暴雨模拟中多普勒雷达径向速度变分同化的应用

针对2008年6月广东地区的一次强降雨过程,利用WRF中尺度数值模式及其三维变分同化系统(WRF-3DVAR),进行了多普勒雷达径向速度变分同化对暴雨过程模拟效果影响研究。结果表明:WRF-3DVAR能够有效地同化多普勒雷达径向速度,同化后的主要影响在于改进了初始动力场,使得初始场包含有更详尽的中尺度特征信息,进而显著提高模式对广东局地暴雨过程的模拟效果。在高分辨率中尺度数值模式中有效地利用多普勒天气雷达资料,是提高中尺度降雨预报的关键。     

多普勒天气雷达资料在暴雨数值模拟中的同化应用

基于中尺度数值模式WRF及其三维变分同化系统WRF-3DVAR对2008年6月广西地区的一次强降雨过程,进行了多普勒天气雷达的多普勒径向速度和反射率因子的三维变分同化对于暴雨过程模拟效果影响研究。结果表明：(1）同化柳州、桂林和永州多普勒天气雷达观测资料后,模式对广西东北部地区特大暴雨的模拟效果明显改进;(2）WRF-3DVAR能够有效地同化多普勒天气雷达径向速度和雷达反射率因子,同化后使得模式初始场包含有更详尽的中尺度特征信息;(3）在高分辨率中尺度数值模式中有效地利用多普勒天气雷达资料,改善了分析场中尺度结构的描述,从而减轻了spin-up现象,能较好的提高中尺度降雨预报。     

多普勒雷达资料在冷涡强对流天气中的同化应用试验

应用WRF模式的三维变分同化系统(WRF-3DVAR),对沈阳多普勒天气雷达资料在东北冷涡暴雨个例中的同化应用进行了试验.研制了多普勒雷达资料质量控制系统,实现了对径向风和反射率因子的直接同化,不但可以反演中尺度三维气象要素场,而且可以为模式提供初始场.以天气尺度资料为背景场同化多普勒雷达资料,WRF-3DVAR可以较好地反演冷涡中尺度对流系统的三维结构,反演的地面强对流辐散气流及在对流层中层涡旋都符合中尺度系统概念模型,通过与实际地面探测资料进行了对比,风场环流基本接近,同化了雷达资料的气象要素场可为预报业务提供较好的包含中小尺度系统的实时三维分析场.通过冷涡个例同化试验,应用WRF-3DVAR同化雷达资料后,中尺度模式对对流降水的预报总体有正的影响,对强对流中的一些中小尺度雨团的预报也略有改善.     

多普勒雷达资料同化的稀疏化方式对暴雨过程的影响研究

利用中尺度非静力WRF(Weather Research and Forecasting)模式及其三维变分同化系统,对2007年7月淮河流域的一次强降雨过程进行多普勒雷达径向速度资料的三维变分同化试验,重点考察雷达资料的不同稀疏化方式对同化结果以及对暴雨数值模拟的影响。结果表明:同化多普勒雷达径向速度资料使得模式初始风场包含了更丰富的中尺度特征信息,有效调整了初始场的环流结构,能够改善模式对暴雨过程的模拟效果;以不同的稀疏化处理方式同化多普勒雷达径向速度资料对分析场会产生不同的影响,进而影响模式的降水预报效果,本次试验中当极坐标网格径向分辨率取10 km的时候降水过程的预报效果最好。     

多普勒雷达资料同化对暴雨预报的影响

诊断分析了2007年8月8日陕西中南部一次突发性大暴雨过程,利用WRFV3.4数值预报模式及WRF-3DVAR变分同化系统,采用直接同化西安C波段多普勒雷达资料的方法,设计了4组试验方案。结果表明,多普勒雷达资料同化能有效改进WRF数值模式性能,不同的同化方案对模式初始场及预报场有不同的改进,同化反射率对初始水汽场的改变较为显著,而同化径向速度对初始风场的改变更为明显。在加入雷达资料同化后模式系统对中小尺度天气系统特征的模拟效果提高,风场的辐合特征更为明显,水汽也有显著增强,降水强度和中心跟实况更为接近。     

