四维数据同化在一次梅雨锋暴雨过程中的应用研究

通过2008年梅雨季内的一次暴雨过程来着重研究WRF模式中四维测站同化技术的应用情况以及不同的同化策略对模拟结果的影响,使用的同化资料包括常规高空和地面探测资料。结果表明:高空探测资料的同化能够较好地修正中α尺度系统的移动发展速度,从而有效地改进强降雨带的落区位置;湿度观测资料的同化反而降低了强降雨带的降水强度,这可能因为同化湿度观测量可能减小近饱和区域内的水汽混合比,从而导致这些区域内的潜热加热减小,对流强度变弱,降水减少;地面观测资料的同化能够对模式行星边界层进行修正,这种同化影响通常在模式最低层上表现得较为明显,向上逐渐减小,而边界层模拟质量对降水至关重要,因此地面观测资料的加入使得模拟降水更加接近于实况。区域嵌套模拟试验表明对粗网格区域进行四维分析同化处理可以有效抑制中α尺度模式误差的增长,对细网格区域进行四维测站同化处理则可以进一步抑制中β尺度模式误差增长。     

探空加密观测资料对西南地区数值预报的影响分析

应用2013年6月逐日全国探空气象加密观测资料和常规观测资料,WRF模式模拟资料,西南地区地面自动站资料等,采用数值模拟、统计方法和天气学方法,分析了探空气象加密观测资料对数值模拟效果的影响。研究得到:(1)探空资料同化,总体上提高了降水的TS评分值,一定程度降低了降水预报空报率,提高了中雨和大雨的6h累积降水预报准确率。(2)探空资料同化主要使降水区上空位势高度增加,气旋环流减弱,从而影响降水落区和降水强度。(3)探空资料同化减小气象要素分析场和预报场的均方根误差,对高空要素预报的改进在前24h较明显,尤其是前6h,对地面气象要素预报在整个积分时段内总体呈现正效果作用。     

ATMS和CrIS卫星资料同化对青藏高原天气预报的影响

利用WRF模式和GSI同化系统同化美国最新一代的ATMS和Cr IS卫星资料,探讨卫星辐射资料同化对青藏高原天气要素预报准确性的影响。进行了四组试验模拟,即无资料同化的控制试验(CTRL)和三组同化试验,三组同化试验分别为:只用常规观测资料进行同化(CONV)、常规观测资料和ATMS卫星资料同化(ATMS)、常规观测资料和Cr IS卫星资料同化(CRIS)。分析了2015年1月及7月的温度场、相对湿度场和风场的预报能力,除了分析近地表2 m温度场、2 m相对湿度场及10 m风场外,也分析了高地形区域以及低地形区域不同高度层上气象要素的预报能力。结果表明:ATMS和CRIS同化对青藏高原天气要素预报效果改进并不具有普遍性,ATM S同化试验可以有效的增进7月低地形区域的2 m温度场、7月高地形区域2 m相对湿度场以及1月高地形区域10 m风场的24 h、48 h预报能力;CRIS同化对1月高地形区域2 m温度场24 h预报、1月与7月高地形区域10 m风场24 h与48 h预报有改善效果。就垂直分层来讨论,CRIS同化试验不管在哪个高度分层都无法有效地改进模式预报能力,ATMS同化试验则在不同分层、不同变量场有着不一样的预报效果。资料同化后温度场预报主要的误差来源是系统性误差,而相对湿度场和风场在同化后主要误差是由非系统性误差造成的。整体上ATMS同化试验效果优于CRIS同化试验。     

