多普勒天气雷达短时预报技术研究进展

简要介绍了短时预报技术的一些概念和基本内容,并就国内外基于多普勒天气雷达的短时预报技术开发进展情况,从临近外推预报和短时数值预报两方面详细叙述了包括雷达资料控制、灾害性天气预警预测、雷达资料同化等技术研究的最新动态。     

"2003.6.2"十堰强对流天气雷达回波和数值模拟分析

利用714C天气雷达回波和数值模拟资料，结合其它天气资料，分析了2003年6月2日发生在十堰境内的强对流天气过程。结果表明，此次强对流天气过程是在有利的大尺度天气形势背景下，由复杂地形触发出初始单体并发展为多单体强风暴产生冰雹和大风天气，雷达回波特征明显。风暴回波强度强，回波结构紧密，顶部有旁瓣假回波，低层存在弱回波区（WER），环境风的垂直切变较强。中β低涡的产生为强对流天气的产生和维持发挥了重要作用。     

天气雷达数字化终端及其应用软件

为解决雷达数据采集、实时显示、数据存储、资料处理自动化等问题，进行了天气雷达数字化终端和应用软件技术的研究和开发。改变了711B-1雷达数据存储、分析自动化程度低的状况。增加和丰富了雷达二次产品，使雷达资料得到了充分的分析和应用，提高了雷达对天气的监测能力。增加了对冰雹、暴雨等强对流天气的预警功能、人工增雨效果检验等功能。     

重庆地区强对流天气雷达回波统计特征

对过去22年(1982～2003)间重庆市发生的中尺度强对流天气雷达资料进行分类统计，研究中尺度强对流天气过程及其天气雷达回波特征，寻找重庆市中尺度强对流天气的运动规律。建立天气雷达回波资料库，将中尺度强对流天气过程雷达回波资料，按天气类型分类研究，结果表明：①重庆市中尺度强对流系统在时空分布上具有明显的不均匀性；②涡旋状回波是暴雨的显著特征；③冰雹回波以块状为主；④强雷雨大风回波的特征具有带状或弓型。     

T213数值预报产品与多普勒雷达图像相结合在对流天气在的应用

利用Micaps系统中的T213数值预报产品和714CD多普勒天气雷达的强度和速度回波资料、径向风场资料，对贵阳机场的对流天气进行分析。指出在用常规天气图进行外推预报的同时，结合T213数值预报物理量预告场提前预测天气趋势和变化，利用多普勒雷达连续探测的特点，弥补时间和空间密度的不足，并运用多普勒速度图和VAD技术来识别和反演流场结构和中小尺度天气统，密切监测对流天气的发生、发展、提高了短时预报的精度。     

基于雷达资料同化的飑线过程数值模拟试验研究

利用中尺度WRF模式及其3DVAR同化系统对2014年3月30日发生在我国华南地区的一次飑线过程展开多普勒天气雷达资料的同化效果试验研究。首先对雷达资料进行去地物杂波、退速度模糊等预处理,后设计了基于不同雷达观测量的同化试验及同化频次的敏感性试验。结果表明:直接循环同化雷达径向风资料和雷达反射率因子能够增加数值模式中的中小尺度信息,提供可靠的水汽分布;不同的同化频次对同化结果影响显著,每12 min同化间隔的结果略优于30 min、60 min同化间隔;同化雷达反射率因子和径向风资料分别对模式的总水场和风场有显著调整,联合同化雷达反射率因子和径向风资料比单独同化反射率因子或径向风更能改善飑线垂直结构配置,促使地面冷池和雷暴高压配合,进一步改善模式对大雨和暴雨量级降水预报效果。     

呼伦贝尔市岭南一次降水过程的雷达回波和卫星云图分析

应用T213数值预报产品、卫星云图,重点应用齐齐哈尔多普勒天气雷达产品资料,着重分析了发生在呼伦贝尔市岭南一次强降水天气过程的回波特征。指出在大尺度环流条件下,卫星云图资料和雷达资料的综合应用分析,对中小尺度天气有很好的监测作用,可以充分完善短时临近预报。     

雷达资料同化方法:回顾与前瞻

自20年前第一个业务天气雷达观测网在美国建立以后,气象界在多普勒天气雷达资料同化方面的研究和应用已取得了显著成果。中国在21世纪初也完成了一个覆盖大多数地区的多普勒天气雷达观测网,在实时监测及预警对流天气、降水及台风等方面起到了重要作用。但是,中国在同化雷达资料以改进细网格数值模式的初始化精度方面的研究及应用仍然处在起步阶段。对数值模式中同化雷达资料利用方法的研究和应用进行了简短回顾,也对未来该领域研究的重点研究方向提出建议。     

一次强对流天气的雷达回波特征分析

利用烟台新一代天气雷达资料，结合自动气象站和常规观测资料，分析了2004年5月16日山东半岛西部强对流天气背景和雷达回波特征。结果表明：此次强对流天气是由高空低涡和地面气旋造成的，在雷达径向速度图上，有中气旋特征，并与地面风场相对应。     

