FY-4A卫星云导风观测误差优化及同化效果影响研究

为了推进FY-4A卫星资料在数值模式中的实际应用,本研究选择云导风产品作为研究对象,首先统计了FY-4A高层水汽通道和红外通道云导风的观测误差,进一步基于WRFDA(Weather Research and Forecasting model Data Assimilation system)系统,利用默认观测误差和新观测误差进行了为期一个月的循环同化及预报试验,并分析了试验期间的台风预报效果。结果表明:相较于默认观测误差,FY-4A云导风产品的新观测误差垂直结构特征更加明显;采用本研究统计的FY-4A云导风观测误差,能够在默认观测误差的基础上改善风场的分析和预报效果;试验期间的两个台风个例分析表明,新观测误差也能够减小台风路径的预报误差。     

Water vapor motion signal extraction from FY-2E longwave infrared window images for cloud-free regions: The temporal difference technique

The aim of this study is to calculate the low-level atmospheric motion vectors （AMVs） in clear areas with FY-2E IR2 window （11.59-12.79 μm） channel imagery,where the traditional cloud motion wind technique fails.A new tracer selection procedure,which we call the temporal difference technique,is demonstrated in this paper.This technique makes it possible to infer low-level wind by tracking features in the moisture pattern that appear as brightness temperature （TB） differences between consecutive sequences of 30-min-interval FY-2E IR2 images over cloud-free regions.The TB difference corresponding to a 10％ change in water vapor density is computed with the Moderate Resolution Atmospheric Transmission （MODTRAN4） radiative transfer model.The total contribution from each of the 10 layers is analyzed under four typical atmospheric conditions：tropical,midlatitude summer,U.S.standard,and midlatitude winter.The peak level of the water vapor weighting function for the four typical atmospheres is assigned as a specific height to the TB ＂wind＂.This technique is valid over cloudfree ocean areas.The proposed algorithm exhibits encouraging statistical results in terms of vector difference （VD）,speed bias （BIAS）,mean vector difference （MVD）,standard deviation （SD）,and root-mean-square error （RMSE）,when compared with the wind field of NCEP reanalysis data and rawinsonde observations.     

基于FY-4A卫星探测区域模式背景误差和观测误差估计的长波红外通道选择研究

中国新一代静止气象卫星风云四号A星（FY-4A）上搭载的干涉式大气垂直探测仪GIIRS（Geostationary Interferometric Infrared Sounder）是世界上首台在静止轨道运行的高光谱红外探测仪器,拥有1650个通道,其中长波通道689个,中波通道961个。由于计算机存储能力、数据传输和变分同化时效性等限制,目前很难在业务环境中同化全部通道,并且多通道卫星信息往往存在一定的空间相关和光谱相似,故在实际应用中必须降低高光谱资料的通道维数,去除数据冗余和观测相关性,挑选出对特定目标起主要作用的通道子集,进而利用有限的通道来最大限度地提供观测信息。考虑GRAPES（Global/Regional Assimilation and Prediction Enhanced System）数值预报系统估计得到的FY-4A观测范围内的背景误差协方差矩阵,并且在GIIRS观测误差后验重估计的基础上,结合通道权重函数峰值和信息熵分步迭代法对其长波通道进行了通道选择研究和试验。结果表明,在给定选择通道个数时,权重函数法和信息熵方法得到的通道组合进行温度和湿度误差分析时误差整体比单一方法小,在给定通道个数（40个）少于单一方案（50个）时,误差分析结果相当。GIIRS最优通道选择的研究为该资料的同化应用建立了基础。      

