An Examination of the Predictability of Tropical Cyclone Genesis in High-Resolution Coupled Models with Dynamically Downscaled Coupled Data Assimilation Initialization

Predicting tropical cyclone(TC)genesis is of great societal importance but scientifically challenging.It requires fineresolution coupled models that properly represent air−sea interactions in the atmospheric responses to local warm sea surface temperatures and feedbacks,with aid from coherent coupled initialization.This study uses three sets of highresolution regional coupled models(RCMs)covering the Asia−Pacific(AP)region initialized with local observations and dynamically downscaled coupled data assimilation to evaluate the predictability of TC genesis in the West Pacific.The APRCMs consist of three sets of high-resolution configurations of the Weather Research and Forecasting−Regional Ocean Model System(WRF-ROMS):27-km WRF with 9-km ROMS,and 9-km WRF with 3-km ROMS.In this study,a 9-km WRF with 9-km ROMS coupled model system is also used in a case test for the predictability of TC genesis.Since the local sea surface temperatures and wind shear conditions that favor TC formation are better resolved,the enhanced-resolution coupled model tends to improve the predictability of TC genesis,which could be further improved by improving planetary boundary layer physics,thus resolving better air−sea and air−land interactions.

A Comparison Study of Tropical Pacific Ocean State Estimation:Low-Resolution Assimilation vs.High-Resolution Simulation

A comparison study is performed to contrast the improvements in the tropical Pacific oceanic state of a low-resolution model respectively via data assimilation and by an increase in horizontal resolution. A low resolution model (LR) (1°lat by 2°lon) and a high-resolution model (HR) (0.5°lat by 0.5°lon) are employed for the comparison. The authors perform 20-yr numerical experiments and analyze the annual mean fields of temperature and salinity. The results indicate that the low-resolution model with data assimilation behaves better than the high-resolution model in the estimation of ocean large-scale features. From 1990 to 2000, the average of HR's RMSE (root-mean-square error) relative to independent Tropical Atmosphere Ocean project (TAO) mooring data at randomly selected points is 0.97℃ compared to a RMSE of 0.56℃ for LR with temperature assimilation. Moreover, the LR with data assimilation is more frugal in computation. Although there is room to improve the high-resolution model, the low-resolution model with data assimilation may be an advisable choice in achieving a more realistic large-scale state of the ocean at the limited level of information provided by the current observational system.

Effect of Meteorological Data Assimilation on Regional Air Quality Forecasts over the Korean Peninsula

The Weather Research and Forecasting model coupled with Chemistry(WRF-Chem),a type of online coupled chemistry-meteorology model(CCMM),considers the interaction between air quality and meteorology to improve air quality forecasting.Meteorological data assimilation(DA)can be used to reduce uncertainty in meteorological field,which is one factor causing prediction uncertainty in the CCMM.In this study,WRF-Chem and three-dimensional variational DA were used to examine the impact of meteorological DA on air quality and meteorological forecasts over the Korean Peninsula.The nesting model domains were configured over East Asia(outer domain)and the Korean Peninsula(inner domain).Three experiments were conducted by using different DA domains to determine the optimal model domain for the meteorological DA.When the meteorological DA was performed in the outer domain or both the outer and inner domains,the root-mean-square error(RMSE),bias of the predicted particulate matter(PM)concentrations,and the RMSE of predicted meteorological variables against the observations were smaller than those in the experiment where the meteorological DA was performed only in the inner domain.This indicates that the improvement of the synoptic meteorological fields by DA in the outer domain enhanced the meteorological initial and boundary conditions for the inner domain,subsequently improving air quality and meteorological predictions.Compared to the experiment without meteorological DA,the RMSE and bias of the meteorological and PM variables were smaller in the experiments with DA.The effect of meteorological DA on the improvement of PM predictions lasted for approximately 58-66 h,depending on the case.Therefore,the uncertainty reduction in the meteorological initial condition by the meteorological DA contributed to a reduction of the forecast errors of both meteorology and air quality.

Data Assimilation Method Based on the Constraints of Confidence Region

The ensemble Kalman filter （EnKF） is a distinguished data assimilation method that is widely used and studied in various fields including methodology and oceanography. However, due to the limited sample size or imprecise dynamics model, it is usually easy for the forecast error variance to be underestimated, which further leads to the phenomenon of filter divergence. Additionally, the assimilation results of the initial stage are poor if the initial condition settings differ greatly from the true initial state. To address these problems, the variance inflation procedure is usually adopted. In this paper, we propose a new method based on the constraints of a confidence region constructed by the observations, called EnCR, to estimate the inflation parameter of the forecast error variance of the EnKF method. In the new method, the state estimate is more robust to both the inaccurate forecast models and initial condition settings. The new method is compared with other adaptive data assimilation methods in the Lorenz-63 and Lorenz-96 models under various model parameter settings. The simulation results show that the new method performs better than the competing methods.

