Predicting future climate has become one of the hottest topics in the last decade. Scientists are eagerly developing more advanced models and using the latest information technology in order to improve the accuracy of their methods.
A study published in the latest issue of the journal Physical Review Letters, reveals how the so-called direct statistical simulation can successfully model fluid jets and flow movement in the atmosphere and in the oceans. The work will also be presented at a meeting of the American Physical Society in Baltimore later this month.
Brad Marston, a professor of physics at Brown University, who is part of the team that conducted the research, states that the findings are essential addition to current knowledge. By introducing basic physics to powerful models, climate science is getting one step closer to achieving the ever-so wanted results.
Currently existing methods of simulation are too complicated and difficult to apply. For instance, techniques such as direct numerical simulation, require long time and powerful technology in order to include all variables and cover long periods of time.
This was one of the main reasons for the team to look into direct statistical simulation. According to Martston, the biggest advantage of the method is that it does not require lengthy time integrations.
The technique takes into account the essential forces that drive climate. This eliminates the need to simulate the weather at every given moment in the past and delivers results on the overall picture.
The concepts behind this type of simulation have been known for more than 50 years, however the tools needed to apply it in climate science are still not fully developed. The main aim of the study conducted jointly by Marston and Steve Tobias, a mathematician from Leeds University, was to assess the possibility of using direct statistical simulation in describing fluid jets and flow movement for weather predictions.
The team conducted a series of simulations of fluid movements using both conventional techniques and statistical simulation.They established that the results were almost identical, although the more data was fed into the statistical model, the more easily the model broke down.
The team however is convinced that despite of the limitations, the technique has great potential. The method is already being integrated into a bigger study by Marston, where the method can be easily applied through a computer program called “GCM.”
The aim is to get citizens involved in climate modelling through their mobile devices.
