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1.
清华大学地球系统科学研究中心在一个标准耦合模式（SC）的基础上建立了交互集合耦合模式系统（IE）,该系统可以实现多个不同大气模式或者同一大气模式采取不同初值组成的多个分量集合之后与海、陆、冰模式进行耦合.本文利用同一大气模式七个不同初值分量与其它模式分量开展在线集合耦合试验,利用积分稳定之后100年的试验结果,分析了IE在减小海-气界面大气噪音的情况下,对北太平洋海表面温度（SST）变率和ENSO的模拟,并与SC模拟结果进行了对比.分析表明,IE减小了北太平洋中高纬度SST方差的85%以上,表明该区域SST变率主要受大气的影响,且主要是通过改变海表湍流热通量实现的.黑潮延伸体区和北太平洋中部副热带涡旋区域平均SST 8年左右的低频周期主要受来自大气内部动力过程的驱动.在集合耦合模拟中,无论是副热带涡旋区SST与ENSO的联系,还是ENSO与北太平洋中高纬度SST的联系都能模拟出来,而标准模式未能模拟出这些现象,意味着大气噪音过强将掩盖ENSO与太平洋热带外SST的联系.IE对与ENSO关联的“太平洋-北美”（PNA）遥相关型的合理模拟,并通过湍流热通量对海表温度的影响,是其能够更好模拟ENSO与北太平洋中高纬度SST关系的重要原因.本文通过分析验证了所建立的交互集合耦合模式系统的合理性,揭示了该系统在海-气相互作用研究领域方面具有一定应用前景. 相似文献
2.
西北太平洋热带气旋在2018年7~8月间的预报,特别是在上海登陆的温比亚(2018)、安比(2018)和云雀(2018),给数值模式和预报均带来巨大的挑战.文章基于ECMWF和NCEP的集合预报对这些热带气旋的预报技巧进行了分析.结果表明,ECMWF的集合预报对热带气旋路径和强度的预报技巧高于NCEP的集合预报.对于在上海登陆的三个台风,ECMWF的集合预报对温比亚(2018)和安比(2018)的强度预报技巧优于NCEP的集合预报,但两者对云雀(2018)在峰值附近的强度预报技巧都较低.为了提高集合预报对热带气旋的预报技巧,文章提出了一种集合预报成员的适应性权重估计方法.该方法利用集合成员的预报场和分析场相对于观测的距离,适应性地估计集合成员在集合平均中的权重.当适应性权重方法应用于ECMWF和NCEP的集合预报时,二者的集合预报对热带气旋路径和强度的预报技巧都得到了改进,并且ECMWF集合预报的改进要优于NCEP集合预报. 相似文献
3.
利用MM5中尺度模式对1999年6月两个出海气旋发展过程进行 数值模拟. 数值模拟的气旋出海后移动路径与实际情况基本一致. 在数值模拟基础上重点讨 论了出海气旋发展过程潜热通量和感热通量的分布及其演变情况. 气旋出海后在气旋中心区 南方和东方存在负潜热通量和感热通量区. 出海气旋的东移和发展，其前方强大正热通量区 的存在可能是重要原因之一. 相似文献
4.
《中国科学:地球科学》2016,(1)
局地强降水可以引发山洪、泥石流等次生灾害,目前准确预报局地强降水依然是天气预报业务的难点.本文针对一次发生在西北太平洋副热带高压边缘、导致12人死亡的极端局地强降水事件,利用集合卡尔曼滤波(En KF)开展多普勒雷达径向风观测资料同化试验,并对En KF同化过程不确定性进行分析.结果表明:不同化观测资料,采用单一初值的确定性预报或增加初值扰动、采用多物理过程的集合预报均不能正确预报强降水发生位置,而利用En KF同化雷达径向速度观测资料能有效改进确定性和集合预报效果,特别是强降水位置预报.通过En KF同化雷达资料,建立深厚的中尺度对流系统是改进降水预报效果的直接原因.在具备了对流发生条件的大尺度环境背景场中,上游地区、对流层中下层经向风和水汽场的合理扰动是影响同化过程和降水预报的关键因素.该个例预报过程受实际可预报性影响,具有不确定性,大尺度初始条件的差异或初始扰动场振幅偏小导致的En KF分析场差异都会对模拟结果造成较大影响,而采用En KF循环同化有助于提高该个例的预报准确性.敏感性试验还表明未来通过改进数值模式或改善观测系统,提供更准确观测信息,可以对此类短时强降水事件做出更准确预报. 相似文献
5.
