On the Influences of Urbanization on the Extreme Rainfall over Zhengzhou on 20 July 2021: A Convection-Permitting Ensemble Modeling Study

This study investigates the influences of urban land cover on the extreme rainfall event over the Zhengzhou city in central China on 20 July 2021 using the Weather Research and Forecasting model at a convection-permitting scale[1-km resolution in the innermost domain(d3)].Two ensembles of simulation(CTRL,NURB),each consisting of 11 members with a multi-layer urban canopy model and various combinations of physics schemes,were conducted using different land cover scenarios:(i)the real urban land cover,(ii)all cities in d3 being replaced with natural land cover.The results suggest that CTRL reasonably reproduces the spatiotemporal evolution of rainstorms and the 24-h rainfall accumulation over the key region,although the maximum hourly rainfall is underestimated and displaced to the west or southwest by most members.The ensemble mean 24-h rainfall accumulation over the key region of heavy rainfall is reduced by 13%,and the maximum hourly rainfall simulated by each member is reduced by 15–70 mm in CTRL relative to NURB.The reduction in the simulated rainfall by urbanization is closely associated with numerous cities/towns to the south,southeast,and east of Zhengzhou.Their heating effects jointly lead to formation of anomalous upward motions in and above the planetary boundary layer(PBL),which exaggerates the PBL drying effect due to reduced evapotranspiration and also enhances the wind stilling effect due to increased surface friction in urban areas.As a result,the lateral inflows of moisture and high-θe(equivalent potential temperature)air from south and east to Zhengzhou are reduced.

Analysis of an Ensemble of High-Resolution WRF Simulations for the Rapid Intensification of Super Typhoon Rammasun(2014)

Diagnostics are presented from an ensemble of high-resolution forecasts that differed markedly in their predictions of the rapid intensification(RI)of Typhoon Rammasun.We show that the basic difference stems from subtle differences in initializations of(a)500-850-h Pa environmental winds,and(b)midlevel moisture and ventilation.We then describe how these differences impact on the evolving convective organization,storm structure,and the timing of RI.As expected,ascent,diabatic heating and the secondary circulation near the inner-core are much stronger in the member that best forecasts the RI.The evolution of vortex cloudiness from this member is similar to the actual imagery,with the development of an inner cloud band wrapping inwards to form the eyewall.We present evidence that this structure,and hence the enhanced diabatic heating,is related to the tilt and associated dynamics of the developing inner-core in shear.For the most accurate ensemble member:(a)inhibition of ascent and a reduction in convection over the up-shear sector allow moistening of the boundary-layer air,which is transported to the down-shear sector to feed a developing convective asymmetry;(b)with minimal ventilation,undiluted clouds and moisture from the down-shear left quadrant are then wrapped inwards to the up-shear left quadrant to form the eyewall cloud;and(c)this process seems related to a critical down-shear tilt of the vortex from midlevels,and the vertical phase-locking of the circulation over up-shear quadrants.For the member that forecasts a much-delayed RI,these processes are inhibited by stronger vertical wind shear,initially resulting in poor vertical coherence of the circulation,lesser moisture and larger ventilation.Our analysis suggests that ensemble prediction is needed to account for the sensitivity of forecasts to a relatively narrow range of environmental wind shear,moisture and vortex inner-structure.

An efficient framework for ensemble of natural disaster simulations as a service

Calculations of risk from natural disasters may require ensembles of hundreds of thousands of simulations to accurately quantify the complex relationships between the outcome of a disaster and its contributing factors.Such large ensembles cannot typically be run on a single computer due to the limited computational resources available.Cloud Computing offers an attractive alternative,with an almost unlimited capacity for computation,storage,and network bandwidth.However,there are no clear mechanisms that define how to implement these complex natural disaster ensembles on the Cloud with minimal time and resources.As such,this paper proposes a system framework with two phases of cost optimization to run the ensembles as a service over Cloud.The cost is minimized through efficient distribution of the simulations among the cost-efficient instances and intelligent choice of the instances based on pricing models.We validate the proposed framework using real Cloud environment with real wildfire ensemble scenarios under different user requirements.The experimental results give an edge to the proposed system over the bag-of-task type execution on the Clouds with less cost and better flexibility.

