有云环境下MODIS亮温资料的变分同化Ⅰ——方案设计与理想试验

云对红外辐射传输过程有十分重要的影响,在资料同化过程中考虑云的作用,不仅可以改进大气参数的同化效果,还可以利用红外资料调整部分云参数,减小云参数的初始误差。在GRAPES-3DVAR（Global and Regional Assimilation and Prediction Enhanced System,全球/区域同化预报系统）基础上,增加云水含量、云冰水含量和云量作为同化系统控制变量,针对晴空、部分有云和完全有云等环境对MODIS（Moderate Resolution Imaging Spectroradiometer,即中分辨成像光谱仪）的16个气象通道亮温进行了同化理想试验,结果表明当背景场模拟的亮温低于观测亮温时,分析场通过增温、减湿、减少云水含量、云冰水含量、云量可以达到升高模拟亮温的目的;反之可以降低模拟亮温;晴空环境下对温度、比湿的调整符合MODIS仪器的设计特点;有云环境下对云层以下的影响减弱。理想试验证实了在红外辐射资料同化过程中将云参数和大气参数同时作为同化系统控制变量,可以利用红外资料调整云参数和常规气象要素场,提高资料的利用率。     

GOES-16大气温度产品资料同化在一次飓风预报中的应用研究

为评价静止卫星大气温度廓线产品资料同化对飓风预报的影响,以2018年飓风"迈克尔"为例,选用GOES-16温度廓线产品,开展静止卫星资料同化及其对飓风预报影响的研究。首先,通过评估温度廓线产品精度,选取质量较好的高度层并以统计的各层均方根误差作为观测误差用于同化试验;然后,利用WRF-3DVar系统进行不同稀疏化及不同同化频次的循环同化敏感性试验;最后,利用WRF模式开展24 h数值预报。试验结果表明,在飓风"迈克尔"期间温度廓线在200～1 000 hPa之间的误差在2 K以内,将水平分辨率稀疏化为模式分辨率的6倍且循环同化频次为6 h时同化该资料对模式的初始场有最为合理的改进,从大尺度环境场上看使模式具备更合理的环流形势,能够有效提高对飓风的路径及强度的预报效果,更准确地模拟降水落区及美国佛罗里达州等降水关键区域的雨强。     

IMPROVEMENT OF OCEAN DATA ASSIMILATION SYSTEM AND CLIMATE PREDICTION BY ASSIMILATING ARGO DATA

The Argo(Array for Real-time Geostrophic Oceanography) data from 1998 to 2003 were used in the Beijing Climate Center-Global Ocean Data Assimilation System(BCC-GODAS). The results show that the utilization of Argo global ocean data in BCC-GODAS brings about remarkable improvements in assimilation effects. The assimilated sea surface temperature(SST) of BCC-GODAS can well represent the climatological states of observational data. Comparison experiments based on a global coupled atmosphere-ocean general circulation model(AOCGM) were conducted for exploring the roles of ocean data assimilation system with or without Argo data in improving the climate predictability of rainfall in boreal summer. Firstly, the global ocean data assimilation system BCC-GODAS was used to obtain ocean assimilation data under the conditions with or without Argo data. Then, the global coupled atmosphere-ocean general circulation model(AOCGM) was utilized to do hindcast experiments with the two sets of the assimilation data as initial oceanic fields. The simulated results demonstrate that the seasonal predictability of rainfall in boreal summer, particularly in China, increases greatly when initial oceanic conditions with Argo data are utilized. The distribution of summer rainfall in China hindcast by the AOGCM under the condition when Argo data are used is more in accordance with observation than that when no Agro data are used. The area of positive correlation between hindcast and observation enlarges and the hindcast skill of rainfall over China in summer improves significantly when Argo data are used.     