本文利用中尺度数值模式WRF,分别采用YSU和MYJ两种边界层参数化方案对2010年超强台风Megi的移动路径进行了模拟,研究了热带气旋(TC)路径模拟对边界层方案的敏感性,并从模拟TC尺度差异所造成的影响角度揭示了模式边界层方案影响TC路径的机理.结果表明:由于两种方案对边界层垂直混合作用过程的描述不同,两个试验模拟的低层水汽垂直输送存在差异.相对于能很好模拟出Megi路径的MYJ方案,YSU方案模拟的TC外围螺旋雨带更活跃,造成TC尺度增大,引起TC中心北侧外围气压梯度和径向风速增加,使得由副高向TC中心输送更多的质量,造成副高异常减弱,从而导致由副高主导的引导气流发生改变,最终使得采用YSU方案模拟的Megi路径出现提前转向. 相似文献
6.
《中国科学:地球科学》2015,(12)
基于国家海洋局第一海洋研究所发展的地球系统模式(FIO-ESM),设计了集合调整Kalman滤波(EAKF)同化方案并开展了海洋卫星资料同化实验.设计的数值实验包括1组控制实验和4组同化实验.控制实验由一组初始场各不相同的模式组成,将FIO-ESM模式积分1年;同化实验则在积分过程中不断对海洋模式分量进行海洋卫星数据同化.前2组同化实验分别对卫星海面高度异常(SLA)和卫星海面温度(SST)数据进行同化,后2组实验中SLA和SST均加入同化,但两种数据同化顺序不同.为了检验同化过程对气候模式中海洋模拟的影响,将实验结果与再分析数据集EN3进行了对比分析.与海洋模式不同,耦合模式在海面的动量和热量通量是由耦合过程实时计算得出,耦合模式中多变量之间的约束关系更接近实际的物理过程.海洋卫星资料EAKF同化整体显著改善了FIO-ESM中海洋模式分量的模拟结果,尤其在1000 m以浅效果更为显著.不同类型的卫星观测数据的同化效果在深度上有所不同,SST的改善效果在表层附近较大,而SLA则对次表层改善较大,且在深层SLA的改善大于SST.联合SLA和SST同化的实验结果均比单独同化一类数据的效果更佳,但不同顺序对这2种数据进行同化的差异不显著. 相似文献
7.
2011年3月11日日本大地震引发了福岛核电站放射性污染物泄漏事故.根据日本官方公布的污染物释放量,通过核泄漏放射性物质的源项设计,采用CMAQ模式中PM2.5作为核污染物的示踪物,并考虑核污染物扩散和干湿沉降过程等,建立了基于大气模式WRF和空气质量模式Models-3/CMAQ的耦合模式系统.在此基础上,分别采用30和4km模式水平分辨率对放射性污染物中远距离和近距离(局地)扩散传输路径和强度进行了5天数值模拟.中远距离模拟结果表明:福岛核事故发生之后,受西风带影响,放射性污染物大部分时间向太平洋东部方向扩散,5天后到达美洲大陆,但浓度仅相当于福岛核电站附近的10-7左右,模拟的污染物到达美国的时间与加利福尼亚州3月18日的监测结果基本吻合,同时发现,由于高空西风风速大于低层,污染物的分布随高度形成向东倾斜的垂直结构.对近距离(局地)高分辨率模拟结果表明:伴随气旋过程的大风和降水可加快污染物的扩散传输和局地沉降,同时,气旋性环流又可使污染物改变传输路径,甚至对局地造成重复影响.污染物于3月14日18时扩散到日本本州岛东南部,模拟结果与当地观测的吸收剂量率增加时间基本一致.结果表明,福岛核事故放射性污染物主要以向东扩散传输为主,即使在气旋系统的影响下,对日本本土的影响时间较短,因此从大气条件角度看,福岛核电站的选址比较科学,对其他核设施的选址和保护具有借鉴意义. 相似文献
8.