The construction of general basis functions in reweighting ensemble dynamics simulations: Reproduce equilibrium distribution in complex systems from multiple short simulation trajectories

Ensemble simulations, which use multiple short independent trajectories from dispersive initial conformations, rather than a single long trajectory as used in traditional simulations, are expected to sample complex systems such as biomolecules much more efficiently. The re-weighted ensemble dynamics（RED） is designed to combine these short trajectories to reconstruct the global equilibrium distribution. In the RED, a number of conformational functions, named as basis functions,are applied to relate these trajectories to each other, then a detailed-balance-based linear equation is built, whose solution provides the weights of these trajectories in equilibrium distribution. Thus, the sufficient and efficient selection of basis functions is critical to the practical application of RED. Here, we review and present a few possible ways to generally construct basis functions for applying the RED in complex molecular systems. Especially, for systems with less priori knowledge, we could generally use the root mean squared deviation（RMSD） among conformations to split the whole conformational space into a set of cells, then use the RMSD-based-cell functions as basis functions. We demonstrate the application of the RED in typical systems, including a two-dimensional toy model, the lattice Potts model, and a short peptide system. The results indicate that the RED with the constructions of basis functions not only more efficiently sample the complex systems, but also provide a general way to understand the metastable structure of conformational space.

Reweighted ensemble dynamics simulations:Theory,improvement,and application

Based on multiple parallel short molecular dynamics simulation trajectories, we designed the reweighted ensem- ble dynamics （RED） method to more efficiently sample complex （biopolymer） systems, and to explore their hierarchical metastable states. Here we further present an improvement to depress statistical errors of the RED and we discuss a few keys in practical application of the RED, provide schemes on selection of basis functions, and determination of the free parameter in the RED. We illustrate the application of the improvements in two toy models and in the solvated alanine dipeptide. The results show the RED enables us to capture the topology of multiple-state transition networks, to detect the diffusion-like dynamical behavior in an entropy-dominated system, and to identify solvent effects in the solvated peptides. The illustrations serve as general applications of the RED in more complex biopolymer systems.

Ensemble Simulation of Land Evapotranspiration in China Based on a Multi-Forcing and Multi-Model Approach

In order to reduce the uncertainty of offline land surface model （LSM） simulations of land evapotranspiration （ET）, we used ensemble simulations based on three meteorological forcing datasets [Princeton, ITPCAS （Institute of Tibetan Plateau Research, Chinese Academy of Sciences）, Qian] and four LSMs （BATS, VIC, CLM3.0 and CLM3.5）, to explore the trends and spatiotemporal characteristics of ET, as well as the spatiotemporal pattern of ET in response to climate factors over China's Mainland during 1982-2007. The results showed that various simulations of each member and their arithmetic mean （EnsAVlean） could capture the spatial distribution and seasonal pattern of ET sufficiently well, where they exhibited more significant spatial and seasonal variation in the ET compared with observation-based ET estimates （Obs_MTE）. For the mean annual ET, we found that the BATS forced by Princeton forcing overestimated the annual mean ET compared with Obs_MTE for most of the basins in China, whereas the VIC forced by Princeton forcing showed underestimations. By contrast, the Ens_Mean was closer to Obs_MTE, although the results were underestimated over Southeast China. Furthermore, both the Obs_MTE and Ens_Mean exhibited a significant increasing trend during 1982-98; whereas after 1998, when the last big EI Nifio event occurred, the Ens_Mean tended to decrease significantly between 1999 and 2007, although the change was not significant for Obs_MTE. Changes in air temperature and shortwave radiation played key roles in the long-term variation in ET over the humid area of China, but precipitation mainly controlled the long-term variation in ET in arid and semi-arid areas of China.

