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.     

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.     

Evaluating Soil Moisture Predictions Based on Ensemble Kalman Filter and SiB2 Model

Soil moisture is an important variable in the fields of hydrology, meteorology, and agriculture, and has been used for numerous applications and forecasts. Accurate soil moisture predictions on both a large scale and local scale for different soil depths are needed. In this study, a soil moisture assimilation and prediction based on the Ensemble Kalman Filter(EnKF) and Simple Biosphere Model(SiB2) have been performed in Meilin watershed, eastern China, to evaluate the initial state values with different assimilation frequencies and precipitation influences on soil moisture predictions. The assimilated results at the end of the assimilation period with different assimilation frequencies were set to be the initial values for the prediction period. The measured precipitation, randomly generated precipitation,and zero precipitation were used to force the land surface model in the prediction period. Ten cases were considered based on the initial value and precipitation. The results indicate that, for the summer prediction period with the deeper water table depth, the assimilation results with different assimilation frequencies influence soil moisture predictions significantly. The higher assimilation frequency gives better soil moisture predictions for a long lead-time. The soil moisture predictions are affected by precipitation within the prediction period. For a short lead-time, the soil moisture predictions are better for the case with precipitation, but for a long lead-time, they are better without precipitation. For the winter prediction period with a lower water table depth, there are better soil moisture predictions for the whole prediction period. Unlike the summer prediction period, the soil moisture predictions of winter prediction period are not significantly influenced by precipitation. Overall, it is shown that soil moisture assimilations improve its predictions.     

A Numerical Investigation on Microphysical Properties of Clouds and Precipitation over the Tibetan Plateau in Summer 2014

In order to improve our understanding of microphysical properties of clouds and precipitation over the Tibetan Plateau (TP), six cloud and precipitation processes with different intensities during the Third Tibetan Plateau Atmospheric Science Experiment (TIPEX-Ⅲ) from 3 July to 25 July 2014 in Naqu region of the TP are investigated by using the high-resolution mesoscale Weather Research and Forecasting (WRF) model. The results show unique properties of summertime clouds and precipitation processes over the TP. The initiation process of clouds is closely associated with strong solar radiative heating in the daytime, and summertime clouds and precipitation show an obvious diurnal variation. Generally, convective clouds would transform into stratiform clouds with an obvious bright band and often produce strong rainfall in midnight. The maximum cloud top can reach more than 15 km above sea level and the velocity of updraft ranges from 10 to 40 m s-1. The simulations show high amount of supercooled water content primarily located between 0 and -20℃ layer in all the six cases. Ice crystals mainly form above the level of -20℃ and even appear above the level of -40℃ within strong convective clouds. Rainwater mostly appears below the melting layer, indicating that its formation mainly depends on the melting process of precipitable ice particles. Snow and graupel particles have the characteristics of high content and deep vertical distribution, showing that the ice phase process is very active in the development of clouds and precipitation. The conversion and formation of hydrometeors and precipitation over the plateau exhibit obvious characteristics. Surface precipitation is mainly formed by the melting of graupel particles. Although the warm cloud microphysical process has less direct contribution to the formation of surface precipitation, it is important for the formation of supercooled raindrops, which are essential for the formation of graupel embryos through heterogeneous freezing process. The growth of graupel particles mainly relies on the riming process with supercooled cloud water and aggregation of snow particles.     

ANALYSING THE CLOUD MICRO- AND MACRO-PHYSICAL PROPERTIES OF THE CYCLONE EYE WALL AND ITS SURROUNDING SPIRAL CLOUD BANDS BASED ON CLOUDSAT AND TRMM DATA

In this study, the micro- and macro-physical properties, thermal structure and precipitation characteristics of cyclone eye walls and their surrounding spiral clouds were analysed with CloudSat and TRMM data for five tropical cyclones (TCs) in 2013. The results show that the ice-phase clouds of a mature TC are mainly above 5 km. With increasing altitude, the cloud droplet effective radius decreases, and the particle number concentration increases. Ice water content first increases and then decreases with increasing height. In the eye area, in addition to the well-known warm-core area, another warm core is also apparent around the eye at a height of 8 to 15 km. The horizontal distribution of precipitation is characterized by large-scale stratiform precipitation mixed with independent convective precipitation. The height of precipitation is mostly below 7.5 km, and the heavy rain is mainly below 5 km. When the peripheral convective clouds are strong enough, ice particles would be generated, thus providing conditions that are favourable for the formation of precipitation below.     