最近,一种基于路径相似的登陆热带气旋降水动力统计集合预报(LTP_DSEF)模型被发展用来预报登陆热带气旋(LTC)带来的强降水.文章把LTP_DSEF模型应用于2018年登陆中国的10个热带气旋(TC)的强过程降水预报,通过测试模型的3452套预报方案确定了对这10个LTC的最佳方案,然后将其性能与三家动力模式(ECMWF、GFS和GRAPES)进行对比.结果表明:LTP_DSEF模型在预报LTC的较强过程降水方面与三家动力模式相比很有优势,特别是预报250mm以上量级的过程降水;对单TC, LTP_DSEF模型预报LTC过程降水的能力优于或者略逊于三家动力模式,特别在三家动力模式对某些TC的强降水均无预报能力时,模型仍能提供宝贵的大于零的TS值;此外虽然与实况相比该模型预测的强降水范围倾向偏大,但它在多数情况下能合理地捕捉到强降水的落区.初步研究表明,尽管LTP_DSEF模型只引入了TC路径和登陆时间两个相似性变量,但它已能为LTC的强过程降水预报提供非常有用的指导. 相似文献
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全球地震台网(GSN)及中国地震台网(CENC)的地震观测数据分析表明:由北大西洋、北冰洋等海域进入北欧的强冷涡气旋(北欧风暴)能引发与其过程相关联的震动,其中由挪威海登陆斯堪的纳维亚半岛的强气旋风暴引发的震动波,几乎可以被整个欧亚大陆的地震仪观测到,该震动主要包含两个信号:一个主频为0.15~0.25 Hz(周期约4~7 s);而另一个是主频为0.08~0.12 Hz(周期8~12 s)的面波信号,它们分别来自不同的产生机理.不同海域和地区的风暴引发的震动信号存在差异,与气旋运动路径经过的地形地貌特征有关,气旋经过的浅海区域、海水深度、登陆地点的地形以及气旋的结构、观测点相对气旋的分布等因素决定了气旋在运动中激发有独特的震动信号.地震观测可以监测气旋在时间和空间的发展变化过程,有助于探索气旋运动过程中与地球表面的相互作用对气旋的影响. 相似文献
11.
The tropical cyclones form over the oceanic regions where conventional meteorological observations are not available. This
contributes to a poor initial analysis of the cyclonic vortex and hence inadequate forecast. One way of overcoming the above
problem is to modify the initial analysis by replacing the weak and ill-defined vortex in the initial analysis with a synthetic
vortex having the correct size and intensity at the correct location. In this study we are investigating the effect of inclusion
of a synthetic vortex based on Rankine as well as on Holland wind profiles, using NCAR-AFWA bogussing scheme for the prediction
of four tropical cyclones, which formed over the Bay of Bengal during November 2002 and 2005, December 2005 and over the Arabian
Sea during May 2004, using the MM5 model. Two numerical experiments are designed in this study for each of the above four
cyclones. In the first experiment the model is integrated with a synthetic vortex based on Rankine wind profile while in the
second experiment we utilize the Holland wind profile. For the November 2002 cyclone, in both the experiments the model is
integrated from 10 November 2002 18 UTC to 12 November, 2002 12 UTC with the synthetic vortex inserted at the initial time.
