Innovating winter road management with Big Data
As a weather authority, we need to keep innovating to provide our customers with the best and most specific weather forecasts possible. We want those specific forecasts to offer added value, now and in the future. This certainly applies to the forecasting of slippery road conditions. At the biennial meeting of the ‘Standing International Road Weather Commission’ (SIRWEC) at the end of May, more than 150 professionals shared their knowledge, expertise, and innovations in the field of road surface forecasting. Our Professional Services and Product Marketing departments were present to show how Big Data can be used to forecast slippery road conditions.
For years, MeteoGroup has been issuing specific forecasts to road managers in various countries. The most important aspects of these forecasts is to get the information to the customer at the right time to enable them to take whatever measures they can to prevent roads from becoming slippery. While safety is of course the top priority, it is also important to avoid salting roads unnecessarily. Not only does this save money, but it also reduces the impact on the environment. To forecast conditions effectively, one must have knowledge of how different weather factors and roads interact, as it were. Temperature, dew point, wind, condensation, snow squalls, sleet - all of these meteorological factors play a role. In the continuous effort to keep improving road condition forecasts, the Professional Services department presented the SIRWEC conference with its research into deploying a large number private weather stations. We speak to Ingeborg Smeding, the department's delivery manager, at her location in Wageningen.
Big Data helps, even if it includes faulty observations
“Quite a lot of people around the world keep a small weather station in their garden or on their balcony,” Ingeborg begins. “A significant number of these are connected to the NETATMO online platform. Often, those measuring points are not located in the best place and the observations contain errors, but you can still use the measurements they provide. Reviewing a large volume of observations allows you to eliminate the errors.”
As it turns out, even the errors themselves are useful. “Rain gauges stop transmitting information if the precipitation turns into snow or hail. The radar image, however, continues to display precipitation. If you compare the information from the private measuring stations to the radar image, you will be able to locate the moving line at which the rain turns into solid precipitation. The location of that line is, of course, crucially important information for meteorologists predicting slippery road conditions, as well as for road managers. So, while the rain gauge ceasing to function may technically be an error, you can use that error to identify the crucial boundary between wet snow and dry snow.”
A second example is the longwave radiation we start observing when the skies clear at night. Most unofficial weather stations are not housed in ventilated weather instrument shelters, which makes them more sensitive to changes in longwave radiation. Those changes indicate breaks in cloud cover and can be very helpful in forecasting slippery road conditions. After all, the temperature of the road surface can drop fairly quickly when exposed to that radiation.
Importance of innovation
There are many experiments underway that are intended to improve forecasting when it comes to slippery road conditions. MeteoGroup, for example, has been working for quite some time on developing a decision support system, or DSS. Ingeborg: “The first priority is making sure that the forecasting office provides sound information to those working to eliminate slippery road conditions. These workers themselves ultimately decide whether and when to salt or plough the roads, and the extent to which this will be done. You can help them with this, of course, by giving them some advice. The DSS takes this one step further than the traditional road surface temperature and conditions forecast by providing customised salting advice, including information on, for example, how much salt will have to be used. This makes it very specific.”
As a company, it is very important to keep working on such innovative developments. “A lot of attention is being devoted to this worldwide,” says Ingeborg. “The computing power of computers has grown exponentially, everything is more accurate now and you of course want to maintain your added value. That was why the conference was such a great opportunity to look around at things, like the cameras and sensors available nowadays. One particularly interesting company installed friction-measuring sensors in car tyres. The taxis travelling around Stockholm and Goteborg are helping them collect up-to-date data on road conditions, and that data can be used to accurately forecast slippery road conditions.” Innovation and experimentation; they go hand in hand and help us make advancements in providing reliable and useful forecasts.
See for yourself how MeteoGroup can help Winter Road Managers to secure their roads and be more efficient and effective.
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Our Decision Support System, using Big Data, takes this one step further than the traditional road surface temperature and conditions forecast by providing customised salting advice, including information on, for example, how much salt will have to be used. This makes it very specific.