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What can we expect from a HF propagation model ?

Propagation prediction calculated with Proppy for a point-to-point link between LX and VU for August 2016 using an isotropic antenna in SSB with 100 W.

Running predictions (V)

When all inputs are encoded in the model, and only then, you can start forecast calculations and explore the various outputs, specialized charts (using submodels) or maps given a propagation overview. Several world maps are self-explanatory, when available :

- the gray-line map showing the location of the sunrise/sunset. In some applications the propagation forecast can be superposed on the gray-line map what permits to see much easier the effects of the sun under the specified conditions.

- the propagation map showing a gray scale (or in false color) of the signal strength at earth scale (area coverage).

NB. the accessible area chart is a modified propagation map. Some applications (e.g. HFProp) do not display the signal strength in gray scale but rather the different entities (prefixes) accessible under the specified conditions. The intensity of each prefix varies from white to gray according to the signal strength. In addition a meter displays the signal strength of any prefix selected in form of green and red LEDs.

- the iso-contour map showing critical frequencies (F2, E, etc), MUF and LUF.

In some applications these data and many other parameters (SNR, reliability, Takeoff angle, BUF, FOT, etc) are displayed in a much less readable form, using line or bar charts, in two or three dimensions, or even text reports for printing purposes. Up to you to appreciate or not one of another display. A table can be useful for a publication whereas a map or a chart is easier to read on screen.

When results are displayed in propagation charts or maps, remain to analyze and properly interpret what we see on screen. For example, you should be able to answer with accuracy to the next questions :  What is the best band to work at a specified time ? How will be the propagation conditions some hours later to reach such a country or continent ? What is the impact of the gray line over such a country ? How long will last this opening or this fading ? You should also be able to link figures with what we hear on the air and thus be able to appreciate for example what represents at the audio an SNR of 80 dB or a S/I of 20 dB, to appreciate what represents -103 dBW or 50 μV on an S-meter, how to manage a low takeoff angle when your antenna radiates best much higher in elevation, etc. This part is probably the hardest task for a beginner who is not used to work with a propagation program and has to learn by himself or herself what represents such a figure or a signal strength displayed on screen to what he or she hear on the air.

This expertise acquires first of all with a serious knowledge of the product, its functionalities and limitations of all parameters, how they interfere each others, then after a long field experience, comparing your forecasts to what your experiment on bands.

At left the table of signal power at receiver (SDBW or dBW). At right the "DB > μV " scale that displays the signal strength greater than 1 mV into 50 ohms at 30 MHz. For example +32 dB > μV is S9 or 50 μV or equivalent to -103 dBW.

Day-to-day variability and forecast validity

First thing to know, by definition a forecast is not valid for real-time "predictions", at best at short-terms (few hours or better for the next day).

The validity of a short-term prediction (but longer too are affected in a lesser extend) depends on daily variables. Any propagation program will have difficulties to provide near-real-time forecasts. Like in the atmosphere or into near-space, the status of the "ionospheric weather" changes constantly. Three variables prevents a model to be very accurate at term shorter than one day :

- The solar radiation intensity : the intensity of the 10.7 cm solar flux fluctuates because of the 11-year solar cycle, the solar rotation that carries with it all surface and coronal structures, seasonal effects (equinoxes), X-ray flares and other CME (that belong to surface details as well);

- The solar wind : particle emission affects the geomagnetic field, creating storms and particle precipitation to the ground and disturbs plasmas (convection);

- The low atmosphere : tides, medium frequency gravity waves (AGWs), energy of thundertorms (lightnings) and other mode of coupling from the low atmosphere affect propagation on the top band and probably, for some effects at least, other bands.

Functions or algorithms used in a ionospheric model are often unable to process these small variations that depend on one or more parameters voluntarily excluded from the model for various reasons (not modelised yet, slow down of calculations, too low effect in common working conditions, etc). However, some "tricks" can be used to simulate a too complex function like using look-up tables of souding data, using an polynom interpolation of high dimension, interfacing the model with add-ons, etc. Unfortunately, these solutions are not often used.

So, do never forget that a short-term forecast will be always less accurate than a prediction requested for the next day or the next week. However the accuracy of a short-term prediction can match its specifications (thus be reliable) if you work well inside the parameter limitations.

All these effects are often unknown or "forgotten" from the end-user when they are simply not ignored by the program. But their will come to you attention as long as he doesn't read the manual or request more information to the publisher when, suddently, for one or more forecasts, results do no more match his or her expectations (e.g. compared with signal reports during a QSO). These undesired effects can generate some big errors and misleading interpretations if you are not aware of this problem (and of course of  the correct interpretation of the meaning of all parameters and curves as well).

Propagation effects

At least three effects must be checked when analyzing a forecast, preferably using either many circuits (e.g. using a VOACAP engine) or a dynamic map to appreciate their evolution in time :

- Sun progression : Your forecast is valid either for 24 hours or for a specified time, accurate to the minute or in the worst case to the hour. But are you sure that the propagation conditions will not be better tomorrow ? The time and date you selected represent a very important factor affecting the remote station coverage. If you program is able to animate the forecast or permit you simpler to change the date and time without resetting all the prediction, display always one or more additional days to appreciate the effects of the days' passage on the propagation. You could be astonished in discovering that the DX station unreachable today is included in "the light" tomorrow or another day. This method is also the best way to learn how "work" the propagation.

- Frequencies : A forecast is usually valid for a range of frequencies with optionally a zoom function able to jump to a larger scale or on a specific band without resetting all the calculation and display. Usually you will note remarkable differences in coverage to various DX stations, even on adjacent bands.

- Solar flux and sunspots : The average solar flux index (SFI) is correlated with the smoothed sunspot number (SSN) over 97%. Both value are thus almost equivalent. Therefore some applications use exclusively the SSN, others the FSI or equally one or another parameter. Most if not all programs use statistical functions and thus the median values; they request the SFI or the SSN index and no other "sun-related" index. To prevent errors in calculations, do never use the Relative sunspot index (RI), the recent solar index (smoothed), the predicted index (SNP) or any other Boulder index to name a few available online. Only the smoothed values got online or offline from stored tables, calculated over time periods of about a year or more can provide results that match the program specifications. The others will generate unattended fluctuations in predictions.

Note however that some small programs do not extend data stored in their table over one solar cycle and you have either to enter manually new data, to wait for an update or a fix if you want to examine forecasts during another solar cycle than the current one.

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Forecasts reliability

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