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Evaluation and Projection of Population Exposure to Temperature Extremes over the Beijing−Tianjin−Hebei Region Using a High-Resolution Regional Climate Model RegCM4 Ensemble

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Advances in Atmospheric Sciences 2024年第6期41卷 1132-1146页

作者： Peihua QIN zhenghui xie Rui HAN Buchun LIU State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Institute of Environment and Sustainable Development in Agriculture Chinese Academy of Agricultural Sciences(CAAS)Beijing 100081China

Temperature extremes over rapidly urbanizing regions with high population densities have been scrutinized due to their severe impacts on human safety and *** of all,the performance of the regional climate model RegCM4 with a hydrostatic or non-hydrostatic dynamic core in simulating seasonal temperature and temperature extremes was evaluated over the historical period of 1991–99 at a 12-km spatial resolution over China and a 3-km resolution over the Beijing−Tianjin−Hebei(JJJ)region,a typical urban agglomeration of *** of spatial distributions of temperature extremes over the JJJ region using RegCM4 with hydrostatic and non-hydrostatic cores showed high spatial correlations of more than 0.8 with the *** a warming climate,temperature extremes of annual maximum daily temperature(TXx)and summer days(SU)in China and the JJJ region showed obvious increases by the end of the 21st century while there was a general reduction in frost days(FD).The ensemble of RegCM4 with different land surface components was used to examine population exposure to temperature extremes over the JJJ *** exposure to temperature extremes was found to decrease in 2091−99 relative to 1991−99 over the majority of the JJJ region due to the joint impacts of increases in temperature extremes over the JJJ and population decreases over the JJJ region,except for downtown ***,changes in population exposure to temperature extremes were mainly dominated by future population ***,we quantified changes in exposure to temperature extremes with temperature increase over the JJJ *** study helps to provide relevant policies to respond future climate risks over the JJJ region.

关键词： CMIP6 convection-permitting population exposure RegCM4 temperature extremes

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Seasonal constraint of dynamic water temperature on riverine dissolved inorganic nitrogen transport in land surface modeling

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Atmospheric and Oceanic Science Letters 2024年第4期17卷 35-40页

作者： Shuang Liu Kaiheng Hu zhenghui xie Yan Wang State Key Laboratory of Mountain Hazards and Engineering Safety Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengduChina State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina The National Key Laboratory of Water Disaster Prevention Nanjing Hydraulic Research InstituteNanjingChina

水体温度变化对河流可溶性无机氮(DIN)输送有着强烈控制作用.然而,在全球尺度上河流DIN输送量对水温度变化的响应尚不清楚.因此,本文基于陆面过程模式,耦合河流水温估算和DIN传输方案,设定有,无动态水温情景,对比研究陆面模拟中水温变... 详细信息

水体温度变化对河流可溶性无机氮(DIN)输送有着强烈控制作用.然而,在全球尺度上河流DIN输送量对水温度变化的响应尚不清楚.因此,本文基于陆面过程模式,耦合河流水温估算和DIN传输方案,设定有,无动态水温情景,对比研究陆面模拟中水温变化对河流DIN通量变化的影响.结果表明:在考虑水温动态变化后,在30°N和30°S之间, DIN通量年振幅减小5%–25%.在中国东部地区,水温动态变化使河流DIN通量在夏季减少1%–3%,在冬季增加1%–5%,对DIN通量具有明显的季节性约束作用,表明动态水温的表达在河流DIN输送模拟中的重要性.

关键词：陆面模拟河流氮输送水温变化季节变化全球尺度

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Coupling of the Calculated Freezing and Thawing Front Parameterization in the Earth System Model CAS-ESM

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Advances in Atmospheric Sciences 2023年第9期40卷 1671-1688页

作者： Ruichao LI Jinbo xie zhenghui xie Binghao JIA Junqiang GAO Peihua QIN Longhuan WANG Si CHEN State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 101408China School of Mathematics and Statistics Nanjing University of Information Science and TechnologyNanjing 210044China

The soil freezing and thawing process affects soil physical properties,such as heat conductivity,heat capacity,and hydraulic conductivity in frozen ground regions,and further affects the processes of soil energy,hydrology,and carbon and nitrogen *** this study,the calculation of freezing and thawing front parameterization was implemented into the earth system model of the Chinese Academy of Sciences(CAS-ESM)and its land component,the Common Land Model(CoLM),to investigate the dynamic change of freezing and thawing fronts and their *** results showed that the developed models could reproduce the soil freezing and thawing process and the dynamic change of freezing and thawing *** regionally averaged value of active layer thickness in the permafrost regions was 1.92 m,and the regionally averaged trend value was 0.35 cm yr–*** regionally averaged value of maximum freezing depth in the seasonally frozen ground regions was 2.15 m,and the regionally averaged trend value was–0.48 cm yr–*** active layer thickness increased while the maximum freezing depth decreased year by *** results contribute to a better understanding of the freezing and thawing cycle process.

