随机参数扰动方法对中国冬季降水集合预报的影响

降水数值预报有很大的不确定性,与降水预报密切相关的物理过程参数化方案中关键参数的不确定性是降水数值预报误差来源之一,对这些参数引入随机扰动的随机参数扰动方法（Stochastically Perturbed Parameterization,简称SPP方法）可以代表模式降水预报的不确定性,是国际集合预报前沿研究领域。为了认识该方法能否代表中国冬季降水数值预报的不确定性,为业务应用提供科学依据,基于中国气象局中尺度区域集合预报模式（Global/Regional Assimilation and Prediction System-Regional Ensemble Prediciton System,简称GRAPES-REPS）,从对模式降水预报不确定性有较大影响的积云对流、云微物理、边界层及近地面层等四个参数化方案中选取了16个与降水密切相关的关键参数,引入了随机参数扰动方法,并通过2018年12月12日至2019年1月12日总计31天的冬季集合预报试验,对比分析了SPP方法对等压面要素及降水的集合预报效果。结果显示:在冬季应用SPP方法时,等压面要素的概率预报技巧总体来说优于无SPP方法扰动的对比试验,且对于低层、近地面要素的改进效果优于对中高层等压面要素的改进;但对降水概率预报而言,尽管检验评分数值略优于对比预报试验,但并未通过显著性检验,这表明,在东亚冬季风影响下,随机参数扰动方法对中国冬季降水概率预报技巧没有明显的改进。究其原因,可能是由于SPP方法主要代表对流性降水预报的不确定性,而中国冬季降水过程主要与斜压不稳定发生发展有关,模式降水以大尺度格点降水为主,对流性降水较少,故对冬季降水预报改进不明显,这为业务集合预报模式中应用随机参数扰动方法提供了科学依据。     

多普勒雷达资料动态定量估测台风小时降水量的研究

在充分考虑传统的最优化方法和概率配对法优缺点的基础上,使用一种改进的最佳窗概率配对法计算Z-I关系中的系数A和b,得到了雷达测得的基本反射率因子Z和雨量计实时测到的小时降水量I的动态关系.利用温州多普勒雷达体扫资料和浙江省自动雨量站资料,使用该方法对"海棠"(Haitang)和"麦莎"(Matsa)两个台风分别进行了动态计算,得到了不同系数的Z-I关系,进而对两个台风的小时降水量进行了定量估测.使用变分技术对估测的小时降水量进行了校准.结果表明,不同台风Z-I关系的系数差别较大,因而造成台风小时降水量的很大不同.使用雷达基本反射率来估测台风小时降水量,能够清楚表现出台风的螺旋雨带和其中的中小尺度雨团,估测的台风小时降水量与实况基本接近.经过变分校准的估测降水量可以较好地表现出台风雨带与地面中尺度流场动力结构的对应关系.误差统计分析表明,变分校准后的估测台风小时降水量要明显好于变分校准前的估测台风小时降水量.变分校准法既保留了雷达估测台风小时降水量的分布特征,又使估测的台风小时降水雨量与实况的误差明显减小.     

Improvement of radar quantitative precipitation estimation based on real-time adjustments to <Emphasis Type="Italic">Z-R</Emphasis> relationships and inverse distance weighting correction schemes

The errors in radar quantitative precipitation estimations consist not only of systematic biases caused by random noises but also spatially nonuniform biases in radar rainfall at individual rain-gauge stations.In this study,a real-time adjustment to the radar reflectivity-rainfall rates(Z-R) relationship scheme and the gauge-corrected,radar-based,estimation scheme with inverse distance weighting interpolation was developed.Based on the characteristics of the two schemes,the two-step correction technique of radar quantitative precipitation estimation is proposed.To minimize the errors between radar quantitative precipitation estimations and rain gauge observations,a real-time adjustment to the Z-R relationship scheme is used to remove systematic bias on the time-domain.The gauge-corrected,radar-based,estimation scheme is then used to eliminate non-uniform errors in space.Based on radar data and rain gauge observations near the Huaihe River,the two-step correction technique was evaluated using two heavy-precipitation events.The results show that the proposed scheme improved not only in the underestimation of rainfall but also reduced the root-mean-square error and the mean relative error of radar-rain gauge pairs.     

