降水预报-观测概率匹配动态订正法在江西降水集中期的应用与检验

为提高数值预报降水预报的准确率,本文利用欧洲中期天气预报中心的高分辨率数值预报（ECMWF）降水预报资料和江西省国家级气象观测站实况降水资料进行概率匹配,选取Gamma累积概率分布函数用于拟合预报与观测的降水累积概率,通过在2017年江西省一次降水集中期的应用试验,得到以下结论：基于ECMWF的降水预报-观测概率匹配动态订正法由于把最新的预报与实况结果带入概率匹配中,并根据近期模式预报调整及误差不断自动更新各量级降水修正值,可实时动态订正模式降水预报;检验发现ECMWF模式降水产品对于24 h内12 h间隔的10 mm及以下量级的预报普遍偏大,25 mm及以上量级的预报普遍偏小,在江西区域九江沿江地区和景德镇的各量级降水预报较为接近实况、预报效果较好.本降水预报订正法能提高小雨和暴雨的TS评分、降低暴雨的漏报率且提升其命中率,但对大雨及部分中雨的订正效果不佳,在实践中应权衡利弊使用.     

智能网格SCMOC及多模式降水预报对比

以三源融合网格实况降水分析资料CMPAS为参照,基于二分法经典检验、预报评分综合图和面向对象MODE检验等方法,对比分析2021年智能网格预报SCMOC以及ECMWF全球、CMA-Meso中尺度模式在秦岭及周边地区的降水预报表现,主要结论如下：1)ECMWF能够很好地刻画日平均降水量、日降水量标准差以及地形影响下降水量、降水频次的空间分布特征,但对于0.1 mm以上量级的降水预报频次远高于观测,暴雨预报频次低于观测,SCMOC、CMA-Meso日降水量大于等于0.1 mm的降水频次和暴雨频次预报更好;SCMOC不足在于降水的空间精细分布特征描述能力相对较弱。2)ECMWF预报的大于等于0.1 mm降水频次日峰值出现时间整体较观测偏早3 h左右,CMA-Meso、SCMOC与观测总体吻合较好。3)三种产品24 h降水量大于等于0.1 mm的TS(Threat Score)评分数值上基本一致,但降水预报表现的特征显著不同,SCMOC成功率高、命中率低,漏报多、空报少,ECMWF、CMA-Meso则相反;24 h、3 h大雨以上量级降水SCMOC的TS评分、成功率、命中率一致优于其他两种产品...     

Downscaling and projection of precipitation from general circulation model predictors in an equatorial climate region by the automated regression-based statistical method

The authors have applied an automated regression-based statistical method, namely, the automated statistical downscaling (ASD) model, to downscale and project the precipitation climatology in an equatorial climate region (Peninsular Malaysia). Five precipitation indices are, principally, downscaled and projected: mean monthly values of precipitation (Mean), standard deviation (STD), 90th percentile of rain day amount, percentage of wet days (Wet-day), and maximum number of consecutive dry days (CDD). The predictors, National Centers for Environmental Prediction (NCEP) products, are taken from the daily series reanalysis data, while the global climate model (GCM) outputs are from the Hadley Centre Coupled Model, version 3 (HadCM3) in A2/B2 emission scenarios and Third-Generation Coupled Global Climate Model (CGCM3) in A2 emission scenario. Meanwhile, the predictand data are taken from the arithmetically averaged rain gauge information and used as a baseline data for the evaluation. The results reveal, from the calibration and validation periods spanning a period of 40 years (1961–2000), the ASD model is capable to downscale the precipitation with reasonable accuracy. Overall, during the validation period, the model simulations with the NCEP predictors produce mean monthly precipitation of 6.18–6.20 mm/day (root mean squared error 0.78 and 0.82 mm/day), interpolated, respectively, on HadCM3 and CGCM3 grids, in contrast to 6.00 mm/day as observation. Nevertheless, the model suffers to perform reasonably well at the time of extreme precipitation and summer time, more specifically to generate the CDD and STD indices. The future projections of precipitation (2011–2099) exhibit that there would be an increase in the precipitation amount and frequency in most of the months. Taking the 1961–2000 timeline as the base period, overall, the annual mean precipitation would indicate a surplus projection by nearly 14~18 % under both GCM output cases (HadCM3 A2/B2 scenarios and CGCM3 A2 scenario). According to the model simulation, the September–November periods might be the more significant months projecting the increment of the precipitation amount around over 50 %, while the precipitation deficit would be seen in March–May periods.     

