基于主客观环流分型的强降水数值预报MODE检验方法及其在2019年暖季东北地区的应用

本文构建了基于主客观环流分型的强降水数值预报空间检验(MODE)方法框架,并利用该框架对欧洲中期天气预报中心全球模式(ECMWF)和中国气象局区域中尺度数值天气预报模式(CMA_MESO)的2019年暖季东北地区强降水预报进行检验。结果表明,2019年暖季东北地区54个强降水日的环流型可分为:西风槽型(15个)、副热带高压影响型(13个)、急流型(5个)、西部(12个)和东部冷涡型(9个)。其中,西风槽型和急流型以区域性强降水为主,模式对其强降水发生与否的预报能力强,TS评分较高;西部、东部冷涡型强降水的局地性强,模式对其强降水发生与否的预报能力差,TS评分低;副热带高压影响型也以区域性强降水为主,模式对其强降水发生与否的预报能力也比较强,但是对其强降水质心位置、强度、面积等属性预报偏差较大,TS评分也相对较低。另外,从两种模式预报性能对比看,CMA_MESO强降水强度和面积预报较实况普遍偏强,虽然其预报的TS评分一般高于ECMWF,但其对强降水预报的空报率也都比ECMWF大,对强降水的属性预报偏差一致性一般也低于ECMWF,其预报的可订正性整体上不及ECMWF。

A Study on Reconstruction of Surface Wind Speed in China Due to Various Climate Variabilities

Using European Centre for Medium-Range Weather Forecasts Reanalysis V5(ERA5)reanalysis data,this study investigated the reconstruction effects of various climate variabilities on surface wind speed in China from 1979 to 2022.The results indicated that the reconstructed annual mean wind speed and the standard deviation of the annual mean wind speed,utilizing various climate variability indices,exhibited similar spatial modes to the reanalysis data,with spatial correlation coefficients of 0.99 and 0.94,respectively.In the reconstruction of six major wind power installed capacity provinces/autonomous regions in China,the effects were notably good for Hebei and Shanxi provinces,with the correlation coefficients for the interannual regional average wind speed time series being 0.65 and 0.64,respectively.The reconstruction effects of surface wind speed differed across seasons,with spring and summer reconstructions showing the highest correlation with reanalysis data.The correlation coefficients for all seasons across most regions in China ranged between 0.4 and 0.8.Among the reconstructed seasonal wind speeds for the six provinces/autonomous regions,Shanxi Province in spring exhibited the highest correlation with the reanalysis,with a coefficient of 0.61.The large-scale climate variability indices showed good reconstruction effects on the annual mean wind speed in China,and could explain the interannual variability trends of surface wind speed in most regions of China,particularly in the main wind energy provinces/autonomous regions.

基于ARIMA模型对定西天气数据的分析与预测

由于天气对农业生产、水资源管理和自然灾害预防等具有重要影响,文章采用ARIMA模型来实现对天气的有效预测。通过利用ACF和PACF图粗略确定ARIMA模型的参数,最终确定最优模型:ARIMA(1,1,1)为日最低气温模型,其残差序列自相关函数与偏自相关函数基本落在95%置信区间内;同时Ljung-Box Q统计结果表明残差不存在相关关系(P>0.05),即残差为白噪声,满足随机性假设;最终计算误差(日最低气温)RMSE、MAPE、MAE分别为2.63、1.22%、2.06,预测结果良好,为定西天气的预测提供了可行的方案。

沧州地区春霜冻特征及短期预报方法的研究

为提早做出春霜冻预判以减少对农作物的危害,利用2016-2023年沧州市春季气象资料,采用皮尔逊相关系数、TS评分等方法,对沧州市春霜冻特征和预报指标进行了统计分析及检验。结果表明,沧州市春霜冻发生在3月至4月,结束日期主要在3月下旬-4月上旬,多发生在晴朗、软风、低湿的天气背景下,空间上呈西多东少的特征。以单因素最低气温判定春霜冻是否发生时,多年平均差值(最低气温与最低地温)并非是最优指标,大多数气象观测站表现为前者低于后者。在日最低气温相同的情况下,天气状况和湿度是影响霜冻形成的关键因素,天气越晴好,湿度越小,越容易形成霜冻。加入天气状况和湿度因素后,以最优指标预报春霜冻时全区TS较单因素时提高了7%左右。检验证明,根据最低气温、天气状况、湿度,采用最优指标查表法预报春霜冻的预报效果更好,比普通查表法更适合应用在沧州市春霜冻预报中。

