A STUDY OF THE INFLUENCE OF MICROPHYSICAL PROCESSES ON TYPHOON NIDA(2016) USING A NEW DOUBLE-MOMENT MICROPHYSICS SCHEME IN THE WEATHER RESEARCH AND FORECASTING MODEL

The basic structure and cloud features of Typhoon Nida(2016) are simulated using a new microphysics scheme(Liuma) within the Weather Research and Forecasting(WRF) model. Typhoon characteristics simulated with the Liuma microphysics scheme are compared with observations and those simulated with a commonly-used microphysics scheme(WSM6). Results show that using different microphysics schemes does not significantly alter the track of the typhoon but does significantly affect the intensity and the cloud structure of the typhoon. Results also show that the vertical distribution of cloud hydrometeors and the horizontal distribution of peripheral rainband are affected by the microphysics scheme. The mixing ratios of rain water and graupel correlate highly with the vertical velocity component and equivalent potential temperature at the typhoon eye-wall region. According to the simulation with WSM 6 scheme,it is likely that the very low typhoon central pressure results from the positive feedback between hydrometeors and typhoon intensity. As the ice-phase hydrometeors are mostly graupel in the Liuma microphysics scheme, further improvement in this aspect is required.

A Methodological Study on Using Weather Research and Forecasting(WRF) Model Outputs to Drive a One-Dimensional Cloud Model

A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale stratiform rainfall event that took place on 4-5 July 2004 in Changchun, China. Sensitivity test results suggested that, with hydrometeor pro files extracted from the WRF outputs as the initial input, and with continuous updating of soundings and vertical velocities （including downdraft） derived from the WRF model, the new WRF-driven 1DSC modeling system （WRF-1DSC） was able to successfully reproduce both the generation and dissipation processes of the precipitation event. The simulated rainfall intensity showed a time-lag behind that observed, which could have been caused by simulation errors of soundings, vertical velocities and hydrometeor profiles in the WRF output. Taking into consideration the simulated and observed movement path of the precipitation system, a nearby grid point was found to possess more accurate environmental fields in terms of their similarity to those observed in Changchun Station. Using profiles from this nearby grid point, WRF-1DSC was able to repro duce a realistic precipitation pattern. This study demonstrates that 1D cloud-seeding models do indeed have the potential to predict realistic precipitation patterns when properly driven by accurate atmospheric profiles derived from a regional short range forecasting system, This opens a novel and important approach to developing an ensemble-based rain enhancement prediction and operation system under a probabilistic framework concept.

Simulation of Quasi-Linear Mesoscale Convective Systems in Northern China：Lightning Activities and Storm Structure

Two intense quasi-linear mesoscale convective systems（QLMCSs） in northern China were simulated using the WRF（Weather Research and Forecasting） model and the 3D-Var（three-dimensional variational） analysis system of the ARPS（Advanced Regional Prediction System） model.A new method in which the lightning density is calculated using both the precipitation and non-precipitation ice mass was developed to reveal the relationship between the lightning activities and QLMCS structures.Results indicate that,compared with calculating the results using two previous methods,the lightning density calculated using the new method presented in this study is in better accordance with observations.Based on the calculated lightning densities using the new method,it was found that most lightning activity was initiated on the right side and at the front of the QLMCSs,where the surface wind field converged intensely.The CAPE was much stronger ahead of the southeastward progressing QLMCS than to the back it,and their lightning events mainly occurred in regions with a large gradient of CAPE.Comparisons between lightning and non-lightning regions indicated that lightning regions featured more intense ascending motion than non-lightning regions;the vertical ranges of maximum reflectivity between lightning and non-lightning regions were very different;and the ice mixing ratio featured no significant differences between the lightning and non-lightning regions.

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.