EFFECTS OF STRATIFORM CLOUD ON THE DEVELOPMENT OF CUMULUS CLOUD AND ITS PRECIPITATION

Based on the two-dimensional slab-symmetric model of cumulus clouds established by the authors,thedevelopment of the cumulus cloud and its precipitation in environments with and without the stratiform cloudpresent has been simulated numerically in almost the same atmospheric stratification.Results show that thepresence of the stratiform cloud has a significant effect on the development of the cumulus cloud and theincreae of its precipitation.The rainfall may increase by scveral to tens of times.It is believed that theconvective-stratiform mixed cloud system may be important for producing heavy to torrential rain.This isin good agreement with what has been observed in the Meiyu frontal cloud system in recent investigations     

Effect of Aerosol Particles on Orographic Clouds:Sensitivity to Autoconversion Schemes

Aerosol particles can serve as cloud condensation nuclei(CCN)to influence orographic clouds.Autoconversion,which describes the initial formation of raindrops from the collision of cloud droplets,is an important process for aerosol-cloud-precipitation systems.In this study,seven autoconversion schemes are used to investigate the impact of CCN on orographic warm-phase clouds.As the initial cloud droplet concentration is increased from 100 cm^-3to 1000 cm^-3(to represent an increase in CCN),the cloud water increases and then the rainwater is suppressed due to a decrease in the autoconversion rate,leading to a spatial shift in surface precipitation.Intercomparison of the results from the autoconversion schemes show that the sensitivity of cloud water,rainwater,and surface precipitation to a change in the concentration of CCN is different from scheme to scheme.In particular,the decrease in orographic precipitation due to increasing CCN is found to range from-87%to-10%depending on the autoconversion scheme.Moreover,the surface precipitation distribution also changes significantly by scheme or CCN concentration,and the increase in the spillover(ratio of precipitation on the leeward side to total precipitation)induced by increased CCN ranges from 10%to 55%under different autoconversion schemes.The simulations suggest that autoconversion parameterization schemes should not be ignored in the interaction of aerosol and orographic cloud.     

20 TO 30-DAY AND 30 TO 60-DAY OSCILLATIONS IN ASSIMILATED GLOBAL DATASETS USING TRMM RAINFALL OBSERVATIONS

The influences of Tropical Rainfall Measuring Mission (TRMM) precipitation products on the structure and underlying physics of intraseasonal oscillation (ISO) are investigated with the U.S.National Aeronautics and Space Administration Goddard Earth Observing System model version 3 (GEOS-3) data assimilation system (DAS).The strong ISO phase in the 1998 summer is apparently located in the Asian monsoon region and the east equatorial Pacific region.The eastward propagation is a dominant feature for the tropical ISO at 20 to 30-day oscillation while the northeastward propagation is the salient ISO at 30 to 60-day oscillation over the 10°N to 25°N belt region.It appears that the Kelvin wave structure is for the tropical 20 to 30-day oscillation.The tropical 30 to 60-day oscillation has the characteristics of the Kelvin-Rossby wave.The impact of satellite-derived precipitation (and its associated latent heating) on the ISO intensity is limited in the GEOS-3 assimilation system.However,its impact on the ISO spatial structures is obvious.Overall,the results demonstrate a better eastward propagation and a northward propagation of ISO with the TRMM precipitation simulation,indicating that latent heating is very important in exciting the equatorial ISO.     

