Ingredients-based Methodology and Fuzzy Logic Combined Short-Duration Heavy Rainfall Short-Range Forecasting:An Improved Scheme

Short-duration heavy rainfall(SHR),as delineated by the National Meteorological Center of the China Me-teorological Administration,is characterized by hourly rainfall amounts no less than 20.0 mm.SHR is one of the most common convective weather phenomena that can cause severe damage.Short-range forecasting of SHR is an important part of operational severe weather prediction.In the present study,an improved objective SHR forecasting scheme was developed by adopting the ingredients-based methodology and using the fuzzy logic approach.The 1.0°×1.0°National Centers for Environmental Prediction(NCEP)final analysis data and the ordinary rainfall(0.1-19.9 mm h-1)and SHR observational data from 411 stations were used in the improved scheme.The best lifted index,the total precipitable water,the 925 hPa specific humidity(Q 925),and the 925 hPa divergence(DIV 925)were selected as predictors based on objective analysis.Continuously distributed membership functions of predictors were obtained based on relative frequency analysis.The weights of predictors were also objectively determined.Experiments with a typhoon SHR case and a spring SHR case show that the main possible areas could be captured by the improved scheme.Verification of SHR forecasts within 96 hours with NCEP global forecasts 1.0°×1.0°data initiated at 08:00 Beijing Time during the warm seasons in 2015 show the results were improved from both deterministic and probabilistic perspectives.This study provides an objectively feasible choice for short-range guidance forecasts of SHR.The scheme can be applied to other convective phenomena.

Dynamic-statistics combined forecast scheme based on the abrupt decadal change component of summer precipitation in East Asia

Based on the 1983~2011 CMAP data,the precipitation anomaly in East Asia and its nearby sea regions（hereafter called East Asia for short） demonstrates the ＂＋-＋＂ pattern before 1999 and the ＂-＋-＂ pattern afterwards; this decadal change is contained principally in the corresponding EOF3 component.However,the NCC_CGCM forecast results are quite different,which reveal the ＂＋-＋-＂ pattern before 1999 and the ＂-＋-＋＂ pattern afterwards.Meanwhile,the probability of improving NCC_CGCM＇s forecast accuracy based on these key SST areas is discussed,and the dynamic-statistics combined forecast scheme is constructed for increasing the information of decadal change contained in the summer precipitation in East Asia.The independent sample forecast results indicate that this forecasting scheme can effectively modify the NCC_CGCM＇s decadal change information contained in the summer precipitation in East Asia（especially in the area of 30°N–55°N）.The ACC is 0.25 and ACR is 61% for the forecasting result based on the V SST area,and the mean ACC is 0.03 and ACR is 51% for the seven key areas,which are better than NCC_CGCM＇s system error correction results（ACC is -0.01 and ACR is 49%）.Besides,the modified forecast results also provide the information that the precipitation anomaly in East Asia mainly shows the ＂＋-＋＂ pattern before 1999 and the ＂-＋-＂ pattern afterwards.

A New Multidimensional Time Series Forecasting Method Based on the EOF Iteration Scheme

In this paper a new .mnultidimensional time series forecasting scheme based on the empirical orthogonal function (EOF) stepwise iteration process is introduced. The scheme is tested in a series of forecast experiments of Nino3 SST anomalies and Tahiti-Darwin SO index. The results show that the scheme is feasible and ENSO predictable.

Demand of Electric Power and Its Forecasting in Iron and Steel Complex

A systematic study on the electrical load forecasting for large-scale iron and steel companies was made. After analyzing the electrical load＇s characteristics, an algorithm framework for the load forecasting in iron and steel complex was formulated based on model combination and scheme filtration. The algorithm features data quality self- adaptation, convenient forecasting model extension, easy practical application, etc. , and has been successfully applied in Baoshan Iron and Steel Co Ltd, Shanghai, China, resulting in great economic benefit.

The Water-Bearing Numerical Model and Its Operational Forecasting Experiments Part I: The Water-Bearing Numerical Model

In first paper of articles, the physical and calculating schemes of the water-bearing numerical model are described. The model is developed by bearing all species of hydrometeors in a conventional numerical model in which the dynamic framework of hydrostatic equilibrium is taken. The main contributions are: the mixing ratios of all species of hydrometeors are added as the prognostic variables of model, the prognostic equations of these hydrometeors are introduced, the cloud physical framework is specially designed, some technical measures are used to resolve a series of physical, mathematical and computational problems arising from water-bearing; and so on. The various problems (in such aspects as the designs of physical and calculating schemes and the composition of computational programme) which are exposed in feasibility test, in sensibility test, and especially in operational forecasting experiments are successfully resolved using a lot of technical measures having been developed from researches and tests. Finally, the operational forecasting running of the water-bearing numerical model and its forecasting system is realized stably and reliably, and the fine forecasts are obtained. All of these mentioned above will be described in second paper.