大型浅水湖泊高时空分辨率风场特征数值模拟研究:以巢湖为例

【目的】大型浅水湖泊的风场是影响湖泊流场、水体富营养化和藻华运移聚集规律的关键因素之一,仅依托气象站点的观测数据难以有效捕捉湖面风场在空间和时间上的快速变化。为精细刻画湖泊高频变化风场,辨识其时空变化特征,【方法】以巢湖为研究对象,综合利用气象观测数据、全球再分析数据集和地理静态数据,通过中尺度天气预报模式和地理空间分析技术,模拟分析巢湖地区2019年高时空分辨率的风场变化过程。【结果】结果显示:巢湖区域风速由东向西、由南向北、由湖面向陆面逐渐减弱;湖面主导风向为东风和偏东风,主导风速为二级至四级,湖面平均风速在11月最大,12月次之,5月最小,不同季节湖面平均风速由大到小依次为冬季、秋季、夏季和春季。【结论】结果表明:巢湖在白天(夜晚)出现冷(暖)湖效应,其风场在早上6时和夜晚23时出现陆风和湖风转换;西半湖受湖陆风和城市热岛影响显著,在夏季会出现明显的环湖湖风锋,其湖风锋穿透内陆距离约4.7~9 km;东半湖受山谷风影响显著,在东南部山脉以东湖区易形成低风速区,在湖口附近受狭管效应易形成高风速区。通过研究成果可进一步认知巢湖区域风场特征,为巢湖水生态环境治理提供技术支撑。

两种再分析资料和Nudging方法在WRF模式降水模拟中的适用性

采用Grid Nudging(GN)和Spectral Nudging(SN)方法,用再分析资料ERA5和FNL驱动中尺度数值天气预报模式(WRF),探究不同再分析资料和Nudging方法对降水模拟效果的改进效果及机理.对2021年3月15日中国南方地区降水过程设计6组试验进行数值模拟,分析不同试验方案对降水及相关物理量的影响.结果表明,WRF模式能较好地模拟出本次降水事件,进行Nudging驱动后显著提升了降水分布、降水中心落区和降水量的模拟效果.与观测数据综合对比,GN的模拟效果优于SN,尤其是使用ERA5资料结合GN模拟效果最佳,能够准确地模拟出发生在安徽省南部的降水中心以及超过33 mm/d的降水强度.模式结果与两个观测站点记录的降水发生时间和降水强度变化较为一致.GN方法使模式有效提高了西南低空急流的强度,校正了风向,对水汽通量和水汽通量散度的刻画更符合实际情况.

Validation of WRF model on simulating forcing data for Heihe River Basin

The research of coupling WRF （Weather Research and Forecasting Model） with a land surface model is enhanced to explore the interaction of the atmosphere and land surface; however, regional applicability of WRF model is questioned. In order to do the validation of WRF model on simulating forcing data for the Heihe River Basin, daily meteorological observation data from 15 stations of CMA （China Meteorological Administration） and hourly meteorological observation data from seven sites of WATER （Watershed Airborne Telemetry Experimental Research） are used to compare with WRF simulations, with a time range of a whole year for 2008. Results show that the average MBE （Mean Bias Error） of daily 2-m surface temperature, surface pressure, 2-m relative humidity and 10-m wind speed were -0.19 ℃, -4.49 hPa, 4.08% and 0.92 m/s, the average RMSE （Root Mean Square Error） of them were 2.11 ℃, 5.37 hPa, 9.55% and 1.73 m/s, and the average R （correlation coefficient） of them were 0.99, 0.98, 0.80 and 0.55, respectively. The average MBE of hourly 2-m surface temperature, surface pressure, 2-m relative humidity, 10-m wind speed, downward shortwave radiation and downward longwave were-0.16 ℃,-6.62 hPa,-5.14%, 0.26 m/s, 33.0 W/m^2 and-6.44 W/m^2, the average RMSE of them were 2.62 ℃, 17.10 hPa, 20.71%, 2.46 m/s, 152.9 W/m^2 and 53.5 W/m^2, and the average R of them were 0.96, 0.97, 0.70, 0.26, 0.91 and 0.60, respectively. Thus, the following conclusions were obtained： （1） regardless of daily or hourly validation, WRF model simulations of 2-m surface temperature, surface pressure and relative humidity are more reliable, especially for 2-m surface air temperature and surface pressure, the values of MBE were small and R were more than 0.96; （2） the WRF simulating downward shortwave radiation was relatively good, the average R between WRF simulation and hourly observation data was above 0.9, and the average R of downward longwave radiation was 0.6; （3） both wind speed and rainfall simulated from WRF model did not agree well with observation data.

