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A data assimilation-based method for optimizing parameterization schemes in a land surface process model

Science China Earth Sciences 2015年第12期58卷 2220-2235页

作者： ZHANG ShengLei CHEN LiangFu SU Lin JIA Li State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences

Optimizing the parameters of a land surface process model(LSPM) through data assimilation(DA) can not only improve and perfect the parameterization schemes in the LSPM through the physical mechanism, but also increase its regional adaptability and simulation capability. This has practical importance for improving simulation results and the climate-prediction capability of general circulation models(GCMs) and regional climate models(RCMs). This paper presents a DA-based method for optimizing the parameterization schemes in LSPMs. We optimize the unsaturated-soil water flow(Un SWF) model as an example by developing a soil-moisture assimilation scheme based on the Un SWF model and the extended Kalman filter(EKF) algorithm, and then combining them with the Variable Infiltration Capacity(VIC) model. Using a month as the assimilation window, we used the Shuffled Complex Evolution–University of Arizona(SCE-UA) algorithm to minimize the objective function through simulated and assimilated soil moisture, achieved the best fit with the given objective function measurement, and optimized the parameters of the Un SWF model, including the saturated-soil hydraulic conductivity, moisture content, matrix potential, and the Clapp and Hornberger constant. The optimal values of the model parameters were obtained during the DA period(the year 1986), and then the optimized parameters were used to improve the Un SWF model. Finally, numerical simulation experiments were carried out from 1986 to 1993 to evaluate the simulation capability of the improved model and to explore and realize the DA-based method for optimizing the soil water parameterization scheme in LSPMs. The experimental results indicated that the optimized model parameters improved and perfected the model based on the physical mechanism, and increased its simulation capability; the optimized model parameters had good temporal portability and their adaptability was stronger, achieving the aim of improving the model. Therefore

关键词： data assimilation land surface process model parameterization scheme SCE-UA algorithm soft moisture

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Plant drought tolerance trait is the key parameter in improving the modeling of terrestrial transpiration in arid and semi-arid regions

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Atmospheric and Oceanic Science Letters 2022年第1期15卷 35-41页

作者： Xintao Liu Xingjie Lu Shulei Zhang Zhongwang Wei Nan Wei Shupeng Zhang Hua Yuan Wei Shangguan Shaofeng Liu Jianfeng Huang Lu Li Xiulan Ye Jinxuan Zhou Wenke Hu Yongjiu Dai Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Guangdong Province Key Laboratory for Climate Change and Natural Disaster StudiesSchool of Atmospheric SciencesSun Yat‐sen UniversityGuangzhouChina

The prediction of precipitation depends on accurate modeling of terrestrial *** recent decades,the trait-based plant hydraulic stress scheme has been developed in land surface models,in order to better predict the hydraulic constraint on terrestrial ***,the role that each plant functional trait plays in the modeling of transpiration remains *** importance of different plant functional traits for modeled transpiration needs to be ***,the Morris sensitivity analysis method was implemented in the Common land model with the plant hydraulic stress scheme(CoLM-P_(50)HS).Traits related to drought tolerance(P_(50);),stomata,and photosynthesis were screened as the most critical from all 17 plant *** 12 FLUXNET sites,the importance of P_(50);,measured by normalized sensitivity scores,increased towards lower precipitation,whereas the importance of stomatal traits and photosynthetic traits decreased towards drier climate conditions.P_(50);was more important than stomatal traits and photosynthetic traits in arid or semi-arid sites,which implies that hydraulic safety strategies are more crucial than plant growth strategies when plants frequently experience *** variation in drought tolerance traits further proved the coexistence of multiple plant strategies of hydraulic *** the variation in drought tolerance traits may potentially bias the modeling of *** measurements of drought tolerance traits are therefore necessary to help better represent the diversity of plant hydraulic functions.

关键词： Transpiration land surface process model Sensitivity analysis Plant hydraulic stress scheme Plant traits

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Influences of agricultural phenology dynamic on land surface biophysical process and climate feedback

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Journal of Geographical Sciences 2017年第9期27卷 1085-1099页

作者： LIU Fengshan CHEN Ying SHI Wenjiao ZHANG Shuai TAO Fulu GE Quansheng Key Laboratory of land surface Pattern and Simulation Institute of Geographic Sciences and Natural Re- sources Research CAS Beijing 100101 China Fujian Agriculture and Forestry University Fuzhou 350002 China College of Resources and Environment University of Chinese Academy of Sciences Beijing 100049 China

Response and feedback of land surface research priorities in the field of geoscience. The process to climate change is one of the current study paid more attention to the impacts of global change on land surface process, but the feedback of land surface process to climate change has been poorly understood. It is becoming more and more meaningful under the framework of Earth system science to understand systematically the relationships between agricultural phenology dynamic and biophysical process, as well as the feedback on climate. In this paper, we summarized the research progress in this field, including the fact of agricultural phenology change, parameterization of phenology dynamic in land surface progress model, the influence of agricultural phenology dynamic on biophysical process, as well as its feedback on climate. The results showed that the agriculture phenophase, represented by the key phenological phases such as sowing, flowering and maturity, had shifted significantly due to the impacts of climate change and agronomic management. The digital expressions of land surface dynamic process, as well as the biophysical process and atmospheric process, were improved by coupling phenology dynamic in land surface model. The agricultural phenology dynamic had influenced net radiation, latent heat, sensible heat, albedo, temperature, precipitation, circulation, playing an important role in the surface energy partitioning and climate feedback. Considering the importance of agricultural phenology dynamic in land surface biophysical process and climate feedback, the following research priorities should be stressed：（1） the interactions between climate change and land surface phenology dynamic; （2） the relations between agricultural phenology dynamic and land surface reflectivity at different spectrums; （3） the contributions of crop physiology characteristic changes to land surface biophysical process; （4） the regional differences of climate feedbacks from phenology d

关键词： agricultural phenology land surface biophysical process land surface process model climate feedback

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