RTTOV散射模块在FY-3 MWHS资料同化中的应用

一直以来,受同化系统中观测算子的限制,云区的卫星微波观测资料在使用时都常会做晴空假设,只考虑大气的吸收作用而忽略散射作用,从而会造成对大气中水汽含量的高估。为了克服这一缺点,文中设计了RTTOV微波散射模块在WRF 3DVAR系统中的应用方案,使得计算辐射能衰减的同时考虑大气的散射作用,并在此基础上通过4组试验进行了风云3 A星微波湿度计亮温以及多普勒雷达反射率因子的同化研究对比。结果表明：RTTOV微波散射模块的引入,能有效抑制晴空辐射模块对大气水汽含量的高估。若先同化雷达反射率因子后再继续同化卫星资料,会发现同化雷达后,同化区域内大气水凝物含量明显增加,受此影响同化卫星资料时大气的散射作用也会随之增大。并且雷达同化区域覆盖率越大,对降水预报的改善效果也愈明显。     

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-3A/MWHS冷空测值受月球影响分析及修正

为解决月球对风云三号卫星微波湿度计在轨实时辐射定标的影响问题,该文根据风云三号卫星微波湿度计在轨实时观测数据分析,通过多项式拟合分析技术,建立修正模型,消除月球影响,得到合理的辐射定标结果。风云三号卫星微波湿度计在轨实测数据分析表明:月球对风云三号卫星微波湿度计在轨辐射定标结果影响最严重时一天内可干扰4~5条轨道,每条轨道有近100个扫描周期受到污染。月球影响致使冷空定标观测数据跳升1000个计数值,如果不进行污染滤除会造成对地观测亮温下降约20 K,导致辐射资料无法同化进入数值天气预报模式。通过与同类载荷的交叉比对分析,修正月球影响后,风云三号卫星微波湿度计在轨实时辐射定标结果精度与在轨测试结果相当。     

评估FY-3A微波湿度计O-B对云的识别能力

应用FY-3A微波湿度计2010年1月份的Level-1c观测亮度温度O,NCEP GFS 6 h的预报场作为背景场,用RTTOV 9.3版本辐射传输模式模拟的亮度温度B以及美国NOAA-18 MHS业务微波地表和降水产品,研究了双权重质量控制算法对FY-3A MWHS 通道3至5云和降水视场的识别能力。研究表明双权重质量控制算法判断的负观测增量O-B的离群点中,大多数都受云和降水影响。通道3约占60%,通道4约80%,通道5超过80%。当降水率大于0.2 mm·h^-1时,通道3负离群点可识别超过60%降水云,随着降水率增大识别率超过80%。而通道4对大于0.2 mm·h^-1的降水的识别率超过90%。通道5负离群点几乎可以剔除100%的降水影响资料。在目前还没有MWHS自身云检测产品的条件下,双权重质量控制算法可剔除大部分云和降水影响视野。     

一次极端短时强降水过程中FY-3微波湿度计观测特征分析

利用FY-3微波湿度计资料和常规观测资料,对2016年贵州至湖北一次强降水事件中极端短时强降水站点、一般性短时强降水站点上空对流云的微波观测特征进行了对比分析。结果表明:(1)极端短时强降水站点上空150 GHz附近窗区探测通道亮温低于一般性短时降水站点。(2)极端短时强降水站点上空水汽通道亮温垂直分布呈现漏斗状,对干侵入有一定指示作用,亮温最低值出现在183.31±7 GHz附近,主要为暖云降水;一般性短时强降水站点上空水汽通道亮温垂直分布则呈竖条形,亮温最低值出现在183.31±3 GHz和183.31±7 GHz探测通道附近,为冷云暖云混合降水。(3)极端短时强降水站点上空未出现冲顶对流,但低层对流发展旺盛;一般性短时强降水站点上空出现冲顶对流,但低层对流发展强度偏弱。     

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。      

FY-3C MWHS-Ⅱ辐射亮温在RMAPS-CA中的同化

中亚地区常规气象观测稀疏，同化极轨卫星FY-3C上的微波湿度探测器-Ⅱ(MWHS-Ⅱ)辐射率资料可有效减小该地区数值预报初始场的不确定性。本研究首次在中亚快速更新多尺度资料分析和预报系统RMAPS-CA中同化了FY-3C/MWHS-Ⅱ辐射率，评估了其同化效果。研究发现：（1）单个时次冷启动的同化时间窗口内，仅约有56%的辐射率资料通过了质量控制并被RMAPS-CA同化。（2）偏差订正整体减小了各水汽通道的背景场辐射亮温偏差，最大减幅出现在通道14，达0.5 K。通道14偏差订正前的观测辐射亮温和背景场辐射亮温间存在较大偏差，是其同化应用中需要特别注意的。（3）FY-3C/MWHS-Ⅱ辐射率同化整体提高了RMAPS-CA系统对高空温度、位势高度、高空风速等的中短期预报准确率。同时，使得2米温度和10米风速的预报准确率预报均方根误差分别平均减小了0.2 K和2 m/s。其同化有效降低了小雨预报的漏报率和空报率，小雨预报的TS评分提升了16%。降低了中雨和大雨预报的漏报率，三个量级降水预报的BIAS评分分别提升了18%、38%和36%。     

