Insights into the Microwave Instruments Onboard the Fengyun 3DSatellite: Data Quality and Assimilation in theMet Office NWP System

正1Met Office, Exeter EX1 3PB, UK2National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China     

AMDAR资料在北京数值预报系统中的同化应用

该文针对北京市气象局业务快速更新循环同化预报系统(BJ-RUC),通过对有无飞机观测资料参加同化的预报试验客观要素预报均方根误差和降水量TS评分的对比分析,探讨了飞机观测资料对短期数值天气预报的影响。结果表明:飞机观测资料的同化对于前9 h预报时效内的高空风和温度预报有明显的正面影响。其中,对风预报的正面影响集中在925~250 hPa高度上;而对温度预报的正面影响主要体现在850~400 hPa之间的各层内。在快速更新循环的暖启动模式下,飞机观测资料同化比冷启动模式下带给预报结果更明显的正面贡献。飞机观测资料参加同化对于降水预报技巧的提高也有正面效应,对24 h和12 h累积降水量TS评分以及12~18 h和18~24 h时段内的6 h累积降水TS评分有明显提高,提高的最大幅度达50%,并对相应阈值和时段内无飞机观测资料参加同化的试验中雨区偏大现象有改善。分析增量分布特征与同化带来的风温要素3 h预报改进的垂直特征基本对应,表明飞机观测资料参加同化对初始场中风场和温度场质量的改进。     

All-sky Data Assimilation of MWTS-2 and MWHS-2 in the Met Office Global NWP System.

Microwave radiances from passive polar-orbiting radiometers have been, until recently, assimilated in the Met Office global numerical weather prediction system after the scenes significantly affected by atmospheric scattering are discarded.Recent system upgrades have seen the introduction of a scattering-permitting observation operator and the development of a variable observation error using both liquid and ice water paths as proxies of scattering-induced bias. Applied to the Fengyun 3 Microwave Temperature Sounder 2(MWTS-2) and the Microwave Humidity Sounder 2(MWHS-2), this methodology increases the data usage by up to 8% at 183 GHz. It also allows for the investigation into the assimilation of MWHS-2 118 GHz channels, sensitive to temperature and lower tropospheric humidity, but whose large sensitivity to ice cloud have prevented their use thus far. While the impact on the forecast is mostly neutral with small but significant shortrange improvements, 0.3% in terms of root mean square error, for southern winds and low-level temperature, balanced by 0.2% degradations of short-range northern and tropical low-level temperature, benefits are observed in the background fit of independent instruments used in the system. The lower tropospheric temperature sounding Infrared Atmospheric Sounding Interferometer(IASI) channels see a reduction of the standard deviation in the background departure of up to 1.2%. The Advanced Microwave Sounding Unit A(AMSU-A) stratospheric sounding channels improve by up to 0.5% and the Microwave Humidity Sounder(MHS) humidity sounding channels improve by up to 0.4%.     

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.     

极轨卫星高层通道在GRAPES同化系统中的应用

针对GRAPES(Global/Regional Assimilation and Prediction System)模式三维变分系统高层背景场温湿廓线外推方案的局限性,提出以气候垂直廓线重新构造高层温湿垂直结构,以减小外推方案的偏差。首先采用一维变分同化系统,展开模拟实验:分析目前模式中使用的外推方案误差及其对反演结果的影响,利用高层大气气候廓线构造垂直结构并分析同化偏差。最后,运用GRAPES全球分析预报系统进行同化实验并分析改进程度。结果显示:模拟研究表明采用高层背景场温湿廓线外推方案与实际观测相比最大偏差在1 h Pa附近可达数十度以上,不仅影响平流层,而且对对流层也有影响;用气候温度数据修正GRAPES高层温度数据,可以减少50%以上的偏差,证明了用气候值高层数据优化现行GRAPES模式中同化系统高层插值方案的可行性。全球GRAPES三维变分同化试验结果显示,改进方案不仅显著的改善平流层分析质量,对对流层中高层也有改进。     

资料同化方法研究进展

数值天气预报模式的不断完善和大气观测探测资料（特别是卫星、雷达等非常规探测资料）的大量涌现,推动着资料同化方法的逐步发展.文章主要回顾了资料同化方法研究的发展过程、目前的应用现状以及对未来同化方法的展望.随着人们对资料同化含义的深入理解,对于资料同化的研究由初始的探索阶段逐步发展到以经验性为主的同化方法,主要包括SCM和nudging;统计方法的引入,成为资料同化方法研究发展道路上具有重要意义的一个里程碑,从而出现了多元统计插值同化,比如OI,3D-Var以及PSAS;针对背景误差协方差固定不变与实际情况的差异,考虑时间维的四维资料同化方法成为目前国际上较为主流的同化研究方法,其中以4D-Var和Kalman滤波为代表;随着计算机技术的进步,更加合理的四维资料同化方法将会成为未来业务预报中主要的资料同化方法.     