在用降水逐日监测干旱的方法中引入蒸发

降水是旱涝最重要的影响因子。在加权平均降水量WAP方法中,当目前没有降水,且前期降水的影响衰减掉以后,WAP便接近于0了,然而此时土壤可能还是较湿润的;若在随后的日子里仍没有降水,WAP则继续保持接近于0的值,但土壤会变的越来越干。为了区分出在WAP同样都为接近于0的状态下土壤湿度(反映在蒸发上)的差异,本文将WAP指数作了进一步的发展,即在所建立的模型中,将蒸发量E显式地表达出来。也就是,涝(旱)状态的变化不仅受降水量P所强迫,而是受P-E所强迫。新方法的基本原理和模型是与WAP方法相仿的,这个显式地考虑了蒸发的新指数WAPE,其值有正有负,接近于正态分布,因而不需再作正态化处理。结果表明,WAPE指数对旱涝的逐日监测有很好的效果。     

Forecasting monthly precipitation in Central Chile: a self-organizing map approach using filtered sea surface temperature

Western South America is subject to considerable inter-annual variability due to El Ni?o–Southern Oscillation (ENSO) so forecasting inter-annual variations associated with ENSO would provide an opportunity to tailor management decisions more appropriately to the season. On one hand, the self-organizing maps (SOM) method is a suitable technique to explore the association between sea surface temperature and precipitation fields. On the other hand, Wavelet transform is a filtering technique, which allows the identification of relevant frequencies in signals, and also allows localization on time. Taking advantage of both methods, we present a method to forecast monthly precipitation using the SOM trained with filtered SST anomalies. The use of the SOM to forecast precipitation for Chillan showed good agreement between forecasted and measured values, with correlation coefficients (r ²) ranging from 0.72 to 0.91, making the combined use filtered SST fields and SOM a suitable tool to assist water management, for example in agricultural water management. The method can be easily tailored to be applied in other stations or to other variables.     

定量测量降水量的回波结构自适应算法研究

为提高临近预报中对流性降水估测的准确性,分析了统计法估算降水的局限性。依据降水物理机制和降水回波结构,研究雷达反射率因子定量测量降水量(QPE-Qualitative Precipitation Estimate)的自适应算法,旨在减少由于雨滴谱变化导致的Z-I关系不稳定所引起的降水量测量误差。同时考虑组合反射率因子RC和垂直液态水含量VIL两个参量对降水的影响,建立适于城市区域的动态自适应的Z-I关系,改进对强降水严重低估的问题。     

基于EMD 和集合预报技术的气候预测方法

气候系统是典型的非平稳性系统,然而对于气候观测数据的处理通常是在时间序列平稳的假定下完成的,比如气温和降水的多步预报,这通常会导致预报准确度较低。为改进该缺陷,首先将非平稳数据序列分解成平稳的、多尺度特征的本征模态函数分量(IMF),再使用数值集合预报与逐步回归分析相结合的方式对每一个IMF 分量构建不同的预报模型,最后线性拟合成预报结果。通过Visual Studio 2008 开发平台使用上述方法建立了一个短期气候预报系统,采用广西区88 个气象站1957—2005 年的2 月距平气温数据进行实际验证。结果表明,相对于普通预测和单一预测方法,加入了EMD 和集合预报技术的方法在仅用历史资料进行多步预测的情况下,对于气候的变化趋势以及突发性气候具有更好的预报能力。      

