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Integrating remotely sensed water stress factor with a crop growth model for winter wheat yield estimation in the North China Plain during 2008–2018

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The Crop Journal 2022年第5期10卷 1470-1482页

作者： Wen Zhuo Shibo Fang Dong Wu Lei Wang Mengqian Li Jiansu Zhang Xinran Gao State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Collaborative Innovation Centre on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science&TechnologyNanjing 210044JiangsuChina School of Geography and Earth Sciences McMaster UniversityHamiltonOntario L8S 4L8Canada

Accurate estimation of regional-scale crop yield under drought conditions allows farmers and agricultural agencies to make well-informed decisions and guide agronomic management. However, few studies have focused on using the crop model data assimilation(CMDA) method for regional-scale winter wheat yield estimation under drought stress and partial-irrigation conditions. In this study, we developed a CMDA framework to integrate remotely sensed water stress factor(MOD16 ET PET) with the WOFOST model using an ensemble Kalman filter(En KF) for winter wheat yield estimation at the regional scale in the North China Plain(NCP) during 2008–2018. According to our results, integration of MOD16 ET PETwith the WOFOST model produced more accurate estimates of regional winter wheat yield than open-loop simulation. The correlation coefficient of simulated yield with statistical yield increased for each year and error decreased in most years, with r ranging from 0.28 to 0.65 and RMSE ranging from 700.08 to1966.12 kg ha. Yield estimation using the CMDA method was more suitable in drought years(r = 0.47, RMSE = 919.04 kg ha) than in normal years(r = 0.30, RMSE = 1215.51 kg ha). Our approach performed better in yield estimation under drought conditions than the conventional empirical correlation method using vegetation condition index(VCI). This research highlighted the potential of assimilating remotely sensed water stress factor, which can account for irrigation benefit, into crop model for improving the accuracy of winter wheat yield estimation at the regional scale especially under drought conditions, and this approach can be easily adapted to other regions and crops.

关键词： WOFOST Evapotranspiration Drought data assimilation Winter wheat yield

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Improving the Analyses and Forecasts of a Tropical Squall Line Using Upper Tropospheric Infrared Satellite Observations

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Advances in Atmospheric Sciences 2022年第5期39卷 733-746页

作者： Man-Yau CHAN Xingchao CHEN Department of Meteorology and Atmospheric Science and Center for Advanced Data Assimilation and Predictability TechniquesThe Pennsylvania State UniversityUniversity ParkPennsylvaniaPA 16802USA

The advent of modern geostationary satellite infrared radiance observations has noticeably improved numerical weather forecasts and analyses.However,compared to midlatitude weather systems and tropical cyclones,research into using infrared radiance observations for numerically predicting and analyzing tropical mesoscale convective systems remain mostly fallow.Since tropical mesoscale convective systems play a crucial role in regional and global weather,this deficit should be addressed.This study is the first of its kind to examine the potential impacts of assimilating all-sky upper tropospheric infrared radiance observations on the prediction of a tropical squall line.Even though these all-sky infrared radiance observations are not directly affected by lower-tropospheric winds,the high-frequency assimilation of these all-sky infrared radiance observations improved the analyses of the tropical squall line’s outflow position.Aside from that,the assimilation of all-sky infrared radiance observations improved the analyses and prediction of the squall line’s cloud field.Finally,reducing the frequency of assimilating these all-sky infrared radiance observations weakened these improvements to the analyzed outflow position,as well as the analyses and predictions of cloud fields.

关键词： data assimilation infrared satellite observations numerical weather prediction mesoscale convective systems tropical meteorology

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assimilation of All-Sky Radiance from the FY-3 MWHS-2 with the Yinhe 4D-Var System

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Journal of Meteorological Research 2022年第5期36卷 750-766页

作者： Shuo MA Weimin ZHANG Xiaoqun CAO Yanlai ZHAO Bainian LIU College of Meteorology and Oceanography National University of Defense TechnologyChangsha 410073

