8.19华北暴雨模拟中微物理方案的对比试验

在中尺度模式多种物理过程中,微物理过程是一个非常关键的环节,其不仅直接影响降水预报,而且也影响模式的动力过程.微物理方案有明确的物理基础,但是在实际暴雨模拟中,究竟采取哪一种方案的结果更理想,需要深入比较,因为不同的微物理方案对降水模拟结果有着很大的差异.本文利用中尺度非静力模式WRF (V3.2.1版本),采用36 km、12 km和4 km的格点分辨率,选用七种微物理方案,对2010年8月18~19 日华北地区的暴雨过程进行了敏感性试验.从降水落区和强度方面对总降水的预报性能进行了对比,模拟结果表明:选用不同的微物理方案,可以不同程度地模拟这场暴雨的范围和强度,且选择合理的微物理方案对细网格（4 km）嵌套的模拟也可以相应的提高,从而提高了暴雨模拟的分辨率,为暴雨中小尺度成因分析提供了参考.其中,水平分辨率为36 km时,Lin方案模拟的雨带范围和降水强度与实况拟合的最好;水平分辨率为12 km时,Thompson方案模拟的强降水位置、强度与实况最为接近;而水平分辨率为4 km时,WSM6方案模拟的强降水位置、强度与实况拟合得较好.再结合垂直速度、涡度、散度和雨水混合比等基本物理量的诊断分析,可以更好地理解各微物理方案对降雨预报的影响,所得的结论对我国华北暴雨强降水预报和中尺度模式微物理过程在业务和研究方面有相当的参考价值.     

The impact of Global Positioning System data on the prediction of an extratropical cyclone: an observing system simulation experiment

In this paper, we report a series of observing system simulation experiments that we conducted to assess the potential impact of Global Positioning System/meteorology (GPS/MET) refractivity data on short-range numerical weather prediction. We first conducted a control experiment using the Penn State/NCAR mesoscale model MM5 at 90-km resolution on an extratropical cyclone known as the ERICA (Experiment on Rapidly Intensifying Cyclones over the Atlantic) IOP 4 storm. The results from the control experiment were then used to simulate GPS/MET refractivity observations with different spatial resolution and measurement characteristics. The simulated refractivity observations were assimilated into an 180-km model during a 6-h period, which was followed by a 48-h forecast integration. Key findings can be summarized as follows:

• The assimilation of refractivity data at the 180-km resolution can recover important atmospheric structures in temperature and moisture fields both in the upper and lower troposphere, and, through the internal model dynamical processes, also the wind fields. The assimilation of refractivity data led to a considerably more accurate prediction of the cyclone.

• Distributing the refractivity randomly in space and applying a line averaging did not alter the results significantly, while reducing the spatial resolution from 180 km to 360 km produced a moderately degraded result. Even at the 360-km resolution, the GPS-type refractivity data still have a notable positive impact on cyclone prediction.

• Restricting the refractivity data to altitude 3 km and above considerably degraded its impact on cyclone prediction. This degradation was greater than the combined effects of distributing the refractivity data randomly, performing line averaging, and reducing the resolution to 360 km.

These results showed that the GPS/MET refractivity data is likely to have a significant impact on short-range operational numerical weather prediction. The random distribution and line averaging associated with the inherent GPS occultation do not pose a problem for effective assimilation. On the other hand, these results also argue that we need to improve the GPS/MET retrieval algorithm in order to recover useful data in the lower troposphere, and to increase the number of low-earth-orbiting satellites carrying GPS receivers in order to increase the density of GPS soundings, so that the potential impact of GPS/MET refractivity data on numerical weather prediction can be fully realized.     