雷达定量降水估计技术及效果评估

为提高雷达定量估测降水的精度,利用广东省6部新一代多普勒天气雷达(CINRAD/SA)回波资料和雨量计降水量观测资料,采用概率配对法(PFT,Probability-fitting technique)建立Z-I关系进行单部雷达降水估测,并采用最优插值法(OI,Optimum Interpolation)对降水估计进行订正;为扩大降水估测的范围,对多部雷达的降水估计进行拼接,采取重叠区域以各部雷达的均方根误差平方的倒数作为权重系数(iω==1/RMSE(K)2/n∑i-1/RMSE(i)2)进行加权平均,并分别分析比较上述方法得到的降水估计与单纯OI雨量计及与雷达拼图回波强度得到的降水估计的优劣。以上各环节误差分析表明,对于单部雷达,雨量计降水强度与其上空9点平均的雷达回波强度关系最为密切;6部相同型号的雷达估测降水精度各异。交叉检验表明,OI雷达法对单部和多部雷达估测降水均可取得较好的校准效果;对于多部雷达的降水估测,单部雷达先分别进行OI订正后拼接,然后对重叠区再次OI订正的结果比直接对未订正的单部雷达降水估计拼接后统一做一次OI订正的效果好。多部雷达降水估计拼接时,前期对于单部雷达降水估计的订正尤为重要;多部雷达降水估计的拼接值精度要明显高于OI雨量计,而相比由雷达拼图回波强度得到的降水估计而言,前者也优于后者。因此,多部雷达降水估计的拼接方法,对雷达资料的应用有较好的参考价值,在业务上也有一定的应用前景。     

华南前汛期暴雨C波段雷达特征应用研究

运用广州白云机场C波段雷达回波强度及径向风资料对华南前汛期强降水过程进行雨带降水估计及其移动特征预测.C波段雷达在雨量充沛地区的强降水背景下,尽管回波强度被衰减,但是近距离范围内其探测云雨精细化结构的能力较强.所采取的雷达数据质量控制系列处理,能够保留雷达数据原有特征,有效滤去杂波和噪声并缓解雷达低仰角数据杂波多、体扫面上沿径向远近高度差较大的问题,并对降水估测提供了技术保障.最优化雷达Z-I强降水估测方法基于单次过程体扫信息,具有计算简洁快速的特点,但是同一体扫面上云状差异对最优化方法参数值比较敏感,混用相同参数,影响降水估测效果.对同一体扫面上雷达云状回波进行区域划分,并选择对应测雨站点,做最优化参数分别确定,有效改善最优化雷达降水估测,提高了C波段雷达在机场近距离范围的应用效果.运用雷达体扫时间分辨率高的特点,识别雷达径向风辐合线以及强回波中心位置,并分别应用外推法预测雨带走向、移速等,验证效果良好.     

重庆山地区域气象要素空间插值方法对比

利用重庆地区1999年和2018年气象数据, 分别采用薄盘光滑样条、协同克里金、普通克里金、反距离加权4种方法, 从年和月两种尺度对气温、降水、太阳总辐射三个要素进行空间插值; 采取交叉验证方法, 用MAE、MRE、RMSE评估插值精度, 确定各要素最优插值方法。结果表明: 气温和太阳总辐射最优插值方法为薄盘光滑样条, 降水为反距离加权; 插值精度上气温、太阳总辐射高值月份优于低值月份, 降水则相反, 但三个要素均表现出年尺度优于月尺度。MRE检验表明, 插值精度为气温>太阳总辐射>降水, 1999年年尺度插值精度分别为1.86%、4.60%、6.87%, 月尺度插值精度分别为2.79%、5.82%、17.42%;2018年太阳总辐射年、月尺度插值精度分别为3.03%、4.88%, 区域站加密后气温、降水年尺度插值精度分别为2.03%、11.20%, 月尺度对应插值精度分别为3.20%、23.14%。     

基于频率匹配法的江西省ECMWF降水预报订正研究

利用2016—2019年ECMWF（European Centre for Medium-Range Weather Forecasts）降水预报资料和江西省93个国家气象站降水资料,基于频率匹配法进行降水偏差订正,采用4种方法统计降水频率对降水预报进行订正试验（不分区试验）,根据江西省汛期暴雨气候特征对汛期降水进行分区订正试验,并对典型强降水个例进行分析。结果表明: 频率匹配法降低了模式预报小雨的空报率和大雨、暴雨的漏报率,预报技巧改进明显。在4种降水频率统计方法中,准对称滑动平均法效果最好。分区试验对强降水的订正效果优于不分区试验,该试验对模式预报正技巧暴雨过程的订正能力大于无技巧过程。对于模式预报效果差（TS=0）、一般（0 < TS < 0.2）、好（TS≥0.2）的暴雨过程,分区试验改善的概率分别为40.8%、89.1%和65.3%。频率匹配分区订正后强降水面积更加接近实况,但强降水落区不能得到明显的改善。订正方法对模式预报强降水形态、位置与实况较接近的过程,效果较好。     

