气象卫星资料同化的科学问题与前景

从数值天气预报资料同化的角度,分析了气象卫星观测与常规气象观测的不同特点形成了卫星资料同化的特殊科学问题.由于各类星载遥感仪器所观测到的是一定波长的电磁辐射,不能像传统的直接观测资料一样被预报模式直接应用.又由于卫星观测对象是整个大气层,而不是特定高度的大气,因此确定卫星观测影响的高度和它的潜在垂直分辨率成为一个关键问题.卫星观测还可能存在着系统性的偏差,这与直接观测的误差互相独立也有很大区别.资料同化通常建立在模式预报(即背景信息)与观测量的比较的基础上,为了实现同化,需要将模式的基本大气变量转换成星载仪器所获得的特定波长的电磁波特征量,或者将观测到的电磁辐射特征量反算成大气的特征量.前者需要引入复杂的观测算子,后者则将复杂的反演过程交给了前处理阶段.这就形成了直接与间接同化卫星资料的两种不同策略,策略的选择取决于同化系统处理复杂观测资料的能力,对同化效果有决定性的影响.逐个分析了目前用于数值预报的5种卫星观测资料,即星载大气垂直探测器资料、大气运动矢量资料、散射仪海面风资料、卫星观测的云与降水信息资料与GPS掩星观测资料的同化的进展与有待解决的主要问题,概述了中国近年在大气垂直探测器等卫星资料同化中的研究进展及其业务应用的效果,并提出了今后需要予以特别关注的研究方向.     

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.     

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.     

卫星探测辐射率在数值天气预报中的直接应用

该文叙述在数值天气预报中直接应用辐射率而不经过反演的原因，变分法在辐射率直接应用中的作用，以及介绍变分问题计算中的伴随方法。还指出ATOVS辐射率同样可以在NWP中直接应用。最后，介绍业务NWP直接应用辐射率的情况。     

A validation of the multivariate and minimum residual method for cloud retrieval using radiance from multiple satellites

The Multivariate and Minimum Residual(MMR) cloud detection and retrieval algorithm, previously developed and tested on simulated observations and Advanced Infrared Sounder radiance, was explored and validated using various radiances from multiple sensors. For validation, the cloud retrievals were compared to independent cloud products from Cloud Sat, MODIS(Moderate Resolution Imaging Spectroradiometer), and GOES(Geostationary Operational Environmental Satellites). We found good spatial agreement within a single instrument, although the cloud fraction on each pixel was estimated independently. The retrieved cloud properties showed good agreement using radiances from multiple satellites, especially for the vertically integrated cloud mask. The accuracy of the MMR scheme in detecting mid-level clouds was found to be higher than for higher and lower clouds. The accuracy in retrieving cloud top pressures and cloud profiles increased with more channels from observations. For observations with fewer channels, the MMR solution was an "overly smoothed" estimation of the true vertical profile, starting from a uniform clear guess. Additionally, the retrieval algorithm showed some meaningful skill in simulating the cloudy radiance as a linear observation operator, discriminating between numerical weather prediction(NWP) error and cloud effects. The retrieval scheme was also found to be robust when different radiative transfer models were used. The potential application of the MMR algorithm in NWP with multiple radiances is also discussed.     

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。     

区域极轨卫星ATOVS辐射偏差订正方法研究

近年来,卫星辐射资料在数值天气预报(NWP)系统中的直接同化研究取得了长足进展。为了利用TIROS业务垂直探测器(ATOVS)的辐射资料,必须对卫星观测辐射值的系统性偏差进行订正。在ECMWF原全球TOVS辐射偏差订正方案基础上,结合ATOVS资料特征和中国的实际情况,建立了适用于区域NOAA-15/16/17极轨气象卫星ATOVS辐射资料的偏差订正方案。该方案偏差订正分两步进行:首先进行扫描偏差订正,然后进行气团偏差订正。扫描偏差是临边测量相对于星下点测量的系统偏差,统计显示该种偏差具有一定的纬度依赖性,所以订正时按每10度的纬度带分别进行订正。气团偏差订正主要就是根据当时的天气条件进行订正,而天气条件一般用预报因子来定量表示。文中从中国国家气象中心T213背景场导出预报因子:(1)1000—300 hPa的厚度,(2)200—50 hPa的厚度,(3)模式地表温度,(4)总可降水量。模式预报因子的使用从观念上将对观测值的订正变为对计算前向辐射值的订正问题。试验结果表明,订正结果显著。     

