With the 2013 hurricane season winding down toward what seems certain to be an unexpectedly quiet finish, this seems like a good enough time to share random thoughts and opinions.
After widespread predictions by the best hurricane forecasters in the government, education and private industry that this was going to be a very busy and potentially dangerous hurricane season, it might be well to remember just how complex the problem of predicting future storm activity is. Hurricane forecasters have made dramatic progress in forecasting where tropical cyclones will go and they are chipping away at the vexing problem of predicting intensity. However, predicting whether a season will be busy or not seems to amount to almost a scientific parlor game.
That is not to belittle the efforts of the scientists who are making those predictions, but in practical terms the average reader of this column problem would probably do well to read such predictions with a mixture of amusement and skepticism then go ahead and prepare for a worst-case scenario. As emergency managers are fond of saying "all it takes is one" to turn the hurricane season into a disaster for you.
The debate over global warming, what's causing it and whether it's happening at all is not anywhere near resolved. One of the problems that's confusing the issue in the minds of a lot of people, it seems to this writer, is forgetting that climate and weather are vastly different things. While they do overlap in some ways, they are represent very different scientific disciplines. While climate issues are sometimes measured in tens of thousands of years, weather is a day-to-day phenomenon that may or may not indicate some sort of climate change. An unusually warm winter day or an unusually early snowfall is just one bit of data in an incredibly complex matrix of information.
Hopefully the zeal for budget cutting in Congress will not delay the replacement of weather satellites. The crisis may not be upon us, but the day may not be far off where the loss of a satellite could leave a signficant drop in the data needed for the most accurate forecasts.