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Simulations of the Tropical Intraseasonal Oscillation by the Atmospheric General Circulation Model of the beijing climate center

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Acta meteorologica Sinica 2010年第5期24卷 571-583页

作者：董敏吴统文王在志张芳 Laboratory for climate Studies of CMA National Climate Center

The performance of BCC （beijing climate center） AGCM 2.0.1 （Atmospheric General Circulation Model version 2.0.1） in simulating the tropical intraseasonal oscillation （TIO） is examined in this *** simulations are validated against observation and compared with the NCAR CAM3 （Community Atmosphere Model version 3） *** BCC AGCM2.0.1 is developed based on the original BCC AGCM （version 1） and NCAR *** reference atmosphere and reference pressure are introduced into the ***,the original prognostic variables of temperature and surface pressure become their departures from the reference atmosphere.A new Zhang-McFarlane convective parameterization scheme is incorporated into the model with a few *** modifications include those in the boundary layer process and snow cover *** simulations are run for 52 yr from 1949 to 2001 under the lower boundary conditions of observed monthly *** TIOs from the model are *** comparison shows that the NCAR CAM3 has a poor ability in simulating the *** simulated strength of the TIO is very *** energy of the eastward moving waves is similar to that of the westward moving waves in *** in observation the former is much larger than the *** seasonal variation and spatial distribution of the TIO produced by CAM3 are also much different from the *** ability of the BCC AGCM2.0.1 in simulating the TIO is significantly *** simulated TIO is *** strength of the TIO produced by the BCC AGCM2.0.1 is close to the *** energy of eastward *** is much stronger than that of the westward moving waves,which is consistent with the *** is no significant difference in the seasonal variation and spatial distribution of the TIO between the BCC model simulation and the *** general,the BCC model performs better than CAM3 in simulating the TIO.

关键词： beijing climate center (BCC) atmospheric general circulation model (AGCM) tropical intraseasonal oscillation (TIO) simulation study

climate effects of the GlobeLand30 land cover dataset on the beijing climate center climate model simulations

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Science China Earth Sciences 2016年第9期59卷 1754-1764页

作者： SHI XueLi NIE SuPing JU WeiMin YU Le National climate center Beijing 100081 China International Institute for Earth System Science (ESSI) Nanjing University Nanjing 210093 China Ministry of Education Key Laboratory for Earth System Modeling Center for Earth System Science Tsinghua University Beijing 100084 China Joint center for Global Change Studies Beijing 100875 China

Land cover is one of the most basic input elements of land surface and climate models. Currently, the direct and indirect effects of land cover data on climate and climate change are receiving increasing attentions. In this study, a high resolution(30 m) global land cover dataset(Globe Land30) produced by Chinese scientists was, for the first time, used in the beijing climate center climate System Model(BCC_CSM) to assess the influences of land cover dataset on land surface and climate simulations. A two-step strategy was designed to use the Globe Land30 data in the model. First, the Globe Land30 data were merged with other satellite remote sensing and climate datasets to regenerate plant functional type(PFT) data fitted for the BCC_CSM. Second, the up-scaling based on an area-weighted approach was used to aggregate the fine-resolution Globe Land30 land cover type and area percentage with the coarser model grid resolutions globally. The Globe Land30-based and the BCC_CSM-based land cover data had generally consistent spatial distribution features, but there were some differences between them. The simulation results of the different land cover type dataset change experiments showed that effects of the new PFT data were larger than those of the new glaciers and water bodies(lakes and wetlands). The maximum value was attained when dataset of all land cover types were changed. The positive bias of precipitation in the mid-high latitude of the northern hemisphere and the negative bias in the Amazon, as well as the negative bias of air temperature in part of the southern hemisphere, were reduced when the Globe Land30-based data were used in the BCC_CSM atmosphere model. The results suggest that the Globe Land30 data are suitable for use in the BCC_CSM component models and can improve the performance of the land and atmosphere simulations.