雷达资料快速更新四维变分同化中增加地面资料同化对强对流临近数值预报的影响

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发展的快速更新雷达四维变分分析系统（VDRAS）,通过在系统中加入地面自动气象站观测资料的同化方法,对发生在北京地区的10个强对流过程开展了地面资料同化的高分辨率模拟分析和检验评估,并与已经业务使用的地面资料融合方法进行对比。研究结果发现,地面观测资料同化使边界层1 km高度以下的分析场改善最为明显,风速和风向的均方根误差分别平均降低0.1 m/s和7.2°,温度的均方根误差降低0.2℃。模式最低层100 m高度的风速均方根误差降低0.5 m/s,风速的误差随高度上升逐渐增大。模式最低层风向的均方根误差降低15.5°,温度的均方根误差降低0.4℃,且1.5 km高度以下的温度偏差都减小。区域内地面10 m高风速的均方根误差平均降低0.2 m/s,风向的均方根误差降低10.8°,地面2 m气温的偏差也降低。随着预报时效的延长,地面温度和风场的误差不断增大,但地面资料同化方法在一定程度上可以提高1 h内地面气象要素的预报效果。对2019年5月17日北京地区局地强对流新生和增强过程的详细分析表明,地面自动气象站观测资料的同化方法相对于融合,可以通过更细致准确地分析低层大气的热动力特征,改善低层气象要素的预报效果。在此基础上,通过探究对流单体的局地触发机理发现,海风锋辐合线与城市的相互作用一定程度上影响了对流的局地新生和发展,该同化方法可以进一步提高北京地区局地突发强对流的临近数值预报能力。      

ATOVS 不同卫星资料在台风模拟中的同化试验研究

利用美国国家大气研究中心(NCAR)开发的中尺度模式WRF(ARW)V3.2 及其三维变分同化系统WRF-3DVAR,以1011 号超强台风“ 凡亚比” 为个例,采用连续循环同化的方法对ATOVS 卫星资料进行同化试验,探讨了同化ATOVS 不同卫星资料对“ 凡亚比” 模拟的影响。结果表明,强度影响方面:同化ATOVS不同资料均可有效改善台风强度,台风中心海平面气压平均偏差从42 hPa 下降到18 hPa,但不同资料间的差异并不显著,平均在6 hPa 以内,这表明仅同化ATOVS 资料对台风强度的改善相对有限。路径影响方面:(1)不同卫星的同一种传感器资料效果略有不同,同化NOAA-18 和NOAA-15 的AMSU-A 资料效果较好,NOAA-16 的AMSU-A 效果较差;同化NOAA-15 和NOAA-16 的AMSU-B 资料效果相当,且均优于AMSU-A 资料。(2) 同一颗卫星不同传感器资料的差异较大,同化AMSU-B 资料的改善较为明显,HIRS-3 次之,AMSU-A较差,而同时同化不同资料并没有带来更为明显的改善。(3) 同时同化多颗卫星ATOVS 资料的试验表明,将多种资料引入到同化系统的同时,也带来相应的累积误差,因而仅同化一颗卫星可能比同时同化两颗或三颗卫星ATOVS 资料的效果要好。      

多普勒雷达基本观测量直接同化对模式物理量场的影响

在GRAPES一3DVar雷达同化模块的基础上,建立了多普勒径向速度和基本反射率因子的直接同化观测算子,实现了雷达反射率因子和径向速度的直接同化,并对2007年7月3日的江淮梅雨进行了模拟试验。结果表明,多普勒径向速度的直接同化的主要影响表现在风场上,能够改善几乎整个三维风场分析,在雷达影响半径范围内,风场明显得到加强,影响当时天气的系统及其高低层配置被合理模拟,但对湿度场影响甚微。雨水混合比的直接同化的主要影响表现在湿度场上,改进了模式对湿度场的模拟,对降水的影响十分显著,有利于准确模拟降水的发展和维持,减小了Spin—up现象;其亦可使整个风场微弱增强,但影响甚微。     

云迹风资料同化对暴雨预报影响的数值模拟

文中运用MM5对 1998年 6月 13～ 14日长江中下游一次暴雨强降水进行了数值模拟及云迹风资料同化试验研究。结果表明 ,云迹风资料同化能有效地改善高空风场质量 ,修正控制试验中模式高空风场对中纬度高空西风急流前沿西风强度的描述 ,使得模拟的暴雨强度与实际降水分布更加接近。分析认为在暴雨预报业务和科研中 ,云迹风资料的使用可有效地改善高空风场分布 ,对提高降水预报质量是一个有效途径 ,值得进一步尝试     