2016-2020年广东省定量降水预报检验评估

对2016-2020年全球模式ECMWF和区域模式GZ_GRAPES、基于模式的解释应用和广东省气象局发布的定量降水预报(QPF)进行检验和评估.结果表明:ECMWF和GZ_GRAPES模式对一般性降水预报技巧在逐年提升,对大雨或以上的降水预报技巧的提升缓慢.GZ_GRAPES对大雨以上降水的预报技巧和定量降水预报的精...     

“7·20”郑州特大暴雨的多模式对比及高分辨率区域模式预报分析

7月20日郑州遭遇特大暴雨，郑州站单日降水量（552.5 mm）和1 h降水量（201.9 mm）皆打破了该站建站以来的历史纪录。本文采用地面降水观测、静止卫星观测、再分析资料和数值模式预报数据对此次过程开展了多模式预报偏差原因分析和江苏省精细化天气分析和预报系统（Precision Weather Analysis and Forecasting System，PWAFS）的极端强降水预报能力分析。主要结论：1）此次暴雨过程因副热带高压西伸与台风”烟花”加强使二者之间的东风急流加强，并叠加地形的抬升作用而引起，前者提供了大尺度水汽条件，后者提供了局部动力条件；2）欧洲中期天气预报中心（European Center for Medium-range Weather Forecasts，ECMWF）模式和美国国家环境预报中心全球预报系统（Global Forecast System，GFS）的降水落区较好，中心略偏北，但强度显著偏低。PWAFS模式预报的降水量级高于全球模式，且具有沿地形分布的特征，但存在降水位置偏西和降水范围更为孤立等问题。3）结合再分析资料和PWAFS预报，对应此次强降水区域，7月20日白天存在中低层切变发展成闭合低压系统的过程，为对流发展提供了动力条件。     

European dry spell length distributions, years 1951–2000

Daily precipitation records of 267 European rain gauges are considered to obtain dry spell length (DSL) series along the second half of the twentieth century. A dry spell consists of consecutive days with daily rain amount below a given threshold, R ₀. Four DSL series are obtained for R ₀ values equal to 0.1, 1.0, 5.0, and 10.0 mm/day, and their empirical distributions are properly fitted to different statistical models: Pearson type III (PE3), Weibull (WEI), generalised Pareto, (GPA) and lognormal distributions. The parameters of every model are estimated by L-moments, and the goodness of fit is assessed by quantifying discrepancies between empirical and theoretical distributions in the L-skewness–kurtosis diagrams. The most common best-fitting model is PE3, especially for 0.1 and 1.0 mm/day. Nevertheless, a few stations in southern Europe are better modelled by the WEI distribution. For 5.0 and 10.0 mm/day, the spatial distribution of the best-fitting model is more heterogeneous than for the lowest thresholds. While PE3 is still the preferred model for Western Europe, some DSL series are better fitted to WEI or GPA models. Maps of DSL average and standard deviation and expected lengths for return periods of 2, 5, 10, 25, and 50 years show some common features. Whereas for thresholds of 0.1 and 1.0 mm/day, a N–S gradient is detected, especially in Mediterranean areas; for 5.0 and 10.0 mm/day, a NW–SE gradient is observed in the Iberian Peninsula and a SW–NE gradient in the Scandinavian Peninsula. Then, the vicinity to Atlantic and Arctic Oceans and the Mediterranean Sea, as well as orographic features, are more determining factors than the latitude in patterns associated with the highest R ₀ thresholds. Finally, a regional frequency analysis based on a clustering algorithm is attempted for the four thresholds R ₀, with the PE3 model as the parent distribution for the largest clusters.     