有云环境下MODIS亮温资料的变分同化Ⅱ——对暴雨预报的影响

卫星资料提供了大量关于云和雨的观测信息,在暴雨预报中可发挥巨大的作用,然而在数值模式资料同化中的应用水平仍然不高,特别是红外辐射资料的应用。由于有云环境下辐射传输过程的模拟难度很大,因此通常只同化晴空环境下的红外辐射资料。基于GRAPES-3DVAR(Global and Regional Assimilation and Prediction Enhanced System,全球/区域同化预报系统),根据RTTOV辐射传输模式(fast radiative transfer model for TOVS,快速辐射传输模式)的特点,增加云水含量、云冰水含量和云量作为同化系统控制变量,在改进辐射传输模式对红外资料模拟的同时,利用红外资料调整初始云参数和大气参数。针对2007年5月26日南海季风爆发后广东地区的一次暴雨过程,选取MODIS(Moderate Resolution Imaging Spectroradiometer,中分辨成像光谱仪)传感器水汽(第27)和云顶观测(第36)通道进行了同化试验,利用WRF(Weather Research and Forecasting Model,天气研究和预报模式)进行了数值模拟,结果表明同化MODIS资料,可以改进初始场水汽和温度分布,间接调整高空风场,调整趋势符合卫星观测,对短时降水预报有正面影响。     

MODIS brightness temperature data assimilation under cloudy conditions Ⅱ: Impacts on rainstorm forecasting

Although satellite observations provide large amount of information of clouds and precipitation and play an important role in the forecast of heavy rainfall, they have not been fully taken advantage of in data assimilation of numerical weather predictions, especially those in infrared channels. Assimilating radiances is common under clear-sky conditions since it is extremely difficult to simulate infrared transmittance in cloudy sky. Based on the Global and Regional Assimilation and Prediction Enhanced System 3-dimensional variance (GRAPES-3DVar), cloud liquid water content, ice-water content and cloud cover are employed as governing variables in the assimilation system. This scheme can improve the simulation of infrared transmittance by a fast radiative transfer model for TOVS (RTTOV) and adjust the atmospheric and cloud parameters based on infrared radiance observations. In this paper, we investigate a heavy rainfall over Guangdong province on May 26, 2007, which is right after the onset of a South China Sea monsoon. In this case, channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) for observing water vapor (Channel 27) and cloud top altitude (Channel 36) are selected for the assimilation. The process of heavy rainfall is simulated by the Weather Research and Forecasting (WRF) model. Our results show that the assimilated MODIS data can improve the distribution of water vapor and temperature in the first guess field and indirectly adjust the upper-level wind field. The tendency of adjustment agrees well with the satellite observations. The assimilation scheme has positive impacts on the short-range forecasting of rainstorm.     

STUDY ON CLOUD CLASSIFICATIONS BY USING AVHRR,GMS-5 AND TERRA/MODIS SATELLITE DATA

This paper presents the automated pixel-scale neural network classification methods beingdeveloped at National Satellite Meteorological Center(NSMC)of China to classify clouds by usingNOAA/AVHRR and GMS-5 satellite imageries.By using Terra satellite MODIS imageries,anautomated pixel-scale threshold technique has been developed to detect and classify clouds.Thestudy focuses on applications of these cloud classification techniques to the Huaihe River and theChangjiang(Yangtze)River drainage basin.The different types of clouds show more clearly onthis cloud classification image than single band image.The results of the cloud classifications arethe basis of studying cloud amount,cloud top height and cloud top pressure.Cloud mask methodsare widely used in SST,LST,and TPW retrieval schemes.Some case studies about cloud maskand cloud classification in satellite imageries,which are related with the study of Global Energyand Water Cycle Experiment(GEWEX)in the Huaihe River and the Changjiang River drainagebasin are illustrated.     

四维变分同化技术在优化Z-C预测模式初始场中的应用试验

文中使用四维变分同化技术将海温观测资料同化到Zebiak-Cane模式中,通过优化模式的初始场提高了模式的预报技巧.通过用理想场进行检验,说明所建立的同化伴随模式是正确的 .用文中建立的四维变分同化模式以1997年1月为初始场所做的预报结果与实况相比,结果较好.这对今后ENSO预报打下了良好的基础.     