面向同化应用的红外高光谱探测资料局地综合通道选择方案及在FY-3D/HIRAS中的初步应用

通道选择是红外高光谱探测资料同化的关键技术。为了最大限度提取红外高光谱探测资料观测信息,减少模式在青藏高原等常规观测稀少地区的初始场的误差,不同区域需要选取不同通道进行同化。基于信号自由度的通道选择方法提出一种面向资料同化的红外高光谱资料的局地综合通道选择方案,该方案综合考虑了局地的大气温度垂直分布特征、背景误差协方差、仪器通道的雅克比函数、权重函数和其他影响红外高光谱模拟和同化的因素。针对CMA_GFS（原GRAPES_GFS）全球背景误差协方差,在高原和海洋两个典型区域对FY-3D/HIRAS红外高光谱资料的温度通道进行局地综合通道选择,并通过一维变分同化评估了局地综合通道选择方案对分析场的影响。结果表明,高原和海洋两个典型区域的大气温度垂直分布特征、背景误差协方差、模式垂直分层以及各通道的雅克比函数和权重函数均有明显的差异,选出的敏感通道也明显不同,相比较在其他区域选择出的通道,在对应地区选择的通道能够显著提高红外高光谱资料的同化效果。      

江西区域多元变量背景误差协方差特征分析

江西省暴雨灾害频繁发生,改善同化系统性能是提高数值天气预报水平的有效手段,构建合理的背景误差协方差是做好资料同化的关键工作。基于WRF模式的江西区域一个月控制预报为样本,计算得到多元变量相关的背景误差协方差,分析其平衡约束特征、特征值、特征向量以及特征长度尺度。结果表明,江西区域模式层中的低层和高层风场辐合、辐散分量的作用更大,各个变量对水汽场的贡献也集中在低层和高层,其中温度场起主导作用;模式层高层温度场的模拟效果偏差,各个变量的垂直相关性较大;相较于风场,温度场和水汽场在水平方向影响范围小,具有较强的局地性。     

伴随模式同化系统在修正模式误差中的应用研究

资料误差和模式误差都是制约数值预报结果准确性提高的关键因素,传统四维资料同化都是假设模式完全正确仅对初始资料进行修正,忽略了模式误差本身造成的预报误差。伴随模式同化系统不仅具有修正资料误差的能力,也可应用于修正模式误差方面的研究。本文将卫星中心导风系统提供的GMS5卫星风场与非常规温度资料用于MM5伴随同化系统修正模式地形误差进行试验性研究表明,该方法能够反演出一个既与初始气象要素场相匹配,又与模式更协调的地形场,得到比一般包络地形更好的效果,改善模式对强降水中心及降水区域的预报;数值试验结果还揭示模式误差对模式预报造成一定的影响,用伴随方法对观测资料进行修正的同时也对模式误差进行修正的方法是可行的。     

The Impact of Satellite Radiance Data Assimilation within a Frequently Updated Regional Forecast System Using a GSI-based Ensemble Kalman Filter

A regional ensemble Kalman filter (EnKF) data assimilation (DA) and forecast system was recently established based on the Gridpoint Statistical Interpolation (GSI) analysis system. The EnKF DA system was tested with continuous threehourly updated cycles followed by 18-h deterministic forecasts from every three-hourly ensemble mean analysis. Initial tests showed negative to neutral impacts of assimilating satellite radiance data due to the improper bias correction procedure. In this study, two bias correction schemes within the established EnKF DA system are investigated and the impact of assimilating additional polar-orbiting satellite radiance is also investigated. Two group experiments are conducted. The purpose of the first group is to evaluate the bias correction procedure. Two online bias correction methods based on GSI 3DVar and EnKF algorithms are used to assimilate AMSU-A radiance data. Results show that both variational and EnKF-based bias correction procedures effectively reduce the observation and background radiance differences, achieving positive impacts on forecasts. With proper bias correction, we assimilate full radiance observations including AMSU-A, AMSU-B, AIRS, HIRS3/4, and MHS in the second group. The relative percentage improvements(RPIs) for all forecast variables compared to those without radiance data assimilation are mostly positive, with the RPI of upper-air relative humidity being the largest. Additionally, precipitation forecasts on a downscaled 13-km grid from 40-km EnKF analyses are also improved by radiance assimilation for almost all forecast hours.     