Analyses and forecasts of a tornadic supercell outbreak using a 3DVAR system ensemble

As part of NOAA’s "Warn-On-Forecast" initiative, a convective-scale data assimilation and prediction system was developed using the WRF-ARW model and ARPS 3DVAR data assimilation technique. The system was then evaluated using retrospective short-range ensemble analyses and probabilistic forecasts of the tornadic supercell outbreak event that occurred on 24 May 2011 in Oklahoma, USA. A 36-member multi-physics ensemble system provided the initial and boundary conditions for a 3-km convective-scale ensemble system. Radial velocity and reflectivity observations from four WSR-88 Ds were assimilated into the ensemble using the ARPS 3DVAR technique. Five data assimilation and forecast experiments were conducted to evaluate the sensitivity of the system to data assimilation frequencies, in-cloud temperature adjustment schemes, and fixed- and mixed-microphysics ensembles. The results indicated that the experiment with 5-min assimilation frequency quickly built up the storm and produced a more accurate analysis compared with the 10-min assimilation frequency experiment. The predicted vertical vorticity from the moist-adiabatic in-cloud temperature adjustment scheme was larger in magnitude than that from the latent heat scheme. Cycled data assimilation yielded good forecasts, where the ensemble probability of high vertical vorticity matched reasonably well with the observed tornado damage path. Overall, the results of the study suggest that the 3DVAR analysis and forecast system can provide reasonable forecasts of tornadic supercell storms.     

对流天气系统自动站雨量资料同化对降雨预报的影响

利用GRAPES(Global and Regional Assimilation and Prediction Enhanced System,全球/区域同化预报系统)三维变分同化系统,针对对流天气系统特点,用改进的郭晓岚对流参数化方案作为观测算子,同化广东省自动站记录的对流天气系统的雨量资料,并且与同化探空资料进行了比较.在雨带有明显改进的区域,分别同化这两种资料都可以调整大气低层水汽辐合增加(或辐散),对流层中下层增暖增湿(或变冷变干),从而增加(或减少)降水,表明降水的同化方案对初始场的调整在一定     

在动力相似预报中引入多个参考态的更新

针对如何更有效地利用历史资料中的相似信息提高预报水平的问题,在已有相似-动力模式研究基础上,进一步探讨了相似误差订正方法(ACE)的若干理论和技术问题,分析表明,ACE是对以相似离差方程和相似误差订正方程为理论依据的方法的再发展。在此基础上,提出了相似的更新问题和多个参考态的引入,并进而发展出一种考虑多参考态更新的动力相似预报新方法(MRSU)。这一方法通过引入相似更新周期的新概念,在预报进行到相似更新周期时重新选取多个参考态,并采用超平面近似法将相似-动力模式产生的多个预报估计成最佳预报向量,这样的“选取-估计”过程循环往复,从而完成整个时段的预报。Lorenz模式试验显示,相比于以往的相似-动力模式预报,MRSU能更有效减小预报误差,提高预报技巧,并且,ACE的理论优势应用前景也被初步证实。综合诸多研究结果,给出了MRSU的概念流程,这里针对复杂数值模式采用了ACE,能够等价实现相似-动力模式预报过程,无需重建模式,更易于推广。     

Evaluation of the 2.5-km Cloud-Resolving Storm Simulator in Predicting Local Afternoon Convection during the Summer in Taiwan

The forecast of summertime afternoon convection by numerical weather prediction models is highly challenging because of its weak dynamical forcing, small scale, and low predictability. To assess such an ability for future improvement, we evaluated the performance of the 2.5-km Cloud-Resolving Storm Simulator (CReSS) in predicting afternoon convection in Taiwan under weak synoptic conditions during the summers (May–October) of 2011 and 2012. For a total of 89 target days, daily CReSS forecasts in three ranges, starting at 0000 UTC (0800 LST) on the same day (D0), the day before (D-1), and 2 days before (D-2), were examined. With regard to the occurrence of afternoon convection anywhere in Taiwan, the predictive skill of the model was considerably high, as evidenced by the threat score (TS) and post-agreement (PA) of D0 (D-1) forecasts reaching 0.75 and 0.90 (0.50 and 0.79), respectively. While the score values decrease when Taiwan is divided into four regions (i.e., the forecast must be in the correct region to be considered a hit), the TS and PA for D0 (D-2) forecasts remain respectable at 0.44 and 0.73 (0.29 and 0.59). Among the four regions, the TS (0.48–0.65) and PA (0.77–0.83) for Central Taiwan are the highest with the best predictive skill. Overall, while the prediction of afternoon convection in the correct region is challenging, the 2.5-km CReSS model has considerable skill (TS ~ 0.30) even 2 days in advance, and can provide useful guidance for afternoon convection in Taiwan.     

