Sun Spot Number (SSN)

Determination of ionospheric characteristics related to HF propagation requires knowledge of the prevailing levels of solar activity (ITU-R P.1239-3, 2012). The Sunspot Number (SSN), quantifying of the number of dark spots visible on the Sun’s surface, has historically served as the primary proxy of solar activity (Clette et al., 2015). Records of SSNs date back over 400 years, providing a valuable insight into the sun's quasi periodic 11-year cycle of activity. Superimposed onto this cycle are shorter term variations that can result in large fluctuations in day-to-day values. More recent research suggests that the 11 year cycle is itself modulated by the interaction of two solar dynamos, accounting for the fluctuations in the level of activity observed during each cycle (Zharkova et al., 2015).

The figure below illustrates how daily values (yellow) may be averaged over month (blue) and monthly smoothed (12-month) (red) periods, eliminating complex short term variations to yield a more predictable indicator of solar activity. The preferred ionospheric metric when determining the critical frequencies of the various layers and the MUF factor M(3000)F2 is a 12-month running mean sunspot number, R12 (ITU-R P.1239-3, 2012). R12 values are a function of sunspot values extending at least six months either side of the month of interest (ITU-R P.371-8, 1999). (Note that this has the unfortunate side effect that an R12 value for a given month ‘m’ cannot be absolutely determined until ‘m+6’ (six months later)).

Figure 1: Daily and Monthly Sunspot Number (last 13 years)
Source: WDC-SILSO, Royal Observatory of Belgium, Brussels

SSN Values

Recommendation ITU-R P.371-8 (1999) states that the SSN (R12) values presented in the ITU's Circular of Basic Indices for Ionospheric Propagation should be used. These are derived from the SSN (Standard Curves method) data published by WDC-SILSO, Royal Observatory of Belgium, Brussels.

In addition to the standard curves data, the SIDC also publish predictions based on the Combined Model and McNish & Lincoln methods.

Podladchikova and Van der Linden (2012) demonstrate how the accuracy of predictions may be improved by the application of a Kalman filter, yielding a total of six sets of predicted SSN data. The (predicted) R12 values for March 2018 are;
ModelStandardKalman Filter
Standard Curves12.09.0
Combined Model9.38.0
McNish & Lincoln10.98.0

It should be noted that selection of the SSN Source parameter only has an effect on predicted values, i.e. values extending from six months ago.

The appropriate SSN value is automatically selected based on the date specified in the Date Picker and the specified SSN Source. The SSN values are updated each month, current values of the Standard Curve set are shown in the table below;

YearJanFebMarApr MayJunJulAug SepOctNovDec
Source: WDC-SILSO, Royal Observatory of Belgium, Brussels (Retrieved: Sat Mar 3 04:02:46 2018)

Daily Values

While smoothed values are required to calculate critical frequencies of the various layers and the MUF factor, it is useful to remember that the actual value on any given day will almost certainly be different to the smoothed monthly value. Figure 2 below indicates the current daily Estimated International Sunspot Number (EISN) obtained by a simple average over available sunspot counts. This data is not intended for long term use but may provide some insight into the stability of solar conditions.

Figure 2: Estimated International Sunspot Number (EISN)
Source: WDC-SILSO, Royal Observatory of Belgium, Brussels