县级区域自动气象站降水资料查询服务系统的开发与应用

为了给县级气象部门开展强降水警报提供方便实用的操作平台,利用区域自动气象站的降水资料,开发了县级区域自动气象站降水警报与服务系统,该系统可对疑误降水数据进行简易甄审,提供了对降水数据的多种统计查询方法,实现了突发性强降水的自动电话语音警报.该系统自动调用Surfer绘制等值线降水色斑图,自动生成服务文档.通过不同的参数设置可适用于其它县级气象部门.     

自动站小时气温数据的质量控制系统研究

逐小时自动站数据对于气象灾害预警、决策服务及预报预测等十分重要。以国家级自动站小时观测气温数据为基础,分析研究了小时气温数据的疑误形式,针对各种疑误数据,利用国家级台站建站以来的日最高、日最低以及4时次(北京时02点、08点、14点、20点)定时观测气温数据,研制形成了适用于中国自动站(区域站和国家站)逐小时气温数据质量控制系统,并将此系统应用到2006-2010年中国27000多自动站小时气温观测数据中。结果表明：区域站的正确率、可疑率、错误率分别为99.43 %、2.24 ‰和3.45 ‰,国家站则分别为99.82 %、1.27 ‰和0.49 ‰;区域站和国家站数据的可疑率相当,但国家站错误率明显比区域站低一个量级。通过历史数据质量控制结果的分析,证明自动站气温质量控制系统设计合理,可以判断出错误和可疑数据,具有可用性。     

Postprocessing of simulated precipitation for impact research in West Africa. Part II: A weather generator for daily data

Data from global and regional climate models refer to grid cells and, hence, are basically different from station data. This particularly holds for variables with enhanced spatio-temporal variability like precipitation. On the other hand, many applications like for instance hydrological models require atmospheric data with the statistical characteristics of station data. Here, we present a dynamical-statistical tool to construct virtual station data based on regional climate model output for tropical West Africa. This weather generator (WEGE) incorporates daily gridded rainfall from the model, an orographic term and a stochastic term, accounting for the chaotic spatial distribution of local rain events within a model grid box. In addition, the simulated probability density function of daily precipitation is adjusted to available station data in Benin. It is also assured that the generated data are still consistent with other model parameters like cloudiness and atmospheric circulation. The resulting virtual station data are in excellent agreement with various observed characteristics which are not explicitly addressed by the WEGE algorithm. This holds for the mean daily rainfall intensity and variability, the relative number of rainless days and the scaling of precipitation in time. The data set has already been used successfully for various climate impact studies in Benin.     

高频探空温度和风速的质量控制方法研究

针对中国高分辨率探空资料,本文提出了一种计算气候学界限值的方法以满足业务中对资料进行质量控制的需求.首先在垂直方向上将整个大气划分为64层,将落在每层范围内的观测数据都收集到一起进行排序并计算百分位,在此基础上通过比较不同百分位廓线值来获得气候学界限值.除了业务台站,本文还使用了TIPEX-Ⅲ的探空数据来验证本方法在科...     

Spatial modelling of air temperature and precipitation for Andorra (Pyrenees) from daily circulation patterns

Based on the daily sea level pressure (SLP) circulation catalogue obtained by Esteban, Martin-Vide and Mases, Int J Climatol 26:1501–1515, (2006) for Western Europe, high-resolution maps of daily maximum and minimum temperature, mean daily precipitation and daily precipitation probability have been obtained for Andorra (Pyrenees). The 20 daily-circulation patterns cover the period 1960–2001 and were generated using new approaches based on the rotated principal component analysis (PCA) and clustering technique. The final maps of Andorra associated with each circulation pattern have been constructed using altitude, latitude, continentality and solar radiation as multiple regression predictors (Ninyerola, Pons and Roure, Int J Climatol 20:1823–1841, 2000). The daily temperature and rainfall series used from Andorran, French and Catalan/Spanish weather stations have been checked for data quality. The results confirm the complexity of the spatial distribution of meteorological phenomena over mountainous areas such as in Andorra, and show the importance of the Mediterranean and Atlantic influence upon the climate of this country of the Pyrenees. On the other hand, different tests have been made showing that the classification results could improve the resulting interpolated climate maps by the use of the circulation-pattern frequencies.     

