风云三号卫星微波大气温度探测仪资料偏差订正方法研究

为推动中国风云三号卫星(FY-3A/B)资料在区域数值天气预报中的同化研究,重点研究FY-3A的大气温度垂直探测仪(MWTS)资料的偏差订正问题。在欧洲中期天气预报中心(ECMWF)原全球TOVS辐射偏差订正方案的基础上,结合MWTS资料特征,建立适用于FY-3A卫星MWTS辐射率资料的偏差订正系统,并评价MWTS的偏差订正效果。结果表明:（1） 同纬度带和扫描位置的扫描偏差不同,各通道表现出不同的偏差特征,通道1扫描偏差较大(0~5 K),通道2、3、4较小(0~0.6 K);（2） 扫描偏差订正和气团偏差订正后的观测残差基本符合均值为零的正态分布;（3） 偏差订正后的观测残差标准方差有所降低,这将提高卫星资料对分析场的调整。证明了FY-3A MWTS资料质量较好,具有同化应用的潜力,开发的偏差订正系统可为FY-3A MWTS资料在区域模式中的同化应用提供条件。      

FY-3A MWHS资料偏差订正方法研究

作为中国新一代极轨气象卫星,风云三号A星(FY-3A)大气垂直探测资料在区域数值天气预报中的同化应用至关重要。为实现FY-3A大气湿度垂直探测仪(MWHS)资料的直接同化应用,重点研究MWHS资料偏差订正问题。根据MWHS资料特征,在参考欧洲中期天气预报中心(ECMWF)原全球TIROS大气垂直探测仪(TOVS)资料偏差订正方案的基础上,建立适用于FY-3A卫星MWHS辐射率资料的偏差订正方案,分析该方案的订正效果。(1) 扫描偏差具有星下点对称性,各通道不同纬度带和扫描角的扫描偏差存在差异,通道1~5的扫描偏差绝对值范围分别为0~1.13 K、0~6.4 K、0~0.76 K、0~0.84 K和0~2.1 K。(2) 偏差订正方法有效,订正后的通道2~4观测残差概率分布呈现均值为0的高斯分布,且通道1和5观测残差更接近均值为0的高斯分布。(3) 偏差订正后观测残差标准差均有所降低,表明偏差订正能够提高MWHS资料对分析场的调整。试验证明FY-3A MWHS资料具有较高的数据质量以及同化应用的潜力;建立的偏差订正方案可为FY-3A MWHS资料直接同化提供条件。      

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。     

偏差订正方法在IASI辐射率资料同化中的应用研究

根据IASI(Infrared Atmospheric Sounding Interferometer)的资料特征和GRAPES(Global/Regional Assimilation and Prediction System)同化系统的具体情况,建立了适用于业务使用的关于IASI辐射率资料的偏差订正方案,该方案包括扫描偏差订正和气团偏差订正。统计表明,IASI资料的扫描偏差不像微波资料一样具有明显的纬度依赖性,但在2x2的像元内存在某种特殊的扫描偏差,临边测量相对于星下点的扫描偏差可以用"扫描角"作为自变量而消除,而2x2的像元内的偏差只能通过稀疏化来规避;气团偏差主要根据当时的天气条件进行订正,利用模式背景场作为预报因子定量给出天气条件,采用1 000~300 h Pa的厚度、200~50 h Pa的厚度、50~20 h Pa的厚度以及模式地表温度作为预报因子。订正方案的试验结果显示,偏差能够长时间维持在比较低的稳定水平,订正结果显著。     

