水物质对云雨区卫星微波观测模拟影响

受云和降水影响卫星资料在数值天气预报中的同化应用对于进一步改善数值预报效果具有重要作用, 这部分工作的开展要求快速辐射传输模式中能够较好地考虑各种水物质的辐射效应。使用美国卫星资料同化联合中心新近开发的快速辐射传输模式CRTM, 通过中尺度数值模式WRF的预报输出提供水物质输入, 分析水物质辐射效应对云雨区卫星微波观测模拟计算的影响。在WRF模式预报水物质的分布和天气系统配置合理并符合云物理基本特征的前提下, 水物质辐射效应的考虑极大改善了卫星观测模拟的效果。结合卫星各通道探测特性, 进一步分析各种水物质粒子对NOAA-16 AMSU A/B各通道卫星亮温模拟的影响和物理机理, 定量统计各类水物质对各卫星观测通道亮温计算偏差和偏差贡献的权重大小。分析结果表明:快速辐射传输模式中, 考虑水物质辐射效应为数值天气预报中云雨区卫星资料的同化应用提供了必需的基础条件。     

有云条件下HIRS/3资料的同化及其对“珍珠”台风的影响

卫星红外辐射资料汽接同化容易受到云的影响,大量卫星资料在有云情况下无法直接同化,其原因之一就是初始云结构难以获取.而云结构是同化系统观测算子的重要输入参数,缺乏云的结构信息,观测算子尤法模拟有云环境下的亮温.热带地区以及台风、暴雨等极端天气系统与云密不可分,要改进卫星辐射资料特别是红外资料直接同化的效果,需要获得较高精度的云三维结构.在GRAPES-3DVAR(Global and Regional Assimilation and Prediction Enhanced System,全球/区域同化预报系统)基础上,结合WRF(Weather Research and Forecasting Model,天气研究和预报模式)对"珍珠"台风云结构的模拟,增加模拟的云参数作为GRAPES-3DVAR同化系统中RTTOV模式(fast radiative transfer model for TOVS,快速辐射传输模式)的输入参数,改进了有云环境下卫星资料直接同化的观测算子,研究了红外辐射资料直接同化的方法,并分析其对"珍珠"台风预报的影响.针对NOAAl6(National Oceanic and Atmospheric Administration,美国国家海洋和大气管理局)的HIRS/3(High Resolution Infrared Radiation Sounder,高分辨率红外辐射探测仪3型)第4-8、10、13 19通道辐射亮温的同化试验表明,结合初始云结构信息改进同化系统观测算子,可以将红外辎射资料的观测信息同化到模式之中,改进台风温度、湿度结构,对短时降水预报有正面影响.     

云区卫星微波通道亮度温度的数值模拟

目前多数资料同化系统中对卫星的观测值都是采用晴空模拟,然而用晴空辐射传输模式模拟云区卫星微波通道的辐射值会造成与观测较大的偏差,导致大量云区卫星资料被直接抛弃无法进入同化系统,因而有必要改进云区卫星辐射亮温的模拟能力,进而提高同化系统中云区卫星资料利用率。以2010年台风“圆规”、“凡比亚”和“鲇鱼”为例,基于先进的微波扫描辐射计AMSR-E观测应用一维变分算法反演台风区域的云宏观参数,包括云液水含量廓线、云冰水含量廓线和雨水含量廓线;然后,以大气温度、湿度廓线及这些反演的云参数作为快速辐射传输模式CRTM的输入参数,模拟AMSR-E各通道的辐射亮温。通过对比晴空、有云两种情况下模拟亮度温度与实际观测亮度温度间的偏差,发现增加云参数作为辅助参数、启动辐射传输的散射模块,可以有效地改进台风外围云区卫星辐射亮温的模拟效果,大幅减少模拟亮温与观测亮温间的偏差,增加了同化进数值预报系统的卫星观测数据量。      

