城乡火险预报模式探讨

文章探讨了建立火险预报模式的必要性和可行性，分析了1981～1990年辽宁省火灾次数与风速、月降水量和相对湿度的关系。并从概念模式出发，讨论了与火险有关的逐因子，建立了定量的火险预报模式，试用效果较好。     

一种偏差订正方法在平昌冬奥会气象预报的应用

为了提高GRAPES_3 km（Global/Regional Assimilation and Prediction System）模式在2018年平昌冬奥会气象服务中的预报能力,采用一阶自适应的卡尔曼滤波方法对GRAPES_3 km模式的2 m气温、2 m相对湿度和10 m风开展偏差订正。结果表明:偏差订正方法明显提高了地面要素的预报效果,其中2 m气温的均方根误差整体减小到2℃左右,站点订正改善率为10%~60%;10 m风速的均方根误差减小到2 m·s-1左右,站点订正改善率为10%~45%;2 m相对湿度减小到20%以下,站点订正改善率为0~20%。与韩国气象厅LDAPS（Local Data Assimilation and Prediction System）及美国宇航局NU-WRF（NASA-Unified WRF）模式相比,GRAPES_3 km模式的风速预报表现更为优异,各站点整体预报效果明显优于LDAPS和NU-WRF模式。偏差订正方法可有效改善模式在复杂地形条件下的预报能力,是提高精细化预报准确率的重要手段。     

北方地区小麦蚜虫气象适宜度预报模型构建

根据1958—2015年我国北方地区8个主产省（市）小麦蚜虫分省发生面积和发生程度资料、1958—2015年601个气象站点相应逐日气象资料和农业气象站小麦发育期资料,采用相关分析、主成分分析和逐步回归等方法,并利用相关系数法进行因子普查,结合小麦蚜虫适宜生理气象指标和华北、黄淮小麦生育期规律,筛选影响小麦蚜虫年发生程度的关键气象因子,构建分区域的小麦蚜虫气象适宜度预报模型,并将气象适宜度指数划分为非常适宜、适宜、较适宜、不适宜4个等级,以反映气象条件对小麦蚜虫发生发展的适宜程度。结果表明:筛选出影响华北小麦蚜虫年发生程度的8个关键气象因子,影响黄淮小麦蚜虫年发生程度的6个关键气象因子。建立的华北、黄淮模型回代检验等级准确率分别为91.2%,93.1%,2016—2018年3年外推预报平均准确率均在75%以上;利用黄淮模型反演苏皖两省2016—2018年小麦蚜虫发生等级、异地检验3年预报效果均较理想。模型适用于从气象角度对华北、黄淮及江淮地区小麦蚜虫发生等级进行监测和预报。     

太阳辐射预报滚动订正方法研究

利用2013年1月至2014年12月北京南郊观象台逐时观测总辐射以及BJ-RUC模式系统预报的该站未来24h逐时总辐射、云量、水汽混合比、云水、云冰含量等14个气象要素数据,运用多种线性订正方案对总辐射预报值进行订正,重点分析了不同方法、不同季节、不同样本数的订正效果差异。结果表明:1不同季节辐射订正的影响因素不尽相同,需采用不同的组合订正因子,其中总辐射、2m比湿、2m相对湿度、低云量、中云量、高云量、总云量、云水雨冰雪霰混合比、水汽混合比可作为推荐因子;2最优样本数选取时需考虑季节差异;3逐时滚动订正方案的订正效果较好,明显优于非滚动方案。订正后总辐射误差显著减小,而且79%的时刻有改进,明显减小了预报偏大的系统误差;4冬春季订正效果优于夏秋季,这与云的宏观和微观物理量预报效果的季节差异有关。本文研究结果可为太阳能资源评估、总辐射和光伏电站发电量预报提供有效的改进方法。     

郑州市相对湿度预报服务系统

从专业服务需求出发，将概率统计学中多种统计方法与天气预报方法相结合，为用户提供了１９８１－１９９０年１０年间有关相对湿度的各项咨询资料，并分月讨论了逐日１４时２４小时相对湿度概率特征区间、特征日和综合预报方法，建立了郑州市相对湿度预报服务系统。供专业咨询和日常相对湿度预报业务使用。     

中国区域3种数值模式的地面气象要素预报初步评估

ECMWF 和 GRAPES(Global/Regional Assimilation and Prediction System)预报产品是国内目前主要的应用服务产品.为了了解ECMWF和GRAPES预报产品的性能,使用户在实际应用中,根据需求可选择性地应用上述预报产品,本文利用中国气象局2421个国家级自动站和81...     

