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HF Ray Tracing

Why HF traces matter

High-frequency (HF) radio waves launched into the ionosphere do not travel in straight lines. The electron-density gradients of the D, E, and F layers continuously refract the wave path, eventually bending it back toward Earth — a process called ionospheric reflection. The virtual height recorded on an ionogram is the apparent (straight-line) travel time converted to distance; the true reflection height, the actual ray path, and the group range all differ because the wave slows and curves as it propagates.

Understanding where a ray actually travels is critical for several reasons:

  • Ionogram inversion: Converting a virtual-height trace to a true electron density profile (the "true-height" problem) requires knowing the full ray geometry, not just the echo delay.
  • HF communication path planning: Predicting skip distance, maximum usable frequency (MUF), and multi-hop propagation demands accurate ray trajectories through a realistic ionospheric model.
  • Space weather impact assessment: Sudden ionospheric disturbances (SIDs), travelling ionospheric disturbances (TIDs), and eclipse-driven depletions all modify ray paths in ways that cannot be seen from the raw trace alone.
  • Validation of autoscalers: Comparing synthetic ionograms (forward-modelled from a density profile via ray tracing) against measured traces provides an objective quality metric for tools like AutoScale-ISCA.

From ionogram to ray path

Pynasonde extracts ionospheric parameters — critical frequencies, virtual heights, electron-density profiles — from raw instrument files. Once those parameters are in hand, the natural next step is to propagate rays through the reconstructed ionosphere to:

  1. Verify that the inverted profile reproduces the observed trace.
  2. Estimate ground-range footprints for oblique-incidence paths.
  3. Explore sensitivity of ray paths to uncertainty in the scaled parameters.

This forward-modelling step goes beyond what Pynasonde does internally. For that we recommend PyTrace.

PyTrace — HF ray-tracing companion

External tool

PyTrace is developed and maintained independently of Pynasonde. Full documentation, installation instructions, and examples are at:

https://pytrace.readthedocs.io/en/latest/

PyTrace is a Python library for numerical HF ray tracing through analytic and empirical ionospheric models. It solves the Haselgrove ray-tracing equations in 3-D, supports both ordinary and extraordinary propagation modes, and can ingest electron-density profiles derived from sources such as Pynasonde's SAO/NGI extractors.

Typical workflow linking Pynasonde → PyTrace

# 1. Extract an electron-density profile with Pynasonde
from pynasonde.digisonde.parsers.sao import SaoExtractor

extractor = SaoExtractor("path/to/file.SAO")
extractor.extract()
hp = extractor.get_height_profile()          # DataFrame: th, ed, pf, …

# 2. Hand the profile to PyTrace (see PyTrace docs for exact API)
#    https://pytrace.readthedocs.io/en/latest/
import pytrace  # installed separately: pip install pytrace

model = pytrace.ProfileModel.from_dataframe(
    hp, height_col="th", density_col="ed"
)
rays = pytrace.trace(
    model,
    frequency_mhz=5.0,
    elevation_deg=75.0,
    azimuth_deg=0.0,
)
rays.plot()

When to reach for PyTrace

Task Tool
Parse .SAO, .RSF, .RIQ, .NGI files Pynasonde
Extract critical frequencies, virtual heights, EDP Pynasonde
Forward ray-trace through a density profile PyTrace
Compute MUF, skip distance, multi-hop paths PyTrace
Validate scaled profiles against measured traces both, in combination

For questions about PyTrace itself — installation, ray-tracing equations, supported ionospheric models — please refer to the PyTrace documentation and its upstream issue tracker.