Space Weather / Aurora Hunting - Wed, 23 Aug 2017 08:21:00 +0000 UTC
| Sunset |
Aurora Oval |
The Moon |
|
|
|
 |
| 3% Illuminated |
|
2 hours ago
06:30
|
|
|
|
4
|
? |
? |
|
Kp Now: 4
|
N/A |
N/A |
|
Field
Polarity
|
|
Solar Wind: 475.1 km/s
24hr Max: 477.1 km/s
24hr Min: 452.8 km/s
Proton Density: 5.8 p/cc
Bz: 5.4 nT |
|
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| Predicted Kp Levels | Predicted Storm Probability | Predicted Flare Probability |
|---|
| |
Wed |
Thu |
Fri |
| 0000 | 2 | 2 | 2 |
| 0300 | 3 | 3 | 2 |
| 0600 | 3 | 2 | 2 |
| 1800 | 2 | 2 | 1 |
| 2100 | 3 | 2 | 2 |
|
| |
Wed |
Thu |
Fri |
| Active | 30% | 10% | 10% |
| Minor Storm | 10% | 1% | 5% |
| Major Storm | 1% | 1% | 1% |
|
| |
Wed |
Thu |
Fri |
| M Class | 15% | 15% | 15% |
| X Class | 1% | 1% | 1% |
|
What does this data mean?
The Sun
The images of the sun are downloaded from the
Solar Dynamics Observatory
they show how the sun looks when viewed through different wavelengths of light.
This is useful because it helps us to pinpoint where there is a lot of energy being released
(sunspots).
Sunspots aid our chances of seeing the Northern Lights because they can often result in
Solar Flares and
Coronal Mass Ejections
The Aurora Oval
The Aurora Oval is the latest data from the
NOAA POES satellite.
The Yellow/Orange/Red ring in the image shows where the visible aurora is likely to be seen at this moment.
When there is a disturbance in the geomagnetic field surrounding the earth the aurora oval stretches down toward the equator.
The Kp Level
The
Kp Index indicates how disturbed the geomagnetic field surrounding the earth is.
We can use the Kp level to determine what the likely chances of seeing the northern lights are.
In the Scottish Borders we are looking for at least a level of
Kp5 to
start seeing the northern lights.
The Forecast Kp Level
The forecast for solar activity is downloaded periodically from the
Space Weather Prediction Center.
Like a weather model, the SWPC use a variety of data fed into the
Costello Model to predict the likely Kp level.
The forecast may sometimes be out of date because sometimes the model is run with limited data and we therefore ignore it's prediction.
