Sunday, December 19, 2010

A 5-Year 10-Meter Es Propagation Study Using PropNET - Part 7

Probability Analysis – A Better Method to Predict “Es” Activity:

Due to the fact that the United States’ distribution of population and Ham activity was not equal, a better measurement practice is to apply an equal value to one single reception (PropNET capture) within a one hour period. In other words, a single occurrence in a measured period equals the occurrence of many. The probability of an occurrence is now measured, not the actual number of captures in the period.

Therefore, every hour documented and measured in the 5 years of data was re-applied. If a capture occurred during the hour it was given a value of one (1). If no capture occurred, it was given a value of zero (0). The result is that statistical probabilities can be applied to any set of days and hourly times in which an opening occurred. The quality and quantity of the hourly opening had no bearing. Opportunity is what is being measured, not how much was being worked.

The key factor is that opportunity will always produce results. The more opportunity existed, the better the results.

The following charts data are based on these factors:
1. The days prior to and after the Summer Solstice (June 21)
2. All 24 hours are used in the day.
3. The probability measured (percent) is that on any hour of that day, we will have at least one occurrence of a 10-Meter PropNET Es capture during any hour.

The results show a very clear trend on how Es begin, increase and then decline during the season. Daily total probability is based on that on the day measured, that on any measured hour, the occurrence of a 10-Meter Es PropNET capture occurred. It was amazing to see the daily differences with 5 years of cumulative volume data. Once difference shown between capture and probability data was that the “median” date for captures was on 6/22 and for probability it was 6/25 a 3 day swing. In other words captures are spread evenly throughout the season, but opportunities slightly favor the second half of the season.

Some probabilities can increase or decrease 30% in one day. As in the total captures chart, the Probability Chart represented the dramatic increase in opportunities in early May. The best day for Es opportunities was after the summer solstice (June 25 and July 4), with 65% of the total hours on these dates having a capture. By May 21, the occurrence of an Es capture for any hour of the day increases to near 50%, and remains fairly consistent for most days until July 29. One factor that draws your attention is why there are certain days less productive than others. The right skewed and tailed appearance in probability is somewhat clearer than the capture volume statistics as the season takes about 2 more weeks after the solstice to finally end.

The regression analysis performed on probability is much better than the one performed on capture statistics. The coefficient of determination is at the upper end of measurement. The trend line indicates that the season begins on April 26 and ends on August 30. The peak for probability occurs on June 27. This trend clearly indicates that Es probability actually favor the second-half of the season.

As in the capture charts, I averaged 3 continuous days of data around the day measured. As in the daily charts, it was surprising how much probabilities will decline or increase in a matter of a couple of days. Still the early seasonal increase, followed by the slow decrease the second half of the season was quite evident.

This trend becomes much clearer when 6 consecutive days of probabilities are averaged for each measured day. Note that both the beginning and end of the Es season are clearly defined.

After measuring hourly probabilities on a daily basis, I decided to measure cumulative weekly periods to further confirm trends that I had seen in the prior charts. Also, I wished to see how probabilities of a capture changed for the actual hours within a day. I again divided the Spring/Summer Es season into 16 weeks. I compiled 7 day segments of data for the 5 years and calculated the probability that at least one capture occurred at any given hour in this weekly period. In 2009, I extended the measurement period by 2 weeks.

Probability Statistics by Hour:
I was also curious to find out if the probability factors would also correlate to a higher number of captures. Probability is based on a single incident during a measured hour, not on total captures. I was very pleased to find out that the two factors did relate closely. Only during the late afternoon were there minor shifts. This might be due to the shifts of average distances (higher) experienced during this period. The shift is negligible. Therefore, quality relates to quantity.

The regression analysis performed for the hourly probability closely represents a typical day on Es that begins at the 6:00AM hour. The peak in terms of probability occurs at 1:00PM local daylight time. The trend then shows a general decline till 5:00AM.

Probability by Weekly Periods:
The following charts are represented and discussed in terms of the week of the Spring/Summer Es season. When it is referenced, each week number corresponds to the following days:

Week 1: 25-Apr - 1-May
Week 2: 2-May - 8-May
Week 3: 9-May - 15-May
Week 4: 16-May - 22-May
Week 5: 23-May - 29-May
Week 6: 30-May - 5-Jun
Week 7: 6-Jun - 12-Jun
Week 8: 13-Jun - 19-Jun
Week 9: 20-Jun - 26-Jun
Week 10: 27-Jun - 3-Jul
Week 11: 4-Jul - 10-Jul
Week 12: 11-Jul - 17-Jul
Week 13: 18-Jul - 24-Jul
Week 14: 25-Jul - 31-Jul
Week 15: 1-Aug - 7-Aug
Week 16: 8-Aug - 14-Aug
Week 17: 15-Aug - 21-Aug
Week 18: 22-Aug - 28-Aug

As shown in the Daily Probability figures, similar trends with the weekly capture computations did occur. Before 2008, the peak of the Es season was the weeks beginning May 23 and May 30 (5th and 6th week). The final 2 years of the study strongly showed the peak after the Summer Solstice (early in the 9th Week). On average, a slow decline begins after the 9th week. The small peak during the week of 7/25 (14th week) also draws your attention and will be addressed later.

By the 5th week of the season, daylight period probabilities become consistent week to week and maintain the high probability levels. The evening and twilight periods (8 PM-6AM) will show rates of change before and after the solstice. The daytime period weekly probabilities changed little once the season was in full swing.

When the study was started, my opinion was that Es activity should form a perfectly shaped bell curve peaking at the Summer Solstice. Throughout the 5 years of this study, it was quite evident that capture totals and probability calculations once charted were showing that Es activity was somewhat right-skewed and right tailed. In other words, Es activity once the season begins rises quickly then peaks before the Summer solstice. Activity then slowing declines for the remainder of the Es season. The end of the Es season will occur further after the Summer Solstice than when it begins before.

Next: Triple Hour Probabilities

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