云参数对RTTOV5模式模拟误差的影响分析

该文根据1998年8月的业务TOVS反演的温度、水汽垂直廓线资料以及其它资料, 利用RTTOV5模式模拟NOAA14极轨气象卫星上相应红外探测 (HIRS) 通道的辐射亮温值, 将模拟值对比实测TOVS探测资料, 结果表明, 晴空模式模拟亮温与实测值的误差小于部分有云时的误差, 模拟误差受云的影响呈反相变化, 对水汽敏感的中低层探测通道在晴空时的误差小于部分有云情况; 通过对比白天和夜间短波窗区探测通道模拟误差, 分析了其受地面反射太阳光辐射的影响的大小及其原因所在; 并利用RTTOV5的伴随模式和Jacobine模式分析了模式模拟误差对初始场云参数的敏感性。该研究为TOVS/ATOVS探测资料在3DR或4DR变分同化中的直接应用奠定了基础。     

水物质辐射效应对卫星观测模拟误差的影响分析

受云和降水影响的卫星资料在数值天气预报中的同化应用,对于进一步改善数值预报效果具有重要的作用,这部分工作的开展要求在快速辐射传输模式中能够较好地考虑各种水物质的辐射效应。使用美国卫星资料同化联合中心新近开发的快速辐射传输模式CRTM,通过中尺度数值模式WRF的预报输出提供其水物质输入,试验分析了快速辐射传输模式中水物质效应对卫星观测模拟计算的影响。在WRF模式预报水物质分布与天气系统配置合理并符合云物理基本特征的基础上,水物质辐射效应的考虑极大地改善了卫星观测模拟的效果。结合卫星各通道探测特性,进一步分析了各种水物质粒子对NOAA16AMSUA／B各通道卫星亮温模拟的影响和物理机理,定量统计了各类水物质对各卫星观测通道亮温计算偏差和水物质对各通道偏差贡献的权重大小。分析结果表明,快速辐射传输模式中水物质效应的考虑为数值天气预报中云雨区卫星资料的同化应用提供了必需的基础条件。     

FY-3A微波探测资料的直接同化应用及云雨条件下的亮温模拟

针对FY-3A星载微波垂直探测的同化应用,在扩展WRF3Dvar中FY-3A微波资料同化功能和快速辐射传输模式RTTOV微波云雨粒子散射RTTOV-SCATT模块接口的基础上,以2008年“凤凰”台风为研究对象,试验了FY-3A晴空条件下微波资料同化应用对数值预报的影响,并以此为控制试验,进一步讨论云检测方案和偏差订正调整对资料应用效果的作用。在WRF3Dvar同一框架下,使用RTTOV和CRTM云雨散射模块对云雨条件下FY-3A微波亮温进行模拟,分析云雨辐射效应对FY-3A微波温度和湿度传感器观测模拟的影响,并比较两个快速辐射传输模式结果间的异同。结果表明:本个例中FY-3A微波资料的使用对台风强度预报误差的减小比路径预报更为明显。云检测是影响卫星资料效能发挥的关键因素之一,3.0和5.0分别是MWTS和MWHS使用单窗区通道作为云检测时的合适阀值。使用FY-3A资料导出的偏差订正系数可以改善偏差订正结果,并提高预报准确率。此外,对于MWTS,通道1是受云雨粒子辐射效应影响最显著的通道,通道2同样具有明显影响。MWHS全部5个探测通道均受云雨粒子辐射效应影响,云雨条件下通道1、2的模拟偏差最大。RTTOV和CRTM的结果具有相同的统计特征,但CRTM云雨粒子辐射效应带来的偏差比RTTOV要大。      