三种数值模式对四川省汛期降水预报性能的检验

应用国家基本观测站资料,基于MET系统的客观统计检验方法,针对24h降水分别评估SWCWARMS模式、GRAPES模式和ECMWF模式对2017～2019年5～10月四川地区汛期预报能力,得到如下几点结论:(1)SWCWARMS模式小到大暴雨降水范围大于实况,GRAPES模式小到暴雨降水范围大于实况、大暴雨多漏报,ECMWF模式小雨和中雨降水范围大于实况、大到大暴雨多漏报,三个模式无降水或微量降水均少于实况。(2)ECMWF模式对四川雨季小到大雨预报能力优于SWCWARMS和GRAPES模式,SWCWARMS模式在部分时次上暴雨和大暴雨预报优于ECMWF模式,GRAPES模式TS评分略偏低。(3)GRAPES模式在2018年秋季开始中雨及以上量级降水预报上改善大于SWCWARMS和ECMWF模式,SWCWARMS模式2019年空报较2017年和2018年显著降低;3个模式在小雨和中雨预报上不相上下,GRAPES模式优势在2019年大雨和暴雨预报上,ECMWF模式优势在2017年秋季和2018年初夏大雨预报上,SWCWARMS模式大雨和暴雨预报能力介于二者之间。(4)ECMWF和SWCWARMS模式川东预报优于川西,GRAPES模式川西预报优于川东;三个模式存在不同程度空报,川东地区空报略多于川西,其中ECMWF模式空报最多。      

概率匹配订正法在湖北襄阳地区降水预报中的应用

数值预报产品在天气预报预警中有着重要的作用。2016—2020年汛期ECMWF模式预报降水与湖北襄阳区域站观测降水的对比分析表明：ECMWF对中雨及以上降雨的预报，第1、2天预报偏小，而第3天预报偏大；三个预报时段强降雨中心位置偏差无规律。为了更好地对ECMWF产品进行释用，提高汛期降水预报准确率，从概率匹配角度研究了不同降水量级订正值，并对2021年汛期ECMWF降水预报进行逐日检验。结果显示：概率匹配订正法可有效地改善模式预报性能，对中雨及以上降雨预报均有良好的订正效果，尤其对第1天暴雨预报改进最为明显。228站平均的TS评分提高了6个百分点，由11.1%增加到17.1%，漏报情况改良了13.5个百分点，由85.0%降为71.5%。采用该订正法开展定量降水预报，由于增加了当地降雨概率分布的背景信息，能表现出比原模式更高的参考价值。     

On the relationship between Indian monsoon withdrawal and Iran’s fall precipitation onset

Indian monsoon is the most prominent of the world’s monsoon systems which primarily affects synoptic patterns of India and adjacent countries such as Iran in interaction with large-scale weather systems. In this article, the relationship between the withdrawal date of the Indian monsoon and the onset of fall precipitation in Iran has been studied. Data included annual time series of withdrawal dates of the Indian monsoon prepared by the Indian Institute for Tropical Meteorology, and time series of the first date of 25 mm accumulated precipitation over Iran’s synoptic weather stations in a 10-day period which is the basis for the cultivation date. Both time series were considered in Julian calendar with the starting date on August 1. The studied period is 1960–2014 which covers 55 years of data from 36 meteorological stations in Iran. By classifying the withdrawal dates of the Indian monsoon in three stages of late, normal, and early withdrawals, its relation with the onset of fall precipitation in western, southwestern, southern, eastern, central, and northern regions of Iran was studied. Results demonstrated that in four out of the six mentioned regions, the late withdrawal of the Indian monsoon postpones the onset of fall precipitation over Iran. No significant relation was found between the onset of fall precipitation in central region of Iran and the monsoon’s withdrawal date. In the western, southwestern, southern, and eastern regions of Iran, the late monsoon delays the onset of fall’s precipitation; while in the south Caspian Sea coastal area, it causes the early onset of autumnal precipitation. The lag in onset of fall precipitation in Iran which is coordinated with the late withdrawal of monsoon is accompanied with prolonged subtropical high settling over Iran’s plateau that prevents the southward movement of polar jet frontal systems. Such conditions enhance northerly wind currents over the Caspian Sea which, in turn, increase the precipitation in Caspian coastal provinces, which has a different behavior from the overall response of Iran’s climate to the late withdrawal of monsoon. In the phase of early monsoon withdrawal, the subtropical jet is located at the 200 hPa level in 32.5° north latitude; compared with the late withdrawal date, it shows a 2° southward movement. Additionally, the 500 hPa trough is also located in the Eastern Mediterranean, and the MSL pressure anomaly is between ? 4 to ? 7 hPa. The Mediterranean trough in the late withdrawal phase is located in its central zones. It seems that the lack of significant correlation between late withdrawal date of Indian monsoon and late fall’s precipitation onset in the central region of Iran depends on three reasons:1. Lack of adequate weather stations in central region of Iran.2. Precipitation standard deviations over arid and warm regions are high.3. Central flat region of Iran without any source of humidity is located to the lee side of Zagros mountain range. So intensification or development of frontal systems is almost prohibited over there.     