基于特定因子的河南省干热风客观预报方法

利用2000—2014年5月1日到6月10日河南省121个气象观测站点的逐日观测数据、欧洲中心模式预报资料,对河南省干热风天气进行分析,总结了干热风天气形势分类模型,同时利用多元回归法建立了河南省干热风天气的客观预报方法。分析结果得出:河南省干热风天气发生主要形势为西北气流型、高压脊型和纬向环流型3类;通过多元回归分析筛选出日最高温度预报因子为前一日最高气温、当日最低气温、08:00气温、EC850hPa 24h温度预报,相对湿度预报因子为EC850hPa 24h相对湿度预报、前一日14:00相对湿度、当日08:00露点温度,风速预报因子为EC细网格过去3h10m阵风预报,建立温度、湿度和风速3要素的预报方程;利用预报方程对2014年预报时段的天气进行检验,结果表明,对于轻干热风预报的TS评分为62%,重干热风预报的TS评分为64%。     

Operative Scheme for the Short-range Complex Forecasting of Surface Air Temperature and Humidity

The statistical scheme is proposed for the forecast of surface air temperature and humidity using operative weather forecasts with 3–5-day lead time from the best forecasting hydrodynamic models as well as the archives of forecasts of these models and observational data from 2800 weather stations of Russia, Eastern Europe, and Central Asia. The output of the scheme includes the forecasts of air temperature for the standard observation moments with the period of 6 hours and extreme temperatures with the lead times of 12–120 hours. The accuracy of temperature and humidity forecasts for the period from July 2014 till June 2017 is much higher than that for the forecasts of original hydrodynamic models. The skill scores for extreme temperature forecasts based on the proposed method are compared with the similar results of the Weather Element Computation (WEC) forecasting scheme and forecasts by weathermen.     

An integrated evaluation of thirteen modelling solutions for the generation of hourly values of air relative humidity

The availability of hourly air relative humidity (HARH) data is a key requirement for the estimation of epidemic dynamics of plant fungal pathogens, in particular for the simulation of both the germination of the spores and the infection process. Most of the existing epidemic forecasting models require these data as input directly or indirectly, in the latter case for the estimation of leaf wetness duration. In many cases, HARH must be generated because it is not available in historical series and when there is the need to simulate epidemics either on a wide scale or with different climate scenarios. Thirteen modelling solutions (MS) for the generation of this variable were evaluated, with different input requirements and alternative approaches, on a large dataset including several sites and years. A composite indicator was developed using fuzzy logic to compare and to evaluate the performances of the models. The indicator consists of four modules: Accuracy, Correlation, Pattern and Robustness. Results showed that when available, daily maximum and minimum air relative humidity data substantially improved the estimation of HARH. When such data are not available, the choice of the MS is crucial, given the difference in predicting skills obtained during the analysis, which allowed a clear detection of the best performing MS. This study represents the first step of the creation of a robust modelling chain coupling the MS for the generation of HARH and disease forecasting models, including the systematic validation of each step of the simulation.     

城市相对湿度的直接模式输出修正预报的研制

给出了一种非统计的直接模式输出（ＤＭＯ）的修正预报方法，它无需任何历史资料（包括数值预报资料及观测资料），仅以我国国家气象中心实时Ｔ１０６模式的离地２ｍ之相对湿度预报格点值（１．１２５°×１．１２５°经纬度）为基础，经非线性插值、部分系统性误差订正及相对湿度的日较差修正后制作全国２６４个城市的相对湿度预报。其中北京、上海、香港等１０个城市的相对湿度预报经预报员把关后，每天晚间由中央电视台播出。     

泌阳春蚕生长的气象条件及春茧产量预报

分析研究了春蚕生长的气象条件，得出了影响春蚕生长诸多气象因素中关键的因素是温度和相对湿度。并以此为线索，寻找春茧产量预报因子，运用双重检验逐步回归方法建立泌阳春蚕产茧量预报方程，其历史拟合率达９１．０％。     

深圳市流感就诊率季节特征及夏季流感就诊率气象预报模型

利用深圳市2003-2007年5年的流感样病例资料和同期气象资料,对深圳市夏季流感与气象条件的关系进行了分析与统计。研究发现深圳市流感高峰期发生在春季和夏季,且存在向夏季转移的趋势,这种流感流行的季节差异与天气条件有很大的关系,受气温、相对湿度的影响显著,在平均气温处于25-30℃之间,相对湿度较高的天气条件下易出现流感高峰。用最低气温、最小相对湿度和日照时数为预报因子,建立了深圳市夏季流感就诊率的等级预报模型。     