贵州冰雹天气的雷达监测和预报

本文在１９７９－１９８９年３－５月贵州冰雹天气的雷达气候统计分析和建立的贵州省冰雹天气资料的微机管理系统等资料的基础上，提出了贵州冰雹天气的雷达监测时次，加密，跟踪观测时次人结合回波形态，回波参数，卫星云图，探空，地面等资料的雷达监测和预测方法。     

水物质对云雨区卫星微波观测模拟影响

受云和降水影响卫星资料在数值天气预报中的同化应用对于进一步改善数值预报效果具有重要作用, 这部分工作的开展要求快速辐射传输模式中能够较好地考虑各种水物质的辐射效应。使用美国卫星资料同化联合中心新近开发的快速辐射传输模式CRTM, 通过中尺度数值模式WRF的预报输出提供水物质输入, 分析水物质辐射效应对云雨区卫星微波观测模拟计算的影响。在WRF模式预报水物质的分布和天气系统配置合理并符合云物理基本特征的前提下, 水物质辐射效应的考虑极大改善了卫星观测模拟的效果。结合卫星各通道探测特性, 进一步分析各种水物质粒子对NOAA-16 AMSU A/B各通道卫星亮温模拟的影响和物理机理, 定量统计各类水物质对各卫星观测通道亮温计算偏差和偏差贡献的权重大小。分析结果表明:快速辐射传输模式中, 考虑水物质辐射效应为数值天气预报中云雨区卫星资料的同化应用提供了必需的基础条件。     

2014年3月30—31日白云机场历史罕见大面积航班延误及强对流天气过程特征分析

利用航班运行信息、常规气象观测、自动气象加密观测、卫星、雷达和模式分析产品等多源资料,重点针对2014年3月30—31日导致白云机场出现历史罕见的大面积航班延误及强对流天气过程特征进行了探讨。对比分析发现：1天气原因导致大面积航班延误多发生在3—4月强对流天气背景下;2天气原因造成的航班大面积严重延误一般在恶劣天气发生2~3 h后出现,但航班恢复正常时间则比恶劣天气结束时间滞后可超过9 h;3导致3月30—31日出现历史罕见的大面积航班延误的强对流天气过程具有强度强、范围广、持续时间长等特征;4过程是在副高强度较弱、脊线偏南,有利于南支槽、高低空急流和地面西南低槽等天气系统持续影响广东的有利背景下发生的。     

Using Protection Motivation Theory to examine information-seeking behaviors on climate change

Many earlier studies concluded that exposure to changes in local weather or extreme weather events prompt public interest in climate change, and in turn raise support for mitigation policies. However, these findings do not square with observations of record-breaking temperatures, and decades of failure to reduce greenhouse gas emissions. To address this conundrum, we use Protection Motivation Theory to form hypotheses on the specific type of climate change-related information that individuals seek during periods of extreme local weather. Using daily-level internet search engine data from Chinese cities, we find that residents are purposeful and rational in seeking information on climate change. Specifically, when faced with high or abnormal temperatures, they are much more likely to seek information to appraise their susceptibility to climate change threats, and evaluate coping responses. On the other hand, due to the lack of direct benefits, they do not seek out information on climate mitigation behaviors. In contrast to earlier studies, our findings suggest that it is unlikely that extreme weather events will prompt support for climate mitigation actions. Instead, as worldwide weather becomes more extreme and unpredictable, it is likely that public’s attention will shift in the direction of adaptation measures.     

济南市区短时强降水特征分析

用2006—2008年5—9月的济南市区区域自动气象观测站资料和高空、地面资料,分析了济南市区出现短时强降水(R≥15mm/h)的年际、月际、时际以及强度特征,并分析了产生短时强降水的不同天气系统类型,为今后济南市区短时强降水的短时临近预报和预警提供参考。     

Damaging Weather Conditions in the United States: A Selection of Data Quality and Monitoring Issues

The limitations of observational data available for the study of damaging weather conditions (e.g., storms and extreme temperature events) are discussed. Crop and property insurance loss records are advocated as a potential supplement to traditional weather observations, as they integrate specific information about the spatial dimension of damaging weather conditions and the cost of damage they cause. Insurance loss data may also be analyzed in combination with meteorological data sets to derive indicator variables for the detection of damaging weather events.Two sets of insurance data are described. One record provides adjusted property losses associated with "catastrophic" weather events since 1949, and the other is an index of the amount of crop-hail losses per year since 1948. Additionally, an example of the benefits of the combination of insurance and meteorological data is presented through a selection of results from a recent study of freezing temperatures in the southeastern United States and associated insurance claims related to pipe bursting.If insurance data are to be applied in the future in similar studies of damaging weather conditions, it is essential that the insurance industry continues to collect and adjust loss data and periodically confirm that adjustment factors are temporally consistent.     

