红外高光谱IASI卫星资料同化对一次大风过程的影响研究

以2019年4月24日发生在辽宁省的一次大风天气过程为例,选取GFS(全球预报系统) 0.25°×0.25°再分析资料,基于WRF模式三维变分同化技术,进行一组IASI资料同化试验,和未同化任何资料的控制试验(CTNL)。通过对比两组试验结果考察IASI资料同化改进数值模式初始场的分析及其后续预报的机制。研究结果表明：经过IASI资料同化的模拟结果质量有很大改善,分析场与背景场相比更靠近观测场；经过云检测之后不同通道使用的观测数目多少不一,资料同化对模拟的改善效果在通道0~800最佳；IASI资料同化对地表10 m风场的预报技巧有显著的提高作用,相比控制试验可以更精准地预报大风天气的区域和强度；IASI同化试验的预报质量高于控制试验且随时间比较稳定。     

AMSU-A全空辐射率资料同化对台风“天鸽”的预报影响研究

利用美国NCEP(National Centers for Environmental Prediction)发展的GSI(Gridpoint Statistical Interpolation)同化系统和GSM(Global Spectral Model)全球频谱预报模式作为循环同化系统,选用2017年第13号台风为研究个例,采用全空和晴空两种同化方案对AMSU-A(The Advanced Microwave Sounding Unit-A)辐射率观测开展同化对比试验,并对台风"天鸽"个例进行5 d预报,研究AMSU-A全空辐射率同化对台风天鸽发展过程预报的影响。结果表明,全空同化方案相比晴空同化方案预报的台风路径、台风中心气压以及台风最大风速预报误差更小;全空同化方案对台风"天鸽"生命周期的模拟更加准确,更接近中国气象局发布的台风天鸽最佳路径的最低气压,而晴空同化方案预报的台风发展较弱,无法预报出成熟期的台风强度;全空同化方案能够增加低层通道海上厚云覆盖区域辐射率资料同化量,增幅占AMSUA同化观测总量10%,从而改进海洋区域天气系统的热力场结构。     

扩展水凝物控制变量的雷达资料同化对台风“天鸽”数值模拟的影响

利用WRF(Weather Research and Forecast)模式及WRFDA(WRF model data assimilation system)系统,针对2017年台风“天鸽”个例通过同化雷达径向速度(Vr)和反射率因子(RF),研究水凝物控制变量的雷达资料同化对台风分析预报的影响。研究表明：雷达径向速度的直接同化有效地改进了模式初始场中台风涡旋区的中小尺度信息,分析场中产生了气旋性的风场增量,对模式背景场中的台风有显著增强作用。通过在传统控制变量中扩展针对水凝物的控制变量可有效地同化雷达反射率因子资料,对初始场的水物质进行调整,并对随后确定性预报的台风路径和强度都有一定的正效果。此外,相比没有水凝物控制变量的雷达同化试验,加入了水凝物控制变量的雷达资料同化试验降水预报效果更好。这为将我国近海的地基多普勒天气雷达用于台风初始化分析和预报提供了一定的技术支撑和保障。     

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%。     

探空和飞机观测资料联合同化对台风“苏迪罗”（2015）数值模拟的影响研究

基于中尺度数值天气预报模式WRF和WRFDA三维变分同化系统,针对2015年台风“苏迪罗”二次登陆过程,利用NCEP ADP提供的无线电探空、飞机报观测资料,同时同化两种资料,并进行36 h模拟预报,从台风移动路径、强度、降水及模式初始场改进等方面分析了同化模拟效果。结果表明,同时同化两种资料能够有效改善台风移动路径、中心附近最低气压的模拟。对浙闽降水关键区24 h降水的TS评分结果表明,该同化方案对台风降水的预报评分有一定程度的改进,尤其是中雨和特大暴雨的改进最明显。对于模式初始场的温度、相对湿度、纬向风、经向风在各高度上的均方根误差,除湿度外均有不同程度的减小。并且同化对于台风结构的模拟也有所调整。      

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。     

多普勒雷达资料循环同化在台风“鲇鱼”预报中的应用

高分辨率的中尺度预报模式ARPS及其3DVAR/云分析系统,针对2010年登陆福建的超强台风“鲇鱼”,研究对流可分辨尺度下,每1h循环同化沿海新一代多普勒雷达网资料分析、研究对台风初始场和预报场的改进作用.结果表明:单独同化雷达资料可显著改善初始场中的台风内核区动力和热力结构,以及台风强度和位置,进而提高18h台风强度、路径和降水预报,但预报路径和降水分布与实况仍存在差异.在雷达资料同化基础上加入常规观测资料,对初始场中台风内核区结构改进不大.但在显著调整大尺度背景场,从而进一步减少台风路径预报误差,能准确预报出福建沿海两个强降水区域的位置和强度.总体而言,雷达资料同化主要提高台风结构分析,而常规观测资料同化主要改善环境场分析,两者有效结合使得预报结果和实况最为接近.     