A STUDY ON SATELLITE DATA ASSIMILATION WITH DIFFERENT ATOVS IN TYPHOON NUMERICAL EXPERIMENTS

Based on the newly developed Weather Research and Forecasting model(WRF)and its three-dimensional variational data assimilation(3DVAR)system,this study constructed twelve experiments to explore the impact of direct assimilation of different ATOVS radiance on the intensity and track simulation of super-typhoon Fanapi(2010)using a data assimilation cycle method.The result indicates that the assimilation of ATOVS radiance could improve typhoon intensity effectively.The average bias of the central sea level pressure(CSLP)drops to 18 hPa,compared to 42 hPa in the experiment without data assimilation.However,the influence due to different radiance data is not significant,which is less than 6hPa on average,implying limited improvement from sole assimilation of ATOVS radiance.The track issue is studied in the following steps.First,the radiance from the same sensor of different satellites could produce different effect.For the AMSU-A,NOAA-15 and NOAA-18,they produce equivalent improvement,whereas NOAA-16 produces slightly poor effect.And for the AMSU-B,NOAA-15 and NOAA-16,they produce equivalent and more positive effect than that provided by the AMSU-A.Second,the assimilation radiance from different sensors of the identical satellites could also produce different effect.The assimilation of AMSU-B produces the largest improvement,while the ameliorating effect of HIRS/3assimilation is inferior to that of AMSU-B assimilation,while the AMSU-A assimilation exhibits the poorest improvement.Moreover,the simultaneous assimilation of different radiance could not produce further improvement.Finally,the experiments of simultaneous assimilation radiance from multiple satellites indicate that such assimilation may lead to negative effect due to accumulative bias when adding various radiance data into the data assimilation system.Thus the assimilation of ATOVS radiance from a single satellite may perform better than that from two or three satellites.     

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.     

微波湿度计资料在GRAPES模式中偏差订正方法研究

根据微波湿度计MHS(Microwave Humidity Sounder)辐射率资料及GRAPES(Global/Regional Assimilation and Pr Ediction System)模式的特点,建立适用于MHS资料的偏差订正系统,该系统包括扫描和气团偏差订正,其中气团偏差订正考虑水汽资料的特性,采用三种不同预报因子组合的方案。偏差订正结果表明:MHS各个通道的扫描偏差表现出不同特征;偏差订正后观测残差基本服从均值为零的高斯分布,且观测残差的均值有所降低并随时间变化平稳;三种气团偏差订正方案都有明显的订正效果,其中方案三的订正效果最佳。     

卫星资料循环同化应用对区域数值预报效果影响分析

为提高卫星资料在同化系统中的利用率及验证卫星微波资料对区域数值预报效果的影响,本文以2008年8月1-31日为研究时段,利用WRF模式及其WRF-3DVAR同化模块,设计并构建了卫星微波资料的快速循环同化方案,分析循环同化方案对数值预报的改进效果.结果表明,相比于单时次同化,循环同化方案使各预报要素的相关系数在一定程度上得到改善,均方差也呈现减小的趋势.此外,对研究时段内暴雨和台风个例的具体分析显示,循环同化方案能够有效改善降水和台风路径的预报.     

