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Propagation Characteristics of the April 21, 2023 CME

This paper demonstrates that incorporating the actual arrival time chronology of the April 21, 2023 CME at STEREO-A and Wind into the Graduated Cylindrical Shell and Advanced Drag-Based Models effectively resolves the significant directional uncertainties inherent in two-viewpoint stereoscopic reconstructions, thereby improving the accuracy of CME propagation and arrival time predictions.

Original authors: Sandeep Kumar, Nandita Srivastava, Parthib Banerjee, Nat Gopalswamy

Published 2026-02-19

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Sandeep Kumar, Nandita Srivastava, Parthib Banerjee, Nat Gopalswamy

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

The Solar "Ghost" Hunt: How Scientists Tracked a Space Storm with a Blurry Camera

Imagine you are trying to track a fast-moving car driving through a thick fog. You only have two security cameras: one is right next to the road, and the other is just a few feet away from the first one. Because the cameras are so close together, the angle they see the car from is almost identical. This makes it incredibly hard to tell exactly where the car is going or how fast it's really moving. You might think it's driving straight, but it could actually be swerving left or right.

This is exactly the problem scientists faced with a massive explosion on the Sun (a Coronal Mass Ejection, or CME) that happened on April 21, 2023.

Here is the story of how they solved the mystery, explained simply.

1. The Problem: A Blurry View of a Solar Storm

Space weather is like a storm on the Sun. When a CME happens, it shoots billions of tons of charged particles into space. If this storm hits Earth, it can mess up satellites, power grids, and GPS. To predict when it will hit, scientists need to know two things: how fast it is going and which direction it is heading.

Usually, scientists use a trick called stereoscopy (like how our two eyes give us 3D vision) to see these storms in 3D. They use two spacecraft:

SOHO: A satellite hovering near Earth.
STEREO-A: A satellite that orbits the Sun, usually far away from Earth.

However, on this specific day, STEREO-A was only 10 degrees away from Earth. That's like holding your two eyes only a few millimeters apart. The "3D vision" was terrible. When the scientists tried to build a 3D model of the storm, the math got confused. It was like trying to guess the shape of a ball when you can only see it from almost the exact same angle twice.

The models gave them two very different answers:

Theory A: The storm is heading straight for Earth.
Theory B: The storm is heading 20 degrees to the West, missing Earth.

Both theories looked "okay" based on the blurry photos, but they predicted very different arrival times.

2. The Solution: The "Race" Between Satellites

Since the cameras couldn't tell the truth, the scientists decided to use a different clue: The Race.

They knew the storm would pass by three different "checkpoints" (spacecraft) on its way through the solar system:

BepiColombo: Closest to the Sun.
STEREO-A: In the middle.
Wind: Closest to Earth.

The scientists asked a simple question: "Which spacecraft got hit first?"

If the storm was heading West (Theory B): It would hit the "Wind" spacecraft (near Earth) before it hit STEREO-A.
If the storm was heading East/Straight (Theory A): It would hit STEREO-A before it hit the "Wind" spacecraft.

3. The Twist: The Storm Swerved!

When the data came in, the scientists saw the actual race results:

The storm hit STEREO-A first.
It hit Wind (Earth) about 4.5 hours later.

This was the "smoking gun." The storm had to be heading toward STEREO-A first. This meant the storm wasn't going straight; it had swerved East while traveling through space.

4. The "Drag" Model: The Windy Car Analogy

To confirm this, the scientists used a computer model called the Advanced Drag-Based Model (ADBM). Think of this like a simulation of a car driving through wind.

The CME is a fast sports car.
The Solar Wind is the air it's driving through.
The Drag is the wind resistance slowing the car down.

The scientists ran the simulation twice:

Simulation 1: They told the computer the car was heading West. The computer predicted the car would hit the "Wind" checkpoint first. Result: Wrong.
Simulation 2: They told the computer the car was heading East (toward STEREO-A). The computer predicted the car would hit STEREO-A first, then Earth. Result: Correct!

By adjusting the direction in the computer model until the "race order" matched reality, they proved that the storm had deflected Eastward by about 20 degrees.

5. Why This Matters

This paper teaches us a valuable lesson about space weather forecasting:

One view isn't enough: When our "eyes" (satellites) are too close together, we get confused.
The "Race" solves the puzzle: Even if our cameras are blurry, knowing the order in which things happen at different locations can tell us exactly where something is going.
Storms change direction: Space storms don't always travel in a straight line. They can get pushed around by magnetic fields and other solar winds, just like a leaf blowing in a gusty wind.

The Bottom Line:
By watching the "race" between three satellites, scientists figured out that a massive solar storm had changed its mind and swerved toward Earth. This helped them predict exactly when the storm would arrive, allowing us to prepare for the space weather effects that followed. It's a reminder that sometimes, to see the big picture, you don't just need better cameras—you need to watch the whole race.

1. Problem Statement

Accurate prediction of Coronal Mass Ejection (CME) arrival times and geoeffectiveness relies heavily on determining their 3D kinematics and propagation direction. Traditionally, stereoscopic reconstruction using three viewpoints (STEREO-A, STEREO-B, and SOHO) provided robust data. However, since the loss of STEREO-B in 2014, reconstructions are limited to two viewpoints.