Improvements in WRF simulation skills of southeastern United States summer rainfall: physical parameterization and horizontal resolution

Realistic regional climate simulations are important in understanding the mechanisms of summer rainfall in the southeastern United States (SE US) and in making seasonal predictions. In this study, skills of SE US summer rainfall simulation at a 15-km resolution are evaluated using the weather research and forecasting (WRF) model driven by climate forecast system reanalysis data. Influences of parameterization schemes and model resolution on the rainfall are investigated. It is shown that the WRF simulations for SE US summer rainfall are most sensitive to cumulus schemes, moderately sensitive to planetary boundary layer schemes, and less sensitive to microphysics schemes. Among five WRF cumulus schemes analyzed in this study, the Zhang–McFarlane scheme outperforms the other four. Further analysis suggests that the superior performance of the Zhang–McFarlane scheme is attributable primarily to its capability of representing rainfall-triggering processes over the SE US, especially the positive relationship between convective available potential energy and rainfall. In addition, simulated rainfall using the Zhang–McFarlane scheme at the 15-km resolution is compared with that at a 3-km convection-permitting resolution without cumulus scheme to test whether the increased horizontal resolution can further improve the SE US rainfall simulation. Results indicate that the simulations at the 3-km resolution do not show obvious advantages over those at the 15-km resolution with the Zhang–McFarlane scheme. In conclusion, our study suggests that in order to obtain a satisfactory simulation of SE US summer rainfall, choosing a cumulus scheme that can realistically represent the convective rainfall triggering mechanism may be more effective than solely increasing model resolution.     

Intercomparison of the performance of MM5/WRF with and without satellite data assimilation in short-range forecast applications over the Indian region

The present study is conducted to verify the short-range forecasts from mesoscale model version5 (MM5)/weather research and forecasting (WRF) model over the Indian region and to examine the impact of assimilation of quick scatterometer (QSCAT) near surface winds, spectral sensor microwave imager (SSM/I) wind speed and total precipitable water (TPW) on the forecasts by these models using their three-dimensional variational (3D-Var) data assimilation scheme for a 1-month period during July 2006. The control (without satellite data assimilation) as well as 3D-Var sensitivity experiments (with assimilating satellite data) using MM5/WRF were made for 48 h starting daily at 0000 UTC July 2006. The control run is analyzed for the intercomparison of MM5/WRF short-range forecasts and is also used as a baseline for assessing the MM5/WRF 3D-Var satellite data sensitivity experiments. As compared to the observation, the MM5 (WRF) control simulations strengthened (weakened) the cross equatorial flow over southern Arabian sea near peninsular India. The forecasts from MM5 and WRF showed a warm and moist bias at lower and upper levels with a cold bias at the middle level, which shows that the convective schemes of these models may be too active during the simulation. The forecast errors in predicted wind, temperature and humidity at different levels are lesser in WRF as compared to MM5, except the temperature prediction at lower level. The rainfall pattern and prediction skill from day 1 and day 2 forecasts by WRF is superior to MM5. The spatial distribution of forecast impact for wind, temperature, and humidity from 1-month assimilation experiments during July 2006 demonstrated that on average, for 24 and 48-h forecasts, the satellite data improved the MM5/WRF initial condition, so that model errors in predicted meteorological fields got reduced. Among the experiments, MM5/WRF wind speed prediction is most benefited from QSCAT surface wind and SSM/I TPW assimilation while temperature and humidity prediction is mostly improved due to latter. The largest improvement in MM5/WRF rainfall prediction is due to the assimilation of SSM/I TPW. The assimilation of SSM/I wind speed alone in MM5/WRF degraded the humidity and rainfall prediction. In summary the assimilation of satellite data showed similar impact on MM5/WRF prediction; largest improvement due to SSM/I TPW and degradation due to SSM/I wind speed.     