关键词： Land cover climate model Application strategy Numerical simulation Air temperature Precipitation

Improvement of Soil Moisture Simulation in Eurasia by the beijing climate center climate System Model from CMIP5 to CMIP6

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Advances in Atmospheric Sciences 2021年第2期38卷 237-252页

作者： Yinghan SANG Hong-Li REN Xueli SHI Xiaofeng XU Haishan CHEN School of Atmospheric Sciences Nanjing University of Information Science&TechnologyNanjing 210044China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Laboratory for climate Studies&CMA-NJU Joint Laboratory for climate Prediction Studies National Climate CenterChina Meteorological AdministrationBeijing 100081China China Meteorological Administration Beijing 100081China

This study provides a comprehensive evaluation of historical surface soil moisture simulation(1979-2012)over Eurasia at annual and seasonal time scales between two medium-resolution versions of the beijing climate center climate System Model(BCC-CSM)—one that is currently participating in phase 6 of the Coupled Model Intercomparison Project(CMIP6),i.e.,BCC-CSM2-MR,and the other,BCC-CSM1.1m,which participated in *** show that BCC-CSM2-MR is more skillful in reproducing the climate mean states and standard deviations of soil moisture,with pattern correlations increased and biases reduced ***-CSM2-MR performs better in capturing the first two primary patterns of soil moisture anomalies,where the period of the corresponding time series is closer to that of reference *** show that BCC-CSM2-MR performs at a high level among multiple models of CMIP6 in terms of centered pattern correlation and“amplitude of variation”(relative standard deviation).In general,the centered pattern correlation of BCC-CSM2-MR,ranging from 0.61 to 0.87,is higher than the multi-model mean of CMIP6,and the relative standard deviation is 0.75,which surmounts the overestimations in most of the CMIP6 *** to the vital role played by precipitation in land-atmosphere interaction,possible causes of the improvement of soil moisture simulation are further related to precipitation in *** results indicate that a better description of the relationship between soil moisture and precipitation and a better reproduction of the climate mean precipitation by the model may result in the improved performance of soil moisture simulation.

关键词： BCC-CSM soil moisture CMIP6 historical simulation Eurasia

Evaluation of the Tropical Variability from the beijing climate center's Real-Time Operational Global Ocean Data Assimilation System

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Advances in Atmospheric Sciences 2016年第2期33卷 208-220页

作者： Wei ZHOU Mengyan CHEN Wei ZHUANG Fanghua XU Fei ZHENG Tongwen WU Xin WANG Laboratory for climate Studies National Climate Center China Meteorological Administration State Key Laboratory of Tropical Oceanography South China Sea Institute of OceanologyChinese Academy of Sciences Ministry of Education Key Laboratory for Earth System Modeling and Center for Earth System ScienceTsinghua University International center for climate and Environment Science Institute of Atmospheric PhysicsChinese Academy of Sciences

The second-generation Global Ocean Data Assimilation System of the beijing climate center （BCC_GODAS2.0） has been run daily in a pre-operational mode. It spans the period 1990 to the present day. The goal of this paper is to introduce the main components and to evaluate BCC_GODAS2.0 for the user community. BCC_GODAS2.0 consists of an observational data preprocess, ocean data quality control system, a three-dimensional variational （3DVAR） data assimilation, and global ocean circulation model [Modular Ocean Model 4 （MOM4）]. MOM4 is driven by six-hourly fluxes from the National centers for Environmental Prediction. Satellite altimetry data, SST, and in-situ temperature and salinity data are assimilated in real time. The monthly results from the BCC_GODAS2.0 reanalysis are compared and assessed with observations for 1990-201 I. The climatology of the mixed layer depth of BCC_GODAS2.0 is generally in agreement with that of World Ocean Atlas 2001. The modeled sea level variations in the tropical Pacific are consistent with observations from satellite altimetry on interannual to decadal time scales. Performances in predicting variations in the SST using BCC_GODAS2.0 are evaluated. The standard deviation of the SST in BCC_GODAS2.0 agrees well with observations in the tropical Pacific. BCC_GODAS2.0 is able to capture the main features of E1 Nifio Modoki I and Modoki II, which have different impacts on rainfall in southern China. In addition, the relationships between the Indian Ocean and the two types of E1 Nino Modoki are also reproduced.

关键词： operational oceanography global ocean 3DVAR E1 Nifio interannual variability

Representation and Predictability of the East Asia-Pacific Teleconnection in the beijing climate center and UK Met Office Subseasonal Prediction Systems

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Journal of Meteorological Research 2020年第5期34卷 941-964页

作者： Jie WU Peiqun ZHANG Lei LI Hong-Li REN Xiangwen LIU Adam A.SCAIFE Shuai ZHANG Laboratory far climate Studies&China Meteorological Administration-Nanjing University Joint Laboratory for climate Prediction Studies National Climate CenterChina Meteorological AdministrationBeijing 100081China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing 100081China Met Office Hadley Centre Exeter EXI 3PBUK College of Engineering Mathematics and Physical SciencesUniversity of ExeterDevon EX44QFUK Secretariat of Jiangxi Meteorological Society Nanchang 330096China Institute of Urban Meteorology China Meteorological AdministrationBeijing 100089China