A high-resolution Asia-Pacific regional coupled prediction system with dynamically downscaling coupled data assimilation

A regional coupled prediction system for the Asia-Pacific(AP-RCP)(38°E-180°,20°S-60°N) area has been established.The AP-RCP system consists of WRF-ROMS(Weather Research and Forecast,and Regional Ocean Model System) coupled models combined with local observational information through dynamically downscaling coupled data assimilation(CDA).The system generates 18-day forecasts for the atmosphere and ocean environment on a daily quasi-operational schedule at Pilot National Laboratory for Marine Science and Technology(Qingdao)(QNLM),consisting of 2 different-resolution coupled models:27 km WRF coupled with 9 km ROMS,9 km WRF coupled with 3 km ROMS,while a version of 3 km WRF coupled with 3 km ROMS is in a test mode.This study is a first step to evaluate the impact of high-resolution coupled model with dynamically downscaling CDA on the extended-range predictions,focusing on forecasts of typhoon onset,improved precipitation and typhoon intensity forecasts as well as simulation of the Kuroshio current variability associated with mesoscale oceanic activities.The results show that for realizing the extended-range predictability of atmospheric and oceanic environment characterized by statistics of mesoscale activities,a fine resolution coupled model resolving local mesoscale phenomena with balanced and coherent coupled initialization is a necessary first step.The next challenges include improving the planetary boundary physics and the representation of air-sea and air-land interactions to enable the model to resolve kilometer or sub-kilometer processes.

风压平衡关系对高分辨率区域模式地面资料同化的影响分析

随着模式分辨率的提高,数值模式可分辨的短波信息增加,以地转平衡为基础的风压平衡约束关系不能完全满足低纬度地区及对流尺度高分辨率模式资料同化的需求。提出了基于多重网格方法构建1 km分辨率数值模式变分同化风压平衡约束关系的方案,基于CMA-MESO (China Meteorological Administration Mesoscale Model)三维变分(Three-Dimensional Variational Data Assimilation,简称3DVAR)和1 km分辨率中尺度区域模式开展了单点同化试验和典型个例分析。单点同化试验表明,气压和风的同化结果在没有平衡约束关系条件下比线性平衡约束下更接近观测。地面自动气象站观测资料同化试验表明新风压平衡约束关系将明显增加模式低层几十千米尺度的分析增量,其次是增加100—200 km尺度的分析增量。新风压平衡约束试验的同化分析增量相对于线性平衡约束的对照试验可以给出更多的增量中心位置,更好描述低层水汽辐合,对模式初始0—3 h降水、0—6 h地面10 m风和地面气压的模拟有改进。研究表明在大尺度风压平衡约束的基础上增加局地无风压平衡约束的订正,可以提高对流尺度天气系统地面短波信息的同化能力,改进高分辨率模式短时临近预报。

Regional and Global Land Data Assimilation Systems: Innovations,Challenges, and Prospects

Since the North American and Global Land Data Assimilation Systems(NLDAS and GLDAS) were established in2004, significant progress has been made in development of regional and global LDASs. National, regional, projectbased, and global LDASs are widely developed across the world. This paper summarizes and overviews the development, current status, applications, challenges, and future prospects of these LDASs. We first introduce various regional and global LDASs including their development history and innovations, and then discuss the evaluation, validation, and applications(from numerical model prediction to water resources management) of these LDASs. More importantly, we document in detail some specific challenges that the LDASs are facing: quality of the in-situ observations, satellite retrievals, reanalysis data, surface meteorological forcing data, and soil and vegetation databases; land surface model physical process treatment and parameter calibration; land data assimilation difficulties; and spatial scale incompatibility problems. Finally, some prospects such as the use of land information system software, the unified global LDAS system with nesting concept and hyper-resolution, and uncertainty estimates for model structure,parameters, and forcing are discussed.

加密自动站数据在睿图-中亚数值模式中的应用

利用睿图-中亚区域数值预报系统(Rapid-refresh Multi-scale Analysis and Prediction System-Central Asia,RMAPS-CA)以及不同的地面气象自动站观测资料进行同化试验,并将试验结果与实况进行对比,旨在通过加密自动站的同化应用来提高RMAPS-CA对于地面要素的预报性能。通过2020年7月为期15天的批量试验结果表明:在保证数据质量的前提下,相比仅同化国家级自动站而言,同化加密自动站后可以有效提高地面温度、湿度和风速的预报准确性。在使用加密自动站的基础上,将RMAPS-CA的地面资料同化方案由原方案改为更新方案后可以降低地面温度预报和风速预报的均方根误差,提升加密自动站的同化应用效果。综上所述,加密自动站的合理使用可以改善RMAPS-CA的预报性能,而同化更新方案可以进一步提高加密自动站观测资料对于数值预报系统的贡献。