Simulation of a torrential rainstorm in Xinjiang and gravity wave analysis

We used a weather research and forecasting model to simulate a torrential rainstorm that occurred in Xinjiang, China during June 16–17, 2016. The model successfully simulated the rainfall area, precipitation intensity, and changes in precipitation. We identified a clear wave signal using the two-dimensional fast Fourier transform method; the waves propagated westwards, with wavelengths of 45–20 km, periods of 50–120 min, and phase velocities mainly concentrated in the-25 m/s to-10 m/s range. The results of wavelet cross-spectral analysis further confirmed that the waves were gravity waves, peaking at 11：00 UTC, June 17, 2016. The gravity wave signal was identified along 79.17–79.93°E, 81.35–81.45°E and 81.5–81.83°E. The gravity waves detected along 81.5–81.83°E corresponded well with precipitation that accumulated in 1 h, indicating that gravity waves could be considered a rainstorm precursor in future precipitation forecasts.

Simulations of Microphysics and Precipitation in a Stratiform Cloud Case over Northern China:Comparison of Two Microphysics Schemes

Using the Weather Research and Forecasting(WRF)model with two different microphysics schemes,the Predicted Particle Properties(P3)and the Morrison double-moment parameterizations,we simulated a stratiform rainfall event on 20–21 April 2010.The simulation output was compared with precipitation and aircraft observations.The aircraft-observed moderate-rimed dendrites and plates indicated that riming contributed significantly to ice particle growth at the mature precipitation stage.Observations of dendrite aggregation and capped columns suggested that aggregation coexisted with deposition or riming and played an important role in producing many large particles.The domain-averaged values of the 24-h surface precipitation accumulation from the two schemes were quite close to each other.However,differences existed in the temporal and spatial evolutions of the precipitation distribution.An analysis of the surface precipitation temporal evolution indicated faster precipitation in Morrison,while P3 indicated slower rainfall by shifting the precipitation pattern eastward toward what was observed.The differences in precipitation values between the two schemes were related to the cloud water content distribution and fall speeds of rimed particles.P3 simulated the stratiform precipitation event better as it captured the gradual transition in the mass-weighted fall speeds and densities from unrimed to rimed particles.

Numerical Simulation of the Heavy Rainfall in the Yangtze-Huai River Basin during Summer 2003 Using the WRF Model

In this study,a 47-day regional climate simulation of the heavy rainfall in the Yangtze-Huai River Basin during the summer of 2003 was conducted using the Weather Research and Forecast(WRF) model.The simulation reproduces reasonably well the evolution of the rainfall during the study period's three successive rainy phases,especially the frequent heavy rainfall events occurring in the Huai River Basin.The model captures the major rainfall peak observed by the monitoring stations in the morning.Another peak appears later than that shown by the observations.In addition,the simulation realistically captures not only the evolution of the low-level winds but also the characteristics of their diurnal variation.The strong southwesterly(low-level jet,LLJ) wind speed increases beginning in the early evening and reaches a peak in the morning;it then gradually decreases until the afternoon.The intense LLJ forms a strong convergent circulation pattern in the early morning along the Yangtze-Huai River Basin.This pattern partly explains the rainfall peak observed at this time.This study furnishes a basis for the further analysis of the mechanisms of evolution of the LLJ and for the further study of the interactions between the LLJ and rainfall.

Deriving Changjiang coastal zone wind from C-band SAR and its application to salinity simulation

Wind plays an important role in hydrodynamic processes such as the expansion of Changjiang(Yangtze) River Diluted Water(CDW), and shelf circulation in the Changjiang estuary. Thus, it is essential to include wind in the numerical simulation of these phenomena. Synthetic aperture radar(SAR) with high resolution and wide spatial coverage is valuable for measuring spatially inhomogeneous ocean surface wind fields. We have collected 87 ERS-2 SAR images with wind-induced streaks that cover the Changjiang coastal area, to verify and improve the validity of wind direction retrieval using the 2D fast Fourier transform method. We then used these wind directions as inputs to derive SAR wind speeds using the C-band model. To demonstrate the applicability of the algorithms, we validated the SAR-retrieved wind fields using QuikSCAT measurements and the atmospheric Weather Research Forecasting model. In general, we found good agreement between the datasets, indicating the reliability and applicability of SARretrieved algorithms under different atmospheric conditions. We investigated the main error sources of this process, and conducted sensitivity analyses to estimate the wind speed errors caused by the effect of speckle, uncertainties in wind direction, and inaccuracies in the normalized radar cross section. Finally, we used the SAR-retrieved wind fields to simulate the salinity distribution off the Changjiang estuary. The findings of this study will be valuable for wind resource assessment and the development of future numerical ocean models based on SAR images.