High-resolution Simulation of an Extreme Heavy Rainfall Event in Shanghai Using the Weather Research and Forecasting Model: Sensitivity to Planetary Boundary Layer Parameterization

In this study,an extreme rainfall event that occurred on 25 May 2018 over Shanghai and its nearby area was simulated using the Weather Research and Forecasting model,with a focus on the effects of planetary boundary layer(PBL)physics using double nesting with large grid ratios(15:1 and 9:1).The sensitivity of the precipitation forecast was examined through three PBL schemes:the Yonsei University Scheme,the Mellor?Yamada?Nakanishi Niino Level 2.5(MYNN)scheme,and the Mellor?Yamada?Janjic scheme.The PBL effects on boundary layer structures,convective thermodynamic and large-scale forcings were investigated to explain the model differences in extreme rainfall distributions and hourly variations.The results indicated that in single coarser grids(15 km and 9 km),the extreme rainfall amount was largely underestimated with all three PBL schemes.In the inner 1-km grid,the underestimated intensity was improved;however,using the MYNN scheme for the 1-km grid domain with explicitly resolved convection and nested within the 9-km grid using the Kain?Fritsch cumulus scheme,significant advantages over the other PBL schemes are revealed in predicting the extreme rainfall distribution and the time of primary peak rainfall.MYNN,with the weakest vertical mixing,produced the shallowest and most humid inversion layer with the lowest lifting condensation level,but stronger wind fields and upward motions from the top of the boundary layer to upper levels.These factors all facilitate the development of deep convection and moisture transport for intense precipitation,and result in its most realistic prediction of the primary rainfall peak.     

Short-range prediction of a heavy precipitation event by assimilating Chinese CINRAD-SA radar reflectivity data using complex cloud analysis

Summary With the ARPS (Advanced Regional Prediction System) Data Analysis System (ADAS) and its complex cloud analysis scheme, the reflectivity data from a Chinese CINRAD-SA Doppler radar are used to analyze 3D cloud and hydrometeor fields and in-cloud temperature and moisture. Forecast experiments starting from such initial conditions are performed for a northern China heavy rainfall event to examine the impact of the reflectivity data and other conventional observations on short-range precipitation forecast. The full 3D cloud analysis mitigates the commonly known spin-up problem with precipitation forecast, resulting a significant improvement in precipitation forecast in the first 4 to 5 hours. In such a case, the position, timing and amount of precipitation are all accurately predicted. When the cloud analysis is used without in-cloud temperature adjustment, only the forecast of light precipitation within the first hour is improved. Additional analysis of surface and upper-air observations on the native ARPS grid, using the 1 degree real-time NCEP AVN analysis as the background, helps improve the location and intensity of rainfall forecasting slightly. Hourly accumulated rainfall estimated from radar reflectivity data is found to be less accurate than the model predicted precipitation when full cloud analysis is used.     

Study on ETKF-Based Initial Perturbation Scheme for GRAPES Global Ensemble Prediction