济宁东部山区风能资源开发潜力研究

分别利用常规地面观测站、区域气象观测站(无人值守加密自动气象站)和临时人工测量站的资料对济宁地区东部山区风能资源进行了对比分析研究。结果表明,处在不同位置的观测站资料对济宁东部山区风能资源开发潜力的估算有较大影响,常规地面观测站或处于测风环境不好的观测站往往低估山区的风能资源;计算结果表明,济宁地区东部山区春季风能资源丰富,可利用风力发电灌溉农田,有效地缓解济宁东部山区部分地区春旱。     

A Model Output Machine Learning Method for Grid Temperature Forecasts in the Beijing Area

In this paper, the model output machine learning (MOML) method is proposed for simulating weather consultation, which can improve the forecast results of numerical weather prediction (NWP). During weather consultation, the forecasters obtain the final results by combining the observations with the NWP results and giving opinions based on their experience. It is obvious that using a suitable post-processing algorithm for simulating weather consultation is an interesting and important topic. MOML is a post-processing method based on machine learning, which matches NWP forecasts against observations through a regression function. By adopting different feature engineering of datasets and training periods, the observational and model data can be processed into the corresponding training set and test set. The MOML regression function uses an existing machine learning algorithm with the processed dataset to revise the output of NWP models combined with the observations, so as to improve the results of weather forecasts. To test the new approach for grid temperature forecasts, the 2-m surface air temperature in the Beijing area from the ECMWF model is used. MOML with different feature engineering is compared against the ECMWF model and modified model output statistics (MOS) method. MOML shows a better numerical performance than the ECMWF model and MOS, especially for winter. The results of MOML with a linear algorithm, running training period, and dataset using spatial interpolation ideas, are better than others when the forecast time is within a few days. The results of MOML with the Random Forest algorithm, year-round training period, and dataset containing surrounding gridpoint information, are better when the forecast time is longer.     

Linking Inuit knowledge and meteorological station observations to understand changing wind patterns at Clyde River,Nunavut

Connecting indigenous and scientific observations and knowledge has received much attention in the Arctic, not least in the area of climate change. On some levels, this connection can be established relatively easily, linking observations of similar phenomena or of various effects stemming from the same cause. Closer examinations of specific environmental parameters, however, can lead to far more complex and difficult attempts to make those connections. In this paper we examine observations of wind at Clyde River, Nunavut, Canada. For Inuit, many activities are governed by environmental conditions. Wind, in particular, is identified by Inuit as one of the most important environmental variables, playing a key role in driving sea ice, ocean, and weather conditions that can either enable or constrain hunting, travel, or other important activities. Inuit observe wind patterns closely, and through many means, as a result of their close connection to the land and sea. Inuit in many parts of Nunavut are reporting changes in wind patterns in recent years. At Clyde River, a community on the eastern coast of Baffin Island, Inuit have observed that at least three key aspects of wind have changed over the last few decades: wind variability, wind speed, and wind direction. At the same time, wind observations are also available from an operational weather station located at Clyde River. An analysis of this information shows little change in wind parameters since the mid-1970s. Though the station data and Inuit observations correspond in some instances, overall, there is limited agreement. Although the differences in the two perspectives may point to possible biases that may exist from both sources—the weather station data may not be representative of the region, Inuit observations or explanations may be inaccurate, or the instrumental and Inuit observations may not be of the same phenomena—they also raise interesting questions about methods for observing wind and the nature of Arctic winds.     

Automatic Identification of Clear-Air Echoes Based on Millimeter-wave Cloud Radar Measurements

Millimeter-wave cloud radar(MMCR) provides the capability of detecting the features of micro particles inside clouds and describing the internal microphysical structure of the clouds. Therefore, MMCR has been widely applied in cloud observations. However, due to the influence of non-meteorological factors such as insects, the cloud observations are often contaminated by non-meteorological echoes in the clear air, known as clear-air echoes. It is of great significance to automatically identify the clear-air echoes in order to extract effective meteorological information from the complex weather background. The characteristics of clear-air echoes are studied here by combining data from four devices: an MMCR, a laser-ceilometer, an L-band radiosonde, and an all-sky camera. In addition, a new algorithm, which includes feature extraction, feature selection, and classification, is proposed to achieve the automatic identification of clear-air echoes. The results show that the recognition algorithm is fairly satisfied in both simple and complex weather conditions.The recognition accuracy can reach up to 95.86% for the simple cases when cloud echoes and clear-air echoes are separate,and 88.38% for the complicated cases when low cloud echoes and clear-air echoes are mixed.     

变分分析技术在城市气象资料分析中的应用

随着城市气象研究和城市气象服务的深入开展,越工需要分辨率更高、精度更高的观测资料,同时,随着城市气象观测网的不断完善,已能提供较多的常规和非常规观测资料。为了得到更完善的气象要素分布场,首先应对这些常规和非常规观测资料进行客观分析。使用上海市的气象哨、常规气象观测站的观测资料和非常规观测资料进行客观分析。使用上海市的气象哨、常规气象观测站的观测资料和上海市的地表分类信息,对变分分析技术进行了实验。