For a long time mankind tried to predict or even control the weather. In former times dances and music were intended to change the weather; more or less successful. More recently, during the Olympic Games 2008 in Beijing, the Chinese government prevented rainy games by injecting silver iodide pellets into clouds before they reached the city. These particles acted as freezing nuclei, allowing the air, oversaturated with water, to form ice droplets. When gained enough weight, these ice crystals fell to the ground as rain.
However, it is not necessary to change the weather. Most people would be satisfied, if there was an accurate forecast. But is this even possible? Why are weather forecasts nowadays just available for a few days and not months in advance? First of all, meteorology is an empirical science, since laboratory conditions cannot be produced in atmospheric magnitude for continuous experiments. It consists of lots of variables, e.g. air temperature, humidity, air pressure etc. Because of that, it is very hard to find reliable “laws” to predict future atmospheric actions based on gained data at a certain time. Just to give an example, it is still impossible to predict the exact locations and amounts of precipitation, even though wind currents or route of clouds, respectively, can be calculated from the position of high and low pressure areas. That is, because actions within clouds are very complex and hard to investigate, since nobody deliberately flies into a thunderstorm to gather data.
Our current forecasts are based on numerical or synoptical meteorology, e.g. calculation of atmospheric processes with supercomputers. The great boost of processing power in the last few decades made forecasts more reliable, but still short-term forecasts (24 hours) have only a reliability of about 91%. For the usually presented three day forecast, the accuracy decreases to 70%. That has two reasons: Firstly, the aperture of the calculations, meaning the lateral length of the grid in which the area is subdivided. The smaller the grid, the more complex are the calculations. Naturally it does not make sense to perform very exact calculations, if the computation finishes after the date it predicts. Secondly, the complexity of the different parameters. This problem is also known as “Butterfly effect”, which means that even small, local turbulences can have an immense effect on large-scale atmospheric processes. Since the meteorological data used for those calculations is only gathered two or three times a day, theses small turbulences are not taken into account.
In conclusion it is safe to say that the accuracy of weather forecasts will increase with rising processing power. However, the uncertainties inherent in numerically solving meteorological equations will keep inaccuracies. So, do not forget to bring an umbrella.
http://www.guardian.co.uk/world/2007/may/12/china.jonathanwatts (last access 27.09.2012)
Ahrens, C. D.; Jackson, P. L.; Jackson, C.: Meteorology Today: An Introduction to Weather, Climate, and the Environment, Nelson College Indigenous, 1 edition (July 1 2011).
Walch, D.; Frater, H.: Wetter und Klima. Das Spiel der Elemente – Atmosph?rische Prozesse verstehen und deuten, Springer Berlin Heidelberg; Auflage: 1 (15. Oktober 2003).