Advanced Search
Article Contents

The Sensitivity of Ground Surface Temperature Prediction to Soil Thermal Properties Using the Simple Biosphere Model (SiB2)}


doi: 10.1007/s00376-011-1162-9

  • Using the Simple Biosphere Model (SiB2), soil thermal properties (STP) were examined in a Tibetan prairie during the monsoon period to investigate ground surface temperature prediction. We improved the SiB2 model by incorporating a revised force-restore method (FRM) to take the vertical heterogeneity of soil thermal diffusivity (k) into account. The results indicate that (1) the revised FRM alleviates daytime overestimation and nighttime underestimation in modeled ground surface temperature (Tg), and (2) its role in little rainfall events is significant because the vertical gradient of k increases with increasing surface evaporation. Since the original formula of thermal conductivity (λ) in the SiB2 greatly underestimates soil thermal conductivity, we compared five algorithms of λ involving soil moisture to investigate the cause of overestimation during the day and underestimation at night on the basis of the revised FRM. The results show that (1) the five algorithms significantly improve Tg prediction, especially in daytime, and (2) taking one of these five algorithms as an example, the simulated Tg values in the daytime are closer to the field measurements than those in the nighttime. The differences between modeled Tg and field measurements are mostly within the margin of error of ±2 K during 3 August to 4 September 1998.
  • [1] GUAN Xiaodan, HUANG Jianping, GUO Ni, BI Jianrong, WANG Guoyin, 2009: Variability of Soil Moisture and Its Relationship with Surface Albedo and Soil Thermal Parameters over the Loess Plateau, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 692-700.  doi: 10.1007/s00376-009-8198-0
    [2] LIU Huizhi, WANG Baomin, FU Congbin, 2008: Relationships Between Surface Albedo, Soil Thermal Parameters and Soil Moisture in the Semi-arid Area of Tongyu, Northeastern China, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 757-764.  doi: 10.1007/s00376-008-0757-2
    [3] Guo DENG, Yuejian ZHU, Jiandong GONG, Dehui CHEN, Richard WOBUS, Zhe ZHANG, 2016: The Effects of Land Surface Process Perturbations in a Global Ensemble Forecast System, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 1199-1208.  doi: 10.1007/s00376-016-6036-8
    [4] ZENG Xinmin, LIU Jinbo, MA Zhuguo, SONG Shuai, XI Chaoli, WANG Hanjie, 2010: Study on the Effects of Land Surface Heterogeneitiesin Temperature and Moisture on Annual Scale Regional Climate Simulation, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 154-163.  doi: 10.1007/s00376-009-8117-4
    [5] DENG Huiping, SUN Shufen, 2010: Extension of TOPMODEL Applications to the Heterogeneous Land Surface, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 164-176.  doi: 10.1007/s00376-009-8146-z
    [6] LI Weiping, LUO Yong, XIA Kun, LIU Xin, 2008: Simulation of Snow Processes Beneath a Boreal Scots Pine Canopy, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 348-360.  doi: 10.1007/s00376-008-0348-2
    [7] JIANG Zhina, 2006: Applications of Conditional Nonlinear Optimal Perturbation to the Study of the Stability and Sensitivity of the Jovian Atmosphere, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 775-783.  doi: 10.1007/s00376-006-0775-x
    [8] Xiaohao QIN, Wansuo DUAN, Hui XU, 2020: Sensitivity to Tendency Perturbations of Tropical Cyclone Short-range Intensity Forecasts Generated by WRF, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 291-306.  doi: 10.1007/s00376-019-9187-6
    [9] GAO Zhiqiu, BIAN Lingen, WANG Jinxing, LU Longhua, 2003: Discussion on Calculation Methods of Sensible Heat Flux during GAME/Tibet in 1998, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 357-368.  doi: 10.1007/BF02690794