有云时大气红外遥感及其反演问题 I. 理论研究

我们已经研究了晴空情况下的大气红外遥感及其反演问题。本文对有云情况下的大气红外遥感及其反演问题进行了研究，首先指出国际上通用的处理有云反演的晴空订正法存在误差放大问题，然后提出了3×3相邻视场同步反演法，在该方法中，假定3×3相邻视场具有共同的大气温度廓线和大气水汽廓线，从而使求解方程数增加到9倍，而反演参数只增加有限的几个，大大提高了有云情况下反演的稳定性。     

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。     

基于亮温通道变率的FY-3C微波湿度计陆地云检测新方法

云检测是卫星资料同化的重要前处理步骤,无论是晴空资料同化还是有云资料同化,都需要准确地区分有云和晴空资料。由于陆地地表发射率的多变性和微波能穿透部分云类的特点,微波湿度计资料在陆地上空的云检测研究一直是难点。利用快速辐射传输模式（CRTM）分析了不同云类条件下FY-3C微波湿度计（MWHS-Ⅱ）各通道亮温的通道间变率特征,根据MWHS-Ⅱ亮温通道间变率随云高以及云中液态水含量的增大而减小的特点,提出了一个基于亮温通道变率的MWHS-Ⅱ陆地资料云检测方法。与已有的云产品比较结果表明:新的云检测算法能有效地剔除大部分受云影响的资料,剔除后的晴空资料观测和模拟偏差更好地符合高斯分布。新方法对过冷水云、冰云、重叠云的检测能力较强,正确检测率可以达到80%,对卷云以及高度较低的水云的检测能力相对较弱。新方法能有效利用MWHS-Ⅱ观测资料自身完成云检测,在MWHS-Ⅱ资料同化中有很好的应用前景。      

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.     

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。     

Assimilating All-sky Infrared Radiances from Himawari-8 Using the 3DVar Method for the Prediction of a Severe Storm over North China

Although radar observations capture storm structures with high spatiotemporal resolutions, they are limited within the storm region after the precipitation formed. Geostationary satellites data cover the gaps in the radar network prior to the formation of the precipitation for the storms and their environment. The study explores the effects of assimilating the water vapor channel radiances from Himawari-8 data with Weather Research and Forecasting model data assimilation system(WRFDA) for a severe storm case over north China. A fast cloud detection scheme for Advanced Himawari imager(AHI)radiance is enhanced in the framework of the WRFDA system initially in this study. The bias corrections, the cloud detection for the clear-sky AHI radiance, and the observation error modeling for cloudy radiance are conducted before the data assimilation. All AHI radiance observations are fully applied without any quality control for all-sky AHI radiance data assimilation. Results show that the simulated all-sky AHI radiance fits the observations better by using the cloud dependent observation error model, further improving the cloud heights. The all-sky AHI radiance assimilation adjusts all types of hydrometeor variables, especially cloud water and precipitation snow. It is proven that assimilating all-sky AHI data improves hydrometeor specifications when verified against the radar reflectivity. Consequently, the assimilation of AHI observations under the all-sky condition has an overall improved impact on both the precipitation locations and intensity compared to the experiment with only conventional and AHI clear-sky radiance data.     

Evaluation of the assimilation of conventional and satellite-based observations in simulating heavy rainfall event using WRFDA over the North-West Himalayan region

Present work elucidates the impact of 3DVAR data assimilation technique for the simulation of one of the heavy rainfall events reported over Kotdwara region in the North-West Himalayan (NWH) region on 4th August 2017. We have examined the impact of conventional and satellite-based radiance datasets on the simulated results with and without assimilating the observations into the Weather Research and Forecasting (WRF) model. Three experiments have been designed with 3 nested domains of variable resolutions, one without assimilation (referred as control experiment) and other two experiments after assimilating conventional and satellite radiances observations (refer as DA-OBS and DA-SAT respectively). In the present study, assimilation of surface, upper air and the satellite-based radiance observations has been carried out for the outermost domain with horizontal resolution of 9 km. Statistical analysis suggests that the correlation coefficient is high (0.55) and root mean square error (RMSE) is low (17.12) for DA-SAT experiment as compared to other two experiments. Substantial improvement in the location, pattern and intensity of extreme rainfall event is noted after assimilation of both conventional and satellite observations with respect to the observed rainfall data. However, it is noted that the assimilation of satellite radiances has greater impact in simulating better intensity of the heavy rainfall event as compared to the assimilation of conventional observations. Plausible reason behind this could be the non-availability of the conventional observations close to the extreme rainfall event affected region.     