台风"杜鹃"的AMSU卫星微波探测资料分析

由于微波具有穿透云的能力,AMSU卫星探测资料得到了越来越广泛的应用。利用AMSU多个通道的资料,对2003年台风“杜鹃”过程进行了分析。通过比较AMSU-B（89GHz和150GHz）与GOES-9的台风结构图像可以发现微波具有较强的垂直探测能力;在AMSU-B的5个通道中,通道2（Ch2）亮温值的大小能够最好地反映热带气旋螺旋雨带冰晶层的深厚程度,从而判定螺旋雨带的强度;Ch2的亮温分布与雷达的强降水回波有较好的对应关系;利用AMSU-A温度反演资料能够清晰地揭示热带气旋的暖心结构、地面风速和中心气压与250hPa温度距平的关系,以及强降水的落区等。结果表明：AMSU资料作为一种新的卫星微波探测资料,在热带气旋的结构、螺旋雨带的强度及其降水强度的分析预报中具有一定的应用价值。     

AMSU微波探测资料同化的质量控制方法概述

微波相比红外、可见光等卫星探测方式有能够穿透薄云的优点,同化微波探测资料能明显改进数值预报模式初始场。由于观测算子在云、降水粒子及性质复杂下垫面等因素影响下模拟辐射传输过程不准确,以及资料的观测误差较大等原因,实际同化应用时必须对微波探测资料加以认真筛选。为充分发挥探测资料作用并保证同化分析效果,在同化AMSU微波探测的研究中,很多机构和学者建立了散射指数、降水检测等质量控制方法,用来剔除观测算子不能准确模拟的观测。研究表明,资料同化过程中引入质量控制能起到改善同化效果,提高数值天气预报准确率的作用。但是,对于各种质量控制方法的原理和使用条件目前尚无完整的分析,使得各业务研究单位使用的质量控制方案差别较大。文章针对AMSU微波探测资料同化,在分析同化误差来源的基础上,总结了散射指数、降水概率、下垫面类型检测等质量控制方法,并简单讨论了质量控制的发展方向。     

在MM5伴随模式中使用AMSU资料对暴雨的数值模拟

在MM5伴随模式中使用NOAA-16极轨卫星探测获得的AMSU 资料,并与MM5数值模式仅使用常规资料的条件下,对发生在2003年7月4-5日江淮流域的一次暴雨过程进行了数值模拟对比研究.结果表明:使用AMSU资料后,湿度场、温度场和风场均得到一定程度的改善,降水的落区和强度也更接近实况.     

应用ATOVS资料和非对称Bogus资料对登陆台风韦帕的4DVAR数值模拟分析

前人研究中BDA方法采用的轴对称Bogus台风不能反映个别台风具体特征并弃掉了背景场的合理成分,也没有考虑大环境场的影响及湿热要素的同化。因此,提出一种充分融合分析场信息和实际观测信息并考虑副高影响的精细非对称台风Bogus方法,并在MM5的伴随同化系统中引入快速辐射传输模式RTTOV8,通过四维变分同化(4DVAR)技术,加入海面风场和气压场Bogus资料及多颗卫星多条轨道上的ATOVS红外和微波卫星辐射亮温资料并考虑Noah陆面过程方案来对登陆台风韦帕进行数值模拟,结果表明,单独同化海面Bogus资料的BDA方案可间接产生初始场非对称三维环流结构和暖心结构,但对湿度场及台风周围大环境场的调整不足,台风登陆后的路径预报改善也不明显;引入陆面过程方案弥补了Bogus资料对台风登陆后路径预报的不足;加入ATOVS资料能对湿度场及台风周围环境场做出调整,重构了大量中尺度结构信息,取得更为精细的初始台风环流和温压湿场结构,保持BDA方案路径及强度预报的优势的同时,使预报的降水强度增加,降水落区发生改变。     

