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Statistical Analysis of Results

Results of the number count of each type of solar prominence.
Prominence Type Number Count Total Percentage (%)
Single Arch 25 7.1
Double Arch 5 1.4
Broken Arch 6 1.7
Unconnected Arch 12 3.4
Straight Pillar 40 11.4
Curved Pillar 12 3.4
Inclined Pillar 28 8.0
Regular Pyramid 48 13.7
Broken Pyramid 7 2.0
Mound 52 14.9
Fork 25 7.1
Hedgerow 21 6.0
Detached 16 4.6
Anomalous 53 15.1
Total 350 100

Morphological Classification

Prominence morphological classification diagram

Link to Full-size Image[44 KB]

This diagram shows the relationships between solar prominence morphological classifications. Arrows indicate morphological similarities.

Prominence morphological classification diagram, showing statistics

Link to Full-size Image [56 KB]

This diagram shows statistics associated with relationships between the classifications. Arrows indicate morphological similarities within statistical bounds.


Error-bars

The total number of prominences in the data set is 350. There are 14 types of prominences in the classification scheme, so therefore there is an average of 25 prominences per bin. If we were to assume that prominence generation on the Sun was truly random, then we would be dealing with

statistics meaning the average per bin is actually 25±5. By comparing this with the statistical analysis of the data, only 4 of the 14 prominence types (29%) are found within 1σ of the mean. For normally distributed data, 68% should be found within 1σ, so therefore this provides very strong evidence that the types of prominence generated are not completely random. Only 8 of the 14 (57%) are found within 3σ, which should contain 99.7%, further proof that it is far from a normally distributed set of data.

This has implications on prominence generation and lifetimes of different types - this is discussed below.

Analysis

We have presented a classification scheme which attempted to give some morphological analysis to solar prominences that to casual observers would generally appear random. The scheme is of course not without its limitations, and these are discussed further below.

Looking at the second classification diagram and the statistics, the three families have fairly similar probabilities of appearance. In total, a pillar form occurred 22.8% of the time, arch form occurred 13.6%, and mound form occurred 28.8%. The detached prominence is ignored as it is a more unique type. Judging by these numbers there is no significant bias to any particular family, though maybe with a larger data set a bias would become more evident. This could give some insight into the workings of the local magnetic fields in active areas on the Sun, although the frame of reference from which we view a particular prominence may change how it is classified. In other words, a prominence may appear as a particular type from one position in space, but from another it may look entirely different.

A prominence that to us appears as an arch would appear as a pillar from another perspective

A prominence that to us appears as an arch would appear as a pillar from another perspective.

The effect that this has on the data set is difficult to gauge, because the appearance of a prominence will not change significantly, if at all, from anywhere on Earth, and prominences exist for only hours or maybe days before disappearing, so the true form of a prominence is essentially impossible to know without being able to observe the Sun from multiple angles at any given time. In other words, the only way to counter this effect would be to compare images taken on Earth with images taken with space telescopes that are positioned at points much further along in our orbit than Earth. Unfortunately the majority of telescopes including SOHO are positioned at the L1 Lagrangian point which puts them at the same point of view as Earth. However, the two NASA Stereo craft may produce some interesting images showing 3D prominence evolution.

One further significant caveat of this classification scheme is that there can be some ambiguity as to whether a prominence falls under one type or another. For example, a tall pyramid could be interpreted as a pillar, a mound could be interpreted as a pyramid, or a broken arch might be seen as a single arch. Whilst we’ve tried to establish some rules with some types as to how they’re defined, there are still inevitably going to be grey areas where one cannot necessarily produce a clear-cut classification between ambiguous morphologies. Some examples of ambiguity are below.

Ambiguous prominence, arch or broken pyramid?

Arch or broken pyramid?

Ambiguous prominence, single or unconnected arch?

Single or unconnected arch?

Ambiguous prominence, single or broken arch?

Single or broken arch?


Leading on from this is another significant limitation, which is that the appearance of any given prominence could vary quite significantly depending on the observing equipment being used. Lower resolution telescopes and filters would not be able to resolve certain details of prominences that the higher resolution equipment could, so one observer may categorise a prominence as being different to another. For example, a pyramid may appear as a regular, unbroken pyramid under basic equipment, but advanced equipment could resolve more gaps and structure in the prominence material, thus it would be categorised as a broken pyramid. More sensitive equipment may also detect low density solar material that might otherwise not be detected, which may for example lead to an unconnected arch being interpreted as a single arch because the density of solar material at one end of the arch is very low. I would say that the equipment used for this project would be classed as moderate to low resolution solar observing equipment, plus the observing location (UK based) is generally not ideal for producing good observing conditions.

There may also be some very rare forms of prominence that were not present in the data set, which could have been added to the scheme. While they would not likely affect the scheme in its current state, they might provide a little more insight into the processes involved in prominences.