极轨卫星观测偏差订正动态更新技术在GRAPES_3Dvar的应用研究

偏差订正技术是卫星辐射率资料同化的关键技术,目前全球GRAPES变分同化系统采用基于Harris和Kelly考虑扫描角和气团的静态偏差订正方案;但是该方案并没有考虑偏差属性的变化（比如仪器老化、观测数据漂移等问题）。因此,本文基于Harris和Kelly的TOVS辐射偏差订正方案以及国外在数值天气预报系统中对卫星数据提出的偏差订正动态更新概念的基础上,结合GRAPES分析预报系统和国家卫星气象中心的卫星预处理系统的特点以及仪器特征,提出了GRAPES偏差订正动态更新方案,来解决数据的漂移等问题。偏差订正动态更新技术是动态方法的一种,采用变分方法对偏差订正预报因子的系数进行调整。为了检验新方案的效果,设计了试验方案。为期两个月的同化试验结果显示,动态更新方案可以自动、迅速地优化已经退化的偏差订正方程,保持偏差订正的效果,运行稳定,结果令人鼓舞。     

ATMS微波资料特征及其对台风路径预报的影响

采用2012年8月1—30日ATMS(Advanced Technology Microwave Sounder)卫星微波资料,在WRFDA系统中进行资料特征统计分析以及偏差订正试验。针对2012年8月第13号台风“启德”、第14号台风“天秤”和第15号台风“布拉万”,检验同化ATMS卫星微波资料对台风路径预报的影响。结果表明:偏差订正前,ATMS除个别窗区通道和湿度通道偏差大于对应AMSUA/MHS通道外,其余通道偏差均小于后者;与AMSUA/MHS相比,ATMS偏差随扫描位置的变化较小且平滑,ATMS96个扫描点的资料均可用;ATMS窗区通道偏差最大,温度中层通道偏差最小;使用ATM S资料导出的偏差订正系数,可减小温度和湿度通道偏差,相比于直接使用NOAA-18偏差订正系数,可改善台风路径和最低气压预报;个例研究表明,同化中加入ATMS资料后可使台风路径预报偏差降低31%。     

L波段探空仪湿度资料偏差订正及同化试验

L波段探空仪观测资料是基础资料之一,无论在天气预报还是在数值天气预报中都起着重要作用,其资料质量直接影响数值模式同化分析及降水预报准确性。通过对我国3种常用的L波段探空仪观测湿度的偏差特性比较,研发适合该仪器的偏差订正方案,并在GRAPES同化系统中加以试验应用。结果表明:L波段探空仪湿度观测资料与ECMWF再分析湿度场比较有偏干现象。多种偏差订正方案订正结果显示:湿度偏差值比订正前减小,特别是在500 hPa以上层次减小明显。在GRAPES分析同化系统中使用Vomel偏差订正方案,分析偏差减小5%;预报模式个例和连续试验中湿度观测订正后预报降水更接近实况,预报降水检验评分显著提高,故该订正方案在实际应用中表现出积极的正效果。     

GRAPES-GFS模式2 m温度预报的最优时窗滑动订正方法

利用2017—2018年GRAPES-GFS模式预报资料和广西区域自动站逐时气温观测资料,分析模式预报偏差特征,发现GRAPES-GFS模式对广西区域2m温度的预报系统性偏低,随着预报时效增加,预报偏差增大,系统性偏差主要出现在桂北山区、左右江河谷及沿海;春夏秋三季的午后气温预报偏差有明显的系统性,冬季午后气温和四季凌晨气温预报偏差的随机性较大。为了确定滑动订正的最优时窗,通过活动时窗长度的方法,设计不同的滑动订正方案,制定最优时窗滑动订正方案,并进一步利用2020年最优时窗滑动订正业务试验产品,对比验证了该方案的订正效果。结果表明:分别采用固定时窗、季节最优时窗、月份最优时窗等滑动平均订正方案进行订正,春夏秋3季的订正效果明显好于冬季、午后订正技巧高于夜间,其中固定时窗滑动平均方案中的长时窗(15～60d)订正、季节最优时窗滑动订正以及月份最优时窗滑动订正这几种方式订正效果最优;所制定的最优时窗滑动平均订正方案,可以在不同滑动方案的基础上稳定地提高预报准确率,达到最优时窗滑动的目的。     