空间面板数据模型在地面气温观测资料质量控制中的应用

由于地面气温观测资料的时空分布符合空间面板数据结构特征,提出一种基于改进空间面板数据模型的地面气温观测资料质量控制算法(ST-RH算法)。该算法在利用邻近站地面气温观测资料时空相关性信息对目标站气温观测资料进行质量控制的基础上,兼顾了地面气温与相对湿度之间的强耦合关系,将相对湿度作为解释变量融入算法,增加了算法的内部复杂度,提高了算法的动态稳定性。为了检验该算法的有效性及适应性,利用ST-RH算法对多个场景地面气温观测资料进行质量控制,并与反距离加权算法(IDW算法)和空间回归算法(SRT算法)进行比较分析。试验结果表明,ST-RH算法相对于IDW算法和SRT算法更能有效地标记出地面气温观测资料中的存疑数据,同时多组独立案例的分析结果说明ST-RH算法具有更好的稳定性和适用性。     

Critical analysis of simulated daily temperature data from the ARPEGE-climate model: application to climate change in the Champagne wine-producing region

As global warming is scientifically and widely accepted, its impacts at regional scales are raising many questions for wine producers. In particular, climate parameters, especially temperature, play a decisive role in vine growth and grape ripening. An overview of expected climate change in terms of bioclimatic indexes (Winkler and Huglin) and thermal extremes in the wine-producing region of Champagne is presented. A variable-grid atmospheric general circulation model, ARPEGE-Climate, with a local zoom at 50 km over the area of interest, is used to investigate potential future changes in thermal extremes and bioclimatic indexes. Changes in daily maximum and minimum temperatures at key stages are discussed for three emission scenarios (B1, A1B, A2) that are currently used in studies of impacts of climate change. Model outputs are analyzed and critically assessed for a control period (1971–2000) and for changes in extreme events in relation to future scenarios, such as a decrease in extreme low temperatures in spring (April) during bud break and an increase in extreme high temperatures in summer, associated with more frequent heat waves during ripening.     

GRAPES全球三维变分同化中卫星微波温度计亮温的背景误差及在质量控制中的应用

模式变量背景误差在观测空间的投影,也即观测变量的背景误差包含了变分同化系统的重要信息,其在诊断和分析变分同化系统中资料的影响等方面具有重要作用,特别是在背景场检查质量控制中。在GRAPES全球三维变分同化(3DVar)系统中仅给定了控制变量的背景误差,并未直接给定观测变量的背景误差。为了能够对GRAPES全球3DVar进行全面的诊断和分析,改进卫星微波温度计资料的质量控制,推导出GRAPES全球3DVar同化系统控制变量随机扰动方法估计观测变量的背景误差的公式,为分析和改进GRAPES全球3DVar提供了一个有力工具,并进而估计了AMSU-A亮温的背景误差,分析了AMSU-A不同通道亮温的背景误差特征,将其应用于GRAPES全球3DVar的AMSU-A亮温的背景场检查质量控制中。结果表明,控制变量随机扰动方法估计的GRAPES全球3DVar同化系统AMSU-A亮温的背景误差正确合理。同化循环预报试验结果表明,亮温的背景误差在背景场检查中的应用显著提高了GRAPES全球3DVar同化的亮温资料的数量,显著提高了GRAPES南半球对流层中高层位势高度场的预报技巧。在GRAPES全球3DVar同化系统中推导和实现的控制变量扰动方法为诊断和分析GRAPES全球3DVar观测资料同化效果提供了有力工具。      

A land data assimilation system using the MODIS-derived land data and its application to numerical weather prediction in East Asia

Land Data Assimilation Systems have been developed to generate the surface initial conditions such as soil moisture and temperature for better prediction of weather and climate. We have constructed Korea Land Data Assimilation System (KLDAS) based on an uncoupled land surface modeling framework that integrates high-resolution in-situ observation, satellite data, land surface information from the WRF Preprocessing System (WPS) and the MODIS land products over the East Asia. To present better surface conditions, the KLDAS is driven by atmospheric forcing data from the in-situ rainfall gauges and satellite. In this study, we 1) briefly introduce the KLDAS, 2) evaluate the meteorological states near the surface and the surface fluxes reproduced by the KLDAS against the in-situ observation, and then 3) examine the performance of the mesoscale model initialized by the KLDAS. We have generated a 5-year, 10 km, hourly atmospheric forcing dataset for use in KLDAS operating across East Asia. The KLDAS has effectively reproduced the observed patterns of soil moisture, soil temperature, and surface fluxes. Further scrutiny reveals that the numerical simulations incorporating the KLDAS outputs show better agreement in both the simulated near-surface conditions and rainfall distribution over the Korean Peninsula, compared to those without the KLDAS.     