OPERATIONAL ENSEMBLE FORECASTING AND ANALYSIS OF TROPICAL CYCLONES OVER THE WESTERN NORTH PACIFIC(INCLUDING THE SOUTH CHINA SEA)

Based on the tropical cyclone data from the Central Meteorological Observatory of China, Japan Meteorological Agency, Joint Typhoon Warning Center and European Centre for Medium-Range Weather Forecasts （ECMWF） during the period of 2004 to 2009, three consensus methods are used in tropical cyclone （TC） track forecasts. Operational consensus results show that the objective forecasts of ECMWF help to improve consensus skill by 2%, 3%-5% and 3%-5%, decrease track bias by 2.5 kin, 6-9 km and 10-12 km for the 24 h, 48 h and 72 h forecasts respectively over the years of 2007 to 2009. Analysis also indicates that consensus forecasts hold positive skills relative to each member. The multivariate regression composite is a method that shows relatively low skill, while the methods of arithmetic averaging and composite （in which the weighting coefficient is the reciprocal square of mean error of members） have almost comparable skills among members. Consensus forecast for a lead time of 96 h has negative skill relative to the ECMWF objective forecast.

Analysis of stable components for extended-range (10-30 days) weather forecast:A case study of continuous overcast-rainy process in early 2009 over the mid-lower reaches of the Yangtze River

A continuous overcast-rainy weather(CORW) process occurred over the mid-lower reaches of the Yangtze River(MLRYR) in China from February 14 to March 9 in 2009,with a large stretch and long duration that was rarely seen in historical records.Using the empirical orthogonal function(EOF),we analyzed the geopotential height anomaly field of the NCEP-DOE Reanalysis II in the same period,and defined the stable components of extended-range(10-30 days) weather forecast(ERWF).Furthermore,we defined anomalous and climatic stable components based on the variation characteristics of the variance contribution ratio of EOF components.The climatic stable components were able to explain the impact of climatically averaged information on the ERWF,and the anomalous stable components revealed the abnormal characteristics of the continuous overcast-rainy days.Our results show that the stable components,especially the anomalous stable components,can maintain the stability for a longer time(more than 10 days) and manifest as monthly scale low-frequency variation and ultra-long-wave activities.They also behave as ultra-long waves of planetary scale with a stable and vertically coherent structure,reflect the variation of general circulation in mid-high latitudes,display the cycle of the zonal circulation and the movement and adjustment of the ultra-long waves,and are closely linked to the surface CORW process.

Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model

Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.

A SIMILARITY SCHEME FOR QUANTITATIVE FORECAST OF PRECIPITATION OF TYPHOONS

A quantitative scheme is put forward in our work of forecasting the storm rainfall of typhoons for specific sites.Using the initial parameters,weather situations and physical quantities as well as numerical weather prediction products,the scheme constructs multivariate,objective and similarity criteria for environmental factors for the time between the current and forthcoming moment within the domain of forecast.Through defining a non-linear similarity index,this work presents a comprehensive assessment of the similarity between historical samples of typhoons and those being forecast in terms of continuous dynamic states under the multivariate criteria in order to identify similar samples.The historical rainfall records of the similar samples are used to run weighted summarization of the similarity index to determine site-specific and quantitative forecasts of future typhoon rainfall.Samples resembling the typhoon being forecast are selected by defining a non-linear similarity index composed of multiple criteria.Trial tests have demonstrated that this scheme has positive prediction skill.

基于多目标协同训练的风电功率预测提升算法

“双碳”目标下,电力系统加速转型,风电预测技术对构建高比例新能源的新型电力系统具有重要意义。为提升风电功率预测的准确性和鲁棒性,文中提出一种基于多目标协同训练的数值天气预报(numerical weather predicition,NWP)隐式校正算法。首先,分析了NWP校正的必要性和基于NWP显式校正的二步预测法存在的问题;然后,针对二步预测法存在的问题,基于多目标协同训练的优化方式利用神经网络进行NWP隐式校正,以端到端的方式训练模型,同时实现NWP隐式校正和风电功率预测的功能。结合某风电场实测数据开展具体算例分析,证明了所提算法对短期及中长期风电功率预测均有提升作用。此外,该算法仅需1个网络且避免了二次计算,节省了计算存储成本。

