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.

Artificial Intelligence Based Meteorological Parameter Forecasting for Optimizing Response of Nuclear Emergency Decision Support System

This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.

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.

Solar Energy Resource Characteristics of Photovoltaic Power Station in Shandong Province

[Objective] The aim was to analyze characters of solar energy in photo- voltaic power stations in Shandong Province. [Method] The models of total solar radiation and scattered radiation were determined, and solar energy resources in pho-tovoltaic power stations were evaluated based on illumination in horizontal plane and cloud data in 123 counties or cities and observed information in Jinan, Fushan and Juxian in 1988-2008. [Result] Solar energy in northern regions in Shandong proved most abundant, which is suitable for photovoltaic power generation; the optimal angle of tilt of photovoltaic array was at 35°, decreasing by 2°-3° compared with local latitude. Total solar radiation received by the slope with optimal angle of tilt exceeded 1 600 kw.h/（m2.a）, increasing by 16% compared with horizontal planes. The maximal irradiance concluded by WRF in different regions tended to be volatile in 1 020-1 060 W/m2. [Conclusion] The research provides references for construction of photovoltaic power stations in Shandong Province.

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.

基于Polar WRF模拟结果估算南极泰山站近地面大气折射率结构常数

天文台址的选择与近地面的光学湍流强度密切相关,南极与中低纬度相比,具有极低的天空背景辐射、极低的气溶胶浓度和非常小的光污染,吸引了世界多国在此建立天文观测站。采用专门用于极地研究的极地数值天气预报模式(Polar WRF)来模拟得到南极泰山站的常规气象参数,对于温度和风速大小,模拟值与观测值的相关系数分别高达0.95和0.89。由模拟得到的常规气象参数根据Monin-Obukhov相似理论估算折射率结构常数(C_n^2),并与位于泰山站处移动式极地大气参数测量系统的观测结果做了对比,结果表明模拟值与观测值变化趋势基本一致,相关系数达0.67。

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 （WRY） 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.

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.

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.

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.

基于Polar WRF的南极Dome A极端低温事件分析

南极作为地球的寒极,其最高点Dome A地区于2013年8月1日气温达到-93.0℃的极低值。利用Polar Weather Research and Forecasting(Polar WRF)3.8.1模式,对发生在南极Dome A地区的3次极端低温事件进行数值模拟分析。通过与自动气象站实测数据对比验证,模拟效果较为理想。结果表明:印度洋和大西洋交界区域的高压加强,其高压脊开始向南极内陆延伸,导致Dome A地区气压升高,使得该地区天气晴好,云量极低,为极端低温事件发生奠定基础;同时,南极中心冷涡加强,长时间的冷平流和稳定的逆温层为Dome A地区提供了足够的降温条件,并且加强了夜间辐射降温效应,稳定的垂直场、极低的向下长波辐射使得Dome A地区的极端低温事件得以维持。

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 Cbangjiang 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 SAR- retrieved 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.

机载双极化气象雷达雷暴回波仿真与验证

雷暴是一种短暂而剧烈的强对流天气,常伴有闪电、冰雹、强降水等危险天气,对民航飞机的飞行安全造成巨大威胁。机载气象雷达作为保证飞行器飞行安全必备的装备,用于探测与显示航路附近的实时气象信息,辅助机组人员规避危险气象。由于极化技术在气象探测方面的优势,双极化雷达成为机载气象雷达的发展方向。但是雷暴天气具有发展迅速、变化复杂,危险性高等特点,使得获取实测机载双极化气象雷达雷暴回波数据困难。为了解决这一问题,本文基于机载双极化气象雷达提出一种雷暴回波仿真方法并进行验证。方法首先利用数值预报模式WRF模式(Weather Research and Forecasting)对雷暴气象场景进行模拟;然后使用T-Matrix方法计算气象粒子的单个粒子散射振幅矩阵,同时结合场景内粒子的微物理特性,计算雷暴目标的反射率因子;最后应用雷达气象方程,基于机载气象雷达系统参数建立雷暴回波信号模型,实现机载双极化气象雷达雷暴回波信号仿真。最后,为检验方法的正确性和准确性,基于雷暴单体识别算法对回波仿真结果进行验证。通过仿真不同仰角下雷暴回波,实验结果表明,基于WRF模式的机载双极化气象雷暴回波仿真方法对雷暴天气具有良好的模拟能力,经单体识别算法验证,结果表明可准确体现雷暴单元的质心分布,结构属性和立体特征,对比实测数据,雷暴回波仿真结果与实测数据相吻合,实验结果具有真实性和准确性。