ATMS卫星资料的同化应用及与AMSUA/MHS的比较研究

针对数值预报中ATMS卫星资料的同化应用问题,在WRFDA框架下扩展了对ATMS卫星资料的同化功能,选择2012年7月第9号强台风“苏拉”开展初步研究,比较了NOAA18卫星上搭载微波传感器AMSUA/MHS的结果,分析卫星资料特征并试验资料同化应用对区域数值预报的影响。结果表明,ATMS探测质量优于或与AMSUA/MHS相当;同时由于ATMS具备的高空间覆盖率、增多的温度探测扫描点和湿度探测通道,可为资料同化系统提供更丰富的观测信息,有效改善数值预报效果。ATMS卫星资料的降噪处理是资料同化应用的一个初始环节,对于个例的研究结果表明,总体上可以降低噪声和提高资料的使用效果,但在湿度探测段低层通道存在经偏差订正后降噪处理结果误差有所增大的现象,说明针对处理方式还需要调整资料应用的多个环节。偏差订正前,卫星微波资料同化目前普遍使用的ATMS温度探测9通道和湿度探测22通道的卫星观测和模拟间存在较大偏差,是ATMS资料同化应用中需要注意的。此外,ATMS卫星探测与AMSUA/MHS探测通道设置较大的差别之一在于窗区通道,由此主要依据窗区通道探测的云检测方案在ATMS资料同化应用中需要加以调整和试验。      

气团订正对静止卫星成像仪资料同化在台风预报中的改进效果研究

基于美国台风预报系统（Hurricane Weather Research and Forecasting,HWRF）,研究了气团订正方法对GOES-13/15静止卫星成像仪资料同化效果的改进作用,选取了2012年6月23日生成于大西洋地区的台风Debby作为研究对象,通过一组对照试验比较了气团订正前后台风路径和初始场相关物理量的差异,结果表明:气团订正能显著减小GOES-13/15静止卫星成像仪资料的系统偏差,明显提高台风路径的预报效果,气团订正使得预报的台风路径与观测路径的平均偏差和标准差降低了30%左右,提前6 h实现了台风路径的正确转向。物理机制分析表明,经过气团订正后的静止卫星资料增强了位于台风东南侧副热带高压的强度,同时增加了台风东部的温度和比湿,在引导气流和大气温、湿场的共同作用下,台风预报路径实现了正确转向。      

TWO BIAS CORRECTION SCHEMES FOR ATOVS RADIANCE DATA

To better assimilate Advanced TIROS Operational Vertical Sounder (ATOVS) radiance data and provide more accurate initial fields for a numerical model, two bias correction schemes are employed to correct the ATOVS radiance data. The difference in the two schemes lies in the predictors use in air-mass bias correction. The predictors used in SCHEME 1 are all obtained from model first-guess, while those in SCHEME 2 are from model first-guess and radiance observations. The results from the two schemes show that after bias correction, the observation residual became smaller and closer to a Gaussian distribution. For both land and ocean data sets, the results obtained from SCHEME 1 are similar to those from SCHEME 2, which indicates that the predictors could be used in bias correction of ATOVS data.     

Application of ATOVS Radiance-Bias Correction to Typhoon Track Prediction with Ensemble Kalman Filter Data Assimilation

In this paper, firstly, the bias between observed radiances from the Advanced TIROS-N Operational Vertical Sounder (ATOVS) and those simulated from a model first-guess are corrected. After bias correction, the observed minus calculated (O-B) radiances of most channels were reduced closer to zero, with peak values in each channel shifted towards zero, and the distribution of O-B closer to a Gaussian distribution than without bias correction. Secondly, ATOVS radiance data with and without bias correction are assimilated directly with an Ensemble Kalman Filter (EnKF) data assimilation system, which are then adopted as the initial fields in the forecast model T106L19 to simulate Typhoon Prapiroon (2006) during the period 2-4 August 2006. The prediction results show that the assimilation of ATOVS radiance data with bias correction has a significant and positive impact upon the prediction of the typhoon’s track and intensity, although the results are not perfect.     

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.     

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.     