不同云微物理方案对飞机结冰气象条件预测评估分析

飞行安全在复杂气象条件下易受结冰影响而受到威胁。能够结合地形特征并准确预测结冰气象条件是保障飞行安全的重要因素。本文利用中尺度天气预报模型模式,以4种不同的云微物理方案组合对美国华盛顿山地区的两次结冰事件进行了数值模拟。结果表明:预测的液态水含量和温度与现有文献匹配较好,而Morrison方案组合在误差分析中表现最佳。此外,讨论了水平分辨率和云微物理方案对液态水含量和云中液滴平均有效直径预测的敏感性。由于地形所引起的垂直运动是产生云水的主要动因,较高的水平分辨率能够做出更为准确的预测。最后利用IC指数对结冰强度进行了分析,表明结冰严重程度具有明显的时空多变特性,以及对云微物理方案的敏感性。本文工作有望加强对云微物理方案的理解和认识,并为选择适合的云微物理方案进行结冰天气预测提供了依据。

基于生态空间微气候调节的城市与水体相互影响作用研究——以水网城市武汉为例

文章以水网城市武汉为例,旨在讨论城市与水体之间的气候调节影响作用,并找到应对城市高强度发展的生态空间调节策略,改善城市气候环境。在中尺度气象模式中构建了高分辨率城市冠层模型,模拟分析了不同季节水体的微气候调节作用,发现:夏季水体对城区有明显的降温效果,日间平均降温幅度达到0.5℃;过渡季(秋季)日出前水体对地表气温增幅达0.6℃,能够有效缓解辐射逆温现象;冬季夜间水体将主城区风速提升了0.2m/s,能够帮助城市空气污染物的疏散,减少雾霾现象。此外,建筑密度的升高增强了水体与高空的对流换热,而城市容积率的升高则削弱了水体的降温效果。

不同陆面过程方案对兰州地区一次强降水对流触发的影响

2018年4月19日,兰州地区发生罕见局地强降水,造成严重城市内涝.为了研究陆面过程对此次降水模拟的影响,选取陆面模式RUC、CLM4和NOAH与中尺度天气预报模式进行耦合,重点分析不同陆面参数化方案对于对流触发的影响.结果表明,RUC能合理地再现此次降水过程,尤其是兰州上空的对流触发过程.陆-气相互作用分析表明,不同陆面过程参数化方案模拟的对流有效位能、对流抑制能、地表感热通量和潜热通量及边界层的时空演化均不同,最终影响对流触发的时空位置.陆面过程参数化方案对此次局地强对流降水模拟的结果影响很大.

基于天气研究与预报模式的林区风能评估

林业生态区风场因林木植被生长周期存在季节性变化特性,使得林区风能评估相较于平原沿海地区具有一定复杂性。采用天气研究与预报(WRF)模式,结合本地化森林冠层特征参数,对复杂地形林业生态区的风场进行数值模拟,并利用激光雷达实测数据对WRF模拟结果进行对比验证,建立复杂地形林区风场模拟方法,进而对复杂地形林区的风能资源进行评估。结果表明:采用WRF模式的林区风场模拟应充分考虑森林的季节性变化,采用本地化的森林冠层特征参数是提高林区风场模拟精度的有效手段。此外,受地形地貌影响,林区风场表现出明显的地形微气候特征,该特征随着离地高度的升高而减弱,当高度达到150m后开始具有稳定且可利用的风能资源。

Improving the Forecasts of Coastal Wind Speeds in Tianjin,China Based on the WRF Model with Machine Learning Algorithms

Characterized by sudden changes in strength,complex influencing factors,and significant impacts,the wind speed in the circum-Bohai Sea area is relatively challenging to forecast.On the western side of Bohai Bay,as the economic center of the circum-Bohai Sea,Tianjin exhibits a high demand for accurate wind forecasting.In this study,three machine learning algorithms were employed and compared as post-processing methods to correct wind speed forecasts by the Weather Research and Forecast(WRF)model for Tianjin.The results showed that the random forest(RF)achieved better performance in improving the forecasts because it substantially reduced the model bias at a lower computing cost,while the support vector machine(SVM)performed slightly worse(especially for stronger winds),but it required an approximately 15 times longer computing time.The back propagation(BP)neural network produced an average forecast significantly closer to the observed forecast but insufficiently reduced the RMSE.In regard to wind speed frequency forecasting,the RF method commendably corrected the forecasts of the frequency of moderate(force 3)wind speeds,while the BP method showed a desirable capability for correcting the forecasts of stronger(force>6)winds.In addition,the 10-m u and v components of wind(u_(10)and v_(10)),2-m relative humidity(RH_(2))and temperature(T_(2)),925-hPa u(u925),sea level pressure(SLP),and 500-hPa temperature(T_(500))were identified as the main factors leading to bias in wind speed forecasting by the WRF model in Tianjin,indicating the importance of local dynamical/thermodynamic processes in regulating the wind speed.This study demonstrates that the combination of numerical models and machine learning techniques has important implications for refined local wind forecasting.

