Published: 2010-01-05 16:16:00
Updated: 2010-01-05 16:27:18
Posted January 5, 2010 4:16 p.m. EST
Updated January 5, 2010 4:27 p.m. EST
By Nate Johnson
It's certainly been cold around here lately, but in some parts of the country, cold weather like what we've been enduring is a way of life for much of the winter. The cold air has certainly been an inconvenience for us and has been, at times, even dangerous. Taken for weeks at a time, though, it can be lethal, especially for some livestock.
That's why a number of National Weather Service offices in the northern Rockies will begin issuing advisories when the weather is forecast to be too cold for newborn calves. Some estimates suggest upwards of 100,000 calves die of cold stress each year. For the ranchers who depend on raising those cattle and selling them at auction, that's potentially millions of dollars lost every year.
This will be the second year for the Cold Advisory for Newborn Livestock (CANL) system, which is focused on the specific weather conditions that are potentially lethal to newborn calves. Specifically, the CANL system takes into account the forecasts for temperature, wind, rain or wet snow, and cloud cover. If certain combinations of conditions are met, an advisory is issued, allowing ranchers to take steps to protect their livestock.
"This system allows us to provide ranchers in Northeast Montana with enough lead time to bring livestock to shelter and mitigate loss due to weather,” said Tanja Fransen, Warning Coordination Meteorologist with National Weather Service's Glasgow, MT, office. The Glasgow office was the original testbed for the CANL system, with other offices in Montana, North Dakota, and South Dakota getting on board this year.
The CANL system was developed in cooperation between the National Weather Service, the University of Miami, and local ranchers in Montana. It is a great example of complex weather forecasts being tailored to the specific needs of people (and critters!) who rely on the weather. I suspect the spokes-cattle for a certain fast food chain would approve.
Can you think of other instances where a specific forecast would be helpful?