The Specific Challenge: When the angular separation between the two available viewpoints (STEREO-A and SOHO) is small (e.g., $10^\circ$ ), stereoscopic techniques suffer from projection effects and parameter degeneracies. This leads to significant uncertainties in estimating CME longitude, tilt, and angular width, which in turn propagates errors into arrival time (ToA) forecasts.
Case Study: The paper focuses on the April 21, 2023 CME, a high-speed event ( $>1000$ km/s) that caused a severe geomagnetic storm (Dst $\approx -213$ nT). It was observed by STEREO-A and SOHO with a separation angle of only $10^\circ$ , presenting a critical test case for these limitations.

2. Methodology

The authors employed a multi-step approach combining remote sensing reconstruction with in-situ validation:

3D Reconstruction (GCS Model):
- Used the Graduated Cylindrical Shell (GCS) model on remote-sensing data from SOHO (LASCO-C2/C3) and STEREO-A (COR2/HI1).
- Due to the small viewing angle, two independent fitting cases were performed by different analysts, resulting in two distinct propagation scenarios:
  1. Case 1 (Westward): Constant longitude ( $\approx +20^\circ$ ), suggesting westward propagation.
  2. Case 2 (Eastward/Earthward): Decreasing longitude ( $+34^\circ \to 0^\circ$ ), suggesting deflection toward the Sun-Earth line.
- Both fits showed geometric degeneracy (trade-offs between height and longitude), highlighting the uncertainty inherent in two-viewpoint reconstruction with small separation.
Propagation Modeling (ADBM):
- The Advanced Drag-Based Model (ADBM) was used to forecast the CME's transit speed and arrival time at various heliocentric distances.
- Inputs included CME take-off time, initial height ( $\approx 40 R_\odot$ ), speed ($1100$ km/s), drag parameters, and solar wind speed ($350$ km/s).
- Crucially, the longitude derived from the GCS fits was used as a variable input to test different propagation directions.
In-Situ Validation:
- The model predictions were compared against actual in-situ data from three spacecraft at different heliocentric distances:
  - BepiColombo ( $\approx 0.63$ AU)
  - STEREO-A ( $\approx 0.96$ AU)
  - Wind ( $\approx 1.0$ AU)
- The chronology of arrival (which spacecraft detected the CME first) was identified as the critical discriminator between the competing GCS models.

3. Key Results

GCS Uncertainty: The two GCS fittings yielded a directional uncertainty of approximately $20^\circ$ . One fit suggested a final westward propagation ( $20^\circ$ ), while the other suggested an Earth-directed path ( $0^\circ$ ).
ADBM Performance & Chronology:
- Westward Scenario: When the ADBM assumed westward propagation, it predicted the CME would hit Wind first, then STEREO-A. This contradicted actual observations. Furthermore, the ToA error for STEREO-A was large ( $\approx +7.8$ hours).
- Earthward Scenario: When the ADBM assumed Earth-directed propagation, it correctly predicted STEREO-A would be hit first, followed by Wind. The ToA errors were significantly reduced (e.g., $\approx +2.5$ hours for STEREO-A).
- Optimized Eastward Deflection: By adjusting the input longitude in the ADBM to $-10^\circ$ (aligning with STEREO-A's position), the model achieved the best fit. It predicted an arrival at STEREO-A at 22:47 UT and Wind at 02:04 UT, matching the observed chronology (STEREO-A $\to$ Wind) with a time difference of $\approx 3.5$ hours (close to the observed 4.5 hours).
Deflection Conclusion: The analysis confirms that the CME underwent a net eastward deflection of approximately $20^\circ$ – $30^\circ$ during its propagation from the corona to the heliosphere, moving from its source region (S21W11) toward the Sun-Earth line.

4. Key Contributions

Methodological Innovation: The paper demonstrates a novel method to resolve directional ambiguities in 3D reconstruction when a third viewpoint is unavailable. By using two-point in-situ observations (specifically the arrival chronology at STEREO-A and Wind) to constrain the ADBM inputs, the authors successfully validated the true propagation direction despite the poor geometric constraints of the remote sensing data.
Quantification of Uncertainty: It quantifies the impact of small viewing angles ( $10^\circ$ ) on GCS fitting, showing how degeneracies can lead to $\approx 20^\circ$ errors in longitude, which drastically alters ToA predictions.
Validation of Physical Mechanisms: The results support theoretical models suggesting that fast CMEs ( $\approx 1100$ km/s) propagating through slower solar wind tend to deflect eastward, consistent with previous studies (e.g., Wang et al., 2004).

5. Significance

Space Weather Forecasting: This study provides a practical workflow for improving CME arrival time forecasts during periods of limited spacecraft coverage. It proves that combining remote sensing with multi-point in-situ data can compensate for the lack of stereoscopic baselines.
Operational Relevance: For space weather agencies, understanding that a CME may deflect significantly (e.g., from a westward trajectory to an Earth-directed one) is vital for issuing accurate alerts. Relying solely on initial GCS fits without in-situ constraints could lead to missed warnings or false alarms.
Future Modeling: The paper highlights the need for full 3D MHD modeling to better capture complex CME deformations (flattening, distortion) that drag-based models simplify, while also validating the utility of hybrid approaches (GCS + ADBM + In-situ) for immediate operational use.

In summary, the paper successfully resolves the ambiguity of the April 21, 2023 CME's trajectory by leveraging the arrival chronology at multiple spacecraft to correct the uncertainties introduced by limited viewing angles, confirming an eastward deflection and refining the arrival time prediction.