一次大暴雨过程的多普勒雷达资料同化的敏感性试验

利用WRF中尺度模式及WRF-3DVAR变分同化系统和LAPS雷达资料前处理模块建立试验平台,直接同化S波段多普勒雷达反射率和径向速度资料,通过对2008年8月15-16日发生在我国长江中游的一次大暴雨过程的各项预报对比试验研究,初步检验和评估不同种类多普勒雷达观测数据同化对改进数值模式初始场及其数值预报能力的影响及作用.初步结果表明:多普勒雷达资料同化对提高暴雨数值预报能力有重要作用.无论在24 h累计降水还是在逐时降水预报方面,同化多普勒雷达资料均可使降水雨带分布和强降水中心预报的准确性得到较大改善;多普勒雷达反射率资料同化对初始水汽场的改变显著,对初始风场影响较小,而同化径向速度对初始水汽场的改变较小,但可增加初始风场的中小尺度信息,使初始风场产生较大变化.总体上看,虽然雷达反射率和径向速度资料同化均可改进强暴雨的数值预报,但雷达反射率资料同化对降水雨带和中心预报的改进更为显著和重要.     

多普勒天气雷达资料在数值模式ARPS中的试验

利用中尺度预报模式ARPS及其资料分析系统ADAS和三维变分同化系统ARPS3DVAR,直接加入多普勒天气雷达基数据反射率因子和径向速度资料进行数值预报试验。试验包括：控制试验、反射率因子同化试验、径向速度同化试验,两种资料同时同化,多时次连续同化等试验。通过模拟2009年7月7日发生在江苏省附近一次暴雨过程,分析了多普勒天气雷达反射率因子和径向速度资料不同组合的加入对改进模式初始湿度场、风场及预报结果的影响。结果表明：同化雷达反射率因子和径向速度资料,分别对湿度场和风场有显著调整;同时同化两种资料比单独同化在2 h内更显优势;多时次连续同时同化两种资料的试验比起其他试验预报的风速更接近探空风速,预报的降水位置与雷达3 h累积降水产品较为对应,但降水量的预报仍有偏差。     

基于雷达资料同化的江西一次暴雨过程的数值模拟试验

采用WRF中尺度模式及其三维变分同化系统WRF-3DVAR,对2014年5月24—25日发生在萍乡、宜春地区一次大暴雨天气过程进行了雷达资料直接同化敏感性试验,并对同化结果和模式降水预报进行了对比分析。结果表明:1)雷达资料的同化能有效改善初始场中风场、湿度场和热力场的量值大小及空间分布,使其包含更多的中尺度系统信息。其中,雷达反射率因子的同化对大气湿度场和温度场的影响较大,而雷达径向速度的同化作用主要是调整大气风场。2)短时降水预报方面,雷达反射率因子的同化对0—12 h短时降水预报的量值影响较大,而径向速度的同化对降水预报的落区影响较大,两者同时的同化对降水预报效果较好。3)雷达资料的同化对较长时间(6—12 h)的降水预报仍有较好效果。     

"7·8"特大暴雨过程雷达风场资料的三维变分同化研究

基于中尺度暴雨预报模式AREM和三维变分同化系统GRAPeS-3dvar对2003年7月8日发生在长江中游的一场特大暴雨过程,进行了武汉、宜昌多普勒雷达风场资料的三维变分同化研究,结果表明:(1)增加了武汉、宜昌多普勒雷达反演风场资料后,模式对湘-鄂交界处特大暴雨区的模拟效果改善非常显著.(2)分别单独增加武汉、宜昌多普勒雷达风场资料的三维变分同化后,降水模拟都有明显改进,但要差于对两部雷达风场资料同时进行变分同化的结果,表明同化的中尺度初始风场信息越多,初始场的质量越高,降水模拟效果越好.(3)雷达风场资料的三维变分同化,改善了分析场中尺度结构的描述,从而减轻了spin-up现象,使得模式在积分初期就能模拟出与实况相近的强降水.     

