Space weather

Space weather and a reference network of non-ionizing radiation detectors across Eurasia.

Xray/Non-ionizing radiation level

(NOAA GOES-17 satellite, xrsb1), and Global Earth Non-ionizing Radiation Power Index (Sensonica sensor net).

As of now, Sensonica has deployed a reference network of non-ionizing radiation detectors across Eurasia. The detectors perceive both local phenomena (with the range limited to one or more detectors) and global phenomena, registered by all sensors of the network. The local phenomena include narrow beams of cosmic radiation falling within the sensitivity range of one or more detectors, as well as events of terrestrial nature, including natural geophysical processes and, possibly, some man-made interference. The global phenomena, with a high degree of probability, include cosmic ray fluxes affecting the entire Earth.

To detect such fluxes, the network data is subjected to correlation processing, which extracts only flashes of radiation detected simultaneously by all sensors in the network. The distribution of such flashes in time (real time) is presented on the chart. For comparison, the same chart shows live data on the level of long-wave X-ray radiation of the Sun (solar flares) according to the GOES-17 satellite. Satellite data obtained from

As it appears to us from the type of charts, the data of the reference network and the level of X-ray radiation of the Sun are related. This dependence has a complex, variable nature, but is clearly traceable. We do not yet know whether solar flares cause streams of non-ionizing radiation, or whether non-ionizing radiation from the depths of space provokes solar flares. However, we hope that, in time, we will be able to figure it out. For the time being, we can say that the data of the reference network allows us to quite successfully detect solar flares and predict magnetic storms (lagging behind the flares by 18-72 hours) without the use of satellite data. Moreover, we are now carefully suggesting that the reference network data may be more suitable for predicting magnetic storms on Earth. And we are currently working on a prediction model here.