The results of the study for the November 2002 cyclone show that the model simulation with the Holland vortex has produced
a stronger cyclone in terms of minimum sea-level pressure and maximum wind speed. Also, the results for the November 2002
cyclone with the Holland vortex showed a better longitudinal height section of the horizontal wind speed across the center
of the cyclone. The track error of the cyclone for the November 2002 cyclone is less in the model simulation with the Holland
vortex at the initial time and at 24 hours of forecast. The results for the November 2002 cyclone with the Rankine vortex
showed greater vertical wind speed as compared to the Holland vortex. However, for the November 2002 cyclone there were no
significant differences in the spatial distribution of precipitation for both the experiments. In order to provide an adequate
number of case studies for a good statistical sample, the present study is extended for three additional cyclones over the
Indian region. All four cyclones studied here show that the Holland vortex has produced a stronger cyclone in terms of the
minimum sea-level pressure and maximum wind speed. The Holland vortex showed a better vertical structure of wind speed in
the longitudinal height section at 24 hours of forecast for the November 2005 cyclone while the structure was better for the
Rankine vortex for the remaining two cyclones. There were no significant differences in the spatial distribution of precipitation
for the two experiments corresponding to all four cyclones. Some statistical results pertaining to all four cyclones are provided
such as the average track error as well as the average difference between the observed and the model minimum sea-level pressure
and the maximum wind speed. The statistical results corresponding to the average of all the four cyclones are at only a slight
variance with the results corresponding to the November 2002 cyclone. 相似文献
12.
Leveraging ensemble meteorological forcing data to improve parameter estimation of hydrologic models
As continental to global scale high-resolution meteorological datasets continue to be developed, there are sufficient meteorological datasets available now for modellers to construct a historical forcing ensemble. The forcing ensemble can be a collection of multiple deterministic meteorological datasets or come from an ensemble meteorological dataset. In hydrological model calibration, the forcing ensemble can be used to represent forcing data uncertainty. This study examines the potential of using the forcing ensemble to identify more robust parameters through model calibration. Specifically, we compare an ensemble forcing-based calibration with two deterministic forcing-based calibrations and investigate their flow simulation and parameter estimation properties and the ability to resist poor-quality forcings. The comparison experiment is conducted with a six-parameter hydrological model for 30 synthetic studies and 20 real data studies to provide a better assessment of the average performance of the deterministic and ensemble forcing-based calibrations. Results show that the ensemble forcing-based calibration generates parameter estimates that are less biased and have higher frequency of covering the true parameter values than the deterministic forcing-based calibration does. Using a forcing ensemble in model calibration reduces the risk of inaccurate flow simulation caused by poor-quality meteorological inputs, and improves the reliability and overall simulation skill of ensemble simulation results. The poor-quality meteorological inputs can be effectively filtered out via our ensemble forcing-based calibration methodology and thus discarded in any post-calibration model applications. The proposed ensemble forcing-based calibration method can be considered as a more generalized framework to include parameter and forcing uncertainties in model calibration. 相似文献
13.
Validation and application of an ensemble Kalman filter in the Selat Pauh of Singapore 总被引：1，自引：1，他引：0
The effectiveness of an ensemble Kalman filter (EnKF) is assessed in the Selat Pauh of Singapore using observing system simulation
experiment. Perfect model experiments are first considered. The perfect model experiments examine the EnKF in reducing the
initial perturbations with no further errors than those in the initial conditions. Current velocity at 15 observational sites
from the true ocean is assimilated every hour into the false ocean. While EnKF reduces the initial velocity error during the
first few hours, it fails after one tidal cycle (approximately 12 h) due to the rapid convergence of the ensemble members.
Successively, errors are introduced in the surface wind forcing. A random perturbation ε is applied independently to each ensemble member to maintain the ensemble spread. The assimilation results showed that the
success of EnKF depends critically on the presence of ε, yet it is not sensitive to the magnitude of ε, at least in the range of weak to moderate perturbations. Although all experiments were made with EnKF only, the results
could be applicable in general to all other ensemble-based data assimilation methods. 相似文献
14.