Compared with traditional microwave humidity sounding capabilities at 183 GHz,new channels at 118 GHz have been mounted on the second generation of the Microwave Humidity Sounder(MWHS-2)onboard the Chinese FY-3C and FY-3D polar orbit meteorological satellites,which helps to perform moisture sounding.In this study,as the allsky approach can manage non-linear and non-Gaussian behavior in cloud-and precipitation-affected satellite radiances,the MWHS-2 radiances in all-sky conditions were first assimilated in the Yinhe four-dimensional variational data assimilation(YH4DVAR)system.The data quality from MWHS-2 was evaluated based on observation minus background statistics.It is found that the MWHS-2 data of both FY-3C and FY-3D are of good quality in general.Six months of MWHS-2 radiances in all-sky conditions were then assimilated in the YH4DVAR system.Based on the forecast scores and observation fits,we conclude that the all-sky assimilation of the MWHS-2 at 118-and 183-GHz channels on FY-3C/D is beneficial to the analysis and forecast fields of the temperature and humidity,and the impact on the forecast skill scores is neutral to positive.Additionally,we compared the impacts of assimilating the 118-GHz channels and the equivalent Advanced Microwave Sounding Unit-A(AMSUA)channels on global forecast accuracy in the absence of other satellite observations.Overall,the impact of the 118-GHz channels on the forecast accuracy is not as large as that for the equivalent AMSUA channels.Nevertheless,all-sky radiance assimilation of MWHS-2 in the YH4DVAR system has indeed benefited from the 118-GHz channels.

关键词： Microwave Humidity Sounder-2 data assimilation Yinhe four-dimensional variational data assimilation all-sky radiance Fengyun-3

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An inversion model based on GEOS-Chem for estimating global and China's terrestrial carbon fluxes in 2019

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气候变化研究进展:英文版 2023年第1期14卷 49-61页

作者： Chong-Yuan WU Xiao-Ye ZHANG Li-Feng GUO Jun-Ting ZHONG De-Ying WANG Chang-Hong MIAO Xiang GAO Xi-Liang ZHANG Monitoring and Assessment Center for GHGs and Carbon&Key Laboratory of Atmospheric Chemistry of China Meteorological Administration Chinese Academy of Meteorological SciencesBeijing 100081China Zhejiang Institute of Meteorological Science Zhejiang Meteorological BureauHangzhou 310017China Laboratory of Climate Change Mitigation and Carbon Neutrality Henan UniversityZhengzhou 450001China State Key Laboratory of Clean Energy Utilization State Environmental Protection Center for Coal-Fired Air Pollution ControlZhejiang UniversityHangzhou 310027China Institute of Energy Environment and EconomyTsinghua UniversityBeijing 100084China

The 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories added the method of assimilating atmospheric CO_(2) concentrations to invert carbon sources and sinks;however,many global carbon inversion models are not publicly available.In addition,our regional assimilation inversion system,CCMVS-R(China Carbon Monitoring,Verification and Supporting for Regional),needs a global carbon inversion model with higher assimilation efficiency to provide boundary conditions.Here,an inversion model based on the global atmospheric chemistry model GEOS-Chem and a more accurate and easier-to-implement ensemble square root Kalman filter(EnSRF)algorithm is constructed and used to infer global and China's carbon fluxes in 2019.Atmospheric CO_(2) concentrations from ObsPack sites and five additional CO_(2) observational sites from China's Greenhouse Gas Observation Network(CGHGNET)were used for data assimilation to improve the estimate.The inverted annual global terrestrial and oceanic carbon uptake is 2.12 and 2.53 Pg C per year,respectively,accounting for 21.1%and 25.1%of global fossil fuel CO_(2) emissions.The remaining 5.41 Pg C per year in the atmosphere is consistent with the global atmospheric CO_(2) growth rates of 5.44 Pg C per year reported by the National Oceanic and Atmospheric Administration(NOAA),showing that the inversion model can provide a reasonable estimate of global-scale natural carbon sinks.The inverted terrestrial carbon sink of China is 0.37 Pg C per year,accounting for approximately 13%of China's fossil CO_(2) emissions.

关键词： CO_(2) data assimilation EnSRF GEOS-Chem Terrestrial carbon fluxes

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Improvement of short-term forecasting in the northwest Pacific through assimilating Argo data into initial fields

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Acta Oceanologica Sinica 2013年第7期32卷 57-65页

作者： FU Hongli CHU Peter C HAN Guijun HE Zhongjie LI Wei ZHANG Xuefeng Key Laboratory of State Oceanic Adminstration for Marine Environmental Information Technology National Marine Data and Information ServiceState Oceanic Administration Naval Ocean Analysis and Prediction Laboratory Naval Postgraduate School

The impact of assimilating Argo data into an initial field on the short-term forecasting accuracy of temper- ature and salinity is quantitatively estimated by using a forecasting system of the western North Pacific, on the base of the Princeton ocean model with a generalized coordinate system （POMgcs）. This system uses a sequential multigrid three-dimensional variational （3DVAR） analysis scheme to assimilate observation da- ta. Two numerical experiments were conducted with and without Argo temperature and salinity profile data besides conventional temperature and salinity profile data and sea surface height anomaly （SSHa） and sea surface temperature （SST） in the process of assimilating data into the initial fields. The forecast errors are estimated by using independent temperature and salinity profiles during the forecasting period, including the vertical distributions of the horizontally averaged root mean square errors （H-RMSEs） and the horizontal distributions of the vertically averaged mean errors （MEs） and the temporal variation of spatially averaged root mean square errors （S-RMSEs）. Comparison between the two experiments shows that the assimila- tion of Argo data significantly improves the forecast accuracy, with 24% reduction of H-RMSE maximum for the temperature, and the salinity forecasts are improved more obviously, averagely dropping of 50% for H-RMSEs in depth shallower than 300 m. Such improvement is caused by relatively uniform sampling of both temperature and salinity from the Argo drifters in time and space.