Based on the empirical orthogonal function(EOF) analysis, the East Asia–Pacific(EAP) teleconnection is extracted as the leading mode of the subseasonal variability over East Asia in summer, with a meridional tripole structure and significant periods of 10–30 and 50–70 days. A two-dimensional phase–space diagram is established for the EAP index and its time tendency so as to monitor the real-time state of EAP events. Based on the phase composite analysis, the general circulation anomalies first occur over the high-latitude area of Europe centered near Novaya Zemlya at the beginning of EAP events. These general circulation anomalies then influence rainfall over Northeast China,North China, and the region south of the Yangtze River valley(YRV) as the phases of EAP event progress. The representation, predictability, and prediction skill of the EAP teleconnection are examined in the two fully coupled subseasonal prediction systems of the beijing climate center(BCC) and UK Met Office(UKMO GloSea5). Both models are able to simulate the EAP meridional tripole over East Asia as the leading mode and its characteristics of evolution as well, except for the weaker precursors over Novaya Zemlya and an inconspicuous influence on precipitation over Northeast China. The actual prediction skill of the EAP teleconnection during May–September(MJJAS) is about 10 days in the BCC model and 15 days in the UKMO model based on correlation measures, but is higher when initialized from the EAP peak phases or when targeted on strong EAP scenarios. However, both of the ensemble prediction systems are under-dispersive and the predictable signals extend to 18 and 30 days in BCC and UKMO models based on signal-to-error metrics, indicating that there may be further scope for enhancing the capability of these models for the EAP teleconnection prediction and the associated impacts studies.

关键词： East Asia–Pacific(EAP)teleconnection subseasonal phase–space diagram prediction skill predictability

Prediction of Primary climate Variability Modes at the beijing climate center

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Journal of Meteorological Research 2017年第1期31卷 204-223页

作者： Hong-Li REN Fei-Fei JIN Lianchun SONG Bo LU Ben TIAN Jinqing ZUO Ying LIU Jie WU Chongbo ZHAO Yu NIE Peiqun ZHANG Jin BA Yujie WU Jianghua WAN Yuping YAN Fang ZHOU Laboratory for climate Studies National Climate CenterChina Meteorological Administration CMA-NJU Joint Laboratory for climate Prediction Studies Institute for Climate and Global Change ResearchSchool of Atmospheric SciencesNanjing University Department of Atmospheric Sciences University of Hawaii Collaborative Innovation center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science & Technology

climate variability modes, usually known as primary climate phenomena, are well recognized as the most impor- tant predictability sources in subseasonal-interarmual climate prediction. This paper begins by reviewing the re- search and development carried out, and the recent progress made, at the beijing climate center （BCC） in predicting some primary climate variability modes. These include the El Nifio-Southern Oscillation （ENSO）, Madden-Julian Oscillation （MJO）, and Arctic Oscillation （AO）, on global scales, as well as the sea surface temperature （SST） modes in the Indian Ocean and North Atlantic, western Pacific subtropical high （WPSH）, and the East Asian winter and summer monsoons （EAWM and EASM, respectively）, on regional scales. Based on its latest climate and statistical models, the BCC has established a climate phenomenon prediction system （CPPS） and completed a hindcast experi- ment for the period 1991-2014. The performance of the CPPS in predicting such climate variability modes is system- atically evaluated. The results show that skillful predictions have been made for ENSO, MJO, the Indian Ocean basin mode, the WPSH, and partly for the EASM, whereas less skillful predictions were made for the Indian Ocean Dipole （IOD） and North Atlantic SST Tripole, and no clear skill at all for the AO, subtropical IOD, and EAWM. Improve- ments in the prediction of these climate variability modes with low skill need to be achieved by improving the BCC＇s climate models, developing physically based statistical models as well as correction methods for model predictions. Some of the monitoring/prediction products of the BCC-CPPS are also introduced in this paper.

