At 6:15 p.m. on Friday, the National Weather Service released an updated forecast predicting snow showers in Butler, Clarion, Jefferson, Armstrong, and Indiana counties through 7:15 p.m.
Snow showers were seen at 6:13 p.m. along a line that ran from close to Sarver to close to Rimersburg. At 30 mph, the movement was east. The meteorological service warns that these snow showers might include winds of more than 30 mph.
The following locations are affected by the alert: Rural Valley, Worthington, Big Run, Dayton, West Hills, Rossiter, Hawthorn, Marion Center, Manorville, Sykesville, Falls Creek, East Brady, Ford City, Reynoldsville, New Bethlehem, West Kittanning, Saxonburg, and Punxsutawney. Reduced visibility and dangerous driving conditions are caused by snow, and slippery roads may form as the snow melts and then rapidly refreezes.
Navigating rainy roads: Safety tips for wet weather
Roads can become dangerous when it rains. Keep yourself updated and heed these weather service recommendations to stay safe during periods of intense precipitation:
Watch out for swift water flow:
Keep your distances from other vehicles safe:
Reduce your speed and drive carefully:
Pick your lane carefully:
Visibility is important.
Be cautious on slick roads:
Stay a safe distance away from big cars:
Be mindful of your wipers:
Visibility may be hampered by overloaded wiper blades. If the rain significantly impairs your vision, stop and wait for the weather to clear up. Seek cover in safe spaces or rest zones. Place your car as far off the road as you can when stopping by the side of the road, preferably beyond guardrails. To warn other drivers, turn on your emergency flashers and keep your headlights on.
You may greatly lower dangers and protect your health when it rains a lot by adhering to these safety precautions. To ensure a safe and sound voyage, keep yourself updated on weather conditions and follow local authorities’ instructions.
United Robots offers a service called Advance Local Weather Alerts that gathers the most recent information from the National Weather Service using machine learning.
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