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Volume 28 Issue 3

May  2011

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2011 >  28(3): 534-550

The Construction of SCM in GRAPES and Its Applications in Two Field Experiment Simulations

  • 1.

    Chinese Academy of Meteorological Sciences, Beijing 100081, Numerical Prediction Center, China Meteorological Administration, Beijing 100081,Chinese Academy of Meteorological Sciences, Beijing 100081, Numerical Prediction Center, China Meteorological Administration, Beijing 100081


doi: 10.1007/s00376-010-0062-8

  • A Single Column Model (SCM) for Global and Regional Atmospheric Prediction Enhanced System (GRAPES) is constructed for the purpose of evaluating physical process parameterizations. Two observational datasets including Wangara and the third Global Energy and Water Cycle Experiment Atmospheric Boundary Layer Study (GABLS-3) SCM field observations have been applied to evaluate this SCM. By these two numerical experiments, the GRAPES_SCM is verified to be correctly constructed. Furthermore, the interaction between the land surface process and atmospheric boundary layer (ABL) is discussed through the second experiment. It is found that CASE3 (CoLM land surface scheme coupled with ABL scheme) simulates less sensible heat fluxes and smaller surface temperature which corresponds with its lower potential temperature at the bottom of the ABL. Moreover, CASE3 simulates turbulence that is weaker during the daytime and stronger during nighttime, corresponding with its wind speed at 200 m which is bigger during daytime and smaller during nighttime. However, they are generally opposite in CASE2 (SLAB coupled with ABL). The initial profile of the water vapor mixing ratio is artificially increased by the experiment setup which results in the simulated water vapor mixing becoming wetter than actually observed. CASE1 (observed surface temperature taken as lower thermal forcing) and CASE2 have no soil moisture prediction and simulate a similar water vapor mixing ratio, while CASE3 has a soil moisture prediction and simulates wetter. It is also shown that the time step may affect the stabilization of the ABL when the vertical levels of the SCM are fixed.
  • [1] Min Dong, Qin Xu, 1996: A Sensitivity Study of Single Column Model, ADVANCES IN ATMOSPHERIC SCIENCES, 13, 313-324.  doi: 10.1007/BF02656849
    [2] Feifan ZHOU, Wansuo DUAN, He ZHANG, Munehiko YAMAGUCHI, 2018: Possible Sources of Forecast Errors Generated by the Global/Regional Assimilation and Prediction System for Landfalling Tropical Cyclones. Part II: Model Uncertainty, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 1277-1290.  doi: 10.1007/s00376-018-7095-9
    [3] Lei ZHANG, Xiquan DONG, Aaron KENNEDY, Baike XI, Zhanqing LI, 2017: Evaluation of NASA GISS Post-CMIP5 Single Column Model Simulated Clouds and Precipitation Using ARM Southern Great Plains Observations, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 306-320.  doi: 10.1007/s00376-016-5254-4
    [4] Zhizhen XU, Jing CHEN, Zheng JIN, Hongqi LI, Fajing CHEN, 2020: Representing Model Uncertainty by Multi-Stochastic Physics Approaches in the GRAPES Ensemble, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 328-346.  doi: 10.1007/s00376-020-9171-1
    [5] LIU Hongya, XUE Jishan, GU Jianfeng, XU Haiming, 2012: Radar Data Assimilation of the GRAPES Model and Experimental Results in a Typhoon Case, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 344-358.  doi: 10.1007/s00376-011-1063-y
    [6] HUANG Bo, CHEN Dehui, LI Xingliang, LI Chao, , 2014: Improvement of the Semi-Lagrangian Advection Scheme in the GRAPES Model: Theoretical Analysis and Idealized Tests, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 693-704.  doi: 10.1007/s00376-013-3086-z
    [7] Shuixin ZHONG, Zitong CHEN, Daosheng XU, Yanxia ZHANG, 2018: Evaluating and Improving Wind Forecasts over South China: The Role of Orographic Parameterization in the GRAPES Model, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 713-722.  doi: 10.1007/s00376-017-7157-4
    [8] Jie HE, Xulin MA, Xuyang GE, Juanjuan LIU, Wei CHENG, Man-Yau CHAN, Ziniu XIAO, 2021: Variational Quality Control of Non-Gaussian Innovations in the GRAPES m3DVAR System: Mass Field Evaluation of Assimilation Experiments, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 1510-1524.  doi: 10.1007/s00376-021-0336-3
    [9] Jing WANG, Bin WANG, Juanjuan LIU, Yongzhu LIU, Jing CHEN, Zhenhua HUO, 2020: Application and Characteristic Analysis of the Moist Singular Vector in GRAPES-GEPS, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 1164-1178.  doi: 10.1007/s00376-020-0092-9
    [10] HUANG Yanyan, XUE Jishan, WAN Qilin, CHEN Zitong, DING Weiyu, ZHANG Chengzhong, 2013: Improvement of the Surface Pressure Operator in GRAPES and Its Application in Precipitation Forecasting in South China, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 354-366.  doi: 10.1007/s00376-012-1270-1
    [11] Jincheng WANG, Xingwei JIANG, Xueshun SHEN, Youguang ZHANG, Xiaomin WAN, Wei HAN, Dan WANG, 2023: Assimilation of Ocean Surface Wind Data by the HY-2B Satellite in GRAPES: Impacts on Analyses and Forecasts, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 44-61.  doi: 10.1007/s00376-022-1349-2
    [12] Ning ZHANG, Yunsong DU, Shiguang MIAO, 2016: A Microscale Model for Air Pollutant Dispersion Simulation in Urban Areas: Presentation of the Model and Performance over a Single Building, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 184-192.  doi: 10.1007/s00376-015-5152-1
    [13] GUO Xia, LU Daren, LU Yao, 2007: A Simple but Accurate Ultraviolet Limb-Scan Spherically-Layered Radiative-Transfer-Model Based on Single-Scattering Physics, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 619-630.  doi: 10.1007/s00376-007-0619-3
    [14] YUE Xu, WANG Huijun, LIAO Hong, FAN Ke, 2010: Direct Climatic Effect of Dust Aerosol in the NCAR Community Atmosphere Model Version 3 (CAM3), ADVANCES IN ATMOSPHERIC SCIENCES, 27, 230-242.  doi: 10.1007/s00376-009-8170-z
    [15] Bian HE, Yimin LIU, Guoxiong WU, Qing BAO, Tianjun ZHOU, Xiaofei WU, Lei WANG, Jiandong LI, Xiaocong WANG, Jinxiao LI, Wenting HU, Xiaoqi ZHANG, Chen SHENG, Yiqiong TANG, 2020: CAS FGOALS-f3-L Model Datasets for CMIP6 GMMIP Tier-1 and Tier-3 Experiments, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 18-28.  doi: 10.1007/s00376-019-9085-y
    [16] Ye PU, Hongbo LIU, Ruojing YAN, Hao YANG, Kun XIA, Yiyuan LI, Li DONG, Lijuan LI, He WANG, Yan NIE, Mirong SONG, Jinbo XIE, Shuwen ZHAO, Kangjun CHEN, Bin WANG, Jianghao LI, Ling ZUO, 2020: CAS FGOALS-g3 Model Datasets for the CMIP6 Scenario Model Intercomparison Project (ScenarioMIP), ADVANCES IN ATMOSPHERIC SCIENCES, 37, 1081-1092.  doi: 10.1007/s00376-020-2032-0
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    • Manuscript History