Evaluation of 2-m temperature and precipitation products of the Climate Forecast System version 2 over Iran

Using a continuous multi-decadal simulations over the period 1981–2010, subseasonal to seasonal simulations of the Climate Forecast System version 2 (CFSv2) over Iran against the Climatic Research Unit (CRU) dataset are evaluated. CFSv2 shows cold biases over northern hillsides of the Alborz Mountains with the Mediterranean climate and warm biases over northern regions of the Persian Gulf and the Oman Sea with a dry climate. Magnitude of the model bias for 2-m temperature over different regions of Iran varies by season, with the least bias in temperate seasons of spring and autumn, and the largest bias in summer. The model bias decreases as temporal averaging period increases from seasonal to annual. The forecast generally produces dry and wet biases over dry and wet regions of Iran, respectively. In general, 2-m temperature over Iran is better captured than precipitation, but the prediction skill of precipitation is generally high over western Iran. Averaged over Iran, observations indicated that 2-m temperature has been gradually increasing during the studied period, with a rate of approximately 0.5 °C per decade, and the upward trend is well simulated by CFSv2. Averaged over Iran, both observations and simulation results indicated that precipitation has been decreasing in spring, with averaged decreasing trends of 0.8 mm (observed) and 1.7 mm (simulated) per season each year during the period 1981–2010. Observations indicated that the maximum increasing trend of 2-m temperature has occurred over western Iran (nearly 0.7 °C per decade), while the maximum decreasing trend of annual precipitation has occurred over western and parts of southern Iran (nearly 45 to 50 mm per decade).     

辽宁省夏季多模式降水预报检验及晴雨预报技术研究

利用辽宁省291个国家气象观测站的降水资料,对2019年夏季（6-9月）8种模式降水预报及中央气象台格点降水预报进行了检验评估和比较,并采用消空方法进行晴雨预报技术研究。结果表明：2019年,EC模式具有最优的暴雨预报性能,而日本模式暴雨TS评分最高;中尺度模式对于局地性暴雨和短时强降水具有较好的预报潜力,性能较好的是GRAPES_MESO模式和睿图东北3 km模式;全球模式对24 h暴雨的预报频率比实况偏低30%,3 h强降水则偏低60%,中尺度模式对24 h暴雨的预报频率比实况偏高30%,3 h强降水则偏低20%。由于对小量级降水存在较多空报,各模式原始预报的晴雨预报大多呈现空报偏多的情况;使用小量级降水剔除的消空策略能够明显提高晴雨准确率,消空之后EC模式具有最优的晴雨预报性能。分别使用24 h和3 h累计降水量优化消空策略,发现分别取1.0 mm和0.8 mm的阈值进行消空可以使24 h晴雨准确率提高15.58%,3 h晴雨准确率提高10%-30%。     