Assimilation of GPM Microwave Imager Radiance for Track Prediction of Typhoon Cases with the WRF Hybrid En3DVAR System

The impact of assimilating radiance data from the advanced satellite sensor GMI(GPM microwave imager) for typhoon analyses and forecasts was investigated using both a three-dimensional variational(3DVAR) and a hybrid ensemble-3DVAR method. The interface of assimilating the radiance for the sensor GMI was established in the Weather Research and Forecasting(WRF) model. The GMI radiance data are assimilated for Typhoon Matmo(2014), Typhoon Chan-hom(2015), Typhoon Meranti(2016), and Typhoon Mangkhut(2018) in the Pacific before their landing. The results show that after assimilating the GMI radiance data under clear sky condition with the 3DVAR method, the wind,temperature, and humidity fields are effectively adjusted, leading to improved forecast skills of the typhoon track with GMI radiance assimilation. The hybrid DA method is able to further adjust the location of the typhoon systematically. The improvement of the track forecast is even more obvious for later forecast periods. In addition, water vapor and hydrometeors are enhanced to some extent, especially with the hybrid method.     

一种新的TOVS大气湿度反演方法及试验

利用国家气象中心的数值天气预报（NWP）6 h预报场。作为同步物理反演模式初估场，由气象卫星垂直探测（TOVS）资料推导出大气湿度，并给出了试验结果。结果表明，TOVS湿度反演的相对误差（RMS）约为20%。其中，夏季反演结果略优于冬季，而且低层（1000 hPa）和高层（500 hPa以上）与初估场相比有较大的改进，中层（850，700 hPa）二者大致相当。与统计回归反演结果相比其精度约提高10%。该研究为在我国建立“卫星反演/数据同化/数值预报”相互影响的循环系统奠定了基础     

Improving the Analyses and Forecasts of a Tropical Squall Line Using Upper Tropospheric Infrared Satellite Observations

The advent of modern geostationary satellite infrared radiance observations has noticeably improved numerical weather forecasts and analyses.However,compared to midlatitude weather systems and tropical cyclones,research into using infrared radiance observations for numerically predicting and analyzing tropical mesoscale convective systems remain mostly fallow.Since tropical mesoscale convective systems play a crucial role in regional and global weather,this deficit should be addressed.This study is the first of its kind to examine the potential impacts of assimilating all-sky upper tropospheric infrared radiance observations on the prediction of a tropical squall line.Even though these all-sky infrared radiance observations are not directly affected by lower-tropospheric winds,the high-frequency assimilation of these all-sky infrared radiance observations improved the analyses of the tropical squall line’s outflow position.Aside from that,the assimilation of all-sky infrared radiance observations improved the analyses and prediction of the squall line’s cloud field.Finally,reducing the frequency of assimilating these all-sky infrared radiance observations weakened these improvements to the analyzed outflow position,as well as the analyses and predictions of cloud fields.     

晨昏轨道微波温度计资料同化对降水定量预报的影响及其对三轨卫星系统的意义

极轨卫星的高级微波温度计(Advanced Microwave Sounding Unit-A,简称AMSU-A)辐射资料对提高降水定量预报的水平有重要作用.但是极轨卫星的轨道特征导致乘载其上的微波温度计资料在区域同化系统中存在严重缺测.本研究重点分析了晨昏轨道卫星上微波温度计资料同化对墨西哥湾沿岸定量降水预报的重要影响.研究选取了早晨星NOAA-15、上午星MetOp-A和下午星NOAA-18,利用美国NCEP(National Centers for Environmental Prediction)的业务同化系GSI(Gridpoint Statistical Interpolation)资料同化系统,进行了加和不加NOAA-15 AMSU-A资料的两组资料同化和预报试验,来阐明晨昏轨道卫星上微波温度计资料同化对墨西哥湾沿岸降水预报的重要影响.试验结果分析表明如果仅同化NOAA-18和MetOp-A资料,在协调世界时00:00和12:00的同化时间,在墨西哥湾和美国西部大陆就是卫星观测资料缺测区,而早晨星NOAA-15资料正好可以填补这个资料空缺.模式预报也表明,同化NOAA-15的AMSU-A资料可以对墨西哥湾降水有持续的正影响.这一研究证明了保持有搭载着AMSU-A或者相似仪器的早晨星,对区域降水预报的重要性.由于目前NOAA-15是唯一的一颗正在运行的、已远超过其正常运行期的早晨星,通过技术手段维持NOAA-15的AMSU-A仪器更超长期运行也就特别重要.