北方公路交通气象环境识别及安全管理策略研究

用沈山高速公路沿线10个交通气象站的逐10 min气温、能见度、路面温度、降水、湿度和风等资料,采用多元逐步线性回归、最小二乘曲线拟合、MLP神经网络建立数学模型对北方公路路面温度、能见度以及冰雪路面等交通气象环境进行识别。通过抽取随机样本对模型进行检验,结果表明:所建立的模型对交通气象环境具有较好的模拟和识别作用。基于交通工程理论建立的不同路况条件下车速预估和交通安全指数模型对公路交通安全管理具有很好的应用价值。     

GRAPES-TYM模式对我国东部近海海雾预报性能评估

基于2020年上半年我国东部近海站点观测资料和葵花-8卫星反演海雾产品对我国自主研发的GRAPES-TYM模式进行了海雾预报性能评估。点、面检验结果表明：模式48 h和72 h TS分别为0.40和0.36,黄海海雾预报性能最优,34°～37°N海域内大部分站点TS高于0.50。黄海海雾落区预报检验显示均压场形势下预报最准确,平均临界成功指数为0.35;气旋后部海雾多空报。2 m相对湿度预报偏差具有局地性特征,相对湿度低估的站海雾预报击中率、TS相对低,反之亦然。另外,模式对成雾相关气象要素预报误差相对小且对成雾有利时海雾预报基本正确;模式预报风向较实际风向偏东南,易出现冷偏差和湿偏差,虚假的有利温湿条件导致海雾空报。     

Impact of surface observations on simulation of rainfall over NCR Delhi using regional background error statistics in WRF-3DVAR model

In this study, efforts are made to improve the simulation of heavy rainfall events over National Capital Region (NCR) Delhi during 2010 summer monsoon, using additional observations from automatic weather stations (AWS). Two case studies have been carried out to simulate the relative humidity, wind speed and precipitation over NCR Delhi in 48-h model integrations; one from 00UTC, August 20, 2010, and the other from 00UTC, September 12, 2010. Several AWS installed over NCR Delhi in the recent past provide valuable surface observations, which are assimilated into state-of-the-art weather research and forecasting (WRF) model using the three-dimensional variational data assimilation (3DVAR). The quality of background error statistics (BES) is a key component in successful 3DVAR data assimilation in a mesoscale model. In this study, the domain-dependent regional background error statistics (RBS) are estimated using National Meteorological Center method in the months of August and September 2010 and then compared with the global background error statistics (GBS) in the WRF model. The model simulations are analyzed and validated against AWS and radiosonde observations to quantify the impact of RBS. The root mean square differences in the spatial distributions of precipitation, relative humidity and wind speed at the surface showed significant differences between both the global and regional BES. Similar differences are also observed in the vertical distributions along the latitudinal cross section at 28.5°N. Model-simulated fields are analyzed at five different surface stations and one upper air station located in NCR Delhi. It is found that in 24-h model simulation, the RBS significantly improves the model simulations in case of precipitation, relative humidity and wind speed as compared to GBS.     

浙江省温度和相对湿度释用技术及其效果检验分析

基于多模式的要素预报和浙江省乡镇站点观测资料,结合全省天气统计特点,利用最优集成方案,改进了温度和相对湿度的1~7 d预报。统计检验发现,模式的温度预报在浙江省中南部主要表现为系统性偏差,在浙江省北部平原地区主要为随机误差。使用滑动平均误差订正后,浙中南等地形复杂地区温度预报的系统性偏差明显减小。在模式订正基础上,使用动态集成进一步减小了浙北平原地区温度预报的随机误差。基于温湿关系,使用改进后的温度预报对相对湿度预报进行订正。与传统的加权平均方法相比,改进后的温度预报均方根误差减小16.7%,相对湿度预报均方根误差减小13.8%,对改善浙江省精细化预报有一定参考意义。     

Validation of the Atmospheric Infrared Sounder Retrieval Products over China and Their Application in Numerical Mode