多普勒雷达资料的直接同化对降雨预报的影响

利用中尺度数值模式WRFV3.1及其三维变分同化系统WRFVAR3.1,对2008年8月10日奥运期间北京地区发生的一次强对流天气过程进行了多普勒雷达资料变分同化试验,并对同化结果和降水预报进行了对比分析。结果表明:(1)雷达资料的同化能有效改善初始场中风场、水汽、温度场的空间分布、量值大小,使其包含更多中尺度信息;(2)雷达反射率同化对大气的湿度场和温度场影响较大,而雷达径向速度同化则主要调整大气的风场;(3)对短时0～6h内的降水预报,反射率的同化对降水预报改善明显,径向速度的同化对降水预报影响相对较小,而两者的联合同化降水预报效果最好;(4)雷达资料的同化对较长时间6～12h的降水预报仍有较好效果。     

ANALYSIS OF THE EFFECT OF 3DVAR AND ENSRF DIRECT ASSIMILATION OF RADAR DATA ON THE FORECAST OF A HEAVY RAINFALL EVENT

The present study designs experiments on the direct assimilation of radial velocity and reflectivity data collected by an S-band Doppler weather radar (CINRAD WSR-98D) at the Hefei Station and the reanalysis data produced by the United States National Centers for Environmental Prediction using the Weather Research and Forecasting (WRF) model, the WRF model with a three-dimensional variational (3DVAR) data assimilation system and the WRF model with an ensemble square root filter (EnSRF) data assimilation system. In addition, the present study analyzes a Meiyu front heavy rainfall process that occurred in the Yangtze -Huaihe River Basin from July 4 to July 5, 2003, through numerical simulation. The results show the following. (1) The assimilation of the radar radial velocity data can increase the perturbations in the low-altitude atmosphere over the heavy rainfall region, enhance the convective activities and reduce excessive simulated precipitation. (2) The 3DVAR assimilation method significantly adjusts the horizontal wind field. The assimilation of the reflectivity data improves the microphysical quantities and dynamic fields in the model. In addition, the assimilation of the radial velocity and reflectivity data can better adjust the wind fields and improve the intensity and location of the simulated radar echo bands. (3) The EnSRF assimilation method can assimilate more small-scale wind field information into the model. The assimilation of the reflectivity data alone can relatively accurately forecast the rainfall centers. In addition, the assimilation of the radial velocity and reflectivity data can improve the location of the simulated radar echo bands. (4) The use of the 3DVAR and EnSRF assimilation methods to assimilate the radar radial velocity and reflectivity data can improve the forecast of precipitation, rain-band areal coverage and the center location and intensity of precipitation.     

雷达反射率三维拼图观测资料在北方区域数值模式预报系统中的同化应用研究

以业务应用为目标,开展雷达反射率三维拼图观测资料在北方区域数值预报系统中的同化应用研究。采用雷达反射率间接同化方法同化北方雷达反射率拼图观测资料,重点关注其对降水、湿度、温度及风的预报能力影响。首先,基于2017年8月雷达拼图观测资料批量同化和对比试验,对雷达拼图资料同化应用效果进行定量评估,结果表明雷达拼图资料同化虽然加大了地面风场预报误差,但在降水预报和湿度、温度预报等方面有明显的改善作用。其次,选择在业务中预报难度较大的强降水个例开展分析研究,分析表明:（1）同化雷达拼图观测资料有效提高了模式降水预报性能,临近降水发生的循环起报时次预报效果更好;（2）对于短时间多次强降水过程发生的预报,循环同化雷达拼图资料可及时弥补模式中由于前次降水导致的水汽、能量等消耗及热/动力条件削弱,持续支持降水系统发展。最后,通过考察雷达反射率的不同同化方案,发现同化反演水凝物或者估计水汽均能改善模式降水预报性能,但是同化估计水汽对降水预报性能的改善更为明显,联合使用两方案能同时对水凝物分布、热力场等进行调整,可提高模式降水预报性能。      

Improved Land Use and Leaf Area Index Enhances WRF-3DVAR Satellite Radiance Assimilation: A Case Study Focusing on Rainfall Simulation in the Shule River Basin during July 2013

The application of satellite radiance assimilation can improve the simulation of precipitation by numerical weather prediction models. However, substantial quantities of satellite data, especially those derived from low-level(surface-sensitive)channels, are rejected for use because of the difficulty in realistically modeling land surface emissivity and energy budgets.Here, we used an improved land use and leaf area index(LAI) dataset in the WRF-3 DVAR assimilation system to explore the benefit of using improved quality of land surface information to improve rainfall simulation for the Shule River Basin in the northeastern Tibetan Plateau as a case study. The results for July 2013 show that, for low-level channels(e.g., channel 3),the underestimation of brightness temperature in the original simulation was largely removed by more realistic land surface information. In addition, more satellite data could be utilized in the assimilation because the realistic land use and LAI data allowed more satellite radiance data to pass the deviation test and get used by the assimilation, which resulted in improved initial driving fields and better simulation in terms of temperature, relative humidity, vertical convection, and cumulative precipitation.     

