摘要:本文基于实况融合降水和雷达反射率因子，采用模糊逻辑法提出了一个新的对流云/层状云判别方法，进而改进了GSI（Gridpoint Statistical Interpolation）同化系统中的云分析方案（简称CUST方案）。以2019年6月19日影响浙江的一次梅雨过程为例，利用WRF（Weather and Forecast Research）模式与GSI同化系统开展了逐小时循环同化试验，分析了CUST方案对降水的模拟改进作用和可能影响过程，并与其他方案进行了对比，探讨了CUST方案的应用效果。结果表明：（1）新提出的CUST方案可较为准确地划分对流云和层状云，以此作为判别因子改进GSI同化系统中的云分析方案切实可行。（2）CUST方案在对流区域采用对流云分析方案，在非对流区域采用层云分析方案，减小了单纯对流云方案在非对流区域的空报现象、以及单纯层云方案在强对流区域的漏报现象，有效提升了短时降水的模拟能力。（3）CUST方案对模式起报初期（6 h甚至3 h内）的改进效果较为明显，且对小雨量级的改进幅度要大于大雨量级。（4）与基于地表感热和潜热通量确定的对流尺度速度作为对流判据的混合云分析方案（简称CSW方案）相比，CUST方案基于实况资料划分的对流云/层状云更为合理，模拟的降水结果占优，说明CUST方案方法有较好的应用前景。
关键词:云分析/
对流云—层状云划分/
降水/
数值模拟
Abstract:A new convective–stratiform separation technique based on the hourly precipitation obtained from CMPAS (China Meteorological Administration multisource precipitation analysis system) and radar reflectivity mosaics data obtained from CMARMOS (China Meteorological Administration radar mosaic operation system) is presented in this paper. The technique, which is based on fuzzy logic, is developed to improve the cloud analysis scheme in the Gridpoint Statistical Interpolation (GSI) assimilation system (referred to as the CUST scheme). The improved scheme was tested in a severe Mei-yu rain that occurred on 19 June 2019, in Zhejiang Province. Several hourly-cycle assimilation experiments were performed using the WRF (weather research and forecasting) model and the GSI assimilation system to analyze the impact of the new scheme on the precipitation simulation, and the scheme was compared with other schemes. The results showed the following: (1) The new convective–stratiform separation technique accurately separated the convective–stratiform cloud, and it can be used as a discriminating factor to improve the cloud analysis scheme in the GSI assimilation system. (2) The CUST scheme adopted the convective cloud analysis scheme in the convective region and the stratiform cloud analysis scheme in the non-convective region, which reduced the false alarm rate in the simple convective cloud scheme and the underestimation in the simple stratiform cloud scheme; this effectively improved the simulation of short-term precipitation. (3) The CUST scheme showed significant improvement in the initial stage of the model (within 6 hours or even 3 hours), and the improvement of small-level rain was greater than that of heavy rain. (4) Compared with the hybrid cloud analysis scheme (referred to as the CSW scheme) based on the convective scale velocity determined by the surface sensible heat and latent heat fluxes, the CUST scheme showed a more reasonable result for the convective–stratiform cloud partition and precipitation simulation, which indicates a good application prospect.
Key words:Cloud analysis/
Convective–stratiform partition/
Precipitation/
Numerical simulation
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