FY-2E卫星云导风定高误差及在同化中的应用

FY-2E气象卫星云导风产品观测误差较大的主要原因是高度指定存在较大误差。针对该问题,采用一维变分方法对云导风高度进行调整。统计分析表明:经高度调整后的FY-2E气象卫星云导风产品质量得到很大改善;采用新息向量法,选取零阶Bessel函数模型,在观测空间分离背景误差和观测误差方差得到云导风的观测误差。运用GRAPES全球模式进行数值模拟,结果表明:采用新的观测误差方案和经过高度调整后的云导风产品能提高数值模式在北半球的短期预报能力,高层的改进效果明显好于中低层。并根据云导风反演原理及算法,讨论了FY-2E气象卫星云导风高度指定系统性偏高的主要原因,以求进一步改善云导风产品的质量。     

Derivation of Cloud-Free-Region Atmospheric Motion Vectors from FY-2E Thermal Infrared Imagery

The operational cloud-motion tracking technique fails to retrieve atmospheric motion vectors(AMVs) in areas lacking cloud; and while water vapor shown in water vapor imagery can be used, the heights assigned to the retrieved AMVs are mostly in the upper troposphere. As the noise-equivalent temperature difference(NEd T) performance of FY-2E split window(10.3–11.5 μm, 11.6–12.8 μm) channels has been improved, the weak signals representing the spatial texture of water vapor and aerosols in cloud-free areas can be strengthened with algorithms based on the difference principle, and applied in calculating AMVs in the lower troposphere. This paper is a preliminary summary for this purpose, in which the principles and algorithm schemes for the temporal difference, split window difference and second-order difference(SD) methods are introduced. Results from simulation and cases experiments are reported in order to verify and evaluate the methods, based on comparison among retrievals and the "truth". The results show that all three algorithms, though not perfect in some cases,generally work well. Moreover, the SD method appears to be the best in suppressing the surface temperature influence and clarifying the spatial texture of water vapor and aerosols. The accuracy with respect to NCEP 800 h Pa reanalysis data was found to be acceptable, as compared with the accuracy of the cloud motion vectors.     

Comparison of Kalpana-1 atmospheric motion vectors with other observations

The operational derivation of atmospheric motion vectors (AMVs) using infrared (10.5–12.5 μm) and water vapor (6.3–7.1 μm) channels of successive geostationary satellite images started in the 1980s. Subsequently, AMVs have become an important component for operational numerical weather prediction throughout the globe for the last decade or so. In India, at the Space Applications Centre, Indian Space Research Organisation, the operational derivation of AMVs (infrared winds and water vapor winds) from the Indian geostationary satellite Kalpana-1 has been initiated a few years back. Recently, an L-band radar lower atmosphere wind profiler (LAWP) has been installed at the National Atmospheric Research Laboratory, Gadanki located at (13.58°N, 79.28°E) for continuous high-resolution wind measurements in the lower atmosphere. In this study, a comparison of Kalpana-1 AMVs with wind measurements from LAWP and radiosonde has been carried out for a period of one and a half years. The performances of Kalpana-1 AMVs are also assessed by a separate comparison of Meteosat-7 AMVs, derived at the European Organisation for the Exploitation of Meteorological Satellites, with wind measurements from LAWP and radiosonde. Both sets of comparison show that AMVs from Kalpana-1 and Meteosat-7 are comparable over the Indian Ocean region.     

FY-2E云导风的算法改进及其在GRAPES中的同化应用研究

2014年国家卫星气象中心全面改进了风云二号卫星云导风产品算法,为评估算法改进后FY-2E云导风资料对我国GRAPES数值模式同化和预报的影响,根据国家卫星气象中心提供的2013年8月算法改进前后的FY-2E红外通道云导风资料,对比分析了两者的观测分布及偏差特征,并利用GRAPES全球模式进行了一个月的连续试验。结果表明,改进算法后的FY-2E红外通道云导风观测数量明显增加,观测误差在600~200 hPa有所减小,风的平均偏差在高层减少,更满足正态分布;连续试验结果表明北半球和东亚地区风场在300~150 hPa分析中改进显著,风的平均偏差和均方根误差明显减少;预报结果显示500 hPa高度场预报距平相关系数略提高,均方根误差略减小;说明改进算法后的FY-2E红外通道云导风对GRAPES数值模式同化和预报均有一定改善。     