2008-07-22襄樊特大暴雨FY-3A微波资料分析

搭载在中国新一代极轨卫星FY-3A上的微波湿度计对于大气湿度以及云雨分布特征具有较好的探测能力。利用其150GHｚ极化波段亮温和183-31GHｚ附近的水汽吸收波段亮温及其反演产品,对2008年7月22日襄樊特大暴雨中10：00-11:00强降水成因进行了分析。结果表明：襄樊10：00-11:00强降水产生时,微波湿度计5个波段亮温均处于低值区的大梯度带;极化比、极化差出现明显的大、小值分裂;微波湿度计的高频通道资料表明,襄樊处于深对流中心地带,正是这种深厚的对流系统导致了襄樊的强降水。     

FY-3A MWHS资料的质量控制——以四川“8.19”暴雨为例

FY-3A MWHS微波湿度计辐射率资料空间分辨率高,同化后能有效地提高中尺度系统的数值预报的准确率。但如果不进行质量控制,任由误差大的离群微波资料进入同化系统,将会降低分析场精度,影响预报准确率。本文选取2010年8月17~19日的暴雨个例,应用主成分分析(PCA)方法,找出FY-3A微波湿度计数据中的离群值。结果表明:采用PCA方法,3天的资料总共识别出148个离群值样本,占总数的19.3%,其中通道三离群值占5.5%,通道四离群值占8.2%,通道五占5.4%。去除这些离群值后的MWHS数据总体分布,更靠近数据中心,各EOF方差贡献更加平滑。这说明PCA方法是一种可以抵抗少数离群值对总平均值影响的有效质量控制方法。      

星载降水雷达机载校飞试验：地基多通道微波辐射计估算雷达路径积分衰减

介绍了在雷达观测降水试验中如何配合利用地基微波辐射计估算雷达路径积分衰减(PIA)的一种方法.所用的GPS高空探空资料和地基多通道微波辐射计的观测资料,均为中国首次星载降水雷达机载校飞试验中获得的数据.由于常规探空资料中没有云水含量的直接信息,因此,通过绝热液态水含量分析方法,从GPS探空数据中计算得到这些云参数值.用MWMOD进行亮温模拟并计算液态水含量.在晴空条件下,用该模式模拟了地基多通道微波辐射计12个通道的下行辐射亮温.通过设置相对湿度阈值,利用MWMOD模式自带的绝热液态水含量分析方法,从探空廓线中分析出液态水廓线,进而模拟出有云情况下的下行辐射亮温.辐射传输模式的模拟亮温和地基多通道微波辐射计观测亮温的对比表明,进行云分析之后的模拟亮温值更接近于实测值.由此,利用由辐射传输模式和地基微波辐射计,从探空廓线中分析出液态水廓线,计算出有云情况下的大气整层透过率,进而得到路径积分衰减,为降水雷达衰减订正提供一种有效手段.     

Development and initial assessment of a new land index for microwave humidity sounder cloud detection

This paper describes a new quality control (QC) scheme for microwave humidity sounder (MHS) data assimilation. It consists of a cloud detection step and an O–B (i.e., differences of brightness temperatures between observations and model simulations) check. Over ocean, cloud detection can be carried out based on two MHS window channels and two Advanced Microwave Sounding Unit-A (AMSU-A) window channels, which can be used for obtaining cloud ice water path (IWP) and liquid water path (LWP), respectively. Over land, cloud detection of microwave data becomes much more challenging due to a much larger emission contribution from land surface than that from cloud. The current MHS cloud detection over land employs an O–B based method, which could fail to identify cloudy radiances when there is mismatch between actual clouds and model clouds. In this study, a new MHS observation based index is developed for identifying MHS cloudy radiances over land. The new land index for cloud detection exploits the large variability of brightness temperature observations among MHS channels over different clouds. It is shown that those MHS cloudy radiances that were otherwise missed by the current O–B based QC method can be successfully identified by the new land index. An O–B check can then be employed to the remaining data after cloud detection to remove additional outliers with model simulations deviated greatly from observations. It is shown that MHS channel correlations are significantly reduced by the newly proposed QC scheme.     

Evaluation of All-Sky Assimilation of FY-3C/MWHS-2 on Mei-yuPrecipitation Forecasts over the Yangtze-Huaihe River Basin

正1School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610025, China2International Center for Climate and Environment Sciences, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 100029, China3University of Chinese Academy of Sciences, Beijing 100049, China     

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。     

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。     

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.     