利用ARGO资料改进海洋资料同化和海洋模式中的物理过程

国际ARGO计划的实施每年将可提供多达 10万个剖面 (0～ 2 0 0 0m水深 )的海水温度和盐度资料 ,这些资料的获取无疑将会大大促进海洋和大气科学的发展 ,使人们加深对海洋过程的了解 ,揭示海 气相互作用的机理 ,为长期天气预报和短期气候预测提供模式初始场 ,提高长期天气预报和短期气候预测的能力。如何利用这些资料开展研究工作以及在实际业务中应用这些资料是目前大气和海洋科学界的一个前沿课题。本研究将ARGO浮标资料引入了国家气候中心的NCC GODAS同化系统 ,结果分析表明 ,同化ARGO资料后所得到的海温场在三大洋中不仅在温度数值的大小 ,而且在分布形式方面都与观测场具有较好的一致性 ,可以很好地反映出观测到的冬季和夏季海温的分布形式以及海温的季节变化特征和异常特征。本研究还应用最新的ARGO海洋观测资料 ,通过建立新的热带西太平洋次表层海温参数化方案 ,改进了Zebiak Cane(1987)海洋模式 (ZC模式 ) ,克服了ZC模式几乎没有模拟赤道西太平洋表层和次表层海温变化能力的缺陷。在ZC模式中引用新的次表层海温参数化方案后 ,在赤道西太平洋不仅次表层海温的模拟得到了改善 ,对海面温度异常的模拟也有了较大的改进 ,不仅模拟出了赤道西太平洋表层和次表层海温异常的年际变化特征 ,也模拟出了与观     

雷达资料的3DVAR和EnSRF直接同化方法对一次暴雨预报的影响分析

利用合肥站雷达资料和NCEP再分析资料,采用WRF模式、WRF-3DVAR和WRF-En SRF同化系统设计了直接同化雷达径向风和反射率的试验,对2003年7月4—5日发生在江淮流域的一次梅雨锋暴雨过程进行数值模拟分析。结果表明:(1)同化雷达径向风资料可以增加暴雨区低层的扰动,增强对流运动,同时可以减少模拟的过量降水;(2)3DVAR同化方法对水平风场调整明显,同化反射率改进了模式中的微物理量和动力场,同时同化径向风和反射率可以更好地调整风场,改善模拟雷达回波带的强度和位置;(3)En SRF同化方法可以将更多小尺度的风场信息同化进入模式,单独同化反射率可以较准确预报出降水中心,同时同化径向风和反射率可以改进模拟雷达回波带的位置;(4)使用3DVAR和En SRF同化雷达径向风和反射率可以提高降水预报,改善雨带的范围,对降水中心位置和强度的预报也有改进。     

THE INVERSE PROBLEM OF KLEIN-GORDON EQUATION BOUNDARY VALUE PROBLEM AND ITS APPLICATION IN DATA ASSIMILATION

Since the solution of elliptic partial differential equations continuously depends on the boundary condition, the Euler equation derived from variational method cannot be solved without boundary condition. It is often difficult to provide the exact boundary condition in the practical use of variational method. However, in some application problems such as the remote sensing data assimilation, the values can be easily obtained in the inner region of the domain. In this paper, the boundary condition is tried to be retrieved by using part solutions in the inner area. Firstly, the variational problem of remote sensing data assimilation within a circular area is established. The Klein-Gordon elliptic equation is derived from the Euler method of variational problems with assumed boundary condition. Secondly, a computer-friendly Green function is constructed for the Dirichlet problem of two-dimensional Klein-Gordon equation, with the formal solution according to Green formula. Thirdly, boundary values are retrieved by solving the optimal problem which is constructed according to the best approximation between formal solutions and high-accuracy measurements in the interior of the domain. Finally, the assimilation problem is solved on substituting the retrieved boundary values into the Klein-Gordon equation. It is a type of inverse problem in mathematics. The advantage of this method lies in that it overcomes the inherent instability of the inverse problem of Fredholm integral equation and alleviates the error introduced by artificial boundary condition in data fusion using variational method in the past.     

Comparisons of Two Cloud-Detection Schemes for Infrared Radiance Observations

The cloud-detection procedure developed by McNally and Watts （MW03） was added to the Weather Research and Forecasting Data Assimilation System. To provide some guidelines for setting up cloud-detection schemes, this study compares the MW03 scheme to the Multivariate and Minimum Residual （MMR） scheme for both simulated and real Advanced Infrared Sounder （AIRS） radiances. Results show that there is a high level of consistency between the results from simulated and real AIRS data. As expected, both cloud-detection schemes perform well in finding the cloud-contaminated channels based on the channels＇ peak levels. The cloud- detection results from MW03 are sensitive to the prescribed brightness temperature innovation threshold and brightness temperature gradient threshold. When increasing the brightness temperature innovation threshold for MW03 to roughly eight times the default threshold, the two cloud-detection schemes produce consistent data rejection distributions overall for high channels. MMR generally retains more data for long-wave channels. For both cloud-detection schemes, there is a high level of consistency between the cloud-free pixels and the visible/near-IR （Vis/NIR） cloud mask.     