The atmospheric infrared sounder (AIRS) instrument onboard Aqua Satellite is a high spectral resolution infrared sounder. In recent years, AIRS has gradually become the primary method of atmospheric vertical observations. To examine the validation of AIRS retrieval products (V3.0) over China, the AIRS surface air temperature retrievals were compared with the ground observations obtained from 540 meteorological stations in July 2004 and January 2005, respectively. The sources of errors were considerably discussed. Based on the error analysis, the AIRS retrieved surface air temperature products were systemically corrected. Moreover, the AIRS temperature and humidity profile retrievals were compared with T213 numerical forecasting products. Because T213 forecasting products are not the actual atmospheric states,to further verify the validation, the AIRS temperature and humidity profile products were assimilated into the MM5 model through the analysis nudging. In this paper, the case on February 14, 2005 in North China was simulated in detail. Then, we investigated the effects of AIRS retrievals on snowfall, humidity field,vertical velocity field, divergence field, and cloud microphysical processes. The major results are: (1) the errors of AIRS retrieved surface air temperature products are largely systematic deviations, for which the influences of terrain altitude and surface types are the major reasons; (2) the differences between the AIRS atmospheric profile retrievals and T213 numerical prediction products in temperature are generally less than 2 K, the differences in relative humidity are generally less than 25%; and (3) the AIRS temperature and humidity retrieval products can adjust the model initial field, and thus can improve the capacity of snowfall simulation to some extent.     

广州地区湿球黑球温度指数预报研究

利用广州地区2009年10月至2010年3月的湿球温度、干球温度、黑球温度,以及附近自动气象站相同时刻的温度、风速、湿度资料进行统计分析,在对广州地区湿球黑球温度（Wet Bulb Globe Temperature,WBGT）统计、特征分析的基础上,分别采用昼夜两段模式和分时模式构建出WBGT预报方程。利用WBGT的实测资料,对上述两种预报方程和直接引用的香港天文台WBGT预报方程一同分析预报误差,对比发现：直接引用的香港天文台的预报方程预报效果最差,分时段WBGT预报模式总体偏差最小;三种预报方法在夜间比白天预报偏差小,昼夜预报法和分时预报法预报偏差不超过1℃,两者对夜间的WBGT预报能力相当,但在白天时段分时预报法明显比昼夜预报法的预报偏差小。据此,文章选取预报效果最好的分时模式建立预报方程,文中最后针对预报方程中温度、相对湿度因子由于预报误差而导致的WBGT预报误差进行了讨论。基于此研究成果,气象部门为第16届亚洲运动会的马术比赛提供了准确、周到的气象服务,为马术比赛的赛事安排及比赛的成功举办提供了重要的决策依据。     

Validation of the Atmospheric Infrared Sounder Retrieval Products over China and Their Application in Numerical Model

The atmospheric infrared sounder (AIRS) instrument onboard Aqua Satellite is a high spectral resolution infrared sounder. In recent years, AIRS has gradually become the primary method of atmospheric vertical observations. To examine the validation of AIRS retrieval products (V3.0) over China, the AIRS surface air temperature retrievals were compared with the ground observations obtained from 540 meteorological stations in July 2004 and January 2005, respectively. The sources of errors were considerably discussed. Based on the error analysis, the AIRS retrieved surface air temperature products were systemi-cally corrected. Moreover, the AIRS temperature and humidity profile retrievals were compared with T213 numerical forecasting products. Because T213 forecasting products are not the actual atmospheric states, to further verify the validation, the AIRS temperature and humidity profile products were assimilated into the MM5 model through the analysis nudging. In this paper, the case on February 14, 2005 in North China was simulated in detail. Then, we investigated the effects of AIRS retrievals on snowfall, humidity field, vertical velocity field, divergence field, and cloud microphysical processes. The major results are: (1) the errors of AIRS retrieved surface air temperature products are largely systematic deviations, for which the influences of terrain altitude and surface types are the major reasons; (2) the differences between the AIRS atmospheric profile retrievals and T213 numerical prediction products in temperature are generally less than 2 K, the differences in relative humidity are generally less than 25%; and (3) the AIRS temperature and humidity retrieval products can adjust the model initial field, and thus can improve the capacity of snowfall simulation to some extent.     

地下水浅埋条件下冬小麦和大豆土壤水分动态预报模型研究

用统计方法和水量平衡法推导出江淮地区潜水蒸发经验计算模型。利用农田水分平衡原理分别在江淮地区建立了引入潜水蒸发量和没有引入潜水蒸发量的冬小麦和大豆土壤水分动态预报模型,并对这两种模型在地下水浅埋条件下的预报准确度进行比较。1980年的比较结果是:当预报时效为10天时,两种作物7个时段的土壤水分平均绝对误差前者为8.2 mm,后者为20.1 mm,平均相对误差分别为2.8%和6.8%。引入潜水蒸发量后,冬小麦和大豆土壤水分动态预报模型的预报准确度明显提高。