基于混合集合同化方案的台风“海鸥”的数值模拟研究

混合变分/集合同化是基于变分+集合思路新兴发展起来的一种资料同化方法。利用WRF和WRFDA最新版本3.5构建混合集合同化的流程,通过单点试验直观体现出混合集合同化方案“流依赖”背景误差协方差的影响。对台风“海鸥”路径和强度的模拟和分析表明,混合集合同化方案在台风路径和强度的预报上要强于三维变分同化方案。对比两种方案同化后的分析场表明,混合集合同化方案分析出的台风中心强度优于三维变分同化方案分析结果,其原因一方面是混合集合同化方案初始场是采用集合平均的结果,另一方面是混合集合同化方案采用“流依赖”背景误差协方差的影响,这两个因素对台风的预报准确性有一定作用。      

葵花8号辐射率资料同化在一次川渝暴雨预报中的应用研究

新一代静止气象卫星葵花8号(Himawari-8)上搭载的静止轨道成像仪AHI (Advanced Himawari Imager)凭借其高时空分辨率可以对重庆地区暴雨进行连续观测。本文选取2019年4月19日的一次区域性暴雨天气过程为试验个例,采用WRF (Weather Research and Forecasting)中尺度模式进行数值模拟。基于WRFDA (Weather Research and Forecasting model Data Assimilation)同化系统对葵花8号静止气象卫星的AHI辐射率资料进行相应的质量控制和云检测,进而开展循环同化试验,考察卫星资料同化对这次强对流天气过程预报结果的改进。结果表明在同化AHI红外辐射率资料之后,辐射传输模式模拟的亮温和观测亮温更为接近。此外,AHI水汽通道辐射率资料同化有效提高了对各层高度上的风场、水汽场、雷达回波等要素特征的分析效果,并且使模式的初始条件更逼近真实的大气状态。研究发现同化AHI水汽通道辐射率资料后模拟的降水整体分布与实际情况更为接近,主要雨带位置以及强降水中心的精确程度显著高于背景场的预报效果。经过...     

台风“灿鸿”(1509)的适应性观测敏感区特征及其模拟观测同化研究

适应性观测可以改善资料同化和预报质量。本文利用集合卡尔曼变换适应性观测系统对2015年09号台风“灿鸿”进行了观测敏感区识别，并以第一目标时刻的观测敏感区为基础，运用观测系统模拟试验方法获取模拟的适应性观测资料。基于WRF中尺度同化和预报系统，开展了适应性观测敏感区模拟资料的同化和预报试验。研究发现，台风“灿鸿”（1509）的观测敏感区主要位于台风中心的东北侧及东南侧。同化敏感区内模拟观测资料比同化常规观测资料能更好地改善分析质量和高度、台风路径的预报质量，但对降水的预报改善较弱。     

Impact of assimilating IASI radiance observations on forecasts of two tropical cyclones

The impact of assimilating Infrared Atmospheric Sounding Interferometer (IASI) radiance observations on the analyses and forecasts of Hurricane Maria (2011) and Typhoon Megi (2010) is assessed using Weather Research and Forecasting Data Assimilation (WRFDA). A cloud-detection scheme (McNally and Watts 2003) was implemented in WRFDA for cloud contamination detection for radiances measured by high spectral resolution infrared sounders. For both Hurricane Maria and Typhoon Megi, IASI radiances with channels around 15-μm CO₂ band had consistent positive impact on the forecast skills for track, minimum sea level pressure, and maximum wind speed. For Typhoon Megi, the error reduction appeared to be more pronounced for track than for minimum sea level pressure and maximum wind. The sensitivity experiments with 6.7-μm H₂O band were also conducted. The 6.7-μm band also had some positive impact on the track and minimum sea level pressure. The improvement for maximum wind speed forecasts from the 6.7-μm band was evident, especially for the first 42 h. The 15-μm band consistently improved specific humidity forecast and we found improved temperature and horizontal wind forecast on most levels. Generally, assimilating the 6.7-μm band degraded forecasts, likely indicating the inefficiency of the current WRF model and/or data assimilation system for assimilating these channels. IASI radiance assimilation apparently improved depiction of dynamic and thermodynamic vortex structures.     