Parameterized Forward Operators for Simulation and Assimilation of Polarimetric Radar Data with Numerical Weather Predictions

Many weather radar networks in the world have now provided polarimetric radar data(PRD)that have the potential to improve our understanding of cloud and precipitation microphysics,and numerical weather prediction(NWP).To realize this potential,an accurate and efficient set of polarimetric observation operators are needed to simulate and assimilate the PRD with an NWP model for an accurate analysis of the model state variables.For this purpose,a set of parameterized observation operators are developed to simulate and assimilate polarimetric radar data from NWP model-predicted hydrometeor mixing ratios and number concentrations of rain,snow,hail,and graupel.The polarimetric radar variables are calculated based on the T-matrix calculation of wave scattering and integrations of the scattering weighted by the particle size distribution.The calculated polarimetric variables are then fitted to simple functions of water content and volumeweighted mean diameter of the hydrometeor particle size distribution.The parameterized PRD operators are applied to an ideal case and a real case predicted by the Weather Research and Forecasting(WRF)model to have simulated PRD,which are compared with existing operators and real observations to show their validity and applicability.The new PRD operators use less than one percent of the computing time of the old operators to complete the same simulations,making it efficient in PRD simulation and assimilation usage.     

TAMDAR Observation Assimilation in WRF 3D-Var and Its Impact on Hurricane Ike (2008) Forecast

This study evaluates the impact of atmospheric observations from the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) observing system on numerical weather prediction of hurricane Ike (2008) using three-dimensional data assimilation system for the Weather Research and Forecast (WRF) model (WRF 3D-Var). The TAMDAR data assimilation capability is added to WRF 3D-Var by incorporating the TAMDAR observation operator and corresponding observation processing procedure. Two 6-h cycling data assimilation and forecast experiments are conducted. Track and intensity forecasts are verified against the best track data from the National Hurricane Center. The results show that, on average, assimilating TAMDAR observations has a positive impact on the forecasts of hurricane Ike. The TAMDAR data assimilation reduces the track errors by about 30 km for 72-h forecasts. Improvements in intensity forecasts are also seen after four 6-h data assimilation cycles. Diagnostics show that assimilation of TAMDAR data improves subtropical ridge and steering flow in regions along Ike’s track, resulting in better forecasts.     

System of Multigrid Nonlinear Least-squares Four-dimensional Variational Data Assimilation for Numerical Weather Prediction (SNAP): System Formulation and Preliminary Evaluation

A new forecasting system—the System of Multigrid Nonlinear Least-squares Four-dimensional Variational(NLS-4DVar) Data Assimilation for Numerical Weather Prediction(SNAP)—was established by building upon the multigrid NLS-4DVar data assimilation scheme, the operational Gridpoint Statistical Interpolation(GSI)-based data-processing and observation operators, and the widely used Weather Research and Forecasting numerical model. Drawing upon lessons learned from the superiority of the operational GS...     

Assimilation of GPM Microwave Imager Radiance for Track Prediction of Typhoon Cases with the WRF Hybrid En3DVAR System

The impact of assimilating radiance data from the advanced satellite sensor GMI(GPM microwave imager) for typhoon analyses and forecasts was investigated using both a three-dimensional variational(3DVAR) and a hybrid ensemble-3DVAR method. The interface of assimilating the radiance for the sensor GMI was established in the Weather Research and Forecasting(WRF) model. The GMI radiance data are assimilated for Typhoon Matmo(2014), Typhoon Chan-hom(2015), Typhoon Meranti(2016), and Typhoon Mangkhut(2018) in the Pacific before their landing. The results show that after assimilating the GMI radiance data under clear sky condition with the 3DVAR method, the wind,temperature, and humidity fields are effectively adjusted, leading to improved forecast skills of the typhoon track with GMI radiance assimilation. The hybrid DA method is able to further adjust the location of the typhoon systematically. The improvement of the track forecast is even more obvious for later forecast periods. In addition, water vapor and hydrometeors are enhanced to some extent, especially with the hybrid method.     