A CRPS-Based Spatial Technique for the Verification of Ensemble Precipitation Forecasts

Traditional precipitation skill scores are affected by the well-known“double penalty”problem caused by the slight spatial or temporal mismatches between forecasts and observations. The fuzzy (neighborhood) method has been proposed for deterministic simulations and shown some ability to solve this problem. The increasing resolution of ensemble forecasts of precipitation means that they now have similar problems as deterministic forecasts. We developed an ensemble precipitation verification skill score, i.e., the Spatial Continuous Ranked Probability Score (SCRPS), and used it to extend spatial verification from deterministic into ensemble forecasts. The SCRPS is a spatial technique based on the Continuous Ranked Probability Score (CRPS) and the fuzzy method. A fast binomial random variation generator was used to obtain random indexes based on the climatological mean observed frequency, which were then used in the reference score to calculate the skill score of the SCRPS. The verification results obtained using daily forecast products from the ECMWF ensemble forecasts and quantitative precipitation estimation products from the OPERA datasets during June-August 2018 shows that the spatial score is not affected by the number of ensemble forecast members and that a consistent assessment can be obtained. The score can reflect the performance of ensemble forecasts in modeling precipitation and thus can be widely used.     

区域Delaunay三角剖分法在全国平均降水量中的应用

介绍了Delaunay三角网的性质及其算法类型;根据1980～2009年全国2200个观测站的降水量资料,将观测点和采集的边界点共同进行普通的Delaunay三角剖分,通过删除边界点及其区域外的三角形以实现区域Delaunay三角剖分,得到了较理想全国陆地的Delaunay三角网;随后对球面上的三角片进行面积计算,在已知站点的经纬度情况下,将大地坐标系转换到空间直角坐标系中,应用平面三角余弦定理获得球面三角内角,从而求得三角片面积,并以面积大小确定各个站点降水量的权重系数,得到全国平均降水量值。对比分析了30年的全国不同时间尺度(日、月、年)平均降水量,Delaunay三角法对应全国平均降水量均值和标准差都明显低于算术平均法,但是两种方法计算的降水量值的相关系数较高;通过Shapiro-Wilk方法进行正态性检验分析,两种计算方法求得的年平均降水量总体服从正态分布;在方差奇性的F检验中,两者的方差具有非奇性特点;使用t检验,在显著性α=0.05时,Delaunay三角剖分法计算的全国平均降水量总体均值偏小。最后,根据欧洲和日本数值模式2009年的降水预报,对于两方法计算结果进行了比较,分析表明在较大区域的平均降水量计算中,较之于传统的算术平均法,基于区域的Delaunay三角剖分法更为合理;区域平均降水量不仅和计算方法有关,还和区域气候特点有密切关系。     

区域决策气象服务产品自动化制作关键技术——以自动站小时累加降水量产品为例

文章对气象应急服务业务中区域决策气象服务产品制作技术进行了分析。讨论了自动站小时降水量较小时的格点插值方法,实现了零值自动站插补的实况降水插值方法,经检验,该方法能够有效提高降水量插值准确性和美观度。提出了采用ArcGIS ModelBuilder模型构建技术,及基于ArcObjects开发的逐小时降水量累加组件、气象要素插值组件、图形产品制作组件,结合ArcGIS提供的空间分析组件,建立区域逐小时累加降水数据处理和图形产品制作模型,完成了决策服务图形产品高效率、自动化执行及高精度图形产品输出。     

天气预报的业务技术进展

该文总结回顾了中央气象台近年来的天气预报业务技术进展。天气预报质量的历史演变显示了预报业务水平的提高, 这种业务能力的提高既反映了预报技术的发展, 也带来了天气预报业务的变化。对业务天气预报中各种预报技术应用进展的分析表明:数值预报在天气预报业务能力提高中发挥着重要的基础性作用; 同时, 基于对不同尺度天气影响系统发展演变过程深入认识的基础上, 天气学的预报方法依然是预报业务中的重要技术方法; 动力诊断预报已成为灾害性天气预报中的重要手段之一, 数值预报产品的解释应用是实现气象要素精细定量预报的技术途径。     