Influence of Surface Temperature and Emissivity on AMSU-A Assimilation over Land

AMSU-A (Advanced Microwave Sounding Unit-A) measurements for channels that are sensitive to the surface over land have not been widely assimilated into numerical weather prediction (NWP) models due to complicated land surface features. In this paper, the impact of AMSU-A assimilation over land in Southwest Asia is investigated with the Weather Research and Forecasting (WRF) model. Four radiance assimilation experiments with different land-surface schemes are designed, then compared and verified against radiosonde observations and global analyses. Besides the surface emissivity calculated from the emissivity model and surface temperature from the background field in current WRF variational data assimilation (WRF-VAR) system, the surface parameters from the operational Microwave Surface and Precipitation Products System (MSPPS) are introduced to understand the influence of surface parameters on AMSU-A assimilation over land. The sensitivity of simulated brightness temperatures to different surface configurations shows that using MSPPS surface alternatives significantly improves the simulation with reduced root mean square error (RMSE) and allows more observations to be assimilated. Verifications of 24-h temperature forecasts from experiments against radiosonde observations and National Centers for Environmental Prediction (NCEP) global analyses show that the experiments using MSPPS surface alternatives generate positive impact on forecast temperatures at lower atmospheric layers, especially at 850 hPa. The spatial distribution of RMSE for forecast temperature validation indicates that the experiments using MSPPS surface temperature obviously improve forecast temperatures in the mountain areas. The preliminary study indicates that using proper surface temperature is important when assimilating lower sounding channels of AMSU-A over land.     

中尺度区域模式层顶高度对高空风场数值模拟的影响分析

本文基于中尺度区域模式WRF,开展模式层顶高度变化对高空气象要素,特别是高空风场数值模拟影响的研究。通过设计模式顶高45、5 hPa两个试验,同化来源于NOAA-15、NOAA-18、NOAA-19和METOP-2的AMSU-A辐射计高通道数据,表明提高模式层顶能够使卫星更多的高通道样本数量进入同化系统,达到减小背景场误差,同时减小高于层顶通道辐射能量对低层通道影响的目的,一定程度上改进了同化效果,从而改善高空气象要素,特别是风场的模拟效果,与观测值的均方根误差减小了约0.4~0.5 m·s^-1。     

A PRELIMINARY STUDY ON THE 3DVAR ASSIMILATION OF THE AMSU-A DATA IN SPACE-TIME MULTISCALE ANALYSIS SYSTEM

Assimilating satellite radiances into Numerical Weather Prediction (NWP) models has become an important approach to increase the accuracy of numerical weather forecasting. In this study, the assimilation technique scheme was employed in NOAA’s STMAS (Space-Time Multiscale Analysis System) to assimilate AMSU-A radiances data. Channel selection sensitivity experiments were conducted on assimilated satellite data in the first place. Then, real case analysis of AMSU-A data assimilation was performed. The analysis results showed that, following assimilating of AMSU-A channels 5–11 in STMAS, the objective function quickly converged, and the channel vertical response was consistent with the AMSU-A weighting function distribution, which suggests that the channels can be used in the assimilation of satellite data in STMAS. With the case of the Typhoon Morakot in Taiwan Island in August 2009 as an example, experiments on assimilated and unassimilated AMSU-A radiances data were designed to analyze the impact of the assimilation of satellite data on STMAS. The results demonstrated that assimilation of AMSU-A data provided more accurate prediction of the precipitation region and intensity, and especially, it improved the 0–6h precipitation forecast significantly.     

土壤湿度对卫星辐射率资料直接同化的影响

本研究利用WRF模式及其三维变分同化系统实现了对NOAA-16 AMSU-A微波资料的直接同化,针对2010年6月19日江西地区的一次强降水过程开展模拟与同化试验,并利用中国区域土壤湿度同化系统(CLSMDAS—China Land Soil Moisture Data Assimilation System)输出的土壤湿度值替换NCEP(National Centers for Environmental Prediction)资料中的土壤湿度,研究土壤湿度初值对辐射率资料直接同化中观测场与背景场偏差调整的影响。结果表明:采用CLSMDAS输出土壤湿度初值条件下模拟的亮温值与实际观测值更为接近,经过质量控制和偏差订正后更多的观测资料能够进入到同化系统中,说明改进的土壤湿度初值条件下观测算子的计算值得到正的调整,对低层地表通道的改进效果明显,尤其以50.3 GHz的窗区通道3的结果最为理想;针对此次强降水过程中24 h累积降水分布的模拟结果,CLSMDAS输出土壤湿度初值条件下同化AMSU-A资料,能够较为准确的把握整个雨带的走向、大雨以上级别降水的落区范围、降水中心落区及强度等。说明准确的土壤湿度初值能够改进卫星辐射率资料的同化结果,进而提高数值模式的模拟预报能力。     