关键词： data assimilation Argo data western North Pacific ocean prediction

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Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China

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Acta Oceanologica Sinica 2015年第7期34卷 54-64页

作者： JI Qiyan ZHU Xueming WANG Hui LIU Guimei GAO Shan JI Xuanliang XU Qing Key Laboratory of Ministry of Education for Coastal Disaster and Defence Hohai University Key Laboratory of Research on Marine Hazards Forecasting National Marine Environmental Forecasting CenterState Oceanic Administration

The prediction of sea surface temperature （SST） is an essential task for an operational ocean circulation model. A sea surface heat flux, an initial temperature field, and boundary conditions directly affect the accuracy of a SST simulation. Here two quick and convenient data assimilation methods are employed to improve the SST simulation in the domain of the Bohai Sea, the Yellow Sea and the East China Sea （BYECS）. One is based on a surface net heat flux correction, named as Qcorrection （QC）, which nudges the flux correction to the model equation; the other is ensemble optimal interpolation （EnOI）, which optimizes the model initial field. Based on such two methods, the SST data obtained from the operational SST and sea ice analysis （OSTIA） system are assimilated into an operational circulation model for the coastal seas of China. The results of the simulated SST based on four experiments, in 2011, have been analyzed. By comparing with the OSTIA SST, the domain averaged root mean square error （RMSE） of the four experiments is 1.74, 1.16, 1.30 and 0.91~C, respectively; the improvements of assimilation experiments Exps 2, 3 and 4 are about 33.3%, 25.3%, and 47.7%, respectively. Although both two methods are effective in assimilating the SST, the EnOI shows more advantages than the QC, and the best result is achieved when the two methods are combined. Comparing with the observational data from coastal buoy stations, show that assimilating the high-resolution satellite SST products can effectively improve the SST prediction skill in coastal regions.

关键词： sea surface temperature data assimilation ensemble optimal interpolation quick correction Bohai Sea Yellow Sea East China Sea

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Reconstruction of eddies by assimilating satellite altimeter data into Princeton Ocean Model

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Acta Oceanologica Sinica 2010年第1期29卷 1-11页

作者： YIN Xunqiang QIAO Fangli XIA Changshui LU Xin＇gang YANG Yongzeng College of Physical and Environmental Oceanography Ocean University of China Qingdao First Institute of Oceanography State Oceanic Administration Qingdao 266061 China Key Laboratory of Marine Science and Numerical Modeling （MASNUM） State Oceanic Administration Qingdao 266061 China

An optimal interpolation assimilation model for satellite altimetry data is developed based on Princeton Ocean Model （POM）, which is applied in a quasi-global domain, by the method of isotropic correlation between sea level anomaly （SLA） and sea temperature anomaly. The performance of this assimilation model is validated by the modeled results of SLA and the current patterns. Comparisons between modeling and satellite data show that both the magnitudes and distribution patterns of the sinmlated SLA are improved by assimilation. The most significant improvement is that meso-scale systems, e.g., eddies, are well reconstructed. The evolution of an eddy located in the northwest Pacific Ocean is traced by using the assimilation model. Model results show that during three months the eddy migrated southwestward for about 6 degrees before merging into the Kuroshio. The three dimensional structure of this eddy on 12 August 2001 is further analyzed. The strength of this warm, cyclonic eddy decreases with the increase of depth. The eddy shows different horizontal patterns at different layers, and the SLA and temperature fields agree with each other well. This study suggests that this kind of data assimilation is economic and reliable for eddy reconstruction, and can be used as a promising technique in further studies of ocean eddies as well as other fine circulation structures.