Recent advances in regional air-sea coupled models

In this paper,we first briefly review the history of air-sea coupled models,and then introduce the current status and recent advances of regional air-sea coupled models.In particular,we discuss the core technical and scientific issues involved in the development of regional coupled models,including the coupling technique,lateral boundary conditions,the coupling with sea waves(ices),and data assimilation.Furthermore,we introduce the application of regional coupled models in numerical simulation and dynamical downscaling.Finally,we discuss the existing problems and future directions in the development of regional air-sea coupled models.

我国自主研制的全球/区域一体化数值天气预报系统GRAPES的应用与展望

介绍了中国气象局自主研制的新一代全球与区域一体化数值天气预报系统(GRAPES),着重讨论了该系统的全可压/非静力平衡动力框架,全球模式/区域模式一体化设计,半隐式-半拉格朗日差分方案,标准化、模块化、并行化、模式程序软件体系等核心技术特点。GRAPES系统已在国家级、区域级气象业务中心,以及一些大学和研究所得到应用,并在不断地完善和发展。

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 andPrEdiction 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。

风廓线雷达资料对华南区域模式预报的影响

设计基于GRAPES_Meso的不同试验模拟2014年3月28日-4月8日的广东前汛期降水过程,评估风廓线资料对同化和预报的影响。对资料同化后分析增量的分析表明:相比同化时仅使用自动气象站资料,风廓线雷达资料对1000 hPa到850 hPa纬向风增量均有贡献,在850 hPa,700 hPa高度以上贡献迅速减小。应用3个试验的预报结果计算探空站、风廓线雷达站预报值与观测值的11 d均方根误差发现,同化加入风廓线雷达资料对各预报要素的改善在850 hPa高度最明显,其中风速预报误差显著降低,为0.7 m·s^(-1)。此外,风廓线雷达资料对700 hPa风速预报有一定改善,而在925 hPa高度模拟效果反而降低。通过对2014年3月30日12:00(世界时)的个例分析发现,同化加入风廓线雷达资料的风速预报均方根误差在大雨级别以上的降水落区更大,其原因还有待于进一步研究。

MODIS反照率产品在模拟黄河源区陆面过程和降水中的应用

地表反照率是陆面过程中一个重要的物理量,其变化直接影响地表能量的收支状况,进而可以影响气温和降水等其它气象要素。本文利用WRF(Weather Research and Forecasting)模式,通过两组数值模拟试验分别探讨了地表反照率改变在黄河源区不同下垫面情况下潜热、感热的分配关系,详细分析了地表反照率改变对降水变化的影响机制,最后应用EOS/MODIS地表反照率产品替代原模式低时空分辨率的地表反照率。研究结果表明:(1)当地表反照率减少(增加)时,模拟的区域平均地表温度、感热、潜热数值相应增大(减少)。当地表反照率减少0.1时,地表温度上升约1.0K,感热和潜热量增量比约为3∶1。(2)地表反照率改变对降水量变化影响最大的区域是黄河源区下游的草场区域,其次是黄河源头区域,最小的是黄河源区北部的稀疏植被区域。地表反照率通过对大气动力、热力以及水汽条件的影响,使得降水发生的环境改变,主要体现在:当地表反照率减少时,地表气压的减少使得大气低层的辐合气流增强,有利于上升运动的发生;2.0m气温的升高增强了大气近地层的热力不稳定度;2.0m比湿的增加表明近地层空气水汽含量增加。(3)与实况对比分析发现,使用卫星遥感产品后在月尺度上能够更准确地模拟降水量的变化过程。

高频地波雷达观测资料对南海北部海流的数值同化实验

文章利用基于区域海洋模式(ROMS)的三维变分同化系统,将双站(博贺站和斗龙站)高频地波雷达的表层海流观测数据同化进模式中,并通过敏感性试验研究了观测覆盖率对同化效果的影响以及同化间隔对同化效果持续性的影响。结果表明,同化高频地波雷达表层海流观测数据能显著改善模式对表层海流的模拟。当观测覆盖率大于40%时,不同的观测覆盖率的同化效果几乎无差别,这表明模式背景误差协方差能够很好地弥补高频地波雷达在空间上的缺测信息。试验结果还表明同化效果的持续性受到同化间隔的影响:过频繁的同化会造成模式初始场动力不平衡加剧,使得同化效果的持续性变差,而过大的同化间隔则会使同化效果在下一次同化到来前消失。当同化间隔取6h或12h时,同化效果的持续性达到最优。同化对模式预报的改善持续的时长为4~6h。