Wind Speed and Altitude Dependent AMDAR Observational Error and Its Impacts on Data Assimilation and Forecasting

Aircraft Meteorological Data Relay (AMDAR) observations have been widely used in numerical weather prediction (NWP) because of its high spatiotemporal resolution. The observational error of AMDAR is influenced by aircraft flight altitude and atmospheric condition. In this study, the wind speed and altitude dependent observational error of AMDAR is estimated. The statistical results show that the temperature and the observational error in wind speeds slightly decrease as altitude increases, and the observational error in wind speed increases as wind speed increases. Pseudo single AMDAR observation assimilation tests demonstrate that the wind speed and altitude dependent observational error can provide more reasonable analysis increment. Furthermore, to assess the performance of wind speed and altitude dependent observational error on data assimilation and forecasting, two-month 3-hourly cycling data assimilation and forecast experiments based on the Weather Research and Forecasting Model (WRF) and its Data Assimilation system (WRFDA) are performed for the period during 1 September-31 October, 2017. The results of the two-month 3-hourly cycling experiments indicate that new observational error improves analysis and forecast of wind field and geo-potential height, and has slight improvements on temperature. The Fractions Skill Score (FSS) of the 6-h accumulated precipitation shows that new wind speed and altitude dependent observational error leads to better precipitation forecast skill than the default observational error in the WRFDA does.     

GRAPES全球三维变分同化业务系统性能

近年来,GRAPES全球三维变分同化系统分析性能和稳定性有了长足进步。该文简要介绍了近两年GRAPES全球:三维变分同化技术的发展与改进情况,包括同化框架技术、资料同化应用技术与系统稳定性等方面。分析诊断了两年的同化循环试验结果,以探空资料作为参考,对ERA-Interim再分析场、NCEP FNL分析场和GRAPES全球三维变分分析场的统计特征进行了比较;以ERA-Interim再分析场作为参考,对NCEP FNL分析场、T639分析场和GRAPES全球三维变分分析场进行比较。结果表明:GRAPES分析场的质量明显优于T639分析场,性能上达到了业务化的要求,但相比NCEP FNL分析场还有一定差距,特别是对流层内湿度分析场的误差还比较大。     

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...     

Developments of the Three-Dimensional Variational Data Assimilation System for the Nonhydrostatic GRAPES

Based on the original GRAPES (Global/Regional Assimilation and PrEdiction System) 3DVAR (p3DAR), which is defined on isobaric surface, a new three-dimensional variational data assimilation system (m3DVAR) is constructed and used exclusively with the nonhydrostatic GRAPES model in order to reduce the errors caused by spatial interpolation and variable transformation, and to improve the quality of the initial value for operational weather forecasts. Analytical variables of the m3DVAR are fully consistent with predictands of the GRADES model in terms of spatial staggering and physical definition. A different vertical coordinate and the nonhydrostatic condition are taken into account, and a new scheme for solving the dynamical constraint equations is designed for the m3DVAR. To deal with the difficulties in solving the nonlinear balance equation at σ levels, dynamical balance constraints between mass and wind fields are reformulated, and an effective mathematical scheme is implemented under the terrain-following coordinate. Meanwhile, new observation operators are developed for routine observational data, and the background error covariance is also obtained. Currently, the m3DVAR system can assimilate all routine observational data. Multi-variable idealized experiments with single point observations are performed to validate the m3DVAR system. The results show that the system can describe correctly the multi-variable analysis and the relationship of the physical constraints. The difference of innovation and the analysis residual for ∏ also show that the analysis error of the m3DVAR is smaller than that of the p3DVAR. The Ts scores of precipitation forecasts in August 2006 indicate that the m3DVAR system provides reduced errors in the model initial value than the p3DVAR system. Therefore, the m3DVAR system can improve the analysis quality and initial value for numerical weather predictions.     

数值天气预报中卫星资料同化应用现状和发展

卫星资料已大量应用于数值天气预报,占据了所用观测资料的主体并对数值天气预报效果的改善具有明显的作用。目前卫星资料的同化应用一方面在努力解决受地表辐射、云和降水影响的卫星观测资料的同化问题,以充分利用现有卫星资料并发挥其效能,同时发展适应伴随全球观测系统建立而带来大数量和多种类新类型卫星资料的同化应用。文章介绍了为满足卫星资料在数值天气预报中同化应用现状与发展而建立的两个卫星资料同化研究中心(JCSDA:Joint Center of Satellite Data Assimilation和NWP SAF:Satellite Applications Facility for Numerical Weather Prediction)的基本情况,并简要讨论我国数值天气预报中卫星资料同化应用。     

