彭飞,李晓莉,陈静. 2020. GRAPES全球集合预报系统不同随机物理扰动方案影响分析. 气象学报,78(6):972-987. DOI: 10.11676/qxxb2020.074
引用本文: 彭飞,李晓莉,陈静. 2020. GRAPES全球集合预报系统不同随机物理扰动方案影响分析. 气象学报,78(6):972-987. DOI: 10.11676/qxxb2020.074
Peng Fei, Li Xiaoli, Chen Jing. 2020. Impacts of different stochastic physics perturbation schemes on the GRAPES Global Ensemble Prediction System. Acta Meteorologica Sinica, 78(6):972-987. DOI: 10.11676/qxxb2020.074
Citation: Peng Fei, Li Xiaoli, Chen Jing. 2020. Impacts of different stochastic physics perturbation schemes on the GRAPES Global Ensemble Prediction System. Acta Meteorologica Sinica, 78(6):972-987. DOI: 10.11676/qxxb2020.074

GRAPES全球集合预报系统不同随机物理扰动方案影响分析

Impacts of different stochastic physics perturbation schemes on the GRAPES Global Ensemble Prediction System

  • 摘要: 为了更好地理解不同随机物理扰动方案对全球中期集合预报的影响差异,本研究基于GRAPES全球集合预报系统(GRAPES-GEPS)对比分析了随机物理倾向扰动(Stochastically Perturbed Parameterization Tendencies,SPPT)、随机动能补偿(Stochastic Kinetic Energy Backscatter,SKEB)及联合使用SPPT与SKEB三种模式扰动方案所产生的扰动特征及其对集合预报的影响。为避免初值扰动影响,考察随机物理方案所产生的扰动特征时,不使用初值扰动。通过扰动与误差相关性分析(PECA)发现,不同随机物理扰动方案所产生的扰动对预报误差均具有一定的描述能力,而且联合使用SPPT与SKEB方案时,扰动对误差的描述能力最好。对所有扰动方案来说,扰动总能量最初主要集中在热带地区对流层中高层以及平流层低层。随着预报时效的延长,扰动总能量不断增大,其大值区不断向热带外地区转移。从扰动总能量的谱结构来看,扰动能量均呈现升尺度发展的特征。在基于奇异向量初值扰动的GRAPES-GEPS中,随机物理扰动方案的使用均能够显著增加不同地区等压面要素的集合离散度,并在一定程度上改善集合平均误差。由于集合离散度的增大,预报失误率显著减小。连续分级概率评分也有所减小,尤其是在热带地区,改进更为明显。此外,中国地区不同量级(小雨、中雨、大雨和暴雨)降水概率预报技巧在一定程度上得到改善。上述改进均在联合使用SPPT与SKEB方案时最好,这与扰动总能量、扰动与误差相关分析结果一致。

     

    Abstract: In order to better understand the impacts of different stochastic physics perturbation schemes on global medium ensemble forecasts, this research conducts a comparative analysis of the features of perturbations yielded by the Stochastically Perturbed Parameterization Tendencies (SPPT) scheme, the Stochastic Kinetic Energy Backscatter (SKEB) scheme, and the combination of the SPPT and SKEB schemes as well as the impacts of these three model perturbation methods on ensemble forecasts based on the GRAPES Global Ensemble Prediction System (GRAPES-GEPS). To avoid the impacts from initial perturbations, initial perturbations are disabled when the features of perturbations produced by the above stochastic physics schemes are explored. Via the perturbation versus error correlation analysis (PECA), it is found that perturbations yielded by different stochastic physics perturbation schemes have the capability to capture forecast errors. Furthermore, when the combination of the SPPT and SKEB schemes is applied, the produced perturbations best simulate forecast errors. For all stochastic perturbation schemes, the total energy of perturbations is initially concentrated in the middle and upper troposphere and the lower stratosphere of the tropics. In addition, the total energy of perturbations increases with the forecast lead time, for which the maxima keep propagating towards the extratropical regions. From the spectra of total energy of perturbations, it is observed that the perturbation energy evolves upscale. In the GRAPES-GEPS built on the initial perturbations derived from singular vectors, the applications of stochastic physics perturbation schemes increase the ensemble spreads for fields at different isobaric surfaces in different regions and improve the root-mean-square errors of the ensemble means to some extent. Due to the increased ensemble spreads, outliers are significantly decreased. The continuous rank probability scores are also reduced, which is more pronounced in the tropics. Furthermore, the probabilistic forecast skills of rainfall in China for light rain, moderate rain, heavy rain, and rainstorm are also improved to some extent. The above-mentioned improvements are the largest when the combination of the SPPT and SKEB schemes is employed. This is consistent with the results from the analyses on total energy of perturbations and PECA.

     

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