线性参照模型在铁路空间数据库中的应用

线性参照模型是以线性参考系统为基础,以动态分段技术为核心的一维空间数据模型。本文针对铁路空间数据的一维线性分布特征与铁路部门以一维线路为主体的运维管理模式,探讨了铁路空间数据的线性建模方法,利用空间数据库技术实现铁路空间数据、属性数据及业务数据的一维线性存储与管理,并提出了基于一套多尺度线性参照模型的铁路空间数据库的设计方案。试验表明,该方案能够为全路提供一套统一的一维管理基准,在动态数据管理、数据更新和共享等方面具有较大优势。     

Statistical diagnosis and gross error test for semiparametric linear model

This paper systematically studies the statistical diagnosis and hypothesis testing for the semiparametric linear regression model according to the theories and methods of the statistical diagnosis and hypothesis testing for parametric regression model. Several diagnostic measures and the methods for gross error testing are derived. Especially, the global and local influence analysis of the gross error on the parameter X and the nonparameter s are discussed in detail; at the same time, the paper proves that the data point deletion model is equivalent to the mean shift model for the semiparametric regression model. Finally, with one simulative computing example, some helpful conclusions are drawn.     

Optimization of land use structure based on ecological GREEN equivalent

Optimization of land use structure consists of economic and social and ecological optimization. Applying the minds of system engineering and principles of ecology, this paper presents such thoughts: the optimal forest-coverage rate calculated according to the reality of a district is set as main standard of ecological rationality in the district; through considering the value of ecosystem services of the land with GREEN equivalent (mainly cultivated land and grassland) and based on the rule, GREEN equivalent, this paper introduces the area conversion between woodland and cultivated land, also between woodland and grassland; this paper establishes a multi-dimension controlling model of optimization of land use structure. In addition, a multi-objective linear programming model for optimization of land use structure is designed. In the end, this paper tests and verifies this theory of ecological optimization, taking Qionghai city in Hainan Province as an example.     

Characteristics of Radar Echo Parameters and Microphysical Structure Simulation of a Short-Time Heavy Precipitation Supercell

By using the conventional observations, radar data, NCEP/NCAR FNL 1o×1o reanalysis data and numerical simulation data and with the construction and calculation of radar echo parameters, this paper presents the structural characteristics and physical processes of a short-time heavy precipitation supercell that occurred in the squall line process in Shanxi Province on 24 June 2020. The results show that this squall line event occurred in front of a surface cold front, combined with infiltration of low-level cold air and continuous increase of near-surface humidity in the afternoon. The surface mesoscale convergence line and mesoscale dew point front contributed to the development and systemization of the squall line by a large degree. The short-time extremely heavy precipitation in Pingshun County was caused by the development of a supercell from thunderstorm cells on the front side of the squall line. The characteristics of sharp increase in vertical integral liquid water content, persistent increase in reflectivity factor and continuous rise in the echo top height appeared about 23 min earlier than the severe precipitation, which has qualitative indicating significance for the nowcasting of short-time heavy precipitation. A quantitative analysis of the radar echo parameters suggests that the “sudden drop”of FV40 was a precursor signal of cells’coalescence and rapid development to the mature stage. The areal change of the echo core at the 6 km height was highly subject to the merging and developing of cells, the rapid change of hydrometeor particles in clouds and the precipitation intensity. Changes in the cross-sectional area of convective cells at different heights can indirectly reflect the changes of liquid particles and ice particles in clouds, which is indicatively meaningful for predicting the coalescing and developing-to-maturing of cells and heavy precipitation 30-45 min earlier. A comprehensive echo parameter prediction model constructed by the random forest principle can predict the magnitude of short-time heavy precipitation 40-50 min in advance. Numerical simulation reveals that large amounts of water vapor existed in the near-surface atmosphere, and that the cells rapidly obtained moisture from the ambient atmosphere and developed rapidly through maternal feeding. The cold cloud zone was narrow, upright and had a high stretch height. The upward motion in clouds was strong and deep, and very rich in liquid water content. The graupel particles had a large vertical distribution range, the coexistence area of graupel and snow was large, the height of raindrops was close to the surface with a wide horizontal scale, and the precipitation efficiency was high. These may be the important elements responsible for the occurrence of the short-time heavy precipitation that exceeded historical extreme values. On the basis of the above analyses, a comprehensive parameter (CP) prediction model is worked out, which can estimate the developing trend of supercells and the intensity of short-time heavy precipitation about 1 h in advance.     