Qiang Dai Dawei Han Lu Zhuo Jun Zhang Tanvir Islam Prashant K. Srivastava 《Stochastic Environmental Research and Risk Assessment (SERRA)》2016,30(1):27-38
Uncertainty analysis of radar rainfall enables stakeholders and users have a clear knowledge of the possible uncertainty associated with the rainfall products. Long-term empirical modeling of the relationship between radar and gauge measurements is an efficient and practical method to describe the radar rainfall uncertainty. However, complicated variation of synoptic conditions makes the radar-rainfall uncertainty model based on historical data hard to extend in the future state. A promising solution is to integrate synoptic regimes with the empirical model and explore the impact of individual synoptic regimes on radar rainfall uncertainty. This study is an attempt to introduce season, one of the most important synoptic factor, into the radar rainfall uncertainty model and proposes a seasonal ensemble generator for radar rainfall using copula and autoregressive model. We firstly analyze the histograms of rainfall-weighted temperature, the radar-gauge relationships, and Box and Whisker plots in different seasons and conclude that the radar rainfall uncertainty has strong seasonal dependence. Then a seasonal ensemble generator is designed and implemented in a UK catchment under a temperate maritime climate, which can fully model marginal distribution, spatial dependence, temporal dependence and seasonal dependence of radar rainfall uncertainty. To test its performance, 12 typical rainfall events (4 for each season) are chosen to generate ensemble rainfall values. In each time step, 500 ensemble members are produced and the values of 5th to 95th percentiles are used to derive the uncertainty bands. Except several outliers, the uncertainty bands encompass the observed gauge rainfall quite well. The parameters of the ensemble generator vary considerably for each season, indicating the seasonal ensemble generator reflects the impact of seasons on radar rainfall uncertainty. This study is an attempt to simultaneously consider four key features of radar rainfall uncertainty and future study will investigate their impacts on the outputs of hydrological models with radar rainfall as input or initial conditions. 相似文献
15.
Assessing hydrological model predictive uncertainty using stochastically generated geological models 
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下载免费PDF全文 In distributed and coupled surface water–groundwater modelling, the uncertainty from the geological structure is unaccounted for if only one deterministic geological model is used. In the present study, the geological structural uncertainty is represented by multiple, stochastically generated geological models, which are used to develop hydrological model ensembles for the Norsminde catchment in Denmark. The geological models have been constructed using two types of field data, airborne geophysical data and borehole well log data. The use of airborne geophysical data in constructing stochastic geological models and followed by the application of such models to assess hydrological simulation uncertainty for both surface water and groundwater have not been previously studied. The results show that the hydrological ensemble based on geophysical data has a lower level of simulation uncertainty, but the ensemble based on borehole data is able to encapsulate more observation points for stream discharge simulation. The groundwater simulations are in general more sensitive to the changes in the geological structure than the stream discharge simulations, and in the deeper groundwater layers, there are larger variations between simulations within an ensemble than in the upper layers. The relationship between hydrological prediction uncertainties measured as the spread within the hydrological ensembles and the spatial aggregation scale of simulation results has been analysed using a representative elementary scale concept. The results show a clear increase of prediction uncertainty as the spatial scale decreases. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
16.
Mechanism for initial brows-like meso-scale vortex effects on tropical cyclone track 总被引：1，自引：0，他引：1
We used a two-dimensional quasi-geostrophic barotropic model simulation to study effects of an initial brows-like meso-scale vortex on tropical cyclone(TC) track.Our results show that the impact of each of the three foundational factors(the environmental current,the asymmetric structure and the asymmetric convection system) on TC track varies with time and the importance of each of the factors is different for the different TC motion time period.They show two kinds of the effects.One is a direct way.The asymmetric outer wind structure and the positive longitudinal wind speed averaged in radial-band(100-300) km in the period of(0-11) h are caused by the introduction of the initial brows-like meso-scale vortex,which results in TC track to turn to the north from the northwest directly.The other is an indirect influence.First,initial TC axisymmetric circulation becomes a non-axisymmetric circulation after the addition of the meso-scale vortex.The initial non-axisymmetric circulation experiences an axisymmetrizational process in the period of(0-11) h.Second,axisymmetrizationed TC horizontal size is enlarged after t=12 h.Third,both the TC asymmetric structure and the TC energy dispersion induced-anticyclone are intensified,which quickens the TC motion and results in the track to turn to the north indirectly.The TC motion is characterized by the unusual track under the direct and the indirect effect.The formation of the unusual track should be attributed to the common effects of three factors,including the environmental flow,the TC asymmetric structure and the asymmetric convection system. 相似文献
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Stephan R. Sain Reinhard Furrer 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(6):821-829
In climate science, collections of climate model output, usually referred to as ensembles, are commonly used devices to study uncertainty in climate model experiments. The ensemble members may reflect variation in initial conditions, different physics implementations, or even entirely different climate models. However, there is a need to deliver a unified product based on the ensemble members that reflects the information contained in whole of the ensemble. We propose a technique for creating linear combinations of ensemble members where the weights are constructed from estimates of variation and correlation both within and between ensemble members. At the heart of this approach is a Bayesian hierarchical model that allows for estimation of the correlation between ensemble members as well as the study of the impact of uncertainty in the parameter estimates of the hierarchical model on the weights. The approach is demonstrated on an ensemble of regional climate model (RCM) output. 相似文献
19.
