Scientific research reveals the invisible battle between atmospheric conditions and wireless communication
Have you ever noticed your mobile phone's signal strength fluctuating dramatically during a heavy tropical downpour? It's not just your imagination. Behind the scenes, invisible atmospheric forces are constantly reshaping how radio waves travel. Research presented at the International Fundamentum Science Symposium 2018 (IFunSS) in Malaysia provided fascinating insights into this very phenomenon, revealing the hidden battle between weather and wireless communication 1 .
At its core, the challenge is one of interference. The ultra-high frequency (UHF) radio bands used for everything from mobile data to television broadcasting are particularly vulnerable to environmental factors 1 . In tropical regions, this is exacerbated by consistently high humidity, temperatures, and wind.
The research team from Universiti Malaysia Terengganu set out to quantify precisely how these tropical weather conditions affect the UHF signals that modern life depends upon. They focused on measuring the Received Power Level (RPL), a direct indicator of signal strength, and correlated it with live weather data 1 . Their work helps telecommunication providers, broadcasters, and satellite services build more resilient networks by finally putting hard numbers on a problem everyone has experienced but few understand.
Moisture in the air absorbs and scatters radio waves
Heat affects air density and signal propagation
Air movement causes signal fluctuations and scattering
To unravel the mystery, researchers designed a meticulous experiment, collecting data around the clock during rainy days to capture weather at its most disruptive.
The experiment was built on a foundation of simultaneous measurement 1 .
A spectrum analyser (Keysight N9915A) was used to continuously monitor the Received Power Level (RPL) of UHF signals at two frequencies: 1800 MHz and 2160 MHz, which are common for modern communications 1 .
A nearby weather station (Vantage Pro 2) logged three key atmospheric predictors: humidity, temperature, and wind speed 1 .
The collected data was then analyzed using SmartPLS 3.2.6, a statistical software that can identify the strongest relationships and predictors within a complex dataset 1 .
The analysis yielded clear, significant relationships. The statistical model showed that changes in weather conditions accounted for 31.4% of the variation in signal strength at 1800 MHz and 25.4% at 2160 MHz 1 . This is a substantial impact, confirming that weather is a major force in signal reliability.
Furthermore, all three weather factors—humidity, temperature, and wind—were found to have an anticorrelation with signal strength. This means that as these values increase, the received power level decreases, leading to a poorer signal 1 . Most strikingly, the research identified humidity as the single strongest predictor, with a statistical path coefficient of β = -0.449 1 . The more moisture in the air, the more the radio signal is weakened.
| Weather Predictor | Path Coefficient (β) | Interpretation |
|---|---|---|
| Humidity | -0.449 | Strongest negative influence |
| Temperature | Data not specified | Significant anticorrelation |
| Wind | Data not specified | Significant anticorrelation |
Source: Adapted from 1
| Frequency | R² (Coefficient of Determination) | Interpretation |
|---|---|---|
| 1800 MHz | 0.314 | Weather changes explain 31.4% of signal variation |
| 2160 MHz | 0.254 | Weather changes explain 25.4% of signal variation |
Source: Adapted from 1
Interactive chart visualization would appear here
Showing the anticorrelation between humidity, temperature, wind and signal strength
Conducting this type of cutting-edge research requires a suite of specialized tools. The following table details the key components used by the scientists to measure and analyze the interaction between tropical weather and radio waves.
| Tool Name | Category | Primary Function |
|---|---|---|
| Spectrum Analyser (Keysight N9915A) | Signal Measurement | Measures the power level (RPL) of specific radio frequencies to precisely quantify signal strength 1 . |
| Weather Station (Vantage Pro 2) | Environmental Monitoring | Logs real-time meteorological data, including humidity, temperature, and wind speed 1 . |
| SmartPLS 3.2.6 Software | Statistical Analysis | Uses advanced partial least squares modeling to determine the strength and significance of relationships between weather data and signal data 1 . |
The investigation into tropical weather effects on radio signals was just one of many groundbreaking studies presented at the International Fundamentum Science Symposium 2018. Held from June 25-26 at the Primula Beach Hotel in Kuala Terengganu, the event was a vibrant hub of interdisciplinary science, featuring 50 presentations across physics, chemistry, and biology 4 .
Scientists explored how stevioside, a compound from the stevia plant, can significantly inhibit the process where fibroblasts turn into fat-storing adipocytes, offering a potential new avenue for treatment 2 .
Researchers synthesized and characterized new Schiff base compounds, which show promise as highly sensitive and selective linkers in future electrochemical DNA sensors 3 .
Studies were presented on developing a polyvinyl alcohol/halloysite nanotubes hydrogel to better control the release mechanism of pharmaceuticals within the body 7 .
The symposium highlighted how cross-disciplinary research can lead to innovative solutions for complex scientific challenges across physics, chemistry, and biology.
The next time your video call freezes during a tropical rainstorm, you'll know the reason why. The research unveiled at the International Fundamentum Science Symposium 2018 demystifies this everyday occurrence, revealing a clear, measurable link between atmospheric humidity and the UHF signals that connect us. These findings provide a critical scientific foundation to help engineers design more robust communication systems capable of withstanding the challenges of our climate. As our world becomes increasingly wireless, understanding these invisible interactions is key to building a more reliably connected future.