    [10] LIU Shuhua, YUE Xu, LIU Huizhi, HU Fei, 2004: Using a Modified Soil-Plant-Atmosphere Scheme (MSPAS) to Study the Sensitivity of Land Surface and Boundary Layer Processes to Soil and Vegetation Conditions, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 717-729.  doi: 10.1007/BF02916369
    [11] Jinlei CHEN, Yuan YUAN, Xianyu YANG, Zuoliang WANG, Shichang KANG, Jun WEN, 2023: The Characteristics and Controlling Factors of Water and Heat Exchanges over the Alpine Wetland in the East of the Qinghai–Tibet Plateau, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 201-210.  doi: 10.1007/s00376-022-1443-5
    [12] Guo Weidong, Sun Shufen, Qian Yongfu, 2002: Case Analyses and Numerical Simulation of Soil Thermal Impacts on Land Surface Energy Budget Based on an Off-Line Land Surface Model, ADVANCES IN ATMOSPHERIC SCIENCES, 19, 500-512.  doi: 10.1007/s00376-002-0082-0
    [13] FANG Changluan, ZHENG Qin, WU Wenhua, DAI Yi, 2009: Intelligent Optimization Algorithms to VDA of Models with on/off Parameterizations, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 1181-1197.  doi: 10.1007/s00376-009-8084-9
    [14] Jiawei YAO, Wansuo DUAN, Xiaohao QIN, 2021: Which Features of the SST Forcing Error Most Likely Disturb the Simulated Intensity of Tropical Cyclones?, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 581-602.  doi: 10.1007/s00376-020-0073-z
    [15] LIU Shuhua, YUE Xu, HU Fei, LIU Huizhi, 2004: Using a Modified Soil-Plant-Atmosphere Scheme (MSPAS) to Simulate the Interaction between Land Surface Processes and Atmospheric Boundary Layer in Semi-Arid Regions, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 245-259.  doi: 10.1007/BF02915711
    [16] Bao Ning, Zhang Xuehong, 1991: Effect of Ocean Thermal Diffusivity on Global Warming Induced by Increasing Atmospheric CO2, ADVANCES IN ATMOSPHERIC SCIENCES, 8, 421-430.  doi: 10.1007/BF02919265
    [17] Haoxin ZHANG, Naiming YUAN, Zhuguo MA, Yu HUANG, 2021: Understanding the Soil Temperature Variability at Different Depths: Effects of Surface Air Temperature, Snow Cover, and the Soil Memory, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 493-503.  doi: 10.1007/s00376-020-0074-y
    [18] Binghao JIA, Longhuan WANG, Yan WANG, Ruichao LI, Xin LUO, Jinbo XIE, Zhenghui XIE, Si CHEN, Peihua QIN, Lijuan LI, Kangjun CHEN, 2021: CAS-LSM Datasets for the CMIP6 Land Surface Snow and Soil Moisture Model Intercomparison Project, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 862-874.  doi: 10.1007/s00376-021-0293-x
    [19] DAN Li, JI Jinjun, LIU Huizhi, 2008: Use of a Land Surface Model to Evaluate the Observed Soil Moisture of Grassland at the Tongyu Reference Site, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 1073-1084.  doi: 10.1007/s00376-008-1073-6
    [20] DAI Qiudan, SUN Shufen, 2007: A Comparison of Two Canopy Radiative Models in Land Surface ProcessesA Comparison of Two Canopy adiative Models in Land Surface Processes, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 421-434.  doi: 10.1007/s00376-007-0421-2

Get Citation+

Export:  

Share Article

Manuscript History

Manuscript received: 10 May 2012
Manuscript revised: 10 May 2012
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

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

The Sensitivity of Ground Surface Temperature Prediction to Soil Thermal Properties Using the Simple Biosphere Model (SiB2)}

  • 1. College of Earth Science, Graduate University of Chinese Academy of Sciences, Beijing 100049, Key Laboratory of Computational Geodynamics, Chinese Academy of Sciences, Beijing 100049, State Key Laboratory of Atmospheric Boundary Layer Physics and Atmosph;State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100081, College of Applied Meteorology, Nanjing University of Information Science and Technology;College of Earth Science, Graduate University of Chinese