Preliminary Study on Direct Assimilation of Cloud-affected Satellite Microwave Brightness Temperatures

Direct assimilation of cloud-affected microwave brightness temperatures from AMSU-A into the GSI three-dimensional variational(3D-Var) assimilation system is preliminarily studied in this paper. A combination of cloud microphysics parameters retrieved by the 1D-Var algorithm(including vertical profiles of cloud liquid water content, ice water content, and rain water content) and atmospheric state parameters from objective analysis fields of an NWP model are used as background fields. Three cloud microphysics parameters(cloud liquid water content, ice water content, and rain water content) are applied to the control variable. Typhoon Halong(2014) is selected as an example. The results show that direct assimilation of cloud-affected AMSU-A observations can effectively adjust the structure of large-scale temperature, humidity and wind analysis fields due to the assimilation of more AMSU-A observations in typhoon cloudy areas, especially typhoon spiral cloud belts. These adjustments, with temperatures increasing and humidities decreasing in the movement direction of the typhoon,bring the forecasted typhoon moving direction closer to its real path. The assimilation of cloud-affected satellite microwave brightness temperatures can provide better analysis fields that are more similar to the actual situation. Furthermore, typhoon prediction accuracy is improved using these assimilation analysis fields as the initial forecast fields in NWP models.     

Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales

This study explores the structures of the correlations between infrared(IR)brightness temperatures(BTs)from the three water vapor channels of the Advanced Baseline Imager(ABI)onboard the GOES-16 satellite and the atmospheric state.Ensemble-based data assimilation techniques such as the ensemble Kalman filter(EnKF)rely on correlations to propagate innovations of BTs to increments of model state variables.Because the three water vapor channels are sensitive to moisture in different layers of the troposphere,the heights of the strongest correlations between these channels and moisture in clear-sky regions are closely related to the peaks of their respective weighting functions.In cloudy regions,the strongest correlations appear at the cloud tops of deep clouds,and ice hydrometeors generally have stronger correlations with BT than liquid hydrometeors.The magnitudes of the correlations decrease from the peak value in a column with both vertical and horizontal distance.Just how the correlations decrease depend on both the cloud scenes and the cloud structures,as well as the model variables.Horizontal correlations between BTs and moisture,as well as hydrometeors,in fully cloudy regions decrease to almost 0 at about 30 km.The horizontal correlations with atmospheric state variables in clear-sky regions are broader,maintaining non-zero values out to~100 km.The results in this study provide information on the proper choice of cut-off radii in horizontal and vertical localization schemes for the assimilation of BTs.They also provide insights on the most efficient and effective use of the different water vapor channels.     

The effect of cirrus clouds on microwave limb radiances

This study presents and analyses the first simulations of microwave limb radiances with clouds. They are computed using the 1D unpolarized version of the Atmospheric Radiative Transfer System (ARTS). The study is meant to set a theoretical foundation for using microwave limb measurements for cloud monitoring. Information about clouds is required for the validation of climate models.Limb spectra are generated for the frequency bands of the Millimeter wave Acquisitions for Stratosphere/Troposphere Exchange Research (MASTER) instrument. For these simulations, the radiative transfer equation is solved using the Discrete Ordinate ITerative (DOIT) method, which is briefly described. Single scattering properties for the cloud particles are calculated using the T-matrix method.The impact of various cloud parameters is investigated. Simulated brightness temperatures most strongly depend on particle size, ice mass content and cloud altitude. The impact of particle shape is much smaller, but still significant. Increasing the ice mass content has a similar effect as increasing the particle size; this complicates the prediction of the impact of clouds on microwave radiances without exact knowledge of these cloud parameters.     

Field study of the potential for winter precipitation enhancement in the Australian Snowy Mountains

A research program was initiated in 1988 to investigate the potential for winter snowpack enhancement in the Snowy Mountains of Australia. Field studies were conducted during the austral winters of 1988 and 1989 in order to characterize the water and ice composition of clouds passing over these mountains. We utilized a dual-channel microwave radiometer and a Ka-band (8.6 mm wavelength) radar in a coordinated observational program to document the distribution of supercooled liquid water, ice phase precipitation and water vapor in the winter storm systems. The vertical temperature, humidity and wind profiles were obtained at high temporal resolution from local rawinsonde launches. Ground-based sampling of the snow crystal types and the stable isotopic composition of the snow provided information on the processes of crystal formation and riming during these storms. A precipitation trajectory model was used to simulate ice crystal growth for snow which precipitates within the study region. Analysis of these data indicate buildup of supercooled liquid water during certain storm periods, while during other periods the ice crystal growth processes efficiently remove cloud liquid. Several aspects of the cloud seeding potential are discussed in this paper and the overall conclusion is that winter precipitation enhancement is scientifically feasible, based upon the World Meteorological Organization criterion of supercooled liquid water availability.     

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...