关键词： climate phenomenon prediction system(CPPS) El Ni?o–Southern Oscillation(ENSO) Madden–Julian Oscillation(MJO) Arctic Oscillation(AO) beijing climate center(BCC)

Investigating the ENSO prediction skills of the beijing climate center climate prediction system version 2

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Acta Oceanologica Sinica 2022年第5期41卷 99-109页

作者： Yanjie Cheng Youmin Tang Tongwen Wu Xiaoge Xin Xiangwen Liu Jianglong Li Xiaoyun Liang Qiaoping Li Junchen Yao Jinghui Yan CMA Earth System Modeling and Prediction Centre China Meteorological Administration(CMA)Beijing100081China State Key Laboratory of Severe Weather China Meteorological AdministrationBeijing100081China College of Environmental Science and Engineering University of Northern British ColumbiaPrince GeorgeV2N 4Z9Canada

The El Niño-Southern Oscillation(ENSO)ensemble prediction skills of the beijing climate center(BCC)climate prediction system version 2(BCC-CPS2)are examined for the period from 1991 to *** upper-limit ENSO predictability of this system is quantified by measuring its“potential”predictability using information-based metrics,whereas the actual prediction skill is evaluated using deterministic and probabilistic skill *** show that:(1)In general,the current operational BCC model achieves an effective 10-month lead predictability for ***,prediction skills are up to 10–11 months for the warm and cold ENSO phases,while the normal phase has a prediction skill of just 6 months.(2)Similar to previous results of the intermediate coupled models,the relative entropy(RE)with a dominating ENSO signal component can more effectively quantify correlation-based prediction skills compared to the predictive information(PI)and the predictive power(PP).(3)An evaluation of the signal-dependent feature of the prediction skill scores suggests the relationship between the“Spring predictability barrier(SPB)”of ENSO prediction and the weak ENSO signal phase during boreal spring and early summer.

关键词： ENSO ensemble prediction skill potential predictability measure BCC-CPS2 climate model

Satellite remote sensing reveals overwhelming recovery of forest from disturbances in Asia

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Atmospheric and Oceanic Science Letters 2025年第1期18卷 46-51页

作者： Yiying Zhu Hesong Wang Anzhi Zhang School of Ecology and Nature Conservation Beijing Forestry UniversityBeijingChina Key Laboratory of Regional climate and Environment for Temperate East Asia Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina College of Forestry and Landscape Architecture Xinjiang Agricultural UniversityUrumqiChina

Forest ecosystems play key roles in mitigating human-induced climate change through enhanced carbon uptake;however,frequently occurring climate extremes and human activities have considerably threatened the stability of *** the same time,detailed accounts of disturbances and forest responses are not yet well quantified in *** study employed the Breaks For Additive Seasonal and Trend method-an abrupt-change detection method-to analyze the Enhanced Vegetation Index time series in East Asia,South Asia,and Southeast *** approach allowed us to detect forest disturbance and quantify the resilience after *** showed that 20%of forests experienced disturbance with an increasing trend from 2000 to 2022,and Southeast Asian countries were more severely affected by ***,95%of forests had robust resilience and could recover from disturbance within a few *** resilience of forests suffering from greater magnitude of disturbance tended to be stronger than forests with lower disturbance *** summary,this study investigated the resilience of forests across the low and middle latitudes of Asia over the past two *** authors found that most forests exhibited good resilience after disturbance and about two-thirds had recovered to a better state in *** findings of this study underscore the complex relationship between disturbance and resilience,contributing to comprehension of forest resilience through satellite remote sensing.

关键词： Forest ecosystem Enhanced vegetation index Breaks for additive seasonal and trend method Disturbance Resilience

Unraveling the significance of cobalt on transformation kinetics,crystallography and impact toughness in high-strength steels

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 380-390页

作者： Yishuang Yu Jingxiao Zhao Xuelin Wang Hui Guo Zhenjia Xie Chengjia Shang Collaborative Innovation center of Steel Technology University of Science and Technology BeijingBeijing 100083China School of Materials Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory for Advanced Metals and Materials University of Science and Technology BeijingBeijing 100083China

This work reveals the significant effects of cobalt(Co)on the microstructure and impact toughness of as-quenched highstrength steels by experimental characterizations and thermo-kinetic *** results show that the Co-bearing steel exhibits finer blocks and a lower ductile-brittle transition temperature than the steel without ***,the Co-bearing steel reveals higher transformation rates at the intermediate stage with bainite volume fraction ranging from around 0.1 to *** improved impact toughness of the Co-bearing steel results from the higher dense block boundaries dominated by the V1/V2 variant ***,the addition of Co induces a larger transformation driving force and a lower bainite start temperature(BS),thereby contributing to the refinement of blocks and the increase of the V1/V2 variant *** findings would be instructive for the composition,microstructure design,and property optimization of high-strength steels.

关键词： high-strength steel cobalt transformation kinetics crystallography impact toughness