Statistical downscaling for daily precipitation in Korea using combined PRISM,RCM, and quantile mapping: Part 1, methodology and evaluation in historical simulation

In this study, we present the Parameter-elevation Relationships on Independent Slopes Model (PRISM)-based Dynamic downscaling Error correction (PRIDE) model, which is suitable for complex topographies, such as the Korean peninsula. The PRIDE model is constructed by combining the PRISM module, the Regional Climate Model (RCM) anomaly, and quantile mapping (QM) to produce high-resolution (1 km) grid data at a daily time scale. The results show that the systematic bias of the RCM was significantly reduced by simply substituting the climatological observational seasonal cycle at a daily timescale for each grid point obtained from the PRISM. QM was then applied to correct additional systematic bias by constructing the transfer functions under the cumulative density function framework between the model and observation using six types of transfer functions. K-fold cross-validation of the PRIDE model shows that the number of modeled precipitation days is approximately 90~121% of the number of observed precipitation days for the five daily precipitation classes, indicating that the PRIDE model reasonably estimates the observational frequency of daily precipitation under a quantile framework. The relative Mean Absolute Error (MAE) is also discussed in the framework of the intensity of daily precipitation.     

BP-CCA方法用于中国冬季温度和降水的可预报性研究和降尺度季节预测

使用变形的典型相关分析(BP-CCA)方法,基于交叉检验的结果建立了东亚冬季500 hPa大尺度环流和中国冬季温度、降水的最优BP-CCA降尺度预测模型,并在此基础上进行了中国冬季温度和降水的可预报性研究,表明用东亚冬季500hPa高度场降维后的大尺度环流来解释中国冬季温度,平均距平相关系数(ACC)为0.7左右,最高可达0.9,解释中国冬季降水的平均ACC为0.3左右,最高可达0.7,温度的可预报性远高于降水,且二者的可预报水平存在明显的区域差异。可预报性研究表明东亚冬季500 hPa大尺度环流异常与中国冬季温度、降水异常有密切的联系,BP-CCA方法可以很好地揭示大尺度环流与温度、降水的内在联系,并且物理意义清晰。在东亚大尺度环流系统中,东亚大槽和西太平洋副热带高压是影响中国冬季温度、降水异常的重要系统。进一步利用国家气候中心海气耦合模式(CGCM/NCC)回报和预测的500 hPa环流场和BP-CCA方法对温度和降水进行降尺度预测应用,对温度和降水的预测效果明显高于模式直接输出的结果,而且对温度预测的改善高于对降水的改善。对模式预测的环流进行EOF(经验正交函数)分析,表明BP-CCA方法对降尺度要素预报的可预报性来源于CGCM/NCC对500 hPa高度场主要大尺度特征的模拟能力较好。     

A Test Pattern Identification Algorithm and Its Application to CINRAD/SA(B) Data简

A variety of faulty radar echoes may cause serious problems with radar data applications,especially radar data assimilation and quantitative precipitation estimates.In this study,＂test pattern＂ caused by test signal or radar hardware failures in CINRAD （China New Generation Weather Radar） SA and SB radar operational observations are investigated.In order to distinguish the test pattern from other types of radar echoes,such as precipitation,clear air and other non-meteorological echoes,five feature parameters including the effective reflectivity data percentage （Rz）,velocity RF （range folding） data percentage （RRF）,missing velocity data percentage （RM）,averaged along-azimuth reflectivity fluctuation （RNr,z） and averaged along-beam reflectivity fluctuation （RNa,z） are proposed.Based on the fuzzy logic method,a test pattern identification algorithm is developed,and the statistical results from all the different kinds of radar echoes indicate the performance of the algorithm.Analysis of two typical cases with heavy precipitation echoes located inside the test pattern are performed.The statistical results show that the test pattern identification algorithm performs well,since the test pattern is recognized in most cases.Besides,the algorithm can effectively remove the test pattern signal and retain strong precipitation echoes in heavy rainfall events.     

A study of weather types at Athens and Thessaloniki and their relationship to circulation types for the cold-wet period, part I: two-step cluster analysis

This paper presents a method for grouping weather types that occur over an area, which combines meteorological parameters, reflecting air mass characteristics at the surface, with synoptic conditions prevailing over an area. Five quantitative meteorological parameters are used in the procedure: temperature, precipitation, relative humidity, wind velocity and sunshine duration. In addition, two qualitative variables related to the prevailing circulation type and whether it is cyclonic or anticyclonic are also included. The study period is 43 years (1958–2000) and is restricted to the cold and wet sub-period of the year, December–March. Weather types are defined using a relatively new method of cluster analysis, two-step cluster analysis, which allows the simultaneous use of both quantitative and qualitative variables. The aim of the present study is to distinguish primary weather patterns so that the investigation into the relationship between weather patterns and circulation types will be more effective. For Athens, six weather types are created, whereas for Thessaloniki five are produced. For both stations, only two weather types are related to anticyclonic situations. The majority of the identified weather types correspond to a distinctive and well-defined synoptic situation. Each weather type differs from the others, not only in terms of the circulation conditions referring to it, but also with reference to meteorological variables such as temperature and precipitation. The results of the evaluation of the aforementioned procedure are considered to be highly satisfactory.     