利用FY-3A近红外资料反演水汽总量

该文介绍了利用搭载在FY-3A卫星上的中分辨率光谱成像仪 (MERSI) 的近红外 (NIR) 通道反演大气水汽总量 (PWV) 的方法。根据预先建立的查找表,大气水汽总量可以通过水汽通道与窗区通道的卫星测值相比反演得到。对MERSI近红外水汽通道灵敏度进行估算,结果表明:处于吸收带两翼的905 nm和980 nm通道对不同水汽量的敏感性表现比较接近,对较大水汽含量最为敏感;当水汽较弱时,强吸收的940 nm通道非常敏感。基于这3个通道对水汽含量敏感性的不同表现,采用3个通道水汽总量的加权平均值作为PWV产品的最终反演值。文中设计了水汽总量业务算法反演流程,并基于FY-3A/MERSI最新观测资料进行晴空大气水汽总量的业务处理生成试验,顺利生成MERSI单轨道水汽总量产品及日拼图中国区域产品和全球产品,同时生成多天合成产品,产品反映出MERSI具有较好的近红外水汽探测能力。将卫星反演结果与探空数据进行初步比对检验,显示卫星反演值有20%~30%系统性偏低,需要进一步改进反演查找表。     

Impact of assimilation of INSAT-3D retrieved atmospheric motion vectors on short-range forecast of summer monsoon 2014 over the South Asian region

The Weather Research and Forecasting (WRF) model and its three-dimensional variational data assimilation system are used in this study to assimilate the INSAT-3D, a recently launched Indian geostationary meteorological satellite derived from atmospheric motion vectors (AMVs) over the South Asian region during peak Indian summer monsoon month (i.e., July 2014). A total of four experiments were performed daily with and without assimilation of INSAT-3D-derived AMVs and the other AMVs available through Global Telecommunication System (GTS) for the entire month of July 2014. Before assimilating these newly derived INSAT-3D AMVs in the numerical model, a preliminary evaluation of these AMVs is performed with National Centers for Environmental Prediction (NCEP) final model analyses. The preliminary validation results show that root-mean-square vector difference (RMSVD) for INSAT-3D AMVs is ～3.95, 6.66, and 5.65 ms^?1 at low, mid, and high levels, respectively, and slightly more RMSVDs are noticed in GTS AMVs (～4.0, 8.01, and 6.43 ms^?1 at low, mid, and high levels, respectively). The assimilation of AMVs has improved the WRF model of produced wind speed, temperature, and moisture analyses as well as subsequent model forecasts over the Indian Ocean, Arabian Sea, Australia, and South Africa. Slightly more improvements are noticed in the experiment where only the INSAT-3D AMVs are assimilated compared to the experiment where only GTS AMVs are assimilated. The results also show improvement in rainfall predictions over the Indian region after AMV assimilation. Overall, the assimilation of INSAT-3D AMVs improved the WRF model short-range predictions over the South Asian region as compared to control experiments.     

风云三号卫星微波湿度计的扫描角偏差订正

首先统计分析了FY-3A卫星MWHS(Micro Wave Humidity Sounder,微波湿度计)2010年1月整月和8月28日—9月6日Level-1b全球观测亮度温度T_O和背景场(NCEP GFS 6 h预报场)用辐射传输模式(美国通用辐射传输模式CRTM 2.0版本)模拟的亮度温度T_B随扫描角的分布特征,发现通道3和4的观测随仪器扫描角有抖动、不连续现象。同时沿着仪器扫描线在星下点两测存在观测不对称现象,而且权重函数峰值越接近地面的通道该不对称现象越明显。在统计观测增量T_O-T_B随扫描角和纬度变化的基础上,定量给出了不同纬度带内(每隔5个纬度)MWHS通道3、4和5的扫描角偏差订正系数,该系数可直接提供给各种资料同化系统同化FY-3A MWHS资料时使用。     