关键词： frozen ground freezing and thawing fronts maximum freezing depth active layer thickness earth system model CAS-ESM

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Elucidating Dominant Factors Affecting Land Surface Hydrological Simulations of the Community Land Model over China

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Advances in Atmospheric Sciences 2023年第2期40卷 235-250页

作者： Jianguo LIU Zong-Liang YANG Binghao JIA Longhuan WANG Ping WANG zhenghui xie Chunxiang SHI School of Mathematics and Computational Science and Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan ProvinceHuaihua UniversityHuaihuaHunan 418008China Department of Geological Sciences The John A.and Katherine G.Jackson School of GeosciencesUniversity of Texas at AustinAustinTexas 78712-1722USA State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China National Meteorological Information Center China Meteorological AdministrationBeijing 100081China

In order to compare the impacts of the choice of land surface model(LSM)parameterization schemes,meteorological forcing,and land surface parameters on land surface hydrological simulations,and explore to what extent the quality can be improved,a series of experiments with different LSMs,forcing datasets,and parameter datasets concerning soil texture and land cover were *** simulations are run for the Chinese mainland on 0.1°×0.1°grids from 1979 to 2008,and the simulated monthly soil moisture(SM),evapotranspiration(ET),and snow depth(SD)are then compared and assessed against *** results show that the meteorological forcing is the most important factor governing *** that,SM seems to be also very sensitive to soil texture information;SD is also very sensitive to snow parameterization scheme in the *** Community Land Model version 4.5(CLM4.5),driven by newly developed observation-based regional meteorological forcing and land surface parameters(referred to as CMFD_CLM4.5_NEW),significantly improved the simulations in most cases over the Chinese mainland and its eight *** increased the correlation coefficient values from 0.46 to 0.54 for the SM modeling and from 0.54 to 0.67 for the SD simulations,and it decreased the root-mean-square error(RMSE)from 0.093 to 0.085 for the SM simulation and reduced the normalized RMSE from 1.277 to 0.201 for the SD *** study indicates that the offline LSM simulation using a refined LSM driven by newly developed observation-based regional meteorological forcing and land surface parameters can better model reginal land surface hydrological processes.

关键词： hydrological simulations land surface model meteorological forcing land surface parameters uncertainty

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Improving microwave brightness temperature predictions based on Bayesian model averaging ensemble approach

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Applied Mathematics and Mechanics(English Edition) 2016年第11期37卷 1501-1516页

作者： Binghao JIA zhenghui xie State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG) Institute of Atmospheric PhysicsChinese Academy of Sciences

The choices of the parameterizations for each component in a microwave emission model have significant effects on the quality of brightness temperature （Tb） sim- ulation. How to reduce the uncertainty in the Tb simulation is investigated by adopting a statistical post-processing procedure with the Bayesian model averaging （BMA） ensemble approach. The simulations by the community microwave emission model （CMEM） cou- pled with the community land model version 4.5 （CLM4.5） over China's Mainland are con- ducted by the 24 configurations from four vegetation opacity parameterizations （VOPs）, three soil dielectric constant parameterizations （SDCPs）, and two soil roughness param- eterizations （SRPs）. Compared with the simple arithmetical averaging （SAA） method, the BMA reconstructions have a higher spatial correlation coefficient （larger than 0.99） than the C-band satellite observations of the advanced microwave scanning radiometer on the Earth observing system （AMSR-E） at the vertical polarization. Moreover, the BMA product performs the best among the ensemble members for all vegetation classes, with a mean root-mean-square difference （RMSD） of 4 K and a temporal correlation coefficient of 0.64.

关键词： Bayesian model averaging (BMA) microwave brightness temperature com-munity microwave emission model (CMEM) community land model version 4.5 (CLM4.5)

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Effects of sample density on the assimilation performance of an explicit four-dimensional variational data assimilation method

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Science China Earth Sciences 2009年第11期52卷 1849-1856页

作者： TIAN XiangJun xie zhenghui ICCES/LASE Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China

The concepts of sample sphere radius and sample density are proposed in this paper to help illustrate that different vector transformations result in diverse sample density with the same sample ensemble, which finally affects their assimilation performance. Several numerical experiments using a onedimensional (1-D) soil water equation and synthetic observations are conducted to evaluate this new theory in land data assimilation.

关键词： POD/SVD-E4DVAR data assimilation sample density

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A land surface soil moisture data assimilation framework in consideration of the model subgrid-scale heterogeneity and soil water thawing and freezing

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Science China Earth Sciences 2008年第7期51卷 992-1000页

作者： TIAN XiangJun xie zhenghui Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China

The Ensemble Kalman Filter (EnKF) is well known and widely used in land data assimilation for its high precision and simple operation. The land surface models used as the forecast operator in a land data assimilation system are usually designed to consider the model subgrid-heterogeneity and soil water thawing and freezing. To neglect their effects could lead to some errors in soil moisture assimilation. The dual EnKF method is employed in soil moisture data assimilation to build a soil moisture data as- similation framework based on the NCAR Community Land Model version 2.0 (CLM 2.0) in considera- tion of the effects of the model subgrid-heterogeneity and soil water thawing and freezing: Liquid volumetric soil moisture content in a given fraction is assimilated through the state filter process, while solid volumetric soil moisture content in the same fraction and solid/liquid volumetric soil moisture in the other fractions are optimized by the parameter filter. Preliminary experiments show that this dual EnKF-based assimilation framework can assimilate soil moisture more effectively and precisely than the usual EnKF-based assimilation framework without considering the model subgrid-scale heteroge- neity and soil water thawing and freezing. With the improvement of soil moisture simulation, the soil temperature-simulated precision can be also improved to some extent.

