Can you trust your road weather forecast?

In the world of weather forecasting, accuracy is everything. The same is true of road weather forecasting in the world of winter road maintenance. But how do you know whether your road weather forecasts are as accurate as possible? The answer lies in the quality of road weather observations and the road weather modeling process itself. Vaisala’s instruments and intelligence combine the best of both. Here’s a closer look at the roles of accurate observations and forecasting.

Part one: The power of accurate observations

Road weather observations play a crucial role in road weather forecasting. They provide the raw data used to predict future weather conditions across a road network. The more accurate these observations are, the more accurate the forecast will be.

It all starts with RWIS

Many winter road maintenance agencies have relied on Road Weather Information System (RWIS) networks based on Vaisala RWS200 for decades. These road weather stations provide unparalleled accurate and reliable road weather data over the widest range. However, across a wide road network there will be blind spots, which impact the road weather forecast accuracy.

Fortunately, today there are mobile and IoT sensors with reference grade performance that can easily fill in these blind spots.

Vaisala mobile detector MD30 monitors road conditions and transmits weather data from snow plows or any vehicle type without disruption.

Wireless, battery-powered Vaisala Cast Sensors with built-in IoT connectivity can be installed virtually anywhere on your road network to fill in the gaps.

Proven IoT sensor accuracy

Vaisala recently published a paper titled "The impact of embedded IoT sensor road observations on road weather forecasts" which discussed how Vaisala IoT sensors can enhance road weather forecasts by providing in-situ measurements. These measurements help in making more accurate predictions for efficient winter road maintenance.

The quantitative assessment showed that Vaisala’s GroundCast IoT sensor observations significantly improve the accuracy of road weather forecasts, particularly for road surface temperature and grip conditions. Here are the key results:

1. Comparable Accuracy: Vaisala IoT sensor observations lead to similar reductions in forecast errors for road surface temperature as professional-grade Vaisala RWIS stations.
2. Grip Forecast Improvement: While less detailed than RWIS observations, IoT sensor data still significantly improves grip forecasts, which is crucial for winter road maintenance decision-making.

Read the whole study.

With reference-level accuracy in a wireless, easy-to-install package, Vaisala Cast Sensors offer a convenient way to fill coverage gaps and enhance your network-wide awareness.

Part two: Unmatched forecasting accuracy and visualization

Wx Horizon, part of our Xweather family of subscription based products, leverages our advanced modeling and algorithms to predict how environmental conditions and other factors will impact the road — a major advantage that you can use to make better decisions.

Wx Horizon combines data from your local sensors with 70+ other data sources to power advanced Machine Learning based Weather Prediction (MLWP). The road weather forecasts are constantly updated using the latest sensor data from your network, meaning you will always have the most up to date accurate forecast information. This unparalleled diversity of proprietary data sources, paired with our MLWP capabilities, is what sets Wx Horizon apart from any other road weather modeling in the industry.

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The future of winter road maintenance is here

By combining advanced forecasting with comprehensive observation data from road weather stations, IoT sensors and mobile sensors, Wx Horizon empowers you to make data-driven decisions that keep your roads safe during winter weather events.