Use of Genetic Algorithms in Numerical Weather Prediction

This paper investigates the use of genetic algorithms in conjunction with the WRF - Weather Research and Forecast numerical weather prediction system in order to optimize the physical parametrization configuration and to improve the forecast of two important atmospheric parameters: 2 meter temperature and relative humidity. Our research showed good results in improving the average prediction error in limited amount of iterations and this could prove helpful in building GA optimized ensemble forecasts, especially when focusing on specific atmospheric parameters. The optimization process performed well in finding optimal physical configurations for humidity prediction, but showed poor results for temperature forecast, more experiments need to be conducted in order to have a clear view over the utility of using GA techniques for physical parametrization optimization.