雷达资料同化与提高模式水平分辨率对短时预报影响的数值对比试验

为对比雷达资料同化与提高模式水平分辨率对短时数值预报的影响,利用美国Oklahoma大学风暴分析和预测中心开发的ARPS(The Advanced Regional Prediction System)模式及其资料分析系统ADAS(ARPS Data AnalysisSystem),对一次华北暴雨过程进行了18,15,9,6,3 km 5种不同水平分辨率的数值对比试验,并对比了使用雷达资料进行云分析时5种分辨率的模拟结果,结果表明,仅使用常规观测资料的情况下,通过提高模式水平分辨率,可以改进6 h内的短时预报,模拟的锋面结构更为细致,降水尤其是强降水预报评分提高了。而使用雷达资料改进模式初始场后,能明显改进模式6 h内的预报尤其是降水强度和落区预报,使得18 km上使用雷达资料同化的预报结果好于3 km不使用雷达资料同化的结果,表明雷达资料同化比单纯提高模式水平分辨率更为有效。不同分辨率上使用雷达资料同化的对比发现,对于40 mm以下的一般性降水,从18—3 km的模拟结果差别不大,而对于强降水,仍然需要提高模式的水平分辨率。但无论初始场是否使用雷达资料同化,但当分辨率由6 km提高到3 km时,模拟结果无明显改进,因此,提高模式分辨率有一定的限度,而在适当提高模式分辨率的同时使用雷达资料同化改进模式初始场,则是提高模式短时预报的一个非常有效的途径。     

对中尺度遥感资料进行四维同化的共轭方法及其数值研究

本文探讨了数值天气预报过程中对非定时观测的常规遥感气象资料进行四维同化，形成预报初始场的新途径，把数值预报初始场的形成提为数学上的一类反问题，运用数值模式及其共轭方程对象气资料进行变分同化的共轭方法，使众多观测资料的四维同化与时变的动力模型在初始场的形成过程中统一考察，克服了以往一些方法的局限性，从理论和数值角度证明该方法的可行性，表明该方法有可能作为发展一个新的初值方案的雏形，有潜在的应用价值。     

基于MODIS数据的城市热岛动态监测及时空变化分析

以人口密集、经济快速发展的福建省沿海地区为研究区，在遥感和地理信息系统技术支持下，采用经优选的MODIS遥感数据反演的地表温度，提取城市热岛和植被覆盖信息，对研究区城市热岛进行动态监测和时空变化分析，并对地表温度与植被覆盖的互动关系进行定性与定量分析。结果表明：福建沿海城市热岛面积整体上呈逐年增长趋势，福州和莆田更为明显；城市热岛主要集中在人口密集、工商业发达的区域，同时沿海平原的热岛效应比内陆山区更为显著；地表温度与植被覆盖呈负相关，并且相关系数逐年增长。     

THE INITIAL WIND SCHEME OF THE HEMISPHERIC SPECTRAL MODEL AND ITS EFFECT ON THE DATA ASSIMILATION

A series of data assimilation and forecast test have been carried out with a hemispheric spectralmodel(T42L9H).It is found that the numerical scheme for determining hemispheric initial wind isimportant to data assimilation and forecast.An inappropriate scheme may cause computationalsources of divergence near the equator,which are responsible for the spurious strong precipitationand corresponding latent heat release.Obviously,this problem differs from either thehemispheric/global domain effect or the tropical data effect pointed by Dalley et al.(1981).Basedon the previous studies,the new scheme of divergence and vorticity correction is presented,andthe difference with other schemes and its effects on the data assimilation are discussed against thecontrol test.Preliminary tests have shown that the new divergence correction scheme proposed in thispaper may be a preferable choice to overcome the initial computational errors in the hemisphericdata assimilation.     