卫星资料变分同化在一次中尺度强暴雨模拟中的应用

利用ATOVS资料和常规观测资料, 采用GRAPES 3D-Var同化系统和中尺度数值模式MM5设计了仅同化常规观测资料的NOATOVS试验和同化常规观测资料及ATOVS辐射率资料的ATOVS试验, 对2004年6月22—24日长江中下游和西南地区东部的特大暴雨进行了分析和模拟。结果表明:直接同化ATOVS辐射率资料获得的分析场可以有效改进对流层温、湿场分布, 对风场也有一定的影响。对比试验结果表明:ATOVS试验可以较好地模拟出暴雨天气形势、主要影响系统, 对降雨的落区、强度也有较好的反映, 模拟的局地暴雨强度与实际降雨量基本一致, 同化卫星资料的改善效果较为明显。即同化ATOVS资料对于改进中尺度局地暴雨过程模拟效果是可行的。     

A Precipitation Detection Method for MWTS-Ⅱ Radiance Assimilation in Typhoon Simulation

FY-3C Microwave Temperature Sounder Ⅱ(MWTS-Ⅱ) lacks observations at 23.8 GHz, 31 GHz and 89 GHz,making it difficult to remove the data contaminated by precipitation in assimilation. In this paper, a fast forward operator based on the Community Radiative Transfer Model(CRTM) was used to analyze the relationship between the observation minus background simulation(O-B) and the cloud fractions in different MWTS-Ⅱ channels. In addition,based on the community Gridpoint Statistical Interpolation(GSI) system, the radiation brightness temperature of the MWTS-Ⅱ was assimilated in the regional Numerical Weather Prediction(NWP) model. In the process of assimilation,Visible and Infrared Radiometer(VIRR) cloud detection products were matched to MWTS-Ⅱ pixels for precipitation detection. For typhoon No. 18 in 2014, impact tests of MWTS-Ⅱ data assimilation was carried out. The results show that,though the bias observation minus analysis(O-A) of assimilated data can be reduced by quality control only with | O-B| 3 K; however, the O-A becomes much smaller while the precipitation detection is performed with F_(virr) 0.9(VIRR cloud fraction threshold of 0.9). Besides, the change of the environmental field around the typhoon is more conducive to make the simulated track closer to the observation. The 72-hour typhoon track simulation error also shows that, after the precipitation detection, the error of simulated typhoon track is significantly reduced, which reflects the validity of a precipitation detection method based on a double criterion of | O-B | 3 K and F_(virr) 0.9.     

Impact of Assimilation of Radiosonde and UAV Observations from the Southern Ocean in the Polar WRF Model

Weather forecasting in the Southern Ocean and Antarctica is a challenge above all due to the rarity of observations to be assimilated in numerical weather prediction(NWP) models. As observations are expensive and logistically challenging,it is important to evaluate the benefit that additional observations could bring to NWP. Atmospheric soundings applying unmanned aerial vehicles(UAVs) have a large potential to supplement conventional radiosonde sounding observations.Here, we applied UAV and rad...     

一种控制变量循环扰动和多参数化方案的混合同化方法

敏感性试验表明集合变换卡尔曼滤波(Ensemble Transform Kalman Filter,ETKF)方法在混合(Hybrid)同化过程中易受观测资料数量变化的影响而产生较大程度的协方差震荡,从而可能导致系统不稳定。为设计一种简便、稳定的Hybrid同化系统,构建了一种基于物理控制变量扰动及多物理参数化方案的Hybrid同化及预报系统。本系统随着循环的进行,不断对Hybrid同化分析场进行控制变量扰动得到集合成员初始场,并且对各集合成员采用不同物理参数化方案以更合理地表征背景场的误差特征。连续10 d的循环同化及预报试验表明,本文同化方案效果明显优于三维变分方案,动力场的整体同化和预报效果与ETKF方案基本相当。本方案相比于ETKF方法不受观测波动影响,在没有经任何参数调试情况下,取得了良好同化和预报效果,为Hybrid同化的便捷运行提供了一种稳定可靠的手段。     

新一代数值预报系统GRAPES研究进展

中国气象科学研究院 (灾害天气国家重点实验室) 自2000年起, 先后在科技部“973”重大基础项目“我国重大天气灾害形成机理和预测理论研究”和“十五”重点攻关项目“中国气象数值预报系统技术创新研究”支持下, 主持承担了中国气象局新一代全球/区域多尺度通用同化与数值预报系统GRAPES (Global/Regional Assimilation and PrEdiction System) 的研究开发, 围绕着资料同化、模式动力框架、物理过程、大型软件工程等核心技术开展了自主创新研究, 取得了非静力中尺度模式、三维变分资料同化、标准化、模块化、并行化模式程序软件等方面的突出成果, 部分成果已在业务上得到了应用, 显示了良好的技术性能和业务发展潜力。GRAPES系统是完全依靠中国科学家的力量自主研究发展的、先进的新一代数值预报系统。该文简要介绍GRAPES的研究内容、主要研究进展和初步应用, 以及未来发展的初步计划。