Initial perturbation scheme is one of the important problems for ensemble prediction. In this paper, ensemble initial perturbation scheme for Global/Regional Assimilation and PrEdiction System (GRAPES) global ensemble prediction is developed in terms of the ensemble transform Kalman filter (ETKF) method.A new GRAPES global ensemble prediction system (GEPS) is also constructed. The spherical simplex 14-member ensemble prediction experiments, using the simulated observation network and error characteristics of simulated observations and innovation-based in ation, are carried out for about two months. The structure characters and perturbation amplitudes of the ETKF initial perturbations and the perturbation growth characters are analyzed, and their qualities and abilities for the ensemble initial perturbations are given. The preliminary experimental results indicate that the ETKF-based GRAPES ensemble initial perturbations could identify main normal structures of analysis error variance and reflect the perturbation amplitudes.The initial perturbations and the spread are reasonable. The initial perturbation variance, which is approximately equal to the forecast error variance, is found to respond to changes in the observational spatial variations with simulated observational network density. The perturbations generated through the simplex method are also shown to exhibit a very high degree of consistency between initial analysis and short-range forecast perturbations. The appropriate growth and spread of ensemble perturbations can be maintained up to 96-h lead time. The statistical results for 52-day ensemble forecasts show that the forecast scores ofensemble average for the Northern Hemisphere are higher than that of the control forecast. Provided that using more ensemble members, a real-time observational network and a more appropriate inflation factor,better effects of the ETKF-based initial scheme should be shown.     

Effects of Resolution,Cumulus Parameterization Scheme,and Probability Forecasting on Precipitation Forecasts in a High-Resolution Limited-Area Ensemble Prediction System

This study investigates the effects of horizontal resolution, cumulus parameterization scheme (CPS), and probability forecasting on precipitation forecasts over the Korean Peninsula from 00 UTC 15 August to 12 UTC 14 September 2013, using the limited-area ensemble prediction system (LEPS) of the Korea Meteorological Administration. To investigate the effect of resolution, the control members of the LEPS with 1.5- and 3-km resolution were compared. Two 3-km experiments with and without the CPS were conducted for the control member, because a 3-km resolution lies within the gray zone. For probability forecasting, 12 ensemble members with 3-km resolution were run using the LEPS. The forecast performance was evaluated for both the whole study period and precipitation cases categorized by synoptic forcing. The performance of precipitation forecasts using the 1.5-km resolution was better than that using the 3-km resolution for both the total period and individual cases. The result of the 3-km resolution experiment with the CPS did not differ significantly from that without it. The 3-km ensemble mean and probability matching (PM) performed better than the 3-km control member, regardless of the use of the CPS. The PM complemented the defect of the ensemble mean, which better predicts precipitation regions but underestimates precipitation amount by averaging ensembles, compared to the control member. Further, both the 3-km ensemble mean and PM outperformed the 1.5-km control member, which implies that the lower performance of the 3-km control member compared to the 1.5-km control member was complemented by probability forecasting.     

基于VDRAS的快速更新雷达四维变分分析系统

基于雷达资料快速更新四维变分同化 (RR4DVar) 技术和三维数值云模式,初步研发了一个针对对流尺度数值模拟的快速更新雷达四维变分分析系统。系统通过对京津冀6部多普勒天气雷达资料进行RR4DVar同化,并融合5 min自动气象站观测和中尺度数值模式结果,可快速分析得到12~18 min更新的低层大气三维动力、热力场的对流尺度结构特征。针对2009年7月22日发生在京津冀的一次强风暴个例,通过一系列敏感性试验,并利用局地加密资料进行检验对比,表明有效的雷达资料RR4DVar同化及自动气象站和中尺度模式资料融合方案、恰当的中尺度背景场设置和动力约束方法是获得合理结果的关键。研究也表明:恰当的系统配置能够模拟出与对流生消发展密切相关的近风暴环境特征,包括低层入流、垂直风切变、低层辐合上升和暖舌等,以及风暴自身形成的冷池、出流等与风暴演变密切相关的对流尺度结构。     

短期降水预报的动力学与热力学

提出了当前短时和短期降水预报中需待解决的3个问题。由这些问题引发了如何把动力学与热力学相结合,如何把大量的观测和模式资料应用于短期无间隙预报的思考。最后给出了一个短期大暴雨预报的应用实例。     