Impacts of Roof/Ground Mitigation Strategies on Improving the Urban Thermal Environment and Human Comfort over the Yangtze River Delta, China

The combined effects of global warming and the urban heat islands exacerbate the risk of urban heat stress. It is crucial to implement effective cooling measures in urban areas to improve the comfort of the thermal environment. In this study, the Weather Research and Forecasting Model(WRF), coupled with a single-layer Urban Canopy Model(UCM), was used to study the impact of heat mitigation strategies. In addition, a 5-km resolution land-cover dataset for China(ChinaLC), which is based on satellite remote sensing data, was adjusted and used, and 18 groups of numerical experiments were designed, to increase the albedo and vegetation fraction of roof/ground parameters. The experiments were conducted for four heatwave events that occurred in the summer of 2013 in the Yangtze River Delta urban agglomeration of China. The simulated results demonstrated that, for the single roof/ground schemes, the mitigation effects were directly proportional to the albedo and greening. Among all the experimental schemes, the superposed schemes presented better cooling effects. For the ground greening scheme, with similar net radiation flux and latent heat flux, its storage heat was lower than that of the roof greening scheme, resulting in more energy flux into the atmosphere, and its daytime cooling effect was not as good as that of the roof greening scheme. In terms of human thermal comfort(HTC), the improvement achieved by the ground greening scheme was better than any other single roof/ground schemes, because the increase in the relative humidity was small. The comprehensive evaluation of the mitigation effects of different schemes on the thermal environment presented in this paper provides a theoretical basis for improving the urban environment through rational urban planning and construction.

城市化对2008年8月25日上海一次特大暴雨的影响

本文利用新一代中尺度数值天气模式Weather Research and Forecasting Model(v3.1.1,WRFV3)、日本气象厅20 km分析资料及自动站观测数据等模拟了2008年8月25日上海一次特大暴雨过程,并研究了城市化对这次暴雨过程的影响.研究结果表明:WRFV3模式能够较好地模拟出上海0825暴雨的主要分布特征,强降水中心以及暴雨随时间变化趋势;上海城市化使得这次暴雨过程在城市中心区域和迎风区降雨增强,城市背风区降雨减少;而城市化引起的陆面粗糙度等变化的动力作用对城市地区低层风场产生阻挡,使得城市迎风区垂直上升运动增强、水汽增多,是造成城市迎风区降雨增强的主要原因.

三维变分同化机载雷达资料对飓风预报的影响研究——2012年Isaac试验

随着气旋内部资料(Inner core data)在热带气旋预报中的使用,其重要性逐渐受到人们越来越多的关注。为了研究该资料中尾部机载雷达(Tail Doppler Radar,TDR)资料在业务系统中的应用效果,本文利用2012年飓风等级热带气旋Isaac期间的TDR资料,采用业务HWRF(Weather Research and Forecasting model for Hurricane)数值模式与业务GSI(Grid-point Statistical Interpolation system)三维变分同化(Three-Dimensional Variational Data Assimilation,3DVar)系统对TDR资料进行了同化,展开了一系列预报试验,并对其效果进行了分析和研究。结果表明与HWRF的业务预报相比,GSI系统同化TDR资料后对热带气旋的路径和强度预报有明显改进;但其同化效果同时也表明业务三维变分中的静态背景误差协方差在TDR资料的应用中仍需要进一步的改进。

内蒙古电网区域风电功率预测系统

内蒙古电网区域风电功率预测系统采用分布式结构,由数值气象预报系统和风电功率预测系统组成:风电功率预测以数值预报模式和风电功率统计预报模型为基础;数值气象预报采用MM5中尺度数值气象预报模式对风电场所在区域未来48h不同高度的风速、风向、温度、湿度、气压和降水进行滚动预测,计算网格水平分辨率为9km。基于相似模型理论,采用人工神经网络方法,建立了区域风电功率预测模型,实现了对单个风电场、特定区域内风电场群和全网风电功率的短期和超短期预测。