适用于新疆电网的风电短期功率预测系统研究

通过分析不同风电功率预测方法的机理和算法,结合新疆风电场的地域特点及风电的基础数据情况,针对新疆各风电场的运行现状,利用微观气象学理论与人工神经网络算法,对风电场分别建模,对子模型进行拟合处理,从而构建预测综合模型,实现新疆风电场短期功率的预测。基于综合预测模型,利用模块化设计方法开发了新疆电网风电规律预测系统。将设计的系统应用于新疆在用风电场的月功率与周功率预测,结果表明该系统对总功率预测结果的均方根误差均在10%以下,符合设计的预期要求。

根据天气预报估算参照腾发量

参照腾发量ET0的实时预测对实时灌溉预报很重要。通过对普通天气预报信息进行解析,取得可用的合理数据,利用Penm an-M on te ith方法估算了北京大兴试区近10年逐日参照腾发量,最后与由实测气象数据计算的结果进行了对比分析。结果表明:解析气象因子与实测数据中,日照时数的相关系数为0.99,风速为0.90;t检验值日照时数为376.9042,风速为122.4295,远远大于t分布相应临界值2.576(α=0.01),表明其可以认为是来自一个近似的总体样本。由日最低气温确定的实际水汽压和由实测相对湿度计算的实际水汽压,二者相关系数达到0.93,t检验值为153.3015。运用天气预报信息计算预测的ET0与实测数据用Penm an-M on te ith方法计算的ET0相比,相关系数达到0.9613,t检验值为209.1194,说明二者具有高度显著的线性相关性。如果日常天气预报准确度能够达到90%以上,用此理论预测参照腾发量将具有较大的参考价值和实际意义。

基于天气预报的漳河灌区参考作物腾发量预报方法比较

为了提出适合湖北省漳河灌区的参考作物腾发量预报方法,以FAO56-Penman-Monteith公式采用历史气象数据计算出的值为基准,利用天气预报数据,比较Hargreaves-Samani(HS)法、逐日均值修正法及该文改进的逐日均值修正法在该灌区钟祥站点的预报精度,并评价各方法适用性。结果表明:利用这3种方法进行参考作物腾发量预报时,1~7 d预见期平均绝对误差均值分别为0.75、0.80、0.76 mm/d,均方根误差分别为1.00、1.07、1.05 mm/d,相关系数分别为0.82、0.80、0.80。1 d预见期最优预报方法为改进逐日均值修正法,2~7 d预见期的最优方法均为HS法。总体而言,预报精度最好的为HS法、改进逐日均值修正法次之、逐日均值修正法最差。对于漳河灌区,建议采用HS法进行预报,可为灌溉预报提供较为准确的数据基础。

区域集合预报扰动方法研究进展综述

集合预报方法是解决单一数值预报不确定性问题的有效手段,而针对强天气预报的中尺度区域集合预报技术已逐渐受到国内外的重视。对于区域集合预报而言,由于其不确定性来源较为复杂,如何发展有效的扰动方法是研究的热点和难点。本文根据国内外区域集合预报的研究进展,从初值扰动、模式扰动以及侧边界扰动三个方面进行了总结和回顾,并对扰动方法的发展趋势进行了介绍。对于初值扰动,较为主流的方法有动力降尺度,沿用传统的由全球集合扰动方法发展而来的技术为区域集合产生初值,以及专门为区域集合设计的扰动方法。鉴于这些方法各有利弊,目前对于初值扰动方法的研究已经开始发展充分包含大尺度和小尺度不确定性信息的混合扰动方法。区域集合预报模式扰动的研究以物理过程扰动为主,典型方法为多物理过程组合以及随机物理过程扰动,其中多物理过程组合方法简单有效,而随机物理过程扰动方法的物理意义更为明确,是物理过程扰动的趋势。通过多模式组合进行模式扰动的方法也开展了一些相关研究,且对于台风等强天气预报均显示出相对于单模式集合较好的效果。侧边界扰动的主流方法是由大尺度集合预报场来为区域集合提供不同的侧边界,研究结果表明此种侧边界扰动方法简便易行,且有助于提高区域集合预报较长预报时效离散度和预报技巧。