GRAPES_GFS模式全球降水预报的主要偏差特征

利用2017年1、4、7、10月“全球降水观测（global precipitation measurement,GPM）计划”每日08时（北京时）的24 h累计降水量和逐30 min降水量观测产品,从降水量和频率等角度,对同期GRAPES全球模式（GRAPES_GFS）第1（D1）、3（D3）、5天（D5）的全球降水预报性能和偏差特征进行细致评估与分析,且对低纬度暖池和北半球中纬度风暴路径区进行了重点观察,初步探讨了降水预报偏差特征在低纬度和中纬度明显不同的可能原因。结果显示:（1）GRAPES_GFS的D1—D5预报对全球日降水（量和频率）分布描述合理,能准确再现纬向平均降水（量和频率）的典型特征—降水“双峰”极大位于南北纬20°之间,次极大位于南北纬40°—50°地区的特征,以及关键区日降水时、空演变和降水日循环逐日演变的主要趋势特征。（2）低纬度的纬向平均湿日（≥0.1 mm/d）频率预报正偏差很小,但日降水量和强降水日（＞25 mm/d）频率预报的正偏差明显、偏差极大值“双峰”位置恰是相应观测极大值所在处（南北纬5°—10°）;中纬度的纬向平均日降水量预报基本无偏,但明显的湿日降水频率预报正偏差（20%—30%）和强降水日频率负偏差出现在南北纬40°—60°。降水偏差正、负分布特征随季节和预报时效基本保持不变,预报均方根误差数倍于平均误差,暗示模式降水预报偏差有系统性且性能表现波动较大。（3）日循环中,模式在暖池的降水量预报正偏差缘于降水强度预报偏强,降水频率预报的弱负偏差主要与降水落区预报偏小有关;而模式在北半球风暴路径区降水频率预报的正偏差则是降水落区预报偏大和空报弱降水事件两方面因素造成。（4）模式降水（量和频率）预报偏差特征在低纬度和中纬度的明显差异与模式次网格尺度和网格尺度降水比例失调有关,改进线索指向模式对流参数化方案中深对流的启动和深对流降水量的处理以及对流参数化方案与云微物理方案的协同问题。      

基于贝叶斯方案的雷达反射率反演水汽及其同化试验

雷达资料是目前为数不多有能力为高分辨率预报模式提供高分辨率信息资料的资料之一。为充分利用该资料所包含的中小尺度信息,文中基于雷达反射率,利用贝叶斯方法反演出大气相对湿度;将质控后的资料引入3Dvar系统进行同化分析,为高分辨率模式提供初值场。以台风“妮妲”登陆为例,通过一维反演及三维变分系统分析,有效地订正了实况有回波而模式预报无回波区域的大气湿度趋于合理,增加背景场的湿度,减小模拟回波比观测偏强的区域的大气湿度;同化大气湿度后模式在前6小时报出的台风外围回波分布、演变更合理,改进了降水雨带的分布与强度。1个月的批量试验反映1D+3Dvar同化雷达资料后,大气对流层中低层（850~400 hPa）增湿明显,其增湿影响程度可延续12小时以上。其逐时降水预报在前12小时的TS均比控制试验高,而大于5 mm以上降水预报偏差则与控制试验的大略一致或更接近1。      

基于WRF模式的对流尺度边界层方案参数随机扰动方法研究

边界层参数化方案的准确性会影响模式对近地面变量和大气低层热动力结构的模拟,对雷暴等强对流天气的预报非常重要,但边界层方案内在的不确定性使得单一预报具有局限性。为了提高对流尺度数值模式中边界层方案的预报效果,基于WRF（The Weather Research and Forecasting Model）模式,应用随机参数扰动（SPP）方法对Mellor-Yamada-Nakanishi-Niino（MYNN）边界层方案中重要的3个不确定参数进行扰动,探究了该方法对北京地区一次雷暴过程模拟的影响。同时考虑了对流尺度集合预报系统的特点,调整随机参数扰动方法的3个参量（去相关时间尺度、空间尺度和格点标准差）探究了对流尺度中对MYNN方案参数进行扰动的最优设置。结果显示:随机扰动MYNN边界层方案参数（SPPM）方法可以有效提高近地面变量和700 hPa以下低层变量的离散度,同时提高了短时强降水位置和强度的预报技巧。3个参量的试验说明,去相关时间尺度增大到12 h集合离散度有明显提高;格点标准差增大到0.20,预报技巧也略有提高;去相关空间尺度维持在默认值700 km较好,尺度过小（150 km）预报技巧明显降低。上述结果表明,在对流尺度中SPPM方法可以有效表达边界层参数化方案的不确定性,提高集合预报系统的预报技巧。      

