针对WRF模式中行星边界层参数化过程倾向项的扰动方法

针对WRF模式中行星边界层参数化过程中的不确定性,发展了一种针对行星边界层参数化过程的随机物理扰动方案(SPPBLPT),该方案针对行星边界层计算的温度、风场、水汽倾向项进行扰动.使用该方案、多行星边界层参数化方案、多参数扰动方案及针对WRF模式总倾向的随机物理过程扰动(SPPT)方案对2014年7月进行对比实验,发现...

Stochastic perturbation on planetary boundary layer parameterization tendencies in the WRF model

In this study,targeted at the uncertainty in the parameterization process of the planetary boundary layer in the WRF model,a Stochastic Perturbation on Planetary Boundary Layer Parameterization Tendency scheme (SPPBLPT) was developed.This scheme perturbs the temperature,wind and water vapor tendencies.A comparative experiment was conducted in July 2014 using the SPPBLPT scheme,multi-planet boundary layer parameterization scheme,multi-parameter perturbation scheme,and Stochastic Physical Process Perturbation (SPPT) scheme.It was observed that the SPPBLPT scheme with a large grid-point variance can effectively reduce the error of 2 m temperature and wind field,and it can also reduce precipitation error,while other schemes do not improve the forecast significantly.The BS scores for the 2 m temperature and wind field show that the SPPBLPT scheme significantly improves the possibility of ensemble forecasting for temperature and wind field,by reducing the reliability score,thereby increasing performance.At the same time,the scheme can significantly improve the GSS score of the precipitation.In all experiments,the SPPBLPT scheme with the larger grid-point variance had a superior performance.Although the SPPBLPT scheme reduced the FSS score,the reduction was not significant.It is thus shown that the SPPBLPT scheme can significantly improve the performance of ensemble forecasting systems,yet the setting of perturbation parameters for this scheme requires further investigation.