The National Weather Service reported Tuesday at 4:44 a.m. that Chemung, Chenango, Otsego, Tioga, Broome, Delaware, and Sullivan counties would have dense fog through 9 a.m.
Visibilities have occasionally been lowered to a quarter mile or less due to the localized, dense fog that has formed this morning. The weather service advises drivers to leave plenty of distance ahead of them and to factor in extra time to get to their destination.
Navigating fog: Safety tips by the weather service
The following safety precautions should be kept in mind if you must drive through fog:
Slow down:
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Slow down and allocate extra travel time to reach your destination safely.
Priority for visibility:
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Ensure your vehicle is visible to others by using low-beam headlights, which automatically activate your taillights. Utilize fog lights if your vehicle is equipped with them.
Steer clear of high beams:
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Refrain from using high-beam headlights, as they create glare that impairs your visibility on the road.
Stay away:
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Maintain a generous following distance to account for abrupt stops or shifting traffic patterns.
Remain in your lane:
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Use the road’s lane markings as a guide to remaining in the correct lane.
Visibility close to zero:
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In cases of near-zero visibility due to dense fog, initiate your hazard lights and locate a secure spot, such as a nearby business parking area, to pull over and come to a halt.
Absence of parking choices
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If no designated parking area is available, pull your vehicle as far off the road as possible. Once stationary, deactivate all lights except the hazard flashers, engage the emergency brake, and release the brake pedal to ensure your tail lights remain unlit, minimizing the chance of other drivers colliding with your stationary vehicle.
You can travel through foggy circumstances more safely by following these weather service precautions, which can lower the chance of accidents and protect your personal safety.
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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