关键词： data assimilation eddy numerical model optimal interpolation POM

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Equipment remaining useful life prediction oriented symbiotic simulation driven by real-time degradation data

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International Journal of Modeling, Simulation, and Scientific Computing 2018年第2期9卷 1-22页

作者： Chenglong Ge Yuanchang Zhu Yanqiang Di Department of Electronic and Optics Engineering Mechanical Engineering College Shijiazhuang 050003P.R.China

As an emerging simulation technology in the field of system modeling and simulation,the equipment symbiotic simulation has become research emphasis.In the field of equipment maintenance support,the outstanding problem of equipment remaining useful life(RUL)prediction is analyzed,i.e.,the stable model parameters without self-evolution ability,which has become the primary factor that hinders self-adaptive prediction of equipment RUL.Combined with parallel systems theory,the equipment RUL prediction oriented symbiotic simulation framework is proposed on the basis of modeling analysis and Wiener state space model(SSM)is taken as the basic simulation model in the framework.Driven by the dynamic injected equipment degradation observation data,the model parameters are updated online by using expectation maximum(EM)algorithm and the data assimilation between simulation outputs and observation data is executed by using Kalman filter,so as to realize dynamic evolution of the simulation model.The simulation model evolution which makes the simulation outputs close to equipment real degradation state provides high fidelity model and data for predicting equipment RUL accurately.The framework is verified by the performance degradation data of a bearing.The simulation results show that the symbiotic simulation method can accurately simulate the equipment performance degradation process and the self-adaptive prediction of equipment RUL is realized on the basis of improving prediction accuracy,proving the feasibility and effectiveness of symbiotic simulation method.

关键词： Symbiotic simulation model evolution remaining useful life data assimilation parameter estimation.

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Assimilating AMSU-A Radiance data with the WRF Hybrid En3DVAR System for Track Predictions of Typhoon Megi(2010)

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Advances in Atmospheric Sciences 2015年第9期32卷 1231-1243页

作者： SHEN Feifei MIN Jinzhong Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science & Technology

The impact of assimilating radiances from the Advanced Microwave Sounding Unit-A（AMSU-A） on the track prediction of Typhoon Megi（2010） was studied using the Weather Research and Forecasting（WRF） model and a hybrid ensemble threedimensional variational（En3DVAR） data assimilation（DA） system.The influences of tuning the length scale and variance scale factors related to the static background error covariance（BEC） on the track forecast of the typhoon were studied.The results show that,in typhoon radiance data assimilation,a moderate length scale factor improves the prediction of the typhoon track.The assimilation of AMSU-A radiances using 3DVAR had a slight positive impact on track forecasts,even when the static BEC was carefully tuned to optimize its performance.When the hybrid DA was employed,the track forecast was significantly improved,especially for the sharp northward turn after crossing the Philippines,with the flow-dependent ensemble covariance.The flow-dependent BEC can be estimated by the hybrid DA and was capable of adjusting the position of the typhoon systematically.The impacts of the typhoon-specific BEC derived from ensemble forecasts were revealed by comparing the analysis increments and forecasts generated by the hybrid DA and 3DVAR.Additionally,for 24 h forecasts,the hybrid DA experiment with use of the full flow-dependent background error substantially outperformed 3DVAR in terms of the horizontal winds and temperature in the lower and mid-troposphere and for moisture at all levels.

关键词： data assimilation radiance observation operator

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Development of a middle and low latitude theoretical ionospheric model and an observation system data assimilation experiment

Development of a middle and low latitude theoretical ionosph...

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中国科学院地质与地球物理研究所2008学术年会

作者： YUE XinAn~(1,2,3),WAN WeiXing~(1+),LIU LiBo~1,LE HuiJun~1,CHEN YiDing~1 & YU Tao~(4,1) 1 Institute of Geology and Geophysics,Chinese Academy of Sciences,Beijing 100029,China 2 Wuhan Institute of Physics and Mathematics,Chinese Academy of Sciences,Wuhan 430071,China 3 Graduate University of Chinese Academy of Sciences,Beijing 100049,China 4 National Center for Spaceweather,CMA,Beijing 100081,China

On the basis of previous work,we develop a middle and low latitude theoretical ionospheric model in this paper,named Theoretical Ionospheric Model of the Earth in the Institute of Geology and Geophysics, Chinese Academy of Sciences(TIME-IGGCAS).TIME-IGGCAS solves the equations of mass continuity, motion and energy of electron and ions self-consistently and uses an eccentric dipole field approximation to the Earth’s magnetic field.We combine the Eulerian and Lagrangian approaches in the model and take account of the plasma E×B drift velocity.Calculation results reveal that the model is steady and credible and can reproduce most large-scale features of ionosphere.By using TIME-IGGCAS,we carried out an observation system data assimilation experiment.assimilation results show that the E×B drift velocity can be accurately estimated by ingesting the observed foF2 and hmF2 into the model applying nonlinear least-square fit method.We suggest that this work is of great significance in the development of ionospheric data assimilation model to give better nowcast and forecast of ionosphere.

关键词： ionosphere theoretical model data assimilation nonlinear least-square fit method

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