New model predicting solar flares is 56% accurate
The uncertainty of science: Using observations from the space-based Solar Dynamics Observatory (SDO), solar scientists have developed a new model for predicting the biggest solar flares, and have found it to able to predict a big flare about 56% of the time.
Kusano and his team looked at the seven active regions from the last solar cycle that produced the strongest flares on the Earth-facing side of the Sun (they also focused on flares from part of the Sun that is closest to Earth, where magnetic field observations are best). SDO’s observations of the active regions helped them locate the right magnetic boundaries, and calculate instabilities in the hot spots. In the end, their model predicted seven out of nine total flares, with three false positives. The two that the model didn’t account for, Kusano explained, were exceptions to the rest: Unlike the others, the active region they exploded from were much larger, and didn’t produce a coronal mass ejection along with the flare. [emphasis mine]
What they did was apply their model to active regions on the Sun during the last solar maximum to see if it would accurately predict the events we know did happen. The model predicted that big flares would spout from ten of twelve active regions on the Sun during the last solar cycle. In reality, only seven of those twelve active regions produced flares.
The press release minimizes the three false positives, making believe they don’t count in the total. That’s hogwash. The model got it wrong, and so these false positives must be counted just like the two false negatives.
A prediction rate of 56% is barely above random, so this model needs a lot of work. Nonetheless, it is a major step forward, because it is not based on simple statistics — counting the number of big sunspots and the number of big flares and then calculating the percentage that flare — which is how most solar science models are structured, and thus are really meaningless. Instead, this model is based an actual analysis of the behavior of the Sun’s magnetic field in big active regions when solar flares erupt. They are trying to pinpoint the precise conditions that cause the big flares, and appear to be narrowing the conditions successfully.
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The uncertainty of science: Using observations from the space-based Solar Dynamics Observatory (SDO), solar scientists have developed a new model for predicting the biggest solar flares, and have found it to able to predict a big flare about 56% of the time.
Kusano and his team looked at the seven active regions from the last solar cycle that produced the strongest flares on the Earth-facing side of the Sun (they also focused on flares from part of the Sun that is closest to Earth, where magnetic field observations are best). SDO’s observations of the active regions helped them locate the right magnetic boundaries, and calculate instabilities in the hot spots. In the end, their model predicted seven out of nine total flares, with three false positives. The two that the model didn’t account for, Kusano explained, were exceptions to the rest: Unlike the others, the active region they exploded from were much larger, and didn’t produce a coronal mass ejection along with the flare. [emphasis mine]
What they did was apply their model to active regions on the Sun during the last solar maximum to see if it would accurately predict the events we know did happen. The model predicted that big flares would spout from ten of twelve active regions on the Sun during the last solar cycle. In reality, only seven of those twelve active regions produced flares.
The press release minimizes the three false positives, making believe they don’t count in the total. That’s hogwash. The model got it wrong, and so these false positives must be counted just like the two false negatives.
A prediction rate of 56% is barely above random, so this model needs a lot of work. Nonetheless, it is a major step forward, because it is not based on simple statistics — counting the number of big sunspots and the number of big flares and then calculating the percentage that flare — which is how most solar science models are structured, and thus are really meaningless. Instead, this model is based an actual analysis of the behavior of the Sun’s magnetic field in big active regions when solar flares erupt. They are trying to pinpoint the precise conditions that cause the big flares, and appear to be narrowing the conditions successfully.
Please consider donating to Behind the Black, by giving either a one-time contribution or a regular subscription, as outlined in the tip jar below. Your support will allow me to continue covering science and culture as I have for the past twenty years, independent and free from any outside influence.
Regular readers can support Behind The Black with a contribution via paypal:
If Paypal doesn't work for you, you can support Behind The Black directly by sending your donation by check, payable to Robert Zimmerman, to
Behind The Black
c/o Robert Zimmerman
P.O.Box 1262
Cortaro, AZ 85652
I think the article forgot to say how far in advance the predictions were made. Even the weather forecast for tomorrow is decently accurate. Week from now probably 56%.
John: Yeah, I think this was a terribly written press release. The focus should have been on what has been learned about the beginning of large solar flares. This science, as described in the release, is fascinating and shows real progress because of SDO.
The model is nice, but it is putting the focus in the wrong place. Kinda like what we did with the Wuhan virus.
I think there is good value in this research, even with such cruddy accuracy. The reason is that it appears to be quite accurate at predicting the locations that are likely to trigger CMEs and that is incredibly important because these are the events that threaten our modern electronic infrastructure.
We cannot stop CMEs, but if we can predict them with reasonable accuracy, then we’re going to be able to tell which ones might impact Earth and when a BIG one may be coming. And knowing that we can plan for how to handle it, perhaps even shutting down our power grid and key systems pre-empively (thank you California, perhaps something useful came from Your wildfire fiascos after all).
CMEs are a real and present danger, and it is simply a matter of when, not if, a big enough one will hit Earth that will be devastating. So I applaud this research and think the results indicate they may be close to having a truly useful tool here.