A Study on Height Reassignment for the AMV Products of the FY-2C Satellite

A method for using height reassignment to improve the quality of satellite-derived atmospheric motion vectors (AMVs) is presented. The rationale underlying height reassignment is explored, and the technical details are studied by applying three height reassignment schemes that use NCEP reanalysis winds. The quality of the AMVs is generally improved following reassignment, although the magnitude of the improvement differs according to the scheme applied. Scheme 3 provides the best quality and stability, followed by Scheme 1 and Scheme 2. The negative biases in the zonal components of the AMVs decrease from [-5,-4] m s-1to <-1 m s-1following reassignment. The meridional components also improve. The AMVs derived from the infrared and water vapor channels improve by 58.7% and 25%, respectively. The feasibility of using Scheme 3 in the operational derivation of AMVs is studied by incorporating the forecast wind field predicted by a T511 medium-range numerical weather prediction (NWP) system. Incorporating the 120-h forecast reduces the negative biases in zonal winds and positive biases in meridional winds retrieved from the water vapor channel, improving the overall quality of the AMVs by 26.7%. Extending the validity period of the forecast field linearly reduces the improvement in retrieved AMVs, but the magnitude of this reduction is small. Incorporating the 120-h forecast field still results in a 13% improvement, although it may eliminate a larger number of AMVs of good quality.     

MWHS/FY-3资料同化在四川盆地暴雨预报中的应用研究

为了研究同化风云三号B星(FY-3B)和C星(FY-3C)的微波湿度计(MWHS及MWHS-2)观测资料在四川暴雨数值预报中的影响,本文基于Weather Research and Forecasting Model(WRF)及其三维变分同化系统Weather Research Forecast Variatinal Data Assimilation System(WRFDA),实现了对MWHS/FY-3B和MWHS-2/FY-3C观测资料的直接同化。针对2018年7月的一次四川盆地区域性暴雨过程的同化试验结果表明:同化风云三号系列卫星的微波湿度计观测资料对试验开始时刻均有改善,对相对湿度和矢量风场等物理量场有一定的正向调整作用,尤其是同化MWHS-2/FY-3C资料对风场的调整较为明显。同化试验对龙门山北部降水有较明显的改善作用,改善了降水的分布与落区,其中同化MWHS/FY-3B对盆地中部到东北部的降水量级的预报更接近实况,雨区更为连续。同化试验证明了同化风云三号系列卫星的微波湿度计观测资料对于四川盆地暴雨数值预报有一定的业务应用价值。      

FY-2和GMS-5红外通道遥感图像质量的功率谱分析

根据遥感图像功率谱的性质,对比分析了FY-2和GMS-5扫描辐射计红外通道的图像质量。计算结果表明,FY-2红外通道遥感图像功率谱各分量之和不高于GMS-5红外A通道遥感图像的功率谱各分量之和。数值模拟试验的结果表明,FY-2红外通道的图像质量大体上与GMS-5红外A通道的图像质量相当。     

Assimilation of the FY-4A AGRI Clear-Sky Radiance Data in a Regional Numerical Model and Its Impact on the Forecast of the “21·7” Henan Extremely Persistent Heavy Rainfall

Assimilation of the Advanced Geostationary Radiance Imager(AGRI) clear-sky radiance in a regional model is performed. The forecasting effectiveness of the assimilation of two water vapor(WV) channels with conventional observations for the “21·7” Henan extremely heavy rainfall is analyzed and compared with a baseline test that assimilates only conventional observations in this study. The results show that the 24-h cumulative precipitation forecast by the assimilation experiment with the addition ...     