双流机场低能见度天气预报方法研究

在信息量较大,而预报对象与预报因子的关系又不清楚的状况下,智能机器学习方法是解决这类问题的较好手段。利用1997—2001年成都站的常规探空资料和双流机场的地面观测资料,使用支持向量机(Support VectorMachines,简称SVM)方法,选取多种核函数进行双流机场低能见度天气的预报建模试验。测试结果表明:以径向基函数和拉普拉斯函数构造的SVM预报模型实验效果最好,Ts评分分别为0.287和0.292,远高于双流机场低能见度天气出现的频率(0.155)。试验结果还表明:以径向基函数构造的SVM预报模型空报较多,漏报较少;而以拉普拉斯函数构造的SVM预报模型空报较少,漏报较多。因此,如果强调模型对低能见度天气预报的准确性,则应采用以拉普拉斯函数构造的预报模型,如果强调对低能见度天气的预防性,则应采用以径向基函数构造的预报模型。

云物理初始化对一次强对流天气数值预报的影响研究

基于第二代华东快速更新循环同化预报模式系统,针对2015年4月28日华东强对流天气,分析了云初始化对强对流数值预报的作用和影响。有无云初始化试验对比结果表明,在循环系统中使用云初始化,能够显著提高0~6 h的降水预报评分,强降水的位置预报更接近实况。云初始化能较好地改善初始场水凝物的质量分布,提供较准确的相关对流系统的初始信息,改进强对流区域内水凝物的预报效果,有效避免了模式初始阶段的降水滞后现象,缩短了模式由于初始微物理信息缺失引起的"spin-up"时间。而积分6 h以后的结果与无云初始化的结果差别不大。

广西“回南天”发生特征及预报着眼点

利用常规MICAPS数据资料,对广西"回南天"发生特征及预报着眼点进行分析研究。结果表明:(1)"回南天"发生在春季低温阴雨后期迅速回暖的转变过程中;(2)有利"回南天"发生的环流形势共同特征为:500 hPa我国北支西风气流转为纬向环流,南支槽加深并向东移动,850 hPa有西南急流,地面冷空气减弱,华南静止锋减弱北抬;(3)T-lnp探空曲线中,锋区逆温层上限持续下降到850 hPa以下,次日落地消失;(4)室外空气露点温度高于室内物体表面温度,暖湿空气中的水汽入室遇冷后,在物体表面发生相变凝结;(5)根据前一天最低气温、当天露点温度及升幅,将"回南天"划分为重度、中度和轻度3个等级;(6)"回南天"有冷性结束和暖性结束两种方式。所得成果可应用到预报业务中。

湖北省冬季大雪成因分析与预报方法研究

针对湖北省冬季大雪天气预报难题,使用常规观测资料和数值预报产品,分析了1988—2005年发生在湖北省冬季的15次大雪过程。结果表明,地面冷空气、700 hPa江南西南急流和500 hPa西风带低槽是决定湖北省冬季大雪的三个主要天气系统,700 hPa江南西南急流强弱决定湖北省大雪强度,地面冷空气强度决定湖北省降温幅度;归纳出有利湖北省大雪的温度条件的垂直分布特征;由于锋面抬升和西南低空急流的作用,在对称不稳定条件下产生倾斜上升和下沉运动,形成中尺度倾斜环流,在充沛环境水汽条件下,产生大雪天气;采取物理参数指标结合数值预报建立的湖北省大雪客观预报方法,在实时预报业务中预运行效果较好。

东北高速公路行车安全气象条件预报业务系统

概述了东北高速公路行车安全气象条件预报业务系统的总体结构,介绍了系统包含的行车安全气象条件预报专用数据库、行车安全气象条件预报方法和预报工作平台。业务应用结果表明:系统为预报员提供了能够满足实时业务需要的高速公路行车安全气象条件预报工作平台,研制的大雾、积雪、道路结冰和湿滑等客观预报方法可为交通管理部门提供高速公路行车安全气象参考信息。

数据挖掘技术应用于天气预报的可行性研究

介绍了数据挖掘的原理和方法,以及数据挖掘的相关知识.并以天气预报中的统计预报方法为背景,采用数理统计为基础的数据挖掘方法,对历史天气资料进行了挖掘.

强对流实时短期预报业务应用

θse特型法是一种强对流天气的短期预报方法 ,它把强对流天气预报化成预报引发背景条件下高能量预警型的强对流大概率事件。 1 995～ 1 998年在上海地区进行强对流实时短期预报 ,准确率达 890/ 0 。