Reliability of X-band Dual-polarization Phased Array Radars Through Comparison with an S-band Dual-polarization Doppler Radar

Based on the observations of a squall line on 11 May 2020 and stratiform precipitation on 6 June 2020 from two X-band dual-polarization phased array weather radars (DP-PAWRs) and an S-band dual-polarization Doppler weather radar (CINRAD/SA-D), the data reliability of DP-PAWR and its ability to detect the fine structures of mesoscale weather systems were assessed. After location matching, the observations of DP-PAWR and CINRAD / SA-D were compared in terms of reflectivity (ZH), radial velocity (V), differential reflectivity (ZDR), and specific differential phase (KDP). The results showed that: (1) DP-PAWR has better ability to detect mesoscale weather systems than CINRAD/SA-D; the multi-elevation-angles scanning of the RHI mode enables DP-PAWR to obtain a wider detection range in the vertical direction. (2) DP-PAWR’s ZH and V structures are acceptable, while its sensitivity is worse than that of CINRAD/SA-D. The ZH suffers from attenuation and the ZH area distribution is distorted around strong rainfall regions. (3) DP-PAWR’s ZDR is close to a normal distribution but slightly smaller than that of CINRAD/SA-D. The KDP products of DP-PAWR have much higher sensitivity, showing a better indication of precipitation. (4) DP-PAWR is capable of revealing a detailed and complete structure of the evolution of the whole storm and the characteristics of particle phase variations during the process of triggering and enhancement of a small cell in the front of a squall line, as well as the merging of the cell with the squall line, which cannot be observed by CINRAD/SA-D. With its fast volume scan feature and dual-polarization detection capability, DP-PAWR shows great potential in further understanding the development and evolution mechanisms of meso-γ-scale and microscale weather systems.     

A Comprehensive Observational Analysis for the Effects of Gas Cannons on Clouds and Precipitation

To analyze the effects of gas cannons on clouds and precipitation, multisource observational data, including those from National Centers for Environmental Prediction (NCEP) reanalysis, Hangzhou and Huzhou new-generation weather radars, laser disdrometer, ground-based automatic weather station, wind profiler radar, and Lin''an C-band dual polarization radar, were adopted in this study. Based on the variational dual-Doppler wind retrieval method and the polarimetric variables obtained by the dual-polarization radar, we analyzed the microphysical processes and the variations in the macro - and microphysical quantities in clouds from the perspective of the synoptic background before precipitation enhancement, the polarization echo characteristics before, during and after enhancement, and the evolution of the fine three-dimensional kinematic structure and the microphysical structure. The results show that the precipitation enhancement operation promoted the development of radar echoes and prolonged their duration, and both the horizontal and vertical wind speeds increased. The dual-polarization radar echo showed that the diameter of the precipitation particles increased, and the concentration of raindrops increased after precipitation enhancement. The raindrops were lifted to a height corresponding to 0 to -20 ℃ due to vertical updrafts. Based on the disdrometer data during precipitation enhancement, the concentration of small raindrops (lgNw) showed a significant increase, and the mass-weighted diameter Dm value decreased, indicating that the precipitation enhancement operation played a certain“lubricating”effect. After the precipitation enhancement, the concentration of raindrops did not change much compared with that during the enhancement process, while the Dm increased, corresponding to an increase in rain intensity. The results suggest the positive effect of gas cannons on precipitation enhancement.     

Annual Frequency of Tropical Cyclones Directly Affecting Guangdong Province:Prediction Based on LSTM-FC

Tropical cyclone (TC) annual frequency forecasting is significant for disaster prevention and mitigation in Guangdong Province. Based on the NCEP-NCAR reanalysis and NOAA Extended Reconstructed global sea surface temperature (SST) V5 data in winter, the TC frequency climatic features and prediction models have been studied. During 1951-2019, 353 TCs directly affected Guangdong with an annual average of about 5.1. TCs have experienced an abrupt change from abundance to deficiency in the mid to late 1980 with a slightly decreasing trend and a normal distribution. 338 primary precursors are obtained from statistically significant correlation regions of SST, sea level pressure, 1000hPa air temperature, 850hPa specific humidity, 500hPa geopotential height and zonal wind shear in winter. Then those 338 primary factors are reduced into 19 independent predictors by principal component analysis (PCA). Furthermore, the Multiple Linear Regression (MLR), the Gaussian Process Regression (GPR) and the Long Short-term Memory Networks and Fully Connected Layers (LSTM-FC) models are constructed relying on the above 19 factors. For three different kinds of test sets from 2010 to 2019, 2011 to 2019 and 2010 to 2019, the root mean square errors (RMSEs) of MLR, GPR and LSTM-FC between prediction and observations fluctuate within the range of 1.05-2.45, 1.00-1.93 and 0.71-0.95 as well as the average absolute errors (AAEs) 0.88-1.0, 0.75-1.36 and 0.50-0.70, respectively. As for the 2010-2019 experiment, the mean deviations of the three model outputs from the observation are 0.89, 0.78 and 0.56, together with the average evaluation scores 82.22, 84.44 and 88.89, separately. The prediction skill comparisons unveil that LSTM-FC model has a better performance than MLR and GPR. In conclusion, the deep learning model of LSTM-FC may shed light on improving the accuracy of short-term climate prediction about TC frequency. The current research can provide experience on the development of deep learning in this field and help to achieve further progress of TC disaster prevention and mitigation in Guangdong Province.     