东北夏季天气分型及EC降水预报空间检验

利用SANDRA（SAN）方法将东北地区2018年5—9月环流背景分型,并在此基础上对EC模式预报的较强降水（>10 mm/24 h）进行空间检验和定量分析。东北地区主要的形势背景分为北部扰动低压型、副热带高压北抬型、东北扰动低涡型、扰动低压东移型。其中,前3类环流型对应较强降水过程发生频率相对较高;将3种类型对应的模式预报较强降水过程进行分析。结果表明：模式对于北部扰动低压型过程中大雨以上量级降水落区面积的预报较实况普遍偏小45%—60%;中雨量级降水落区面积,36 h时效预报较实况偏大40%,84 h时效偏小19%;36 h、60 h、84 h时效,较强降水预报位置偏西分别为0.19°、0.53°、1.39°,平均强度预报分别偏低2.9 mm、3.1 mm、3.4 mm,极值预报分别偏低7.3 mm、8.1 mm、9.4 mm;副热带高压北抬型过程预报面积与实况之间的偏差没有一致的倾向性,预报位置较实况分别偏南0.25°、0.15°、0.37°,降水强度上有65%—72%的个例表现为平均强度及极值预报较实况偏弱的特征;东北扰动低涡型过程,预报位置偏差分别为36 h偏东0.18°、偏南0.55°,60 h偏东0.20°、偏南0.58°和84 h偏东0.74°;另外,3个时效对应平均强度预报分别偏低3.3 mm、3.7 mm、3.9 mm,极值预报平均偏低为10.2 mm、10.6 mm、11.6 mm。     

Evaluation of TIGGE Ensemble Forecasts of Precipitation in Distinct Climate Regions in Iran

The application of numerical weather prediction(NWP) products is increasing dramatically. Existing reports indicate that ensemble predictions have better skill than deterministic forecasts. In this study, numerical ensemble precipitation forecasts in the TIGGE database were evaluated using deterministic, dichotomous(yes/no), and probabilistic techniques over Iran for the period 2008–16. Thirteen rain gauges spread over eight homogeneous precipitation regimes were selected for evaluation.The Inverse Distance Weighting and Kriging methods were adopted for interpolation of the prediction values, downscaled to the stations at lead times of one to three days. To enhance the forecast quality, NWP values were post-processed via Bayesian Model Averaging. The results showed that ECMWF had better scores than other products. However, products of all centers underestimated precipitation in high precipitation regions while overestimating precipitation in other regions. This points to a systematic bias in forecasts and demands application of bias correction techniques. Based on dichotomous evaluation,NCEP did better at most stations, although all centers overpredicted the number of precipitation events. Compared to those of ECMWF and NCEP, UKMO yielded higher scores in mountainous regions, but performed poorly at other selected stations.Furthermore, the evaluations showed that all centers had better skill in wet than in dry seasons. The quality of post-processed predictions was better than those of the raw predictions. In conclusion, the accuracy of the NWP predictions made by the selected centers could be classified as medium over Iran, while post-processing of predictions is recommended to improve the quality.     

Quantitative relationships between precipitation and temperature over Northeast China, 1961–2010

This paper investigates monthly and seasonal precipitation–temperature relationships (PTRs) over Northeast China using a method proposed in this study. The PTRs are influenced by clouds, latent and sensible heat conversion, precipitation type, etc. In summer, the influences of these factors on temperature decrease are different for various altitudes, latitudes, longitudes, and climate types. Stronger negative PTRs ranging from ?0.049 to ?0.075 °C/mm mostly occur in the semi-arid region, where the cold frontal-type precipitation dominates. In contrast, weaker negative PTRs ranging from ?0.004 to ?0.014 °C/mm mainly distribute in Liaoning Province, where rain is mainly orographic rain controlled by the warm and humid air of East Asian summer monsoon. In winter, surface temperature increases owing to the release of latent heat and sensible heat when precipitation occurs. The stronger positive PTRs ranging from 0.963 to 3.786 °C/mm mostly occur at high altitudes and latitudes due to more release of sensible heat. The enhanced atmospheric counter radiation by clouds is the major factor affecting increases of surface temperature in winter and decreases of surface temperature in summer when precipitation occurs.     