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。     

江苏不同量级降雪过程的对比分析和预报指标研究

利用常规观测资料和NCEP 1°×1°再分析资料,通过对2008-2018年共11年间发生在江苏省的区域性中雪、区域性大雪、区域性暴雪天气过程的对比分析,发现影响江苏区域性降雪的主要天气系统是500 hPa西风槽、700 hPa西南急流和地面冷空气。决定降雪量级的因素主要是700 hPa西南急流强度和范围,降雪区上空水汽输送强度、水汽辐合强度、水汽辐合厚度也与降雪量级有一定的正相关关系。暴雪时700 hPa水汽通量≥14 g·cm^-1·hPa^-1·s^-1,且水汽来源更为丰富,均来自于孟加拉湾和南海;大雪和中雪时,700 hPa水汽通量分别≥12 g·cm^-1·hPa^-1·s^-1和10 g·cm^-1·hPa^-1·s^-1。暴雪期间,水汽辐合区内水汽通量散度都≤^-1×10^-7g·s^-1·hPa^-1·cm^-2,水汽辐合厚度达200~400 hPa,明显强于大雪和中雪。有利于江苏发生区域降雪过程的温度垂直分布条件为:地面≤2℃、t₉₂₅≤-1℃、t₈₅₀≤-2℃、t₇₀₀≤-1℃、t₅₀₀≤-14℃。随着降雪量级的增大,中低层温度阈值呈降低趋势。中低层逆温是产生区域性大雪及暴雪的必要条件,而中雪发生时不一定都有逆温层结,只要近地层温度条件合适,就能产生降雪。随着降雪量级的增大,逆温层强度明显增强、厚度明显增厚。暴雪、大雪和中雪时逆温强度阈值分别为3~8℃、2~8℃和1~3℃,其逆温层厚度分别为150~200 hPa、100~200 hPa和50~100 hPa。降雪过程中上升运动强中心位于600400 hPa。暴雪时,上升运动区相对大雪和中雪时的更为深厚,基本整层都为上升运动区,垂直运动发展旺盛。暴雪和大雪时上升运动中心值均≤-0.7 Pa·s^-1,中雪时中心值≤-0.3 Pa·s^-1。     

Spatio-temporal variability of atmospheric rivers and associated atmospheric parameters in the Euro-Atlantic region

We study the spatio-temporal variability of Atmospheric Rivers (ARs) and associated integrated water vapor and atmospheric parameters over the Euro-Atlantic region using long-term reanalysis datasets. Winds, temperature, and specific humidity at different pressure levels during 1979–2018 are used to study the water vapor transport integrated between 1000 and 300 hPa (IVT300) in mapping ARs. The intensity of ARs in the North Atlantic has been increasing in recent times (2009–2018) with large decadal variability and poleward shift (~ 5° towards the North) in landfall during 1999–2018. Though different reanalysis datasets show similar spatial patterns of IVT300 in mapping ARs, bias in specific humidity and wind components led to IVT300 mean bias of 50 kg m⁻¹ s⁻¹ in different reanalysis products compared to ERA5. The magnitude of winds and specific humidity in the lower atmosphere (below 750 hPa) dominates the total column water vapor and intensity of ARs in the North Atlantic. Reanalysis datasets in the central North Atlantic show an IVT300 standard deviation of 200 kg m⁻¹ s⁻¹ which is around 33% of the ARs climatology (~ 600 kg m⁻¹ s⁻¹). Though ARs have a higher frequency of landfalling over Western Europe in winter half-year, the intensity of IVT300 in winter ARs is 3% lower than the annual mean. The lower frequency of ARs in the summer half-year shows 3% higher IVT300 than the annual mean. While ARs in the North Atlantic show a strong decadal change in frequency and path, the impact of the North Atlantic Oscillation (NAO) and Scandinavian blocking on the location of landfall of ARs are significant. Furthermore, there is a strong latitudinal dependence of the source of moisture flux in the open ocean, contributing to the formation and strengthening ARs.