基于多源数据的湘北地区春季一次冰雹过程的观测分析

新型探测资料在强对流短临预报中发挥着重要作用.该文以2020年3月22日湘北地区春季一次冰雹过程为研究对象,运用多普勒天气雷达、风廓线雷达和地基微波辐射计等新型探测资料对该过程观测分析。结果表明：①此次过程发生在冷空气南下与南支槽前暖湿空气交汇背景下,受中低层切变线与急流影响,冰雹风暴生成前回暖明显,环境垂直风切变大;风暴由地面辐合线触发产生。②此次超级单体降雹过程在雷达回波中表现出“三体散射”、“V型缺口”、中气旋等特征;VIL、低仰角大风速核对冰雹、大风预警有很好的指示。③风廓线雷达探测到,风暴影响前超低空急流加强,中层有干侵入,低层垂直速度出现波动,风暴临近时超低空急流减弱。④地基微波辐射计监测发现,风暴影响前高空湿度增大,K指数、TT指数呈同趋势变化,而K指数预警灵敏度高于TT指数;风暴影响阶段,高空温度、相对湿度和大气不稳定指数出现不同程度跃升和突降。     

复杂地形下C波段雷达定量降水估计算法

C波段雷达定量降水估计（QPE）精度受到很多因素的影响,主要包括:（1）雷达标定,（2）非气象回波的干扰,（3）降水物垂直空间变化,（4）地形或地物的严重遮挡,（5）Z-R关系的代表性,（6）雷达拼图的质量,（7）雷达观测回波衰减等。文中雷达定量降水估计算法基于陕西省C波段天气雷达展开,从雷达探测数据质量控制、地形遮挡、Z-R关系和雷达拼图等方面提高C波段天气雷达定量降水估计的精度,产生降水类型产品和1 h定量降水估计产品,产品空间分辨率为0.01°×0.01°,时间分辨率为6 min。通过对7次降水过程进行评估,结果表明:基于混合仰角反射率因子处理模块和降水类型分类模块进行雷达定量降水估计,得到的结果与地面雨量站观测降水接近,1 h累计降水量的统计评分指标均方根误差稳定在3 mm以下,相对误差稳定在50%左右,相对偏差保持在?30%以内,雷达定量降水估计产品的离散度和绝对偏差都较低,表明该算法得到的雷达定量降水估计稳定可靠。      

深圳S波段与X波段双偏振雷达在定量降水估计中的应用

双偏振多普勒天气雷达的一个重要应用是进行定量降水估计（QPE）,它可以获得反射率（Z_H）、差分反射率（Z_DR）和差传播相移率（K_dp）这些与降水粒子有关的信息,常用的双偏振雷达降水估计方法有基于Z_H的R（Z_H）、基于Z_H和Z_DR的R（Z_H,Z_DR）、基于K_dp的R（K_dp）和基于K_dp与Z_DR的R（K_dp,Z_DR）这4种。文中利用深圳市S波段和X波段双偏振多普勒雷达探测资料,结合高精度地形数据和雨滴谱仪观测数据,设计了基于双偏振量的定量降水估计方法:首先利用地形数据和雷达地理信息,分析了雷达的遮挡状况,形成了这两部雷达的复合平面扫描仰角信息;随后利用雨滴谱仪观测资料,使用T矩阵方法统计得到了深圳地区的上述4种降水反演方法的参数;最后设计了混合降水反演方法,基于双偏振信号（即K_dp和Z_DR）的强弱,使用不同的降水反演方法进行定量降水估计。基于12个降水个例,利用各反演方法产生的定量降水估计结果与雨量计观测资料比较。结果表明,混合降水反演方法在降水反演的准确度和稳定性上均优于任何一种单一定量降水估计反演方法。基于文中介绍的定量降水估计方法,使用深圳S波段和X波段雷达产生了定量降水估计产品,并与深圳目前业务定量降水估计产品进行对比评估。结果表明,使用本方法产生的定量降水估计产品在准确度和稳定性上要优于目前的业务产品。此外,X波段雷达的定量降水估计产品性能要略高于S波段雷达的定量降水估计产品,这说明高时、空分辨率的X波段雷达可以提高定量降水估计精度。但由于雷达扫描平面内双偏振雷达对融化层和冰区的偏振量观测与降水的关系尚未明确,因此,本方法仅适用于雷达扫描平面内液态降水区。