Errors and Correction of Precipitation Measurements in China

In order to discover the range of various errors in Chinese precipitation measurements and seek a correction method, 30 precipitation evaluation stations were set up countrywide before 1993. All the stations are reference stations in China. To seek a correction method for wind-induced error, a precipitation correction instrument called the ＂horizontal precipitation gauge＂ was devised beforehand. Field intercomparison observations regarding 29,000 precipitation events have been conducted using one pit gauge, two elevated operational gauges and one horizontal gauge at the above 30 stations. The range of precipitation measurement errors in China is obtained by analysis of intercomparison measurement results. The distribution of random errors and systematic errors in precipitation measurements are studied in this paper. A correction method, especially for wind-induced errors, is developed. The results prove that a correlation of power function exists between the precipitation amount caught by the horizontal gauge and the absolute difference of observations implemented by the operational gauge and pit gauge. The correlation coefficient is 0.99. For operational observations, precipitation correction can be carried out only by parallel observation with a horizontal precipitation gauge. The precipitation accuracy after correction approaches that of the pit gauge. The correction method developed is simple and feasible.     

双线偏振多普勒雷达对一次降雹超级单体发展减弱阶段的演变分析

2015年4月28日,在高空冷涡的天气背景下,一个伴有较长生命史中气旋的超级单体在上海南汇双线偏振多普勒雷达观测范围内经历了发展减弱阶段,并产生了冰雹、雷雨大风、短时强降水等灾害性天气。利用常规天气观测、南汇双线偏振多普勒雷达、双雷达反演风场等资料分析发现,超级单体在发展成熟阶段呈现出回波悬垂、低层入流缺口、中气旋以及三体散射等经典特征,以及表示雷暴处于发展加强阶段的差分反射率因子柱。差分反射率因子柱通常意味着雷暴中上升气流的加强,同时说明大量的水滴可以被强上升气流托举到0℃层以上,形成过冷水滴,从而有利于冰雹的形成。超级单体经过的区域0～6 km垂直风切变达到了22～26 m·s~(-1),强垂直风切变环境有利于水平涡度发展,南汇雷达观测范围内中气旋维持了100 min左右,有利于雷暴的发展维持。此外,基于模糊逻辑法对此次降雹强对流天气过程开展了相态识别,结果表明,模糊逻辑法对此次强对流天气过程中的冰雹、降水等不同性质的降水能够进行有效的识别,有助于对雷暴降水相态本质的认识。     

Application of Radar Reflectivity Factor in Initializing Cloud-Resolving Mesoscale Model. Part Ⅱ： Numerical Simulation Experiments

Microphysics elements and vertical velocity retrieved were incorporated using the nudging method into the initial data assimilation of GRAPES （Global/Regional Assimilation and Prediction System） model. Simulation experiments indicated that nudging technique was effective in forcing the model forecast gradually consistent to the observations, yielding the thermodynamically and dynamically balanced analysis field. As viewed from the simulation results, water vapor is vital to precipitation, and it is a governing factor for the amount and duration of precipitation. The initial cloud water, rain water, and vertical velocity determine the strength distribution of convection and precipitation at the beginning time of forecast; the horizontal wind field steers the motion of the mesoscale weather system embedded in and impacts the position of precipitation zone to a large extent. The simulation experiments show that the influence of the initial retrieval data on prediction weakens with the increase of forecast time, and within the first hour of forecast, the retrieval data have an important impact on the evolution of the weather system, but its influence becomes trivial after the first three hours. Changing the nudging coefficient and the integral time-spacing of numerical model will bring some influences to the results. Herein only one radar reflectivity was used, the radar observations did not cover the whole model domain, and some empirical parameters were used in the retrieval method, therefore some differences still lie between simulation and observation to a certain extent, and further studies on several aspects are expected.     