Effect of Length Scale Tuning of Background Error in WRF-3DVAR System on Assimilation of High-Resolution Surface Data for Heavy Rainfall Simulation

We investigated the impact of tuning the length scale of the background error covariance in the Weather Research and Forecasting(WRF) three-dimensional variational assimilation(3DVAR) system.In particular,we studied the effect of this parameter on the assimilation of high-resolution surface data for heavy rainfall forecasts associated with mesoscale convective systems over the Korean Peninsula.In the assimilation of high-resolution surface data,the National Meteorological Center method tended to exaggerate the length scale that determined the shape and extent to which observed information spreads out.In this study,we used the difference between observation and background data to tune the length scale in the assimilation of high-resolution surface data.The resulting assimilation clearly showed that the analysis with the tuned length scale was able to reproduce the small-scale features of the ideal field effectively.We also investigated the effect of a double-iteration method with two different length scales,representing large and small-length scales in the WRF-3DVAR.This method reflected the large and small-scale features of observed information in the model fields.The quantitative accuracy of the precipitation forecast using this double iteration with two different length scales for heavy rainfall was high;results were in good agreement with observations in terms of the maximum rainfall amount and equitable threat scores.The improved forecast in the experiment resulted from the development of well-identified mesoscale convective systems by intensified low-level winds and their consequent convergence near the rainfall area.     

基于WRF-3DVAR同化多源融合数据对近海风模拟的改进试验

本文利用WRF模式及其3DVAR同化系统,以2008年4月20日00时—23日00时的江苏近海10 m风场为研究个例,对Quik SCAT、Wind SAT、多源测风融合数据进行同化试验,通过比较WRF-3DVAR同化系统对模拟风场初始场和预报场的改进,检验了同化不同类型资料后WRF模式对研究区域内单点及区域近地层风速的预报效果。结果表明:同化试验对初始场有改进,且对预报场的改进较FNL资料明显;不同资料对风场模拟的影响不同,同化星星、星地多源融合资料效果最佳,Quik SCAT次之,Wind SAT最差。此外,在模式分辨率一定的情况下,提高观测资料的分辨率并不一定能够改善模拟效果,资料的稀疏分辨率存在最佳选择。     

NUMERICAL EXPERIMENTS FOR THE EFFECTS OF TWO MODEL INITIALIZATION SCHEMES ON RAINFALL FORECAST IN THE 2008 FLOODING SEASON

In this paper, based on heavy rain numerical forecast model AREM （Advanced Regional Eta Model）, two different initialization schemes, LAPS and GRAPES-3DVAR, are used to run assimilation experiments of AREM-LAPS and AREM-3DVAR with the same data source （NCEP forecast field, surface data and radio-soundings） during the period from 21 May to 30 July 2008 to investigate the effect of the two initialization schemes on the rainfall simulation. The result suggests that： （1） the forecast TS score by the AREM-LAPS is higher than that by the AREM-3DVAR for rainfall in different areas, at different valid time and with different intensity, especially for the heavy rain, rainstorm and extremely heavy rain; （2） the AREM-3DVAR can generally simulate the average rainfall distribution, but the forecast area is smaller and rainfall intensity is weaker than the observation, while the AREM-LAPS significantly improves the forecast; （3） the AREM-LAPS gives a better forecast for the south-north shift of rainfall bands and the rainfall intensity variation than the AREM-3DVAR; （4） the AREM-LAPS can give a better reproduction for the daily change in the mean-rainfall-rate of the main rain band, and rainfall intensity changes in the eastern part of Southwest China, the coastal area in South China, the middle-lower valleys of Yangtze river, the Valleys of Huaihe river, and Shandong peninsula, with the rainfall intensity roughly close to the observation, while the rainfall intensity simulated by the AREM-3DVAR is clearly weaker than the observation, especially in the eastern part of Southwest China; and （5） the comparison verification between the AREM-LAPS and AREM-3DVAR for more than 10 typical rainfall processes in the summer of 2008 indicates that the AREM-LAPS gives a much better forecast than AREM-3DVAR in rain-band area, rainfall location and intensity, and in particular, the rainfall intensity forecast is improved obviously.