Observation system simulation experiments using an ensemble-based method in the northeastern South China Sea

An ensemble-based method for the observation system simulation experiment(OSSE)is employed to design optimal observation stations and assess the present observation stations in the northeastern South China Sea(SCS).We employed the 20-year(1992-2012)sea surface height(SSH)data to design an array to monitor the intraseasonal to interannual variability.The results show that the most key region was found located at the northwest of Luzon Island(LI)where the energetic Luzon cyclonic gyre(LCG)occurs;other key regions include the edge of the LCG,the northwest of the Luzon Strait(LS),and the southwest of Taiwan,China.By contrast,we found that the present observation stations might oversample at the northwest of the LS and undersample at the northwest of LI.In addition,the optimal stations perform better in a larger area than the present stations.In vertical direction,the key layer is located within the upper 200-m depth,of which the surface and subsurface layers are most valuable to the observing system.

GIBBS ENSEMBLE MONTE CARLO SIMULATION OF VAPORLIQUID EQUILIBRIA FOR SIMPLE FLUIDS

The Gibbs ensemble Monte Carlo simulation method has been investigated and used to calculate the vaporliquid equilibria of a real binary mixture, argon-methane. In this simulation, the micro-structural and macroscopic properties, including the distribution function, internal energy, densities and compositions of coexisting vapor and liquid phases as well as the enthalpy of vaporization are obtained. Compared with experimental data and calculated results from equations of state, our simulated phase equilibrium properties are of good accuracy, which demonstrates that this simulation methods is a powerful tool in research on phase equilibria of fluids.

Improving the simulation of terrestrial water storage anomalies over China using a Bayesian model averaging ensemble approach

作为全球能量和水分循环的关键参量,陆地水储量包括土壤水、地表水、地下水、积雪和生物体水等,在水文、气候、农业、生态等众多领域起重要影响。与地面观测和遥感反演相比,陆面模式在刻画陆地水储量的时空变率等方面具有明显优势。然而不同模式参数化方案以及大气强迫驱动导致陆地水储量模拟存在不确定。为了减少陆地水储量模拟不确定性,本研究建立了基于贝叶斯模型平均(BMA)和多强迫多模式集合的陆地水储量模拟系统,获得了中国区域1979–2008年陆地水储量数据集。选取2004–08年的数据与GRACE重力卫星数据比较分析,结果显示BMA集合模拟的陆地水储量异常(Terrestrial water storage anomalies,TWSA)优于所有单个模拟结果,与GRACE观测的TWSA有更高的相关系数和更小的误差。

Ensemble Cloud Model Application in Simulating the Catastrophic Heavy Rainfall Event

An attempt has been made in the present research to simulate a deadly flash-flood event over the City of Skopje,Macedonia on 6 August 2016.A cloud model ensemble forecast method is developed to simulate a super-cell storm’s initiation and evolutionary features.Sounding data are generated using an ensemble approach,that utilizes a triple-nested WRF model.A three-dimensional(3-D)convective cloud model(CCM)with a very fine horizontal grid resolution of 250-m is initialized,using the initial representative sounding data,derived from the WRF 1-km forecast outputs.CCM is configured and run with an open lateral boundary conditions LBC,allowing explicit simulation of convective scale processes.This preliminary study showed that the ensemble approach has some advantages in the generation of the initial data and the model initialization.The applied method minimizes the uncertainties and provides a more qualitative-quantitative assessment of super-cell storm initiation,cell structure,evolutionary properties,and intensity.A high-resolution 3-D run is capable to resolve detailed aspects of convection,including high-intensity convective precipitation.The results are significant not only from the aspect of the cloud model’s ability to provide a qualitative-quantitative assessment of intense precipitation but also for a deeper understanding of the essence of storm development,its vortex dynamics,and the meaning of micro-physical processes for the production and release of large amounts of precipitation that were the cause of the catastrophic flood in an urban area.After a series of experiments and verification,such a system could be a reliable tool in weather services for very short-range forecasting(now-casting)and early warning of weather disasters.