加密探空资料在华东区域业务模式中的应用试验

采用中国气象局2014年6月1日—30日14时加密探空资料,利用华东区域中尺度数值预报业务系统比较同化加密探空观测资料前后模式预报结果的差异。研究表明,同化加密探空资料后,对模式初始时刻不同高度的位势高度、比湿、温度、风速等变量均有一定的影响;对位势高度、温度和风场的影响在高层100—150 h Pa比较显著,而对比湿的影响主要体现在低层700—750 h Pa。同化加密探空资料后模式初始场更接近实况。批量数值试验的统计检验表明,同化加密探空观测资料后对强降水及形势场预报均有不同程度改进,24 h暴雨和大暴雨量级降水的预报技巧分别提高了2.5%和8.1%。

西南区域自动站资料对区域模式预报影响的同化试验分析

为了探讨区域地面站资料对数值预报的影响,本文采用西南区域业务模式系统,设计多组试验方案,开展基于西南区域地面站资料的同化试验,分析区域地面站资料对模式初值及预报的影响。研究表明:西南区域自动站资料的同化有一定的正效果,如对地面要素的改善,提高24h小雨预报TS值,对强降水落区和低涡结构的描述更准确等,但不显著;相对而言,是否同化区域站资料在较强降水过程中的作用更明显,通常同化的自动站资料越多,所起的作用越大,AWS_2015的同化效果略好于AWS_2016的同化效果。如何更好地发挥区域地面站资料在数值同化模拟中的效果,还有待做深入的研究工作。

ATOVS微波观测对2008年台风预报影响的初步评估

为了评估同化ATOVS卫星微波资料在台风数值预报中的影响,利用中尺度模式WRF和三维变分同化系统WRFDA,采用国家卫星气象中心接收处理的卫星微波温度计AMSU-A辐射率L1c数据集,针对在2008年台风季中影响我国大陆的8个台风典型,开展批量卫星资料同化和数值预报试验。对同化效果的检验和对同化前、后西太平洋副热带高压的分析表明:AMSU-A资料对台风预报有改进作用,在44%的48 h预报样本中同化后路径有改善;同化微波资料后,副热带高压的改变直接影响台风路径。

雷达反演潜热在华南区域数值模式汛期短时临近降水预报的应用试验

为了评估潜热对短临降水预报的影响,基于雷达反演潜热的基础上,以2014年3月30日的强降水个例和2013年5月的31天为样本,进行了初值有无引入潜热释放引起位温增量的批量试验。(1)强降水个例模拟试验发现,初值引进潜热后预报的12 h累积降水中心与实况一致,预报的前4 h雷达反射率从范围、强度上更接近观测的反射率,逐小时TS比无潜热试验要高。(2)诊断分析表明模式初值引进潜热后,调整降水区域上空大气的温度结构,订正或加强次级环流,触发对流不稳定能量释放,利于成云致雨。(3)批量对比试验反映初值潜热对前12 h逐时降水预报一直保持正影响。

CMA-TYM混合En3DVar方案的设计和初步试验

基于CMA-TYM的3DVar系统,发展了利用扩展控制变量引入流依赖背景误差协方差(集合扰动成员统计表达)的混合En3DVar同化方案。测试显示,单点台风中心气压数据同化会引起风场非对称增量形成,以及导致传统3DVar方案认为不相关的湿度增量出现。台风个例试验表明,混合En3DVar方案能提取台风内零散观测资料信息,并按实际台风动力特征和分布区域向四周传播,从而影响分析场中台风涡旋强度、结构。同时,与3DVar方案相比,混合En3DVar方案对提高台风路径、强度预报效果明显。

淮河流域能量和水分循环观测系统及作用

淮河流域是中国南北气候重要的过渡带,气象灾害频繁发生。这里水网、农田、丘陵、山地、城镇密布,地-气作用复杂,干冷与暖湿空气时常交汇于此,造成局地或流域旱涝经常发生。淮河流域处于梅雨区,且是中国重要的农业生产基地,具有气象和水文综合观测系统,积累了长序列的气象和水文观测资料。因此,淮河流域是研究能量和水分循环的理想试验区。国家自然科学基金重大项目"淮河流域能量与水分循环试验和研究(HUaihe river Basin Experiment,简称HUBEX)"于1998、1999年夏在淮河流域开展了气象和水文联合观测试验。文中回顾了HUBEX试验的目的、观测网设计与布局,介绍了HUBEX推动下的淮河流域综合观测网的发展,总结了HUBEX观测试验对区域气候事件和暴雨等灾害性天气机理研究、提高模式模拟和预报能力及建立长期连续的气象观测数据集等方面的成果和作用。