By Manfred Dworschak
The Reading supercomputer can predict a season's weather months in advance.
The measure of variance, though, is also always known. The farther apart the 41 models are, the less reliable the average becomes. "That's the real breakthrough," says Hagedorn. What it does is enable the researchers to determine, rather accurately, just how inaccurate the forecast is.
For companies, this information can actually be very useful. For example, for the operator of a wind farm, it is really advantageous to know that one-fifth of the models are predicting such powerful storms that he will have to shut down his wind turbines. As soon as the residual risk is quantifiable, he can include it in his calculations.
However, sometimes the uncertainty is so great that guessing becomes just as effective. If the models happen to be correct sometimes, this is because of the skillful pre-selection of data. The computer pays little attention to the temperamental atmosphere, which -- as we all know -- changes its mind on a daily basis. Instead, it makes its calculations using mostly variables that only change slowly, such as the global dispersal of snow and ice, soil moisture and ocean temperatures.
The oceans, in particular, have a lasting effect on complex weather patterns. As a temperature sink, they essentially act as the long-term memory of weather patterns. As a rule, a high pressure system in the atmosphere disappears after a few days, almost as if it had never existed. But excessive warming of the western Pacific Ocean is something that the weather doesn't forget for months.
The researchers in Reading have just discovered that additional factors should be taken into account, such as the carbon cycle and the greenhouse gas effect associated with it or the distribution of suspended particles in the atmosphere that filter sunlight. Until now, these processes have only been simulated in climate models that compute the course of several centuries. But, as scientists are learning, they also play a role in shaping the current weather. "That's why we are trying to incorporate them into the forecasts," says Hagedorn. "Besides, climate and weather models are becoming more and more alike."
Fine-Tuning the Forecast
The ECMWF could also have used a more fine-tuned climate simulation to develop its seasonal forecasts. "But weather models happen to be our great strength," says Hagedorn. In fact, the center in Reading is the leader in the exclusive world league of major weather forecasting centers. In global performance comparisons, the European model usually comes out on top.
Nevertheless, the supercomputer in Reading also has its limits. The weather model used to develop the daily short-term weather forecast divides the atmosphere into a grid network consisting of individual cells 25 kilometers (15.5 miles) wide. But to perform the half-year forecast, the grid had to be modified to make the cells 125 kilometers (77.7 miles) wide, so that the computer can handle 41 models simultaneously. However, this is still more precise than climate simulation, which often operates using cells 200 kilometers (124.3 miles) wide. But satisfactory it is not.
"A finer resolution would improve the results significantly," says Hagedorn. She adds that she would also like to feed more observation data into the computer and run more models simultaneously. "In theory," says Hagedorn, "a few thousand would also be possible. That could only improve the forecast."
Given this need for expansion, it makes sense that the next supercomputer has already been ordered. It is planned to go into operation near the end of the year. Just as its predecessor was when it went into service, the giant machine will likely be one of the world's fastest computers.
Translated from the German by Christopher Sultan
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