星载毫米波测云雷达在研究冰雪天气形成的云物理机制方面的应用潜力

从2008年1月10日起,受强冷空气和暖湿气流共同影响,中国南方大部分地区遭遇1954年以来罕见的冰冻天气,此次天气过程持续时间长、冰冻范围广、受灾程度重.文中简要介绍了毫米波雷达的探测特点及衰减特性;重点利用CloudSat 卫星上搭载的3 mm波长云廓线毫米波雷达(CPR)的探测结果分析了1月28日、2月10日南方冰雪天气形成的云物理机制,并且与C波段测雨雷达探测结果对比;结果表明:(1)毫米波雷达具有高空间分辨率,能够清楚地反映云的垂直和水平结构,且清晰地反映云中0℃层融化带的垂直特征.(2)1月28日湖南冻雨、2月10日贵州冻雨分别是"冰雪-雨-过冷雨"和"过冷云-过冷雨"两种典型的云物理机制,云内0℃层融化带的强度和厚度与近地面温度的高低是能否形成冻雨天气的关键因素.(3)毫米波雷达在冰冻天气研究中有很大的应用潜力;充分将毫米波雷达与天气测雨甫达以及其他遥感手段结合,可以取长补短、相得益彰.发展毫米波探测技术将对研究各种天气形成的微观物理机制、云物理的发展、气候变化的研究及人工影响天气等工作均有重要意义.     

A study of weather types at Athens and Thessaloniki and their relationship to circulation types for the cold-wet period, part II: discriminant analysis

A discriminant analysis is applied in order to determine the relationships between circulation types in the middle troposphere and prevailing weather types over two major Greek cities, Athens and Thessaloniki. In order to describe the synoptic conditions, an automatic classification scheme for the Greek region is used. For each circulation type identified (14 in total), several meteorological parameters at the 500 hPa level are calculated such as geopotential heights and their anomalies, temperature and relative vorticity. Weather group-types that reflect the conditions at the surface, were previously defined using a two-step cluster analysis. These types result from a combination of five meteorological parameters—maximum temperature, precipitation amount, relative humidity, wind velocity and sunshine duration. The study period is 43 years long (1958–2000) and is restricted to the cold and wet period of the year, from December until March. For Athens, six weather types are developed, whereas for Thessaloniki five are produced. By means of a stepwise discriminant analysis (DA) model, the most important variables from the 500 hPa level are found and are used to generate the necessary functions that can discriminate weather types over the two stations. The aim of the present study is first to discriminate weather types effectively and to identify the most important discriminating variables, and second, to connect these weather types to elements of the prevailing synoptic pattern, through mathematical functions provided by DA. The results of the evaluation of the aforementioned procedure are considered to be very satisfactory.     

Air temperature and atmospheric precipitation fields in the regions with a sparse measurement network (with a reference to the Lena River Basin)

A technique for spatial detailing of temperature and precipitation aimed at correcting archive data is developed. It is based on topographic, reflective, and other characteristics of the surface. A detailed areal distribution of monthly mean temperature and precipitation is derived for the Lena River basin, a region which is extremely irregularly and poorly covered by meteorological observational data.     

High-resolution mesoscale analysis data from the South China heavy rainfall experiment (SCHeREX): Data generation and quality evaluation

In this study, the observational data acquired in the South China Heavy Rainfall Experiment (SCHeREX) from May to July 2008 and 2009 were integrated and assimilated with the US National Oceanic and Atmospheric Administration’s (NOAA) Local Analysis and Prediction System (LAPS; information available online at ). A high-resolution mesoscale analysis dataset was then generated at a spatial resolution of 5 km and a temporal resolution of 3 h in four observational areas: South China, Central China, Jianghuai area, and Yangtze River Delta area. The quality of this dataset was evaluated as follows. First, the dataset was qualitatively compared with radar reflectivity and TBB image for specific heavy rainfall events so as to examine its capability in reproduction of mesoscale systems. The results show that the SCHeREX analysis dataset has a strong capability in capturing severe mesoscale convective systems. Second, the mean deviation and root mean square error of the SCHeREX mesoscale analysis fields were analyzed and compared with radiosonde data. The results reveal that the errors of geopotential height, temperature, relative humidity, and wind of the SCHeREX analysis were within the acceptable range of observation errors. In particular, the average error was 45 m for geopotential height between 700 and 925 hPa, 1.0–1.1°C for temperature, less than 20% for relative humidity, 1.5–2.0 m s⁻¹ for wind speed, and 20°–25° for wind direction. The above results clearly indicate that the SCHeREX mesoscale analysis dataset is of high quality and sufficient reliability, and it is applicable to refined mesoscale weather studies.