ECMWF和华东WARMS模式对山东半岛汛期暴雨的预报能力检验

利用欧洲中期天气预报中心细网格模式（以下简称ECMWF-Thin）产品和模式水平分辨率为9 km的华东区域气象中心中尺度数值预报模式V1.0（以下简称SMS-WARMS）产品,对山东半岛2016—2017年汛期35个暴雨日（26次过程）的暴雨预报能力进行检验。结果表明：1）对于降水强度,ECMWF-Thin预报偏弱导致暴雨和大暴雨漏报率偏高,大暴雨几乎全部漏报,当其预报有50 mm以上降水时出现暴雨的概率达90%以上,SMS-WARMS则预报降水量偏强、空报率较高,SMS-WARMS降水强度量级预报总体优于ECMWF-Thin,24 h预报能力最佳;2）对于强降水开始时间的预报,两家模式均表现为偏晚为主,且偏晚3 h以内的概率较大,在参考其预报结论的基础上可适当提前3 h;3）对于强降水落区,ECMWF-Thin略优于SMS-WARMS,SMS-WARMS对台风暴雨的落区预报较为精准,而其他类型暴雨的落区ECMWF-Thin预报多偏南或偏向西南1°以内,因此预报员需向偏东或东北1°范围内的区域调整;4）对于强降水范围大小的预报,ECMWF-Thin预报暴雨范围偏小的概率较大,而SMS-WARMS预报范围偏大的概率较大,因此需综合考虑两种数值预报结论进行折中预报。     

岳阳市ECMWF数值模式降水预报检验与释用

该文应用TS评分、预报偏差（BIAS）等方法,对ECMWF模式预报的2015年12月—2018年12月岳阳市降水场资料,开展晴雨和分级降水检验。晴雨预报检验结果表明：ECMWF模式对岳阳市晴雨预报性能总体较稳定,年际变化幅度较小;晴雨预报准确率季节差异大,冬季最高,秋季次之,夏季最低;从逐月晴雨预报检验来看,12月份最高,8月最低;晴雨预报还存在明显的日变化规律,对夜间的预报能力明显优于白天;空间上总体呈北高南低的空间分布特征。分级降水预报检验结果表明：小雨量级降水预报评分明显高于其他量级降水,中雨次之,大雨及以上量级评分较低且无明显规律;小、中、大雨3个量级任一时效的空报率整体上比漏报率大,小雨量级表现得尤为明显,说明小雨量级的空报更为严重。针对小雨降水预报空报率高的现象,该文对岳阳市ECMWF模式预报降水量1.2 mm以下消空处理后进行了预报释用,结果表明：冬季订正空间较小,夏季各时效可适度订正;春季和秋季可视情况适度订正,订正后可以有效提升预报技巧,但增加了一定漏报风险。     

Investigation of temporal and spatial climate variability and aridity of Iran

The aim of this research is to study the spatial and temporal variability of aridity in Iran, through analysis of temperature and precipitation trends during the 48-year period of 1961–2008. In this study, four different aridity criteria have been used to investigate the aridity situation. These aridity indexes included Lang’s index or rain factor, Budyko index or radiational index of dryness, UNEP aridity index, and Thornthwaite moisture index. The results of the analysis indicated that the highest and lowest mean temperatures occurred in July and January respectively in all locations. Among the study locations, Ahvaz with 37.1 °C and Kermanshah with 20.2 °C has the highest and lowest in July. For January, the highest was 12.4 °C for Ahvaz and the lowest was ?4.5 °C for Hamedan and Kermanshah together. The range of monthly mean temperature of study locations indicated that the maximum and minimum difference between day and night temperatures, almost in all study locations, occurred in September and January, respectively, and the highest and lowest fluctuation of temperature was observed in Kerman and Tehran. The temperature anomalies showed that the most significant increasing temperature occurred at the beginning of twenty-first century (2000–2008) in all locations. The long-term mean of monthly rainfall showed that, in most study locations, the maximum and minimum of mean precipitation occurred in winter and summer, respectively. Rasht with 1,355 mm had the highest and Yazd with 55 mm had the lowest of total precipitation compared with other locations. According to precipitation anomalies, all locations experienced dry and wet periods, but generally dry periods occurred more often especially in the beginning of twenty-first century. According to applied different aridity indexes, all the study locations often experienced semi-arid to arid climate, severe water deficit to desert climate, arid to hyperarid climate, and semi-arid climate during the study period.     