Ensemble Forecast for Tropical Cyclone Based on CNOP-P Method:A Case Study of WRF Model and Two Typhoons

In this paper,we set out to study the ensemble forecast for tropical cyclones.The case study is based on the Conditional Nonlinear Optimal Perturbation related to Parameter(CNOP-P)method and the WRF model to improve the prediction accuracy for track and intensity,and two different typhoons are selected as cases for analysis.We first select perturbed parameters in the YSU and WSM6 schemes,and then solve CNOP-Ps with simulated annealing algorithm for single parameters as well as the combination of multiple parameters.Finally,perturbations are imposed on default parameter values to generate the ensemble members.The whole proposed procedures are referred to as the PerturbedParameter Ensemble(PPE).We also conduct two experiments,which are control forecast and ensemble forecast,termed Ctrl and perturbed-physics ensemble(PPhyE)respectively,to demonstrate the performance for contrast.In the article,we compare the effects of three experiments on tropical cyclones in aspects of track and intensity,respectively.For track,the prediction errors of PPE are smaller.The ensemble mean of PPE filters the unpredictable situation and retains the reasonably predictable components of the ensemble members.As for intensity,ensemble mean values of the central minimum sea-level pressure and the central maximum wind speed are closer to CMA data during most of the simulation time.The predicted values of the PPE ensemble members included the intensity of CMA data when the typhoon made landfall.The PPE also shows uncertainty in the forecast.Moreover,we also analyze the track and intensity from physical variable fields of PPE.Experiment results show PPE outperforms the other two benchmarks in track and intensity prediction.

An ensemble-based SST nudging method proposed for correcting the subsurface temperature field in climate model

An ensemble-based assimilation method is proposed for correcting the subsurface temperature field when nudging the sea surface temperature(SST) observations into the Max Planck Institute(MPI) climate model,ECHAM5/MPI-OM. This method can project SST directly to subsurface according to model ensemble-based correlations between SST and subsurface temperature. Results from a 50 year(1960–2009) assimilation experiment show the method can improve the subsurface temperature field up to 300 m compared to the qualitycontrolled subsurface ocean temperature objective analyses(EN4), through reducing the biases of the thermal states, improving the thermocline structure, and reducing the root mean square(RMS) errors. Moreover, as most of the improvements concentrate over the upper 100 m, the ocean heat content in the upper 100 m(OHT100 m)is further adopted as a property to validate the performance of the ensemble-based correction method. The results show that RMS errors of the global OHT100 m convergent to one value after several times iteration,indicating this method can represent the relationship between SST and subsurface temperature fields well, and then improve the accuracy of the simulation in the subsurface temperature of the climate model.

Hierarchical Visual Analysis and Steering Framework for Astrophysical Simulations

A framework for accelerating modern long-running astrophysical simulations is presented, which is based on a hierarchical architecture where computational steering in the high-resolution run is performed under the guide of knowledge obtained in the gradually refined ensemble analyses. Several visualization schemes for facilitating ensemble management, error analysis, parameter grouping and tuning are also integrated owing to the pluggable modular design. The proposed approach is prototyped based on the Flash code, and it can be extended by introducing userdefined visualization for specific requirements. Two real-world simulations, i.e., stellar wind and supernova remnant, are carried out to verify the proposed approach.

Bridging element-free Galerkin and pluri-Gaussian simulation for geological uncertainty estimation in an ensemble smoother data assimilation framework

The facies distribution of a reservoir is one of the biggest concerns for geologists,geophysicists,reservoir modelers,and reservoir engineers due to its high importance in the setting of any reliable decisionmaking/optimization of field development planning.The approach for parameterizing the facies distribution as a random variable comes naturally through using the probability fields.Since the prior probability fields of facies come either from a seismic inversion or from other sources of geologic information,they are not conditioned to the data observed from the cores extracted from the wells.This paper presents a regularized element-free Galerkin(R-EFG)method for conditioning facies probability fields to facies observation.The conditioned probability fields respect all the conditions of the probability theory(i.e.all the values are between 0 and 1,and the sum of all fields is a uniform field of 1).This property achieves by an optimization procedure under equality and inequality constraints with the gradient projection method.The conditioned probability fields are further used as the input in the adaptive pluri-Gaussian simulation(APS)methodology and coupled with the ensemble smoother with multiple data assimilation(ES-MDA)for estimation and uncertainty quantification of the facies distribution.The history-matching of the facies models shows a good estimation and uncertainty quantification of facies distribution,a good data match and prediction capabilities.