The Regional Integrated Multi-Hazard Early Warning System (RIMES), an international, intergovernmental organization based in Thailand is engaged in disaster risk reduction over the Asia–Pacific region through early warning information. In this paper, RIMES’ customized Weather Research Forecast (WRF) model has been used to evaluate the simulations of cyclone Nargis which hit Myanmar on 2 May 2008, the most deadly severe weather event in the history of Myanmar. The model covers a domain of 35oE to 145oE in the east—west direction and 12oS to 40oN in the north—south direction in order to cover Asia and east Africa with a resolution of 9?km in the horizontal and 28 vertical levels. The initial and boundary conditions for the simulations were provided by the National Center for Environmental Prediction-Global Forecast System (NCEP-GFS) available at 1o lon/lat resolution. An attempt is being made to critically evaluate the simulation of cyclone Nargis by seven set of simulations in terms of track, intensity and landfall time of the cyclone. The seven sets of model simulations were initialized every 12?h starting from 0000 UTC 28 April to 01 May 2008. Tropical Rainfall Measurement Mission (TRMM) precipitation (mm) is used to evaluate the performance of the simulations of heavy rainfall associated with the tropical cyclone. The track and intensity of the simulated cyclone are compared by making use of Joint Typhoon Warning Center (JTWC) data sets. The results indicate that the landfall time, the distribution and intensity of the rainfall, pressure and wind field are well simulated as compared with the JTWC estimates. The average landfall track error for all seven simulations was 64?km with an average time error of about 5?h. The average intensity error of central pressure in all the simulations were found out to be approximately 6?hPa more than the JTWC estimates and in the case of wind, the simulations under predicted it by an average of 12?m?s?1. 相似文献
20.
—A ten-level axi-symmetric primitive equation model with cylindrical coordinates is used to simulate the tropical cyclone evolution from a weak vortex for the Bay of Bengal region. The physics of the model comprises the parameterization schemes of Arakawa-Schubert cumulus convection (Lord et al., 1982) and Deardorff’s (1972) planetary boundary layer. The initial conditions have been taken from the climate mean data for November of Port Blair (92.4 E, 11.4 N) in the Bay of Bengal, published by the India Meteorological Department. An initial vortex has been designed to have tangential wind maximum of 10 m/s at 120-km radius with a central surface pressure of 1008 hPa. As a control experiment, referred to as ASBB1, the model is integrated for 240 h maintaining the sea-surface temperature (SST) constant at 301 K. The results of the control experiment reveal a slow decrease of the Central Surface Pressure (CSP) from the initial value of 1008 hPa to 970 hPa at 156 h. After 156 h the CSP decreased sharply until 186 h, attaining 890 hPa. The tangential wind at 1 km level attained the Cyclone Threshold Intensity (CTI) of 17 m/s around 78 h and a maximum of 87 m/s was found at 210 h. These features indicate a predeveloping stage up to 156 h, a deepening stage of 30 h from 156–186 h followed by the mature stage. The mature stage is characterized by the simulation of the central eye region, warm core, strong cyclonic circulation in the central 300 km with low-level inflow; strong vertical motion at the eye wall and outflow aloft. The convection features of the different cloud types conform with the circulation features. The control experiment clearly indicates the evolution of a cyclone with hurricane intensity from a weak vortex. In part two of the paper, results from sensitivity experiments with respect to variations in latitude, SST and initial thermodynamic state have been presented. 相似文献