Evaluation of radar and automatic weather station data assimilation for a heavy rainfall event in southern China

To improve the accuracy of short-term(0–12 h) forecasts of severe weather in southern China, a real-time storm-scale forecasting system, the Hourly Assimilation and Prediction System(HAPS), has been implemented in Shenzhen, China. The forecasting system is characterized by combining the Advanced Research Weather Research and Forecasting(WRF-ARW)model and the Advanced Regional Prediction System(ARPS) three-dimensional variational data assimilation(3DVAR) package. It is capable of assimilating radar reflectivity and radial velocity data from multiple Doppler radars as well as surface automatic weather station(AWS) data. Experiments are designed to evaluate the impacts of data assimilation on quantitative precipitation forecasting(QPF) by studying a heavy rainfall event in southern China. The forecasts from these experiments are verified against radar, surface, and precipitation observations. Comparison of echo structure and accumulated precipitation suggests that radar data assimilation is useful in improving the short-term forecast by capturing the location and orientation of the band of accumulated rainfall. The assimilation of radar data improves the short-term precipitation forecast skill by up to9 hours by producing more convection. The slight but generally positive impact that surface AWS data has on the forecast of near-surface variables can last up to 6–9 hours. The assimilation of AWS observations alone has some benefit for improving the Fractions Skill Score(FSS) and bias scores; when radar data are assimilated, the additional AWS data may increase the degree of rainfall overprediction.     

不同 AMDAR资料同化时间窗对台风“摩羯”预报影响研究

2018年第14号台风“摩羯”对山东造成了大范围暴雨和大风天气,基于WRF（Weather Research and Forecasting）模式及其Hybrid-3DVAR混合同化预报系统,对Hybrid-3DVAR不同集合协方差比例和不同航空气象数据转发（aircraft meteorological data relay,以下简称AMDAR）资料同化时间窗对台风“摩羯”预报的影响进行了数值研究。结果表明：加大集合协方差比例对台风“摩羯”路径预报有较大影响和改进;当全部取来自集合体的流依赖误差协方差时,预报的台风路径最好,降水预报也最接近实况;AMDAR资料同化对于台风路径和降水预报也有正的改进作用,但加大集合协方差比例到100%时对台风路径预报影响更大;不同资料同化时间窗会影响同化的AMDAR资料数量,从而影响台风降水精细化预报;45 min同化时间窗的要素预报误差最小,对台风造成的强降水精细特征预报最接近实况;不同资料同化时间窗主要影响台风降水预报落区分布,对台风路径预报影响相对较小。     

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.     

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.     

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 ...     

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     

AMSR2辐射率资料同化对台风“山神”分析和预报的影响研究

在WRFDA-3DVar（Weather Research and Forecasting model's 3-dimensional variational data assimilation）的框架下,添加了新的探测器AMSR2（Advanced Microwave Scanning Radiometer 2）微波辐射率资料的同化模块,实现了AMSR2辐射率资料在中小尺度同化系统中的有效使用。台风"山神"（Son-Tinh）直接同化AMSR2资料的个例试验结果表明,AMSR2资料可以很好的探测出台风的形态,并且与没有同化该资料的控制试验相比,同化AMSR2辐射率资料可以有效提高模式分析场的质量,进一步提高了台风中心气压,最大风速和台风路径的预报。     

台风“利奇马”(1909)影响期间上海强降水成因诊断分析

2019年第9号台风“利奇马”(1909)在8月9—11日影响上海期间造成了严重的风雨影响。基于ERA5逐小时再分析资料和上海区域高时空分辨率的地面观测资料,采用非地转Q矢量分解等方法诊断分析了此次强降水成因。结果表明,台风“利奇马”在上海造成的强降水主要来自台风东侧的螺旋雨带。强降水区东南西北各边界的相对湿度在垂直方向上随时间的变化差异明显,水汽的垂直输送和大气整层水汽含量在台风强降水中起重要作用。进一步利用非地转Q矢量分解方法揭示了东边界的大尺度和北边界的中尺度系统在强降水中起主要作用。台风登陆时呈现出整层大气被抬升之后最大强迫中心由高层向低层下传的态势,且此下传效应中尺度比大尺度强迫更加明显,从而有利于强降水的发生。     

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。     

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.