Real-Time Short-Term Forecasting Based on Information Management

Traffic congestions and road accidents continue to increase in industry countries. There are three basic strategies to relieve congestion. The first strategy is to increase the transportation infrastructure. However, this strategy is very expensive and can only be accomplished in the long-term. The second strategy is to limit the traffic demand or make traveling more expensive that will be strongly opposed by travelers. The third strategy is to focus on efficient and intelligent utilization of the existing transportation infrastructures. This strategy is gaining more and more attention because it’s well. Currently, the Intelligent Transportation System (ITS) is the most promising approach to implementing the third strategy. Various forecast schemes have been proposed to manage the traffic data. Many studies showed that the moving average schemes offered meaningful results compared to different forecast schemes. This paper considered the moving average schemes, namely, simple moving average, weighted moving average, and exponential moving average. Furthermore, the performance analysis of the shortterm forecast schemes will be discussed. Moreover, the real-time forecast model will consider the abnormal condition detection.

OPERATIONAL FORECAST OF RAINFALL INDUCED BY LANDFALLING TROPICAL CYCLONES ALONG GUANGDONG COAST

Following previous studies of the rainfall forecast in Shenzhen owing to landfalling tropical cyclones(TCs),a nonparametric statistical scheme based on the classification of the landfalling TCs is applied to analyze and forecast the rainfall induced by landfalling TCs in the coastal area of Guangdong province,China.All the TCs landfalling with the distance less than 700 kilometers to the 8 coastal stations in Guangdong province during 1950—2013 are categorized according to their landfalling position and intensity.The daily rainfall records of all the 8 meteorological stations are obtained and analyzed.The maximum daily rainfall and the maximum 3 days’accumulated rainfall at the 8 coastal stations induced by each category of TCs during the TC landfall period(a couple of days before and after TC landfalling time)from 1950 to 2013 are computed by the percentile estimation and illustrated by boxplots.These boxplots can be used to estimate the rainfall induced by landfalling TC of the same category in the future.The statistical boxplot scheme is further coupled with the model outputs from the European Centre for Medium-Range Weather Forecasts(ECMWF)to predict the rainfall induced by landfalling TCs along the coastal area.The TCs landfalling in south China from 2014 to 2017 and the corresponding rainfall at the 8 stations area are used to evaluate the performance of these boxplots and coupled boxplots schemes.Results show that the statistical boxplots scheme and coupled boxplots scheme can perform better than ECMWF model in the operational rainfall forecast along the coastal area in south China.

洪水预报在蓄滞洪区启用条件中的应用研究

针对蓄滞洪区的启用涉及到的蓄滞洪区内人员和财产转移等诸多问题,本文将洪水预报引入蓄滞洪区启用的条件中,通过构建一套河系预报,可提前8 d预报出江桥站的流量是否达到启用蓄滞洪区的标准,并通过分级启用蓄滞洪区的方式,为决策和人员财产提供了时间的保障。同时文中还分析了各主要站点预报方案的精度和拉林河洪水的影响,以确保预报的可靠性和蓄滞洪区启用标准的合理性。

李家岩水库施工期洪水预报方案编制

针对李家岩水库施工期洪水预报方案编制的技术路线和相关成果进行总结。根据李家岩水情测报系统站网选取预报依据站,结合流域地形及水系进行分块和划分计算单元,选择三水源新安江水文模型进行模型参数率定,对铁索站10场次洪水的模拟结果进行统计分析,并初步确定预报方案精度等级达到乙等。开发实时洪水预报功能进行方案验证分析并提出相关应用改进建议。由于收集的历史洪水资料年限及数量均没有达到规范要求,且存在雨量站资料缺失、水文控制站流量精度难以校核、流域未建代表性蒸发站等问题,会在一定程度上影响模型参数率定及其预报精度。期望该预报方案在实际应用中通过进一步积累洪水资料,能进行定期修订并达到较好成效。