Enhanced Arctic Ice Concentration Estimation Merging MODIS Ice Surface Temperature and SSM/I Sea-Ice Concentration

Ice concentration data from passive microwave sensors are not reliable during the summer melt season. In this study passive microwave ice concentration estimates are improved upon through the assimilation of ice surface temperature data from the Moderate-Resolution Imaging Spectroradiometer (MODIS). Ice concentration from the analysis is converted to ice extent and compared with data from the Interactive Multisensor Snow and Ice Mapping System (IMS). Ice concentration analysis from data assimilation is in better agreement with the IMS data than the original passive microwave data, with the largest improvements occurring during sea-ice melt.     

基于雷达资料同化的2003年7月一次暴雨过程的数值模拟及分析

利用我国CINRAD/SA多普勒雷达资料与中尺度模式ARPS的资料分析系统ADAS,对初始场进行调整,然后利用高分辨率的中尺度模式WRF对2003年7月4-5日的暴雨过程进行了数值模拟,在模拟结果可信的前提下,对暴雨过程中的中尺度对流系统(MCS)的结构及演变过程进行了分析.表明:多普勒雷达资料有助于提高暴雨模拟的精确度,利用其对中尺度系统进行高分辨率数值模拟,可以进一步认识中尺度系统的细致结构及演变情况;在中-β对流系统发展的过程中,大尺度环境场的有利条件可以对其发展起到促进作用,但具有中尺度特征的水汽条件、上升运动等因素也会起到关键的作用;中-β对流系统中可以同时有一支或多支的上升气流支出现,与降水有密切关系;2003年7月4-5日的两个中-β对流系统在发展过程中有从低空向高空移动的现象,即在发展初期,系统的中心位于低空,而在其旺盛时期则移至高空.     

资料同化对2017年登陆广东沿海台风的短期降水与路径预报影响

利用华南精细数值天气预报模式,设计了无同化资料(CTRL)、同化雷达反演水汽(EXP1)以及同化雷达反演水汽、地面和探空资料(EXP2)三个试验,对2017年登陆广东沿海的四个台风降水预报与路径预报进行模拟,以评估资料同化对登陆台风短期降水预报、路径预报的影响。分析结果如下:雷达反演水汽同化后对未来24小时降水预报技巧均有正的改善,对台风路径预报影响不大;在此基础上同化地面、探空资料后对台风路径预报有改进,对降水预报改进不明显(与EXP1比)。通过诊断分析台风“玛娃”,发现模式初值场水汽的增量配合对流上升区有利于短时间内成云致雨,从而提高短时降水预报;地面及探空资料同化有利于登陆台风的短时路径预报。      

曲率修正线性平衡方程及其在变分同化风压约束中的应用

针对强涡旋系统（热带气旋、一些中尺度系统）变分同化分析中风压平衡约束关系的特点,提出了一个新的风压平衡约束关系——曲率修正线性平衡方程,它具有形式与线性平衡方程相同,并清晰地包含了曲率的作用,同时,当曲率较小时可退化成线性平衡方程。曲率修正线性平衡方程能方便地应用于中国数值预报研究中心开发的三维变分同化分析系统Grapes3DV中,试验结果证明其具有较好的效果和较理想的特性,提高了分析质量,并改善预报水平。     

VARIATIONAL DATA ASSIMILATION USING WAVELET BACKGROUND ERROR COVARIANCE: INITIALIZATION OF TYPHOON KAEMI (2006)

Background error covariance plays an important role in any variational data assimilation system, because it determines how information from observations is spread in model space and between different model variables. In this paper, the use of orthogonal wavelets in representation of background error covariance over a limited area is studied. Based on the WRF model and its 3D-VAR system, an algorithm using orthogonal wavelets to model background error covariance is developed. Because each wavelet function contains information on both position and scale, using a diagonal correlation matrix in wavelet space gives the possibility to represent some anisotropic and inhomogeneous characteristics of background error covariance. The experiments show that local correlation functions are better modeled than spectral methods. The formulation of wavelet background error covariance is tested with the typhoon Kaemi (2006). The results of experiments indicate that the subsequent forecasts of typhoon Kaemi’s track and intensity are significantly improved by the new method.