetic
forecasting methods and improve the Geospace Model used by NOAA
for operational purposes.

They hope to increase the lead time for space weather events
from 30 minutes to 1-3 days, localize space weather forecasts,
and provide uncertainty estimates.



FULL STORY ========================================================================== "There are only two natural disasters that could impact the entire U.S.," according to Gabor Toth, professor of Climate and Space Sciences and Engineering at the University of Michigan. "One is a pandemic and the
other is an extreme space weather event."

========================================================================== We're currently seeing the effects of the first in real-time.

The last major space weather event struck the Earth in 1859. Smaller,
but still significant, space weather events occur regularly. These
fry electronics and power grids, disrupt global positioning systems,
cause shifts in the range of the Aurora Borealis, and raise the risk of radiation to astronauts or passengers on planes crossing over the poles.

"We have all these technological assets that are at risk," Toth said. "If
an extreme event like the one in 1859 happened again, it would completely destroy the power grid and satellite and communications systems -- the
stakes are much higher." Motivated by the White House National Space
Weather Strategy and Action Plan and the National Strategic Computing Initiative, in 2020 the National Science Foundation (NSF) and NASA created
the Space Weather with Quantified Uncertainties (SWQU) program. It brings together research teams from across scientific disciplines to advance
the latest statistical analysis and high performance computing methods
within the field of space weather modeling.

"We are very proud to have launched the SWQU projects by bringing together expertise and supports across multiple scientific domains in a joint
effort between NSF and NASA," said Vyacheslav (Slava) Lukin, the Program Director for Plasma Physics at NSF. "The need has been recognized for
some time, and the portfolio of six projects, Gabor Toth's among them,
engages not only the leading university groups, but also NASA Centers, Department of Defense and Department of Energy National Laboratories, as
well as the private sector." Toth helped develop today's preeminent space weather prediction model, which is used for operational forecasting by the National Oceanic and Atmospheric Administration (NOAA). On February 3,
2021, NOAA began using the Geospace Model Version 2.0, which is part
of the University of Michigan's Space Weather Modeling Framework, to
predict geomagnetic disturbances.



========================================================================== "We're constantly improving our models," Toth said. The new model
replaces version 1.5 which has been in operations since November
2017. "The main change in version 2 was the refinement of the numerical
grid in the magnetosphere, several improvements in the algorithms,
and a recalibration of the empirical parameters." The Geospace Model
is based on a global representation of Earth's Geospace environment
that includes magnetohydrodynamics -- the properties and behavior of electrically conducting fluids like plasma interacting with magnetic
fields, which plays a key role in the dynamics of space weather.

The Geospace model predicts magnetic disturbances on the ground resulting
from geospace interactions with solar wind. Such magnetic disturbances
induce a geoelectric field that can damage large-scale electrical
conductors, such as the power grid.

Short-term advanced warning from the model provides forecasters and
power grid operators with situational awareness about harmful currents
and allows time to mitigate the problem and maintain the integrity of
the electric power grid, NOAA announced at the time of the launch.

As advanced as the Geospace Model is, it provides only about 30 minutes of advanced warning. Toth's team is one of several groups working to increase
lead time to one to three days. Doing so means understanding how activity
on the surface of the Sun leads to events that can impact the Earth.



========================================================================== "We're currently using data from a satellite measuring plasma parameters
one million miles away from the Earth," Toth explained. Researchers hope
to start from the Sun, using remote observation of the Sun's surface
-- in particular, coronal mass ejections that produce flares that are
visible in X-rays and UV light. "That happens early on the Sun. From
that point, we can run a model and predict the arrival time and impact
of magnetic events." Improving the lead time of space weather forecasts requires new methods and algorithms that can compute far faster than
those used today and can be deployed efficiently on high performance
computers. Toth uses the Frontera supercomputer at the Texas Advanced
Computing Center -- the fastest academic system in the world and the
10th most powerful overall -- to develop and test these new methods.

"I consider myself really good at developing new algorithms," Toth
said. "I apply these to space physics, but many of the algorithms I
develop are more general and not restricted to one application." A key algorithmic improvement made by Toth involved finding a novel way to
combine the kinetic and fluid aspects of plasmas in one simulation model.

"People tried it before and failed. But we made it work. We go a
million times faster than brute-force simulations by inventing smart approximations and algorithms," Toth said.

The new algorithm dynamically adapts the location covered by the kinetic
model based on the simulation results. The model identifies the regions
of interests and places the kinetic model and the computational resources
to focus on them.

This can result in a 10 to 100 time speed up for space weather models.

As part of the NSF SWQU project, Toth and his team has been working on
making the Space Weather Modeling Framework run efficiently on future supercomputers that rely heavily on graphical processing units (GPUs). As
a first goal, they set out to port the Geospace model to GPUs using the
NVIDIA Fortran compiler with OpenACC directives.

They recently managed to run the full Geospace model faster than real-time
on a single GPU. They used TACC's GPU-enabled Longhorn machine to reach
this milestone. To run the model with the same speed on traditional supercomputer requires at least 100 CPU cores.

"It took a whole year of code development to make this happen, Toth
said. "The goal is to run an ensemble of simulations fast and efficiently
to provide a probabilistic space weather forecast." This type of
probabilistic forecasting is important for another aspect of Toth's
research: localizing predictions in terms of the impact on the surface
of Earth.

"Should we worry in Michigan or only in Canada? What is the maximum
induced current particular transformers will experience? How long will generators need to be shut off? To do this accurately, you need a model
you believe in," he said. "Whatever we predict, there's always some uncertainty. We want to give predictions with precise probabilities,
similar to terrestrial weather forecasts." Toth and his team run
their code in parallel on thousands of cores on Frontera for each
simulation. They plan to run thousands of simulations over the coming
years to see how model parameters affect the results to find the best
model parameters and to be able to attach probabilities to simulation
results.

"Without Frontera, I don't think we could do this research," Toth
said. "When you put together smart people and big computers, great
things can happen." The Michigan Sun-to-Earth Model, including the
SWMF Geospace and the new GPU port, is available as open-source at https://github.com/MSTEM-QUDA. Toth and his collaborators published a
review of recent and in-progress developments to the model in the May
issue of EOS.

========================================================================== Story Source: Materials provided by University_of_Texas_at_Austin,_Texas_Advanced_Computing Center. Original written by Aaron Dubrow. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Tuija Pulkkinen, Tamas Gombosi, Aaron Ridley, Gabor Toth, Shasha
Zou. The
Space Weather Modeling Framework Goes Open Access. Eos, 2021;
102 DOI: 10.1029/2021EO158300 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2021/08/210811162847.htm

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