WRF模式中参数化方案对新疆北部不同地形地区风场模拟的影响

WRF(weather research and forecasting)模式中参数化方案的选择与近地面风场的仿真模拟结果关系密切。为解决新疆北部不同地形地区风场模拟准确性的问题,采用WRF中尺度气象模式,探究4类参数化方案(边界层、微物理、陆面过程、近地面层)以及次网格地形方案对新疆北部不同地形地区风场模拟结果的影响。结果表明:每组试验均能模拟出风速的变化趋势;陆面过程RUC(rapid update cycle)方案和微物理Lin(Purdue Lin)方案对平原地区模拟结果较好,陆面过程Noah方案和微物理WSM6(WRF single moment 6 class)方案对山区地形模拟结果较好,且对于平原和山谷地形,次网格地形方案对模拟地区均能起到较好的修正作用。

沿江货运铁路通道布局及实施方案研究

完善沿江货运铁路通道布局对于充分发挥铁路绿色低碳优势、缓解长江三峡“肠梗阻”问题、加快构建综合立体交通走廊、支撑长江经济带经济发展等具有重要意义。研究首先分析沿江货运铁路通道现状及存在问题;其次,从综合交通的角度出发,统筹考虑铁路趋势运量、“水转铁”运量、“公转铁”运量进行近期(2030年)、远期(2035年)、远景(2050年)需求预测;最后,提出铁路通道布局和分期实施方案,即规划沿江货运铁路通道由北辅助通道、中通道(轻快通路、普货通路、专线通路)、南辅助通道组成。按照“两步走”进行实施,一是对长荆铁路、鸦宜铁路进行扩能改造,二是规划建设常岳九铁路等构建沿江货运专线通路。

阳宇会水位站洪水预报方法研究和应用

吕梁市地形复杂,暴雨多发,容易形成滑坡、泥石流、山洪等自然灾害,造成经济损失和人员伤亡,因此对上述自然灾害的预防、预控、预警、预报十分重要。分析研究适用于本地区中小河流的洪水预报,立足流域单元,遵循“降雨—产流—汇流—演进”规律,并以阳宇会水位站为例阐述了具体预报方法和流程。

多元回归洪水预警方案中预报因子系数不合理问题的探讨

利用多元回归方程建立预警方案,各预报因子方程系数应符合物理意义。针对陆屋水文站多元回归洪水预警方案中预报因子系数不合理的情况,通过分析钦江陆屋水文站的流域特性,找出不合理的原因,完善多元回归洪水预警方案。

跨城市间轨道交通站间运输需求预测及开行方案设计

随着城市边缘化规模不断扩大,人口数量和密度逐步增加,中心城市与外围城市之间缺乏较好的横向联系,使得城市间出行困难,对城市群的整体发展造成了不良影响,因此运量大、速度快、污染小、正点率高、公交化的绿色交通已成为各大城市解决交通日益紧张问题的关键。城市间客流大小决定城市轨道交通建设规模及运营技术方式。本文在城市化进程加速发展的时代大背景下,致力于城市间轨道交通方式出行特征和模式来预测西安地铁11号线初期的客流并设计列车开行方案。并对客流预测结果进行敏感性分析,利用得出的站间OD计算出全日、高峰小时以及分时断面客流量,在此基础上,计算开行列数、行车间隔、全日列车开行方案,选择合适的列车编组方案、交路方案和停站方案,再用已知数据,设计西安地铁11号线的列车开行方案,为未来地铁11号线运营停供依据。

不同物理过程参数化方案对江淮梅雨降水预报的影响分析

为研究不同物理过程参数化方案对江淮梅雨降水预报的影响,基于WRFv4.4.2,利用GFS预报数据、第六版MODIS土地覆盖类型产品和ERA5-Land观测数据集,使用均方根误差、相关系数、公平技巧评分和偏差评分等方法,模拟评估Ferrier、WSM6和Thompson这3种云微物理过程参数化方案,以及KF、BMJ和Tiedtke这3种积云对流参数化方案共9种组合,对2020年7月14日00:00—17日00:00江淮流域梅雨期一次降水过程的预报效果进行分析。结果表明,(1)积云对流参数化方案对江淮梅雨降水预报有更为明显的影响,使用BMJ可以获得较好的预报结果;(2)WRF模式在山地、城市等区域表现不佳,在平原、农田等区域表现尚可,适用性存在一定不足;(3)在江淮流域北部地区(32.7°N以上)使用WSM6和BMJ的实验组合综合表现较佳,可较为准确地预报降水过程变化趋势,对小雨和中雨量级的降水落区有较高的预报技巧。为今后江淮梅雨期降水预报提供参考。