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.

考虑大气稳定度的“沙戈荒”风电基地风资源评估

“沙戈荒”风电基地昼夜温差大、易受大气稳定度影响、缺乏代表性测风数据,亟需开展“沙戈荒”风电基地的风资源特性评估。以正在建设的内蒙古阿拉善盟“沙戈荒”风电基地为研究对象,采用天气研究与预报模式进行数值模拟,并利用测风数据验证模型的准确性,重点探究大气稳定度的时空分布特征及其对风速的影响。研究表明,该地区的风速和风功率密度在11月至次年5月较高,主要受到西北季风影响,在寒潮过境后,风功率会出现急剧下降;中性大气状态在冬季占比最大,且中性条件下风速最大;相较于平坦地形,山地区域的强稳定和强不稳定大气状态占比显著下降,中性大气稳定状态占比显著增加,山地区域冬季的中性大气状态占比可达48.4%。本研究可为“沙戈荒”风电基地微观选址提供理论依据和技术支撑。

基于WRF模拟的中国西北河谷城市夏季的大气边界层特征

为提高河谷地形气象场的模拟效果,利用第5代再分析资料(ERA5)和全球再分析资料(FNL)作为初始场,以天水市为研究对象,驱动中尺度天气预报模式比较对西北河谷城市边界层模拟的适用性,分析西北河谷城市夏季的大气边界层特征.结果表明, ERA5模拟的天水市主城区近地面温度、近地面风速、风向以及相对湿度与观测值的相关性更好,尤其是近地面风速和风向,分别比FNL模拟的结果提升25.4%和70.0%.天水市主城区的气象场空间分布呈明显的城市热岛效应和山谷风环流,相对开阔的麦积区城市热岛效应更强;白天发生的降水会弱化谷风环流和热岛效应,河谷内及周边风速均较小.天水市主城区夏季近地面温度与风速呈正相关,与相对湿度呈负相关,大气边界层高度呈现明显的日变化,大气层结稳定.

WRF模式对三峡库区万州段特大暴雨的模拟分析

为提升三峡库区万州段暴雨模拟与预报精度,基于中尺度模式WRF及FNL再分析资料,针对三峡库区万州段4次典型暴雨事件,由5种云微物理方案、3种积云对流方案、RRTM长波辐射方案、Dudhia短波辐射方案、YSU边界层方案和Noah陆面方案组合的15种物理参数组合方案,系统分析不同参数化方案组合对降水时空特征的模拟能力,并优选物理参数化方案,构建适用于研究区的WRF模式,提高模拟精度。研究结果表明:WRF模式能够较好地再现降水时空变化特征,但强降水时段存在超前现象,且降水模拟值普遍偏低,每小时降水量的平均绝对误差范围为-0.62~-0.12 mm,48 h累积降水量空间分布的相对误差范围为-66.90%~16.75%;WSM6-GD-Noah-RRTM/Dudhia(A5)方案综合表现最佳,其48 h累积降水量模拟相对误差仅为2.79%,对大雨和暴雨量级模拟的平均TS评分最高,达到0.26,尤其是暴雨中心降水量值显著优于其他方案;A5方案模拟的降水特征与实况最为吻合,为提升该区域气象模拟精度和防灾减灾提供了重要的理论支持。

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。