    Manuscript received: 10 May 2011
    Manuscript revised: 10 May 2011
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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    The Construction of SCM in GRAPES and Its Applications in Two Field Experiment Simulations

    • 1. Chinese Academy of Meteorological Sciences, Beijing 100081, Numerical Prediction Center, China Meteorological Administration, Beijing 100081,Chinese Academy of Meteorological Sciences, Beijing 100081, Numerical Prediction Center, China Meteorological Administration, Beijing 100081
    • Manuscript received: 2011-05-10
    • Manuscript revised: 2011-05-10

    Abstract: A Single Column Model (SCM) for Global and Regional Atmospheric Prediction Enhanced System (GRAPES) is constructed for the purpose of evaluating physical process parameterizations. Two observational datasets including Wangara and the third Global Energy and Water Cycle Experiment Atmospheric Boundary Layer Study (GABLS-3) SCM field observations have been applied to evaluate this SCM. By these two numerical experiments, the GRAPES_SCM is verified to be correctly constructed. Furthermore, the interaction between the land surface process and atmospheric boundary layer (ABL) is discussed through the second experiment. It is found that CASE3 (CoLM land surface scheme coupled with ABL scheme) simulates less sensible heat fluxes and smaller surface temperature which corresponds with its lower potential temperature at the bottom of the ABL. Moreover, CASE3 simulates turbulence that is weaker during the daytime and stronger during nighttime, corresponding with its wind speed at 200 m which is bigger during daytime and smaller during nighttime. However, they are generally opposite in CASE2 (SLAB coupled with ABL). The initial profile of the water vapor mixing ratio is artificially increased by the experiment setup which results in the simulated water vapor mixing becoming wetter than actually observed. CASE1 (observed surface temperature taken as lower thermal forcing) and CASE2 have no soil moisture prediction and simulate a similar water vapor mixing ratio, while CASE3 has a soil moisture prediction and simulates wetter. It is also shown that the time step may affect the stabilization of the ABL when the vertical levels of the SCM are fixed.

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