用FY-1C两个近红外太阳反射光通道的观测数据反演水汽总含量

FY-1C极轨气象卫星扫描辐射仪第10通道的观测波长为0.90~0.965μm，位于弱水汽吸收区，邻近的第2通道观测波长为0.84~0.89μm，位于大气窗区。该文根据R.Frouin提出的算法，用FY-1C资料实现了近红外水汽吸收区和窗区两个通道联合反演水汽总含量。所用的反演关系式为其中，水汽吸收区与窗区两个通道的反射率之比r可以从卫星测值中求出；在探空站所在的地方，沿光路的水汽总含量m为己知量，可以用统计方法求出系数A和B；在没有探空站的地方，可以根据系数A和B，用反演关系式求m。影响系数A的因素主要是大气的温、压、湿廓线和仪器的通道响应函数，影响系数B的因素是地表反射率。由于这些对反演关系式中的系数取值有影响的因素随时间和地点有变化，对不同地区和时段的探空站分别进行统计，得到不同的系数进行反演，取得了较好的效果。另外，还用质量控制手段控制了定位误差可能带来的影响。独立样本真实性检验表明，反演值和探空测值之间的偏差约为15%~20%，相关系数在90%以上。     

FY-2E晴空风矢同化对台风分析和预报的影响研究

为了研究“二阶差分法”反演的晴空区风矢同化在台风分析和预报中的作用,以1509号台风“灿鸿”和1211号台风“海葵”为例,首先利用WRF-3DVAR系统对晴空风矢进行同化,探讨了晴空风矢的引入对模式初始场的影响。然后利用WRF模式对两个个例分别进行48 h的预报试验。通过对比控制试验和同化试验,结果表明,同化晴空风矢资料能够对初始风场和位势高度场进行合理的调整,在台风周围引导气流的作用下,台风路径与实况更靠近,从而提高了台风路径的预报效果。除此之外,同化晴空风矢对台风强度以及风场预报也有一定的改善作用,还可更准确地预报出降水的落区及雨强,提高降水预报质量。因此,晴空风矢的引入,有利于改善模式的初始场,从而提高WRF模式对台风的预报能力。      

FY-4A AGRI辐射率资料偏差特征分析及订正试验

风云四号A星（Fengyun-4A,简称FY-4A）作为我国最新一代静止气象卫星,各方面技术指标都体现了“高、精、尖”特色,处于国际领先地位。其上搭载的多通道扫描成像辐射计（Advanced Geosynchronous Radiation Imager,简称AGRI）较上一代静止卫星风云二号的可见光红外自旋扫描辐射仪观测精度更高、扫描时间更短,充分体现AGRI观测资料将有效提高“一带一路”沿线国家和地区的天气预报和灾害预警水平。偏差订正是卫星资料处理的重要环节之一,因此本文通过在WRFDA v3.9.1（Weather Research and Forecasting model’s Data Assimilation v3.9.1）搭建AGRI同化接口,利用RTTOV v11. 3辐射传输模式和GFS全球预报系统（Global Forecast System）分析场研究了FY-4A AGRI红外通道8～14晴空辐射率资料的偏差特征并进行偏差订正对比试验,分析了卫星天顶角对AGRI资料偏差订正的影响,为将来实现AGRI红外通道辐射率资料在中尺度模式中的同化应用奠定基础。结果表明:（1）通道8～10及14为正偏差,通道11～13为负偏差。水汽通道9和10偏差及其标准差相对较小,偏差海陆差异不明显。通道11～14探测高度较低,陆地上观测受地表发射率影响大,质量控制时可剔除这些通道陆地上的观测。（2）各通道偏差随卫星天顶角变化的拟合直线斜率都小于0.035,对比试验结果表明偏差与卫星天顶角的关系不明显,预报因子中无需考虑卫星天顶角的作用。（3）通道8及11～14的偏差随着目标亮温的变化比水汽通道9～10明显,偏差有较强的目标亮温依赖特征。（4）根据分析的偏差特征对2018年5月13日18时（协调世界时,下同）至15日18时进行变分偏差订正试验,系统性偏差得到了有效的订正。     

