New dawn for space storm alerts could help shield Earth's tech

Space storms could soon be forecasted with greater accuracy than ever before thanks to a big leap forward in our understanding of exactly when a violent solar eruption may hit Earth.

Scientists say it is now possible to predict the precise speed a coronal mass ejection (CME) is travelling at and when it will smash into our planet -- even before it has fully erupted from the Sun.

CMEs are bursts of gas and magnetic fields spewed into space from the solar atmosphere.

They can cause geomagnetic storms that have the potential to wreak havoc with terrestrial technology in Earth's orbit and on its surface, which is why experts across the globe are striving to improve space weather forecasts.

Advancements such as this one could make a huge difference in helping to protect infrastructure that is vital to our everyday lives, according to researchers at Aberystwyth University, who will present their findings today at the Royal Astronomical Society's National Astronomy Meeting in Hull.

They made their discovery after studying specific areas on the Sun called 'Active Regions', which have strong magnetic fields where CMEs are born. The researchers monitored how these areas changed in the periods before, during and after an eruption.

A vital aspect which they looked at was the "critical height" of the Active Regions, which is the height at which the magnetic field becomes unstable and can lead to a CME.

"By measuring how the strength of the magnetic field decreases with height, we can determine this critical height," said lead researcher Harshita Gandhi, a solar physicist at Aberystwyth University.

"This data can then be used along with a geometric model which is used to track the true speed of CMEs in three dimensions, rather than just two, which is essential for precise predictions."

She added: "Our findings reveal a strong relationship between the critical height at CME onset and the true CME speed.

"This insight allows us to predict the CME's speed and, consequently, its arrival time on Earth, even before the CME has fully erupted."

When these CMEs hit the Earth they can trigger a geomagnetic storm which is capable of producing stunning aurorae, often referred to in the northern hemisphere as the Northern Lights.

But the storms also have the potential to disrupt vital systems we rely on daily, including satellites, power grids, and communication networks, which is why scientists worldwide are working hard to improve our ability to better predict when CMEs will hit Earth.

This requires knowing a more accurate speed of the CME shortly after it erupts from the Sun to better provide advance warnings of when it will reach our planet.

Accurate speed predictions enable better estimates of when a CME will reach Earth, providing crucial advance warnings.

"Understanding and using the critical height in our forecasts improves our ability to warn about incoming CMEs, helping to protect the technology that our modern lives depend on," Gandhi said.

"Our research not only enhances our understanding of the Sun's explosive behaviour but also significantly improves our ability to forecast space weather events.

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Underused satellite, radar data may improve thunderstorm forecasts

Tens of thousands of thunderstorms may rumble around the world each day, but accurately predicting the time and location where they will form remains a grand challenge of computer weather modeling. A new technique combining underused satellite and radar data in weather models may improve these predictions, according to a Penn State-led team of scientists.

"Thunderstorms are so ubiquitous it's hard to count how many you get in Pennsylvania, or the United States or globally every day," said Keenan Eure, doctoral student in the Department of Meteorology and Atmospheric Science at Penn State. "A lot of our challenges, even today, are figuring out how to correctly predict the time and location of the initiation of thunderstorms."

The scientists found that by combining data from the geostationary weather satellite GOES-16 and ground-based Doppler radar they could capture a more accurate picture of initial conditions in the boundary layer, the lowest part of the atmosphere, where storms form.

"There's value in improving thunderstorm predictions from both Doppler radar observations and satellite observations that are currently underused and we showed that not only can they be used to improve predictions but putting them together has lots of benefits," said Eure, lead author on the study. "The sum is greater than the individual parts."

The technique showed promise in improving forecasts of convection initiation, the conditions that spawn storms, several hours before the thunderstorms occurred in a case study from May 2018 in the Texas panhandle. The scientists reported their findings in the journal Monthly Weather Review.

"Keenan focused on using satellite observations to better define the environment in which the storms would later form, and on using radar observations to improve the low-level wind fields that eventually helped to create the storms," said David Stensrud, professor of meteorology at Penn State and Eure's advisor and co-author on the study. "This observation combination had not been studied previously and ended up adding significant value to the model forecasts on this day."

The scientists used data assimilation, a statistical method that can paint the most accurate possible picture of current weather conditions in the weather model, important because even small changes in the atmosphere can lead to large discrepancies in forecasts over time.

Understanding conditions in the boundary layer is particularly important because it strongly influences the ingredients for convection -- near-surface moisture, lift and instability -- a process that causes warm air near the Earth's surface to rise and form clouds.

"We obviously can't model every molecule in the atmosphere, but we want to get as close as possible," Eure said. We really believe this work adds a lot of valuable information that models currently don't have and that we can help the depiction of the lowest part of the atmosphere."

The team assimilated satellite and radar data separately and simultaneously and found the best results came from combining infrared brightness temperature observations from the satellite and radial wind velocity and boundary height observations from the radar.

The work uses all-sky satellite data assimilation, developed by Penn State's Center for Advanced Data Assimilation and Predictability Techniques, that assimilates satellite data from all weather conditions, including cloudy and clear skies. Forecasting previously relied on clear-sky observations, due to challenges in diagnosing the complex physical processes within clouds, the scientists said.

"While more cases need to be explored, these observations are currently available and could be used to improve thunderstorm prediction over the coming decade as NOAA continues to advance its Warn-on-Forecast paradigm in which computer model predictions help to make severe weather warnings more accurate and timely," Stensrud said.

Other Penn State researchers on the project were Matthew Kumjian and Steven Greybush, associate professors, Yunji Zhang, assistant professor and Paul Mykolajtchuk, former graduate student, in the Department of Meteorology and Atmospheric Science.

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