基于Stacking集成学习模型的苹果树逐日蒸散量模拟研究

为准确模拟苹果树逐日蒸散量,以支持向量机(SVM)、多层感知机(MLP)、随机森林(RF)和梯度提升决策树(GBDT)为初级学习器,以多元线性回归(MLR)为次级学习器,基于Stacking策略建立集成学习模型(LSM),将LSM模型的模拟精度与MLR、SVM、MLP、RF、GBDT模型的模拟精度进行对比。结果表明,影响苹果树蒸散量的主要因子为日平均太阳辐射、相对湿度、风速、温度和日序数,最大互信息值分别为0.97、0.72、0.63、0.62、0.60,表层土壤温度及土壤含水率对蒸散量的影响较小。相比于MLR、SVM、MLP、RF、GBDT模型,LSM模型的模拟精度最高,MLR模型的模拟精度最低;使用日平均太阳辐射、相对湿度、风速、温度及日序数5个特征参数在准确模拟苹果树蒸散量的同时,还能降低特征的获取成本。研究结果可为苹果树逐日蒸散量的精准模拟提供有效方法。

黄土高原沟壑区典型流域不同算法土壤侵蚀集成模拟比较

为探究集成模拟技术对减少不同模型模拟土壤侵蚀的不确定性,以黄土高原昕水河流域为研究对象,采用Bates-Granger(BG)集成、等权重集成和Granger-Ramanathan集成技术,对广泛运用的Morgan-Morgan-Finney(MMF)、修正土壤流失方程(RUSLE)和中国土壤流失方程(CSLE)等进行集成模拟。集成模拟以流域出口泥沙观测进行率定,并根据纳什系数(NSE)、相关系数(R)、均方根误差(RMSE)进行模型模拟评价。结果表明:1)对于单一模型而言,MMF模拟效果在多数情况下优于CSLE和RUSLE模拟效果;2)集成模拟可显著改善土壤侵蚀模型模拟效果,集成模拟前后,模型评价指标如NSE、R、RMSE分别提高23.6%、15.8%、46.4%;3)不同集成模拟中BG集成算法在模型不确定性方面更加稳定、可靠。研究认为,在基于经验性模型开展流域土壤侵蚀模拟时,可以采用集成模拟技术进一步提升其模拟性能。

一次复杂地形下边界层抬升型暖区暴雨对流触发条件和可预报性的数值研究

长江中下游地区的暖区暴雨过程易受复杂下垫面强迫的影响,具有较大的预报不确定性,尤其是其中的对流触发过程。为探讨此类过程的触发条件及揭示其可预报性受限制程度,本文针对2020年6月23日一次复杂地形包裹下的长江中下游暖区暴雨展开高分辨率的数值模拟和对流尺度集合模拟,通过Lagrange气块后向轨迹分析、去除地形和关闭热效应的敏感性试验以及集合敏感性分析等方法对此次过程的对流触发阶段展开分析。结果表明,此次过程被抬升气块的主要源地为1.5 km以下的边界层,仙霞岭和杉岭在正午时分因热力作用而驱动的出谷风是引发局地辐合抬升的动力源,高低层散度、湿位涡的垂直配置以及偶极型位涡异常对此次对流触发过程具有较好的指示意义。此外,该过程对前期近地面2 m高度处温度和模式底层视热源具有较高的敏感性,该结果证实下垫面强迫的精确刻画对于提升暖区暴雨的预报效果至关重要。逐步减小初始场误差的初值敏感性试验进一步表明,此次暖区对流过程的可预报性显著低于北边的锋面过程,表现为锋面对流的偏差总能量能随初始误差的缩小持续性降低,而暖区对流的偏差总能量曲线则仍能增长至与原水平相近,呈现出非线性辐合收缩特征。因此,对于天气尺度强迫显著的锋面对流,或可优先考虑通过加强资料同化能力等手段降低初始场误差来减小预报误差;但对于复杂地形下的暖区暴雨对流触发过程,则需要更加强调通过集合预报来捕捉其不确定性。