风云三号微波观测资料的海雾同化模拟

数值模式边界层物理过程和初值场条件的欠缺是海雾模拟准确率偏低的主要原因。本文为改进模式初始场,开展针对海雾模拟的卫星观测资料同化试验,将质量控制和偏差订正后的FY-3A卫星微波湿度计（MWHS）和微波温度计（MWTS）的优选通道数据,经3DVar（Three-dimensional variational data assimilation）进入WRF模式以试验其对黄、渤海海雾模拟的影响。通过分析静止气象卫星检测到的海雾区模拟大气温、湿场同化分析增量,发现代表环境场条件的海雾类型及模式对其模拟能力的差异,显著影响了同化效果,表现为同化对模式模拟能力较强的平流冷型海雾改进明显,对模拟效果不甚理想的非典型混合过程中的暖型海雾阶段则基本没有改进效果。为寻找原因,对包括海雾区低层大气模拟场逆温结构在内的温湿度场与邻近探空观测进行了对比,分析了随时间演变的海雾格点温、湿场同化分析增量,发现冷型海雾区格点同化分析增量能弥补观测—模拟差异,使气温调减,相对湿度调增,同时水汽和液态水也出现负相关的变化,边界层相关热力动力场同化分析增量在垂直方向也有配合迹象,相比而言,主体是暖型海雾的非典型过程则未见此类现象和其他的有益调整迹象。     

半透明云风矢量高度算法中云下背景辐射的估计

半透明云风矢量高度指定是卫星风矢量算法的重要部分,需要来自半透明云体的辐射和云下背景辐射两个变量。云下背景辐射发生在云层下面,未被卫星直接观测到,为了在半透明云风矢量高度指定算法中更精确地获得云下背景辐射,使用风矢量附近无云区的红外/水汽散点图,估计云下背景辐射。分析表明:在追踪区域里存在无云区的情况下,追踪区的最高红外亮温可代表红外通道的背景辐射;而水汽通道的背景辐射,却在红外亮温高值区段内水汽亮温相对较低区段。追踪区内找不到无云区时应扩大搜索范围,找到无云区后可估计云下背景辐射。在半透明云风矢量高度指定算法中使用云下背景辐射估计的改进算法前后,计算FY-2气象卫星进行风矢量,并将结果与欧洲中期天气预报中心（ECMWF）分析场进行对比表明,在半透明风矢量高度指定算法中使用云下背景辐射估计,FY-2气象卫星风矢量误差明显降低。     

集合卡尔曼滤波同化多普勒雷达资料的数值试验

利用集合卡尔曼滤波(EnKF)在云数值模式中同化模拟多普勒雷达资料,并考察了不同条件下EnKF同化方法的性能.结果显示,经过几个同化周期后,EnKF分析结果非常接近真值.单多普勒雷达资料EnKF同化对雷达位置不太敏感,双雷达资料同化结果在同化的初期阶段比单雷达资料同化结果准确.同化由反射率导出的雨水比直接同化反射率资料更有效,联合同化径向速度和雨水有利于提高同化分析效果.协方差对EnKF同化效果起着非常重要的作用,考虑模式全部预报变量与径向速度协方差的同化效果比仅考虑速度场与径向速度协方差的同化效果好.雷达资料缺值降低了同化效果,此时增加地面常规观测资料的同化可以明显提高同化分析效果.EnKF同化技术对雷达观测资料误差不太敏感.初始集合对同化分析有较大影响.EnKF同化受集合大小和观测资料影响半径.同化对模式误差较敏感.利用EnKF同化双多普勒雷达资料,分析了一次梅雨锋暴雨过程的中尺度结构.结果表明,EnKF同化技术能够从双多普勒雷达资料反演暴雨中尺度系统的动力场、热力场和微物理场,反演的风场是较准确的,反演的热力场和微物理场分布也是基本合理的.中低层切变线是此次暴雨的主要动力特征,对流云表现为低层辐合、高层辐散并有垂直上升运动伴随,其热力特征表现为低层是低压区,高层为高压区,中部为暖区而上、下部为冷区,水汽、云水和雨水分别集中在对流云体内、上升气流区和强回波区.