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 Regularized WSM6 Microphysical Scheme and Its Validation in WRF 4D-Var

A cold cloud assimilation scheme was developed that fully considers the water substances, i.e., water vapor, cloud water, rain, ice, snow, and graupel, based on the single-moment WSM6 microphysical scheme and four-dimensional variational(4D-Var) data assimilation in the Weather Research and Forecasting data assimilation(WRFDA) system. The verification of the regularized WSM6 and its tangent linearity model(TLM) and adjoint mode model(ADM) was proven successful. Two groups of single observation a...     

背景误差协方差变量平衡特征及其对台风同化和预报的影响

构造合理的背景场误差协方差是做好资料同化的关键。分析了背景误差协方差中变量相关关系在台风季节和非台风季节隐含的不同动力平衡特征,并讨论其对台风同化和预报的影响。分析发现,与非台风季节相比,在台风季节温度与非平衡速度势具有更强的动力相关性,拟相对湿度与其他控制变量的相关性也更显著。这些动力相关性在背景场误差中协方差的引入,将在同化分析过程中使得观测信息可以合理地对同化分析场产生影响。台风循环同化和预报的结果验证了对变量平衡特征的分析:背景误差协方差中新平衡关系的建立,对同化和预报有较大的正面影响,尤其是相对湿度和其他控制变量相关的建立,明显改善了台风路径、强度和降水的预报效果。      

台风数值预报中受云影响微波卫星资料的同化试验

目前, 数值预报中卫星资料的应用主要只是针对晴空条件, 大量受云和降水影响的卫星资料被丢弃不加以使用。但是, 云雨区观测往往包含有大量与天气系统发生发展密切相关的大气信息, 对这部分资料的同化应用由此成为当前研究的一个重要问题。在快速辐射传输模式中云雨粒子辐射效应的考虑还有待于进一步完善情况下, 云雨区卫星资料的应用通常是采用云检测方案对观测受云影响的严重程度进行判识并决定使用的取舍。以0604号热带气旋Bilis作为研究个例, 该文设计了一组受云影响微波卫星资料不同云检测方案和通道选择的应用试验。对AMSU-A资料, 云检测方案包括散射因子、降水概率和小雨检测3种, AMSU-B卫星资料的云检测方法选用了通道2亮温模拟观测误差和Bennartz散射因子。在对进入分析系统卫星资料与天气系统的配置关系、卫星模拟与实际观测偏差特征的统计以及对初始分析影响研究的基础上, 探讨了它们对台风不同阶段数值预报效果的影响。     

ASSIMILATION OF REAL OBSERVATIONAL DATA WITH THE GSI-HYBRID DATA ASSIMILATION SYSTEM TO IMPROVE TYPHOON FORECAST

A hybrid GSI (Grid-point Statistical Interpolation)-ETKF (Ensemble Transform Kalman Filter) data assimilation system has been recently developed for the WRF (Weather Research and Forecasting) model and tested with simulated observations for tropical cyclone (TC) forecast. This system is based on the existing GSI but with ensemble background information incorporated. As a follow-up, this work extends the new system to assimilate real observations to further understand the hybrid scheme. As a first effort to explore the system with real observations, relatively coarse grid resolution (27 km) is used. A case study of typhoon Muifa (2011) is performed to assimilate real observations including conventional in-situ and satellite data. The hybrid system with flow-dependent ensemble covariance shows significant improvements with respect to track forecast compared to the standard GSI system which in theory is three dimensional variational analysis (3DVAR). By comparing the analyses, analysis increments and forecasts, the hybrid system is found to be potentially able to recognize the existence of TC vortex, adjust its position systematically, better describe the asymmetric structure of typhoon Muifa and maintain the dynamic and thermodynamic balance in typhoon initial field. In addition, a cold-start hybrid approach by using the global ensembles to provide flow-dependent error is tested and similar results are revealed with those from cycled GSI-ETKF approach.     

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.     

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 ...