Application of Radar Reflectivity Factor in Initializing Cloud-Resolving Mesoscale Model. Part Ⅱ: Numerical Simulation Experiments

Microphysics elements and vertical velocity retrieved were incorporated using the nudging method into the initial data assimilation of GRAPES (Global/Regional Assimilation and Prediction System) model.Simulation experiments indicated that nudging technique was effective in forcing the model forecast gradually consistent to the observations, yielding the thermodynamically and dynamically balanced analysis field. As viewed from the simulation results, water vapor is vital to precipitation, and it is a governing factor for the amount and duration of precipitation. The initial cloud water, rain water, and vertical velocity determine the strength distribution of convection and precipitation at the beginning time of forecast; the horizontal wind field steers the motion of the mesoscale weather system embedded in and impacts the position of precipitation zone to a large extent. The simulation experiments show that the influence of the initial retrieval data on prediction weakens with the increase of forecast time, and within the first hour of forecast, the retrieval data have an important impact on the evolution of the weather system, but its influence becomes trivial after the first three hours. Changing the nudging coefficient and the integral time-spacing of numerical model will bring some influences to the results. Herein only one radar reflectivity was used, the radar observations did not cover the whole model domain, and some empirical parameters were used in the retrieval method, therefore some differences still lie between simulation and observation to a certain extent, and further studies on several aspects are expected.     

Response of the East Asian summer monsoon to doubled atmospheric CO2: Coupled climate model simulations and projections under IPCC AR4

Summary The East Asian (China, Korea and Japan) summer monsoon precipitation and its variability are examined from the outputs of the coupled climate models performing coordinated experiments leading to the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4). Out of the 22 models examined, 14 reproduce the observed shape of the annual cycle well with peak during the boreal summer (June through August), but with varying magnitude. Three models simulate the maximum a month later and with lower magnitudes. Only one model considerably underestimates the magnitude of the annual cycle. The remaining 4 models show some deviations from the observed. Models are unable to simulate the minimum in July with peaks in June and August associated with northward shifts of the Meiyu-Changma-Baiu precipitation band. The realistic simulation of the annual cycle does not appear to depend on the model resolution. The inter-model variation is slightly larger during summer, implying larger diversity of the models in simulating summer monsoon precipitation. The spatial rainfall patterns are reasonably well simulated by most of the models, with several models able to simulate the precipitation associated with the Meiyu-Changma-Baiu frontal zone and that associated with the location of the subtropical high over the north Pacific. Simulated spatial distribution could be sensitive to model resolution as evidenced by two versions of MIROC3.2 model. The multi-model ensemble (MME) pattern reveals an underestimation of seasonal precipitation over the east coast of China, Korea-Japan peninsular and the adjoining oceanic regions. This may be related with the mass-flux based scheme employed for convective parameterization by majority of the models. Further the inter-model variation of precipitation is about 2 times stronger south of 30° N, than north of this latitude, indicating larger diversity of the coupled models in simulating low latitude precipitation. The simulated inter-annual variability is estimated by computing the mean summer monsoon seasonal rainfall and the coefficient of variability (CV). In general the mean observed seasonal precipitation of 542 mm and CV of 6.7% is very well simulated by most of the models. Except for one model mean seasonal precipitation varies from 400 to 650 mm. However the CV varies from 2 to 9%. Future projections under the radiative forcing of doubled CO₂ scenario are examined for individual models and by the MME technique. Changes in mean precipitation and variability are tested by the t-test and F-ratio respectively to evaluate their statistical significance. The changes in mean precipitation vary from −0.6% (CNRM-CM3) to about 14% (ECHO-G; UKMO-HadCM3). The MME technique reveals an increase varying from 5 to 10%, with an average of 7.8% (greater than the observed CV of 6.7%) over the East Asian region. However the increases are significant over the Korea-Japan peninsula and the adjoining north China region only. The increases may be attributed to the projected intensification of the subtropical high, Meiyu-Changma-Baiu frontal zone and the associated influx of moist air from the Pacific inland. The projected changes in the amount of precipitation are directly proportional to the projected changes in the strength of the subtropical high. Further the MME suggests a possible increase in the length of the summer monsoon precipitation period from late spring through early autumn. The changes in precipitation could be stabilized by controlling the CO₂ emissions.