攀西地区2021年夏季多模式降水预报检验

为提高定量降水预报产品在攀西地区的预报能力,对2021年夏季格点预报（Grid Weather Forecasting,GWF）、西南区域模式（South West Center-WRF ADAS Real-time Modeling System,SWCWARMS）、欧洲中心中期预报 （European Centre for Medium-Range Weather Forecasting,ECMWF）及中国气象局中尺度模式（China Meteorological Administration Meso-Scale Model,CMA-MESO）降水预报情况进行了检验分析。结果表明:（1）ECMWF模式雨日空报最明显,但其暴雨量级预报较实况偏干,其余各家产品中各量级降水均以湿偏差为主。有雨日数在攀西地区南部预报效果较好,其余地方空报较大。大雨日数在凉山州中部预报偏差较大,攀西地区南部预报偏差较小。（2）从16次过程检验来看,各预报产品在8月份过程中的表现优于其余月份,GWF产品25 mm以上TS（Threat Score）评分高于20分的过程次数最多且预报效果最稳定,CMA-MESO模式空报最大。（3）各产品3 h累计强降水开始时间大多早于实况,SWCWARMS模式雨强偏大且对于持续时间较长的过程预报效果较好,而GWF、ECMWF模式累计雨量较实况偏小。      

动态最优网格降水消空技术

为了提高5 km分辨率的网格降水预报准确率,针对数值模式网格降水预报产品中尚存在许多降水空报的现象,基于网格降水实况,应用动态建模和机器训练择优技术,借助新检验参数归一化后的单调性、新降水TS公式在计算上的便利性,建立了两种动态最优降水消空技术方案,开展网格降水消空研究。研究表明,两步法抑制了消空阈值偏大现象,归一化法使阈值优选更加直接。用这两种方法,晴雨准确率全部上升,其中,ECMWF(European Centre for Medium range Weather Forecasts)提高最大（2.39%～4.76%）;降水TS评分,ECMWF提高最大,白天提高多（2.98%～3.64%）,夜间提高少（1.61%～1.78%）,但CMA SH9(中国气象局上海数值预报模式系统)和CMA BJ(中国气象局北京快速更新循环数值预报系统)则出现下降。归一化法在白天使晴雨准确率提高最多。分析表明,经过消空处理后,雨空百分率下降数值明显大于雨漏百分率增加数值,从而使空报率出现大幅下降,晴雨准确率也升高明显。     

多数值模式对2021年7月两次大暴雨过程预报能力检验评估

传统点对点的二分类检验方法能够客观反映模式预报的整体表现,但该方法存在双重惩罚现象。本文在传统检验基础上结合FSS（Fraction Skill Score）评分和MODE（Method of Object-based Diagnostic Evaluation）方法,对2021年7月影响四川的两次区域性大暴雨过程开展检验评估,对比分析了华东区域BCSH模式、ECMWF模式、西南区域SW3KM和SW9KM模式的预报性能。结果表明:（1）BCSH和ECMWF模式在小到中雨评分上略优于西南区域2个模式,SW3KM模式优势体现在暴雨预报上;BCSH和SW9KM模式预报偏差无显著规律,ECMWF模式小到大雨多空报,SW3KM模式中到暴雨多空报。（2）邻域半径为7个格点时,SW3KM模式在72 h预报时效上小雨、36~72 h大雨、24~66 h暴雨评分高于其它模式;区域模式分辨率提高,其FSS和TS评分相应增加,随着预报时间延长,区域模式FSS评分以大于ECMWF模式为主,SW9KM模式各级降水评分整体低于SW3KM模式。（3）4个模式降水落区质心位置预报的经向偏差略大于纬向,BCSH和SW9KM模式降水质心较实况偏西北,ECMWF模式暴雨质心偏西北、大暴雨质心偏西南,SW3KM模式暴雨质心多偏西南、大暴雨质心较实况多偏西北。ECMWF模式对雨带走向和面积的把控好于区域模式;SW3KM模式在72 h预报时效上多个属性值优于BCSH模式,SW3KM模式匹配目标属性值以优于SW9KM模式为主;BCSH、ECMWF和SW3KM模式均存在降水强度预报偏大的特征。