With the passage of Hurricane Irene, what's next? Right now, America's biggest threat is Tropical Storm Katia, which is predicted to become Hurricane Katia later this week. Whether or not it poses any threat to the US is completely up in the air as Katia may harmlessly pass the Eastern seaboard. Forecasters, especially in the early stages of a tropical storm, cannot predict its long term path due to changing weather patterns over the Atlantic. Even as Katia gets closer to the US, the storm's predicted path is never 100% certain.
You're already familiar with the "cones" that you see on news reports, which feature the storm with a bent cone coming out of it. The area within that cone is all fair game for a direct hit from that storm, with the farthest and thickest part of the cone being the area of greatest uncertainty. This "cone of probability" is the closest meteorologists can get to predicting hurricanes, which is accurate 60 to 70 percent of the time. Those who are familiar with seeing these cones may have noticed that, for the latest Hurricane Irene, the cone was significantly narrower than in years past. This is a testament to the work that researchers have done over the years to try to improve hurricane path forecasts.
Although the predicted path of a hurricane is never 100% accurate, especially with long term predictions, an incredible amount of technology goes in to making forecasts for both a hurricane's path, and intensity, which is harder to predict. Complex equations, billions of calculations and many different kinds of simulated models run on extremely fast computers, which gather data from airplanes, ships, and satellites. More specifically:
Airplanes and balloons flying inside or around the storm measure things such as humidity, wind direction, wind speed, temperature, and atmospheric pressure. Despite all of these measurements, they are sometimes not enough to predict its intensity, which is much harder to forecast that future location, as witnessed by Hurricane Irene. Even though scientists use a variety of tools to insert into the hurricane, including dropped parachutes and hovering airplanes, they are still far from the heart of the storm, which is hard to measure due to its vitality. Despite technologies limitations, scientists have been at work in developing systems, and gathering data, that can predict hurricane paths and intensity with increasing accuracy…
The hurricane imaging radiometer (Hurricane Imaging Radiometer), a recent development by scientists and engineers at NASA, gathers wind speed data, deep within the storm, by measuring activity on the ocean surface. Such measurements can be used to determine how intense a hurricane will be.
Super computers can now model the birth of hurricanes that have already happened. As such, these computers can predict what will happen to future hurricanes, whose activity is similar to ones that have already been modeled.
Late last year, researchers at the National Autonomous University of Mexico (UNAM) found out that hurricanes that develop in certain parts of the Atlantic Ocean have a pattern of forming hurricanes of the same intensity, depending on where they formed. This model can be used to predict the intensity of future hurricanes.
The Global Hawk, an unmanned aerial vehicle developed by NASA last year, is able to fly around hurricanes for as long as 20 hours at a time without refueling. The amount of time it spends in hurricane territory and the plethora of instruments, on board, allow it to bring back valuable data.
Although advances in hurricane prediction technology have been slow, especially in terms of predicting intensity (as witnessed by Hurricane Irene last week), scientists are making significant progress with recent technology. Despite the challenges, today's 48 hour landfall predictions are as good as the 24 hour predictions that existed in the 90's. Whether Tropical Storm Katia poses a threat to the US is unclear. What is clear, however, is that advances in hurricane technology have made it less of a question mark than it would have been in years past.