Assimilating AMSU-a radiance data with the WRF hybrid En3DVAR system for track predictions of Typhoon Megi (2010)

The impact of assimilating radiances from the Advanced Microwave Sounding Unit-A (AMSU-A) on the track prediction of Typhoon Megi (2010) was studied using the Weather Research and Forecasting (WRF) model and a hybrid ensemble three-dimensional variational (En3DVAR) data assimilation (DA) system. The influences of tuning the length scale and variance scale factors related to the static background error covariance (BEC) on the track forecast of the typhoon were studied. The results show that, in typhoon radiance data assimilation, a moderate length scale factor improves the prediction of the typhoon track. The assimilation of AMSU-A radiances using 3DVAR had a slight positive impact on track forecasts, even when the static BEC was carefully tuned to optimize its performance. When the hybrid DA was employed, the track forecast was significantly improved, especially for the sharp northward turn after crossing the Philippines, with the flow-dependent ensemble covariance. The flow-dependent BEC can be estimated by the hybrid DA and was capable of adjusting the position of the typhoon systematically. The impacts of the typhoon-specific BEC derived from ensemble forecasts were revealed by comparing the analysis increments and forecasts generated by the hybrid DA and 3DVAR. Additionally, for 24 h forecasts, the hybrid DA experiment with use of the full flow-dependent background error substantially outperformed 3DVAR in terms of the horizontal winds and temperature in the lower and mid-troposphere and for moisture at all levels.     

时间加密探空观测对分析和预报质量的敏感性研究

探空观测是气象资料同化中最基本的常规观测资料,对同化分析和预报的有效改善具有重要作用。由于现有探空观测站的空间分辨率较低,分布不均匀,且每日仅有两次观测,数量偏少,限制了其分析场对中小尺度大气状态的准确再现能力。自我国L波段雷达-数字探空仪更新换代以来,探空观测具备了获取每日4次、垂直分辨为秒级和分钟级的大气廓线资料。本文利用WRF中尺度数值模式,通过06时（世界时,下同）加密探空资料和12时常规探空资料的有效同化,研究分析了时间加密探空观测资料对同化分析和预报质量的敏感性影响。结果表明：同化06时的时间加密探空资料的午后暴雨预报质量优于12时常规探空观测。具体而言,同化06时的时间加密探空资料预报的大雨和暴雨的预报技巧高于12时常规探空资料;位势高度、温度和风场等预报场的均方根误差在高层的改进效果更加明显;06时的时间加密探空资料的同化对高层的高空急流和低层的水汽通量散度的预报质量贡献更大。批量试验进一步证实了有效同化时间加密探空资料对分析和数值预报效果改进的积极意义。     

AMSU资料变分同化及在暴雨数值模拟中的应用研究

在中尺度数值模拟中,利用中国气象科学研究院数值天气预报创新基地开发的GRAPES三维变分同化系统,对AMSU-A/B微波遥感资料进行了同化试验,研究了这种资料在我国夏季暴雨数值预报中的作用。以2003年7月4日的一次暴雨过程为例,分析了同化结果及模拟结果,结果表明:(1)单独同化AMSU-A资料主要改进了初始温度场,而单独同化AMSU-B资料主要改进了初始湿度场;(2)无论是同化AMSU-A资料还是同化AMSU-B资料,对暴雨预报都有一定的改进作用,但是同化AMSU-B资料的改进作用更明显;(3)同时同化AMSU-A/B资料比只使用其中一种资料的模拟效果好,可以更好地改进模拟的暴雨落区及强度,使结果与实况更加接近。使用AMSU资料,对我国夏季暴雨数值预报有改进作用。     

