These models have become ever more complex as the science has advanced. These are needed because of the complexity of forecast models that approximate atmospheric processes. In February, the UK completed a £10m upgrade of its rainfall radar network, allowing it to deliver five times more data than before.Īll this data is fed into “petaflop” supercomputers capable of doing a thousand trillion calculations per second. Nasa’s GOES-16 satellite, declared operational in December, scans the Earth much more quickly and in greater resolution than previous satellites. The Met Office, for example, is integrating wind-speed data gathered from transponders carried by large aircraft for navigation purposes into its models. The number of weather observations has risen dramatically, along with their quality. Meteorologists' ability to predict atmospheric pressures three to 10 days ahead has improved at a rate of about one day per decade since 1981 No wonder huge sums have been invested in improving predictive capabilities. A 2011 study by the economist Jeffrey Lazo found that US GDP alone could vary by as much as $485bn (£366bn), depending on the weather. The impact of weather forecasting on human activities is hard to overstate. Forecast models consisting of sets of equations governing physical and chemical processes use this as a starting point to calculate future conditions. Gaps in the data are filled by extrapolating from available observations and past forecasts. Photograph: The foundation of modern weather forecasting involves gathering huge amounts of data on the state of the atmosphere and Earth’s surface, such as temperature, humidity and wind conditions. Nasa’s GOES-16 weather satellite scans more quickly and in greater resolution than previous devices.
0 kommentar(er)
