predict the weather with the robot

Weather forecasters may not have the best reputation for accuracy, but with the technology available today, perhaps to make pretty reliable weather predictions up to 48 hours. Researchers at MIT, however, believe that autonomous aircraft running smart storm-chasing algorithms could figure up to four days. Better weather forecasting could help farmers and transportation authorities with planning and even save lives by giving advance warning of storms and bad weather, says Jonathan How, chief researcher at MIT's Department of Aeronautics and Astronautics.

Long-term prediction is not necessarily wrong because the forecasting model, but rather because the initial conditions are not accurately measured, said Ralph Martin, a researcher at the National Oceanic and mereorologi atmosefer Administration Earth laboratoriuun system, in Boulder, CO as inaccuracies come from gaps in the data, he said.

Ground-based sensors have been used to record temperature, wind speed, humidity, air density, and rainfall, but they only measure conditions on the ground, says How. At sea, where a lot of bad weather comes. Satellite observations help to build up a picture, but the satellites are blind to some kind of useful data, such as wind speed and atmospheric boundary conditions, said Ralph.

To get the most accurate forecasting, you really want to get the sensor to the weather itself, but how? In theory, weather balloons can do this, but only if they happen to be in the right place at the right time. So weather services currently attempt to track weather systems using piloted planes that fly prescribed routes, taking measurements along the way. The logistics of deploying the planes are so complicated, however, that it is difficult to change their routes in response to changing weather conditions.

Consequently, says How, there has been much interest in using unmanned aerial vehicles, or UAVs, instead. The idea is that there will be a constant number of UAVs in the air, continue to work together to position themselves in what collectively will be the most useful sites.

The problem, says How, is that calculating the location of the most useful is a very complex task. Analyzing involves more than one million data states from hundreds of thousands of sensor locations, and uses this data to predict weather conditions six to eight hours from now. But that's the challenge that dealt with the MIT researchers.