短时强降水历史个例查询与潜势预报平台

短时强降水作为强对流的一种天气现象,是宿迁市较为常见的灾害性天气之一,常常对工农业生产、交通航运、建筑设施等造成影响。然而,预报一直是难点,因此如何利用现有的气象资料,开展短时强降水预报服务,并形成日常业务流程,对提高预报预警和防灾减灾能力十分重要。本文利用自动站逐时雨量资料、Micaps高低空和地面资料、NECP 1°× 1°的再分析资料和T213数值预报产品,基于Visual Basic语言开发了宿迁市短时强降水历史个例查询与潜势预报平台,以提高短时强降水预报质量,减少或避免气象灾害给社会经济造成的损失。     

APPLICATION EXPERIMENT OF ASSIMILATING RADAR-RETRIEVED WATER VAPOR IN SHORT-RANGE FORECAST OF RAINFALL IN THE ANNUALLY FIRST RAINY SEASON OVER SOUTH CHINA

A scheme of assimilating radar-retrieved water vapor is adopted to improve the quality of NWP initial field for improvement of the accuracy of short-range precipitation prediction. To reveal the impact of the assimilation of radar-retrieved water vapor on short-term precipitation forecast, three parallel experiments, cold start, hot start and hot start plus the assimilation of radar-retrieved water vapor, are designed to simulate the 31 days of May, 2013 with a fine numerical model for South China. Furthermore, a case of heavy rain that occurred from 8—9 May 2013 over the region from the southwest of Guangdong province to Pearl River Delta is analyzed in detail. Results show that the cold start experiment is not conducive to precipitation 12 hours ahead; the hot start experiment is able to reproduce well the first 6 hours of precipitation, but badly for subsequent prediction; the experiment of assimilating radar-retrieved water vapor is not only able to simulate well the precipitation 6 hours ahead, but also able to correctly predict the evolution of rain bands from 6 to 12 hours in advance.     

雾与能见度数值预报诊断SW方案和FSL方案改进的研究及评估

为了提高雾与能见度的预报水平,对业务上常用的两种能见度诊断方案,即Stoelinga and Warner（SW）方案与Forecast Systems Laboratory（FSL）方案的改进进行预报试验,SW方案基于Gultepe方案考虑了液态水粒子数浓度对能见度的影响,FSL改进方案中利用了递减平均法对公式中用到的温度与露点温度进行订正,并用其重新计算公式中的相对湿度。基于山东省气象科学研究所逐时更新循环（hourly update cycle,HUC）业务模式输出结果,从2015—2016年选取10次雾天气过程,并详细分析了2015年11月13—14日这次雾天气过程的预报结果,比较了改进前后各方案对雾与能见度的预报效果,结果显示：在模式预报的雨水含量占总液态含水量比例较大的预报时效,改进后的SW方案对雾与能见度预报效果优于原始方案,在模式预报液态含水量接近0的预报时效,改进前后的SW方案对雾与能见度的预报效果相当;利用订正的温度与露点温度重新计算相对湿度,其平均绝对误差（mean absolute error,MAE）降低明显的预报时段,改进后的FSL方案对雾与能见度的预报效果大大提升。将两种改进后的方案相融合并进行预报试验,结果显示,综合对能见度与雾的预报效果,Combined Visibility（CVIS）方案要优于其他两种改进方案。