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。     

Impact of Assimilating Radiances with the WRFDA ETKF/3DVAR Hybrid System on Prediction of Two Typhoons in 2012

The impacts of AMSU-A and IASI (Infrared Atmospheric Sounding Interferometer) radiances assimila-tion on the prediction of typhoons Vicente and Saola (2012) are studied by using the ensemble transform ...     

Quality Assessment and Forecast Sensitivity of Global Remote Sensing Observations

The satellite-derived wind from cloud and moisture features of geostationary satellites is an important data source for numerical weather prediction(NWP) models. These datasets and global positioning system radio occultation(GPSRO)satellite radiances are assimilated in the four-dimensional variational atmospheric data assimilation system of the UKMO Unified Model in India. This study focuses on the importance of these data in the NWP system and their impact on short-term24-h forecasts. The quality of the wind observations is compared to the short-range forecast from the model background. The observation increments(observation minus background) are computed as the satellite-derived wind minus the model forecast with a 6-h lead time. The results show the model background has a large easterly wind component compared to satellite observations. The importance of each observation in the analysis is studied using an adjoint-based forecast sensitivity to observation method. The results show that at least around 50% of all types of satellite observations are beneficial. In terms of individual contribution, METEOSAT-7 shows a higher percentage of impact(nearly 50%), as compared to GEOS, MTSAT-2and METEOSAT-10, all of which have a less than 25% impact. In addition, the impact of GPSRO, infrared atmospheric sounding interferometer(IASI) and atmospheric infrared sounder(AIRS) data is calculated. The GPSRO observations have beneficial impacts up to 50 km. Over the Southern Hemisphere, the high spectral radiances from IASI and AIRS show a greater impact than over the Northern Hemisphere. The results in this study can be used for further improvements in the use of new and existing satellite observations.     

在NCEPGDAS中同化MSG和GOES资料

首次将MSG-2（Meteosat Second Generation-2）卫星上的旋转增强可见光及红外成像仪（Spin—ning Enhanced Visibleand Infrared Imager,SEVIRI）的观测资料同化到美国国家环境预报中心（Na—tional Centers for Environmental Prediction,NCEP）全球资料同化系统（globaldataassimilationsys—tern,GDAS）中。对当前的地球静止业务环境卫星（Geostationary Operational Environmental Satel—lite,GOES）成像仪资料的同化问题也进行了进一步探讨。利用CRTM（The Community Radiative Transfer Model）模式,对SEVIRI辐射率观测资料进行了模拟。为了对红外辐射率资料进行模拟,CRTM模式中的几个关键部分得到改进,例如：动态更新地面发射率资料以及采用了快速精确的气体吸收模块。为了改进对SEVIRI和GOES成像仪辐射率资料的模拟效果,采用了GSICS（The Global Space—Based Inter—Calibration System）标定订正。初步研究结果表明,包含对SEVIRI辐射率资料的水汽通道（6．25和7．35μm）和二氧化碳通道（13．40μm）的同化对GFS（Global Forecast System）6d预报具有显著的正影响;而对其他5个SEVIRI红外窗口通道资料的同化则减小了这种正影响。通过应用GSICS标定算法,订正了SEVIRI和GOES-12成像仪观测资料的偏差,提高了对GFS预报的影响。此外,还需作进一步研究来提高对SEVIRI红外窗口通道辐射率资料同化的有效性。     

Assimilation of FY-3D MWTS-Ⅱ Radiance with 3D Precipitation Detection and the Impacts on Typhoon Forecasts

Precipitation detection is an essential step in radiance assimilation because the uncertainties in precipitation would affect the radiative transfer calculation and observation errors. The traditional precipitation detection method for microwave only detects clouds and precipitation horizontally, without considering the three-dimensional distribution of clouds.Extending precipitation detection from 2D to 3D is expected to bring more useful information to the data assimilation without using the a...     

大气遥感辐射传输模式的一种有效的Jacobian算法

介绍并验证了一种快速、精确地计算Jacobian的解析方法(辐射传输方程的线性化,简称LR方法),将其结果与NAST-I真正的线性模式及数值方法(差分方法)的Jacobian值进行比较。结果表明,这种解析算法不仅快速、精确,而且独立于辐射传输方程,在有效Jacobian计算中只需要输入大气透过率,可适用于任何垂直探测器权重函数的计算。