长江上游近61年来水文干旱演变特征及归因

水文干旱受气候变化和人类活动的共同影响,揭示变化环境下水文干旱演变特征及驱动机制,有助于提高防旱抗旱能力。基于长江上游1960—2020年长系列气象水文数据,采用多模型集合模拟重建天然径流并计算标准化径流指数,采用广义可加模型构建时变标准化径流指数,通过指数对比定量区分气候变化和人类活动对水文干旱的影响。结果表明:长江上游水文干旱自然演变总体呈加剧态势,人类活动进一步加剧了旱情;长江上游水文干旱演变驱动因子表现出明显的时空差异,气候变化是金沙江、沱江和乌江流域年尺度水文干旱演变的主导因子,人类活动是岷江、嘉陵江和整个上游流域年尺度水文干旱演变的主导因子,季节尺度主导因子与年尺度并不完全一致。

基于EEMD-SVM的光伏阵列直流电弧故障检测

光伏阵列随着运行时间的增长,阵列内数量众多的连接线缆、连接头容易产生破损或连接失效等问题,引发直流电弧故障,严重影响系统的安全运行,因此需要采用合适的检测方法进行故障诊断,以及时发现电弧故障。直流电弧故障的检测方法大致可以分为基于物理特性和时频特性两类。前者成本高,难度大,不适合大型光伏系统;后者随着近几年人工智能技术的兴起,大多数是提取直流电弧故障的时频域特征值形成数据集,运用神经网络或智能算法对其进行识别、训练、归纳等,达到检测目的,目前实际应用的检测方法侧重于后者。选用基于时频域特性的集合经验模态分解和支持向量机结合方法进行检测,在MATLAB/Simulink仿真平台搭建光伏阵列模型和直流电弧故障仿真模型,模拟光伏阵列不同位置的串、并联电弧故障,对电流信号进行采集、分析与处理。实验结果表明,支持向量机模型能够较好地对光伏阵列直流电弧故障进行识别和检测,有效区分光伏阵列正常工作状态与故障工作状态。

Climate Changes in the 21st Century over the Asia-Pacific Region Simulated by the NCAR CSM and PCM

The Climate System Model (CSM) and the Parallel Climate Model (PCM), two coupled global climate models without flux adjustments recently developed at NCAR, were used to simulate the 20th century climate using historical greenhouse gas and sulfate aerosol forcing. These simulations were extended through the 21st century under two newly developed scenarios, a business-as-usual case (BAU, CO2≈710 ppmv in 2100) and a CO2 stabilization case (STA550, CO2≈540 ppmv in 2100). The simulated changes in temperature, precipitation, and soil moisture over the Asia-Pacific region (10°-60°N, 55°-155°) are analyzed, with a focus on the East Asian summer monsoon rainfall and climate changes over the upper reaches of the Yangtze River. Under the BAU scenario, both the models produce surface warming of about 3-5℃ in winter and 2-3℃ in summer over most Asia. Under the STA550 scenario, the warming is reduced by 0.5-1.0℃ in winter and by 0.5℃ in summer. The warming is fairly uniform at the low latitudes and does not induce significant changes in the zonal mean Hadley circulation over the Asia-Pacific do- main While the regional precipitation changes from single CSM integrations are noisy, the PCM ensemble mean precipitation shows 10%-30% increases north of ～ 30°N and～10% decreases south of ～ 30°N over the Asia-Pacific region in winter and 10%-20% increases in summer precipitation over most of the region. Soil moisture changes are small over most Asia The CSM single simulation suggests a 30% increase in river runoff into the Three Gorges Dam, but the PCM ensemble simulations show small changes in the runoff