融合时序关联动态图与常微分方程的区域间出租车需求预测

为解决出租车行业中的高空驶率和不均衡的需求分布问题,通过对出租车出行的区域进行深入研究,提出了一个融合时序关联动态图与常微分方程的需求预测模型TCG-ODE(temporal correlation graphs-ordinary differential equations)。首先,模型使用ODE(ordinary differential equation)对图卷积神经网络(graph convolutional network,GCN)进行微分方程建模,将堆叠局部特征信息抽象为动态图,以节点的时序特性来推进局部节点状态;然后,设计了一种基于注意力分数调整采样策略的蒸馏方案,提高对多层稀疏图的适应效果,以更稳定地表征复杂时空特征,最终实现对区域间出租车需求量的预测。在真实的出租车订单数据集上进行实验,研究结果表明,TCG-ODE模型的预测效果均优于对照模型和改进前的模型。通过精准预测不同区域之间的出租车需求量,可以为出租车司机和乘客出行提供决策支持信息,从而优化供需关系。

WRF模式对三峡库区万州段特大暴雨的模拟分析

为提升三峡库区万州段暴雨模拟与预报精度,基于中尺度模式WRF及FNL再分析资料,针对三峡库区万州段4次典型暴雨事件,由5种云微物理方案、3种积云对流方案、RRTM长波辐射方案、Dudhia短波辐射方案、YSU边界层方案和Noah陆面方案组合的15种物理参数组合方案,系统分析不同参数化方案组合对降水时空特征的模拟能力,并优选物理参数化方案,构建适用于研究区的WRF模式,提高模拟精度。研究结果表明:WRF模式能够较好地再现降水时空变化特征,但强降水时段存在超前现象,且降水模拟值普遍偏低,每小时降水量的平均绝对误差范围为-0.62~-0.12 mm,48 h累积降水量空间分布的相对误差范围为-66.90%~16.75%;WSM6-GD-Noah-RRTM/Dudhia(A5)方案综合表现最佳,其48 h累积降水量模拟相对误差仅为2.79%,对大雨和暴雨量级模拟的平均TS评分最高,达到0.26,尤其是暴雨中心降水量值显著优于其他方案;A5方案模拟的降水特征与实况最为吻合,为提升该区域气象模拟精度和防灾减灾提供了重要的理论支持。

人工神经网络技术在海浪预报中的应用

利用人工神经网络中的算法,建立了南海硇洲岛海区风浪的预报方案。结果表明,人工神经 BP 网络方法在海浪的定性及定量预报上,均有较好的拟合历史风浪浪高的能力。该方案对风浪浪高的预报也达到了一定的精度。文中还针对网络容易产生振荡,易发生不收敛的情况,建立了不同的预报方案并 BP 进行了对比分析,达到了较好的预报效果。

水电站施工期洪水预报系统设计与开发

为了克服水电站施工期洪水预报方案不足,解决施工期洪水预报工作中存在的一些实际问题,针对水电站施工期的河道特性变化,分析了水电站施工期洪水预报的特定需求,提出水电站施工期洪水预报系统的设计思路和研发目标。总体设计方案包括系统开发及运行环境、设计的基本原则、预报模型配制的技术方案、施工期各阶段到运行期预报方案转换的思路等。系统总体上由数据支撑层、应用层、人机交互层构成。重点介绍了该系统开发的预报方案编制与修正、实时洪水预报等主要应用功能。本系统可针对水电站施工的不同阶段快速建立或调整预报方案;实时洪水预报可人机交互进行,支持增加输入预见期内降雨数据的预报,可为早期的防洪决策提供参考依据。该系统已集成到四川锅浪跷水电站施工期水情自动测报系统投入实际应用,从应用情况来看,该系统运行稳定、实用,达到了预期的研发目标,为开展施工期洪水预报工作提供了有效工具。

基于SSA-AR方法的MJO指数预报模型试验

采用奇异谱分析(SSA)与自回归向量(AR)预报模型相结合的方法,对热带地区大气季节内振荡(MJO)指数向量作自适应滤波意义下的预报试验。结果表明,通过对MJO原始序列进行SSA的分解重建,无论采用对重建的分量序列进行AR(P)建模的方案,还是利用对重建合成序列进行AR(P)建模的方案,均可得到两周以上的MJO指数预报能力,其提前20天指数预报值与实况之间平均相关系数达到0.5,与直接对MJO原始序列进行AR建模相比较,该方法有较高的预报技巧和超前预报能力,预报效果也较稳定,故将SSA-AR方案进一步完善,可望作为MJO指数业务预报的有效模型。