关键词： dual EnKF NCAR/CLM soil moisture assimilation framework subgrid-heterogeneity soil water thawing and freezing

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Impacts of hydraulic redistribution on eco-hydrological cycles： A case study over the Amazon basin

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Science China Earth Sciences 2018年第9期61卷 1330-1340页

作者： Yuanyuan WANG Binghao JIA zhenghui xie Beijing Meteorological Observatory Beijing 100089 China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China

Hydraulic redistribution(HR)refers to the process of soil water transport through the low-resistance pathway provided by plant *** has been observed in field studies and proposed to be one of the processes that enable plants to resist water ***,most land-surface models(LSMs)currently do not include this underground root *** this study,a HR scheme was incorporated into the Community Land Model version 4.5(CLM4.5)to investigate the effect of HR on the eco-hydrological *** paired numerical simulations(with and without the new HR scheme)were conducted for the Tapajos National Forest km83(BRSa3)site and the *** for the BRSa3 site in the Amazon showed that HR during the wet season was small,<0.1 mm day^(–1),transferring water from shallow wet layers to deep dry layers at night;however,HR in the dry season was more obvious,up to 0.3 mm day^(–1),transferring water from deep wet layers to shallow dry layers at *** incorporating HR into CLM4.5,the new model increased gross primary production(GPP)and evapotranspiration(ET)by 10%and 15%,respectively,at the BRSa3 site,partly overcoming the *** the Amazon,regional analysis also revealed that vegetation responses(including GPP and ET)to seasonal drought and the severe drought of 2005 were better captured with the HR scheme incorporated.

关键词：亚马逊 eco 再分配水文学土壤水分蒸发蒸腾损失总量水力案例周期

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An explicit four-dimensional variational data assimilation method based on the proper orthogonal decomposition: Theoretics and evaluation

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Science China Earth Sciences 2009年第2期52卷 279-286页

作者： TIAN XiangJun xie zhenghui Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China

The proper orthogonal decomposition (POD) method is used to construct a set of basis functions for spanning the ensemble of data in a certain least squares optimal sense. Compared with the singular value decomposition (SVD), the POD basis functions can capture more energy in the forecast ensemble space and can represent its spatial structure and temporal evolution more effectively. After the analysis variables are expressed by a truncated expansion of the POD basis vectors in the ensemble space, the control variables appear explicitly in the cost function, so that the adjoint model, which is used to de-rive the gradient of the cost function with respect to the control variables, is no longer needed. The application of this new technique significantly simplifies the data assimilation process. Several as-similation experiments show that this POD-based explicit four-dimensional variational data assimila-tion method performs much better than the usual ensemble Kalman filter method on both enhancing the assimilation precision and reducing the computation cost. It is also better than the SVD-based ex-plicit four-dimensional assimilation method, especially when the forecast model is not perfect and the forecast error comes from both the noise of the initial filed and the uncertainty of the forecast model.

关键词： POD data assimilation 4DVAR explicit method

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A new approach for Bayesian model averaging

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Science China Earth Sciences 2012年第11期55卷 1336-1344页

作者： TIAN XiangJun xie zhenghui WANG AiHui YANG XiaoChun The International Center for Climate and Environment Sciences Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Nansen-Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Meterological Bureau of Xi'an City Xi'an 710016China

Bayesian model averaging(BMA) is a recently proposed statistical method for calibrating forecast ensembles from numerical weather ***,successful implementation of BMA requires accurate estimates of the weights and variances of the individual competing models in the *** methods,namely the Expectation-Maximization(EM) and the Markov Chain Monte Carlo(MCMC) algorithms,are widely used for BMA model *** methods have their own respective strengths and *** this paper,we first modify the BMA log-likelihood function with the aim of removing the addi-tional limitation that requires that the BMA weights add to one,and then use a limited memory quasi-Newtonian algorithm for solving the nonlinear optimization problem,thereby formulating a new approach for BMA(referred to as BMA-BFGS).Several groups of multi-model soil moisture simulation experiments from three land surface models show that the performance of BMA-BFGS is similar to the MCMC method in terms of simulation accuracy,and that both are superior to the EM *** the other hand,the computational cost of the BMA-BFGS algorithm is substantially less than for MCMC and is al-most equivalent to that for EM.

关键词：贝叶斯模型平均 MCMC方法非线性优化问题拟牛顿算法天气预报模型 EM算法 BFGS算法

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