WRF模式中同化地基微波辐射计对降水的影响

地基微波辐射计观测已经用于数值预报中,并对预报效果产生不同的影响。目前,中国约有上百台地基微波辐射计,但是观测数据用到数值预报系统的很有限。本文尝试将两台地基微波辐射计数据同化到WRF数值预报模式,并针对北京一次暴雨过程,进行同化试验,结合地面雨量计测量结果进行比对。试验结果比较表明:同化地基微波辐射计能较明显影响降水初期的降水强度和分布,与雨量计分布更为接近;随着暴雨系统发展,同化两台地基微波辐射计对大面积强降水系统的影响甚微。     

Application of ATOVS Microwave Radiance Assimilation to Rainfall Prediction in Summer 2004

Experiments are performed in this paper to understand the influence of satellite radiance data on the initial field of a numerical prediction system and rainfall prediction. First, Advanced Microwave Sounder Unit A （AMSU-A） and Unit B （AMSU-B） radiance data are directly used by three-dimensional variational data assimilation to improve the background field of the numerical model. Then, the detailed effect of the radiance data on the background field is analyzed. Secondly, the background field, which is formed by application of Advanced Television and Infrared Observation Satellite Operational Vertical Sounder （ATOVS） microwave radiance assimilation, is employed to simulate some heavy rainfall cases. The experiment results show that the assimilation of AMSU-A （B） microwave radiance data has a certain impact on the geopotential height, temperature, relative humidity and flow fields. And the impacts on the background field are mostly similar in the different months in summer. The heavy rainfall experiments reveal that the application of AMSU-A （B） microwave radiance data can improve the rainfall prediction significantly. In particular, the AMSU-A radiance data can significantly enhance the prediction of rainfall above 10 mm within 48 h, and the AMSU-B radiance data can improve the prediction of rainfall above 50 mm within 24 h. The present study confirms that the direct assimilation of satellite radiance data is an effective way to improve the prediction of heavy rainfall in the summer in China.     

Improved tropical cyclone forecasts over north Indian Ocean with direct assimilation of AMSU-A radiances

The Weather Research and Forecasting (WRF-ARW) model and its three-dimensional variational data assimilation (3D-Var) system are used to investigate the impact of the Advanced Microwave Sounding Unit-A (AMSU-A) radiances on the prediction of Indian Ocean tropical cyclones. Three tropical cyclones are selected for this study: cyclone Mala (April 2006; Bay of Bengal), cyclone Gonu (June 2007; Arabian Sea), and cyclone Sidr (November 2007; Bay of Bengal). For each case, observing system experiments are designed, by producing two sets of analyses from which forecasts are initialized. Both sets of analyses contain all conventional and satellite observations operationally used, including, but not limited to, Quick Scatterometer (QuikSCAT) surface winds, Special Sensor Microwave/Imager (SSM/I) surface winds, Meteosat-derived atmospheric motion vectors (AMVs), and differ only in the exclusion (CNT) or inclusion (EXP) of AMSU-A radiances. Results show that the assimilation of AMSU-A radiances changes the large-scale thermodynamic structure of the atmosphere, and also produce a stronger warm core. These changes cause large forecast track improvements. In particular, without AMSU-A assimilation, most forecasts do not produce landfall. On the contrary, the forecasts initialized from improved EXP analyses in which AMSU-A data are included produce realistic landfall. In addition, intensity forecast is also improved. Even if the analyzed cyclone intensity is not affected by the assimilation of AMSU-A radiances, the predicted intensity improves substantially because of the development of warm cores which, through creation of stronger gradients, helps the model in producing intense low centre pressure.