A CLOUD-RESOLVING MODELING STUDY OF SURFACE RAINFALL PROCESSES ASSOCIATED WITH LANDFALLING TYPHOON KAEMI(2006)

The detailed surface rainfall processes associated with landfalling typhoon Kaemi(2006) are investigated based on hourly data from a two-dimensional cloud-resolving model simulation. The model is integrated for 6 days with imposed large-scale vertical velocity, zonal wind, horizontal temperature and vapor advection from National Center for Environmental Prediction (NCEP) / Global Data Assimilation System (GDAS) data. The simulation data are validated with observations in terms of surface rain rate. The Root-Mean-Squared (RMS) difference in surface rain rate between the simulation and the gauge observations is 0.660 mm h^-1, which is smaller than the standard deviations of both the simulated rain rate (0.753 mm h^-1) and the observed rain rate (0.833 mm h^-1). The simulation data are then used to study the physical causes associated with the detailed surface rainfall processes during the landfall. The results show that time averaged and model domain-mean P_s mainly comes from large-scale convergence (Q_WVF) and local vapor loss (positive Q_WVT). Large underestimation (about 15%) of P_s will occur if Q_WVT and Q_CM (cloud source/sink) are not considered as contributors to P_s. Q_WVF accounts for the variation of P_s during most of the integration time, while it is not always a contributor to P_s. Sometimes surface rainfall could occur when divergence is dominant with local vapor loss to be a contributor to P_s. Surface rainfall is a result of multi-timescale interactions. Q_WVE possesses the longest time scale and the lowest frequency of variation with time and may exert impact on P_s in longer time scales. Q_WVF possesses the second longest time scale and lowest frequency and can explain most of the variation of P_s. Q_WVT and Q_CM possess shorter time scales and higher frequencies, which can explain more detailed variations in P_s. Partitioning analysis shows that stratiform rainfall is dominant from the morning of 26 July till the late night of 27 July. After that, convective rainfall dominates till about 1000 LST 28 July. Before 28 July, the variations of in rainfall-free regions contribute less to that of the domain-mean Q_WVT while after that they contribute much, which is consistent to the corresponding variations in their fractional coverage. The variations of Q_WVF in rainfall regions are the main contributors to that of the domain-mean Q_WVF, then the main contributors to the surface rain rate before the afternoon of 28 July.     

暴雨模拟中多普勒雷达径向速度变分同化的应用

针对2008年6月广东地区的一次强降雨过程,利用WRF中尺度数值模式及其三维变分同化系统(WRF-3DVAR),进行了多普勒雷达径向速度变分同化对暴雨过程模拟效果影响研究。结果表明:WRF-3DVAR能够有效地同化多普勒雷达径向速度,同化后的主要影响在于改进了初始动力场,使得初始场包含有更详尽的中尺度特征信息,进而显著提高模式对广东局地暴雨过程的模拟效果。在高分辨率中尺度数值模式中有效地利用多普勒天气雷达资料,是提高中尺度降雨预报的关键。     

RELATIONSHIP BETWEEN SUMMER LOW-FREQUENCY RAINFALL OVER SOUTHERN CHINA AND PROPAGATION OF TROPICAL INTRASEASONAL OSCILLATION

This study investigates the relationship between summer low-frequency rainfall over southern China and tropical intraseasonal oscillation (ISO) in the atmosphere by examining systematically the propagation features of the tropical ISO in terms of focusing on five large-scale low-frequency rainfall regimes in summer over southern China. It is demonstrated that there is a close linkage between the five rainfall regimes over southern China and the northward propagation of the tropical ISO. The moist ISO signals, which influence the low-frequency rainfall events in different regions of southern China, mainly propagate northwestward from the tropical ocean to the southeast of China. The southeast China rainfall regime is intimately associated with the moist ISO signals propagating northwestward from the equatorial mid-western Pacific Ocean. For both the Yangtze River regime and South of Yangtze River regime, the moist ISO signals over the northern South China Sea show an evident northward propagation towards the Yangtze River region, and then propagate westward. It is further found that the interaction between the northward propagation of low-latitude ISO signals and the southward propagation of high-latitude ISO signals can also make a clear influence on the low-frequency rainfall in southern China. For the Southern China regime, the moist ISO signals show a significant northward propagation from the Philippines. Moreover, for the rainless regime, southern China is under dry ISO signals’ control, and the latter shows no clear propagation to southern China. This study may provide insights for the extended-range forecasting of summer rainfall in southern China.     

年最大日雨量极值分布拟合与推算

采用红河州12个站近48～58年的年最大日雨量资料,用PearsonⅢ型分布、耿贝尔分布、对数正态分布等3种概率分布模型分别进行了拟合,选择拟合最好的分布模型来估算最大给定重现期极值.结果表明:3种分布均能较好地拟合年最大日雨量的分布,在红河州12个站的拟合中,有7个站用耿贝尔分布,4个站用Pearson-Ⅲ分布,1个...     

基于不同微物理过程的广西沿海南风型暖区暴雨的数值模拟研究

基于WRFV3.6.1,利用其8个云微物理参数化方案对2010—2016年华南汛期（4—9月）的6个南风型暖区暴雨个例进行数值模拟与多方案集成试验,并采用基于对象的诊断评估方法（MODE）对模拟结果进行评估。结果发现对于大多数个例,WRF模式都能较好地模拟出暖区暴雨的降水带,对暖区降水带模拟最好的参数化方案是WSM6方案,其次是Lin方案;模拟效果较差的参数化方案为CAM5.1与NSSL 2-mon方案。选取模拟结果较好的个例进行诊断分析,发现不同参数化方案得到的动力学特征以及云微物理特征相关变量存在较大差异,导致模拟降水的差异。在单方案模拟的基础上,开展多方案集成试验,发现多方案集成方法能够有效降低模式模拟的不确定性,产生更稳定的模拟结果。     

Application of a cloud-texture analysis scheme to the cloud cluster structure recognition and rainfall estimation in a mesoscale rainstorm process

It is thought that satellite infrared (IR) images can aid the recognition of the structure of the cloud and aid the rainfall estimation. In this article, the authors explore the application of a classification method relevant to four texture features, viz. energy, entropy, inertial-quadrature and local calm, to the study of the structure of a cloud cluster displaying a typical meso-scale structure on infrared satellite images. The classification using the IR satellite images taken during 4–5 July 2003, a time when a meso-scale torrential rainstorm was occurring over the Yangtze River basin, illustrates that the detailed structure of the cloud cluster can be obviously seen by means of the neural network classification method relevant to textural features, and the relationship between the textural energy and rainfall indicates that the structural variation of a cloud cluster can be viewed as an exhibition of the convection intensity evolvement. These facts suggest that the scheme of following a classification method relevant to textural features applied to cloud structure studies is helpful for weather analysis and forecasting.     

吸湿性播撒对暖性对流云减雨影响的数值模拟

利用以色列特拉维夫大学二维面对称分档云模式（two-dimensional slab-symmetric detailed spectral bin microphysical model of Tel Aviv University）,对2016年9月4日16:00（北京时）前后我国华东地区的一次暖性浅对流云降水过程进行模拟,模式模拟的强回波中心高度和最大回波强度范围与观测基本一致。并在此基础上进行了小于1 μm的吸湿性核的播撒减雨试验,分别考虑了不同播撒时间、不同播撒高度以及不同播撒剂量的敏感性测试。结果表明:在云的发展阶段早期播撒能起到更好的减雨效果,播撒时间越早对大粒子生长过程的抑制作用越强,随着播撒时间向后推移,受抑制作用最显著的粒径段向小粒径端偏移;在云中心过饱和度大的区域下方进行播撒,减雨效果更加明显,当播撒剂量为350 cm-3时,地面累积降水量减少率可达23.3%;另外,随着播撒剂量的增加,减雨效果更加显著,甚至能达到消雨的效果。因此,在暖性浅对流云中合理地播撒小于1 μm的吸湿性核能达到较好的减雨或消雨效果。     

北京山区泥石流预警阈值初步研究

泥石流预警阈值,是突发地质灾害防灾减灾的重要参考指标。本文结合北京山区泥石流灾害特点和已有降雨阈值研究成果,一方面在泥石流沟易发性、物源和危害人数进行分级的基础上,提出不同级别沟谷在不同前期降雨条件下,不同发灾概率的激发雨量,极大地方便了中短期预警实际工作;另一方面将泥石流流域降雨量、土壤含水率、次声、泥位4个参数,作为泥石流短临灾害预警关键物理参数,开展了泥石流专业监测设备预警阈值研究。最终,从技术层面上构建不同时间维度的泥石流监测预警阈值体系,为北京山区泥石流监测预警提供技术支持。     

降雨对松散堆积体滑坡稳定性影响探讨——以贵州省沿河土家族自治县为例

降雨是引发滑坡灾害的主要原因之一。通过对沿河土家族自治县具代表性的四个松散堆积体滑坡的分析,认为最大降雨量与滑坡的稳定性系数、滑面倾角均成反比,而滑带土内摩擦角增加时,滑坡启动需要的降雨强度就越大,成正比。其认识与目前该类滑坡的监测数据变化特征总体相吻合。     

The Seasonal Prediction of the Exceptional Yangtze River Rainfall in Summer 2020

During June and July of 2020, the Yangtze River basin suffered from extreme mei-yu rainfall and catastrophic flooding. This study explores the seasonal predictability and associated dynamical causes for this extreme Yangtze River rainfall event, based on forecasts from the Met Office GloSea5 operational forecast system. The forecasts successfully predicted above-average rainfall over the Yangtze River basin, which arose from the successful reproduction of the anomalous western North Pacific subtropical high (WNPSH). Our results indicate that both the Indian Ocean warm sea surface temperature (SST) and local WNP SST gradient were responsible for the westward extension of the WNPSH, and the forecasts captured these tropical signals well. We explore extratropical drivers but find a large model spread among the forecast members regarding the meridional displacements of the East Asian mid-latitude westerly jet (EAJ). The forecast members with an evident southward displacement of the EAJ favored more extreme Yangtze River rainfall. However, the forecast Yangtze River rainfall anomaly was weaker compared to that was observed and no member showed such strong rainfall. In observations, the EAJ displayed an evident acceleration in summer 2020, which could lead to a significant wind convergence in the lower troposphere around the Yangtze River basin, and favor more mei-yu rainfall. The model forecast failed to satisfactorily reproduce these processes. This difference implies that the observed enhancement of the EAJ intensity gave a large boost to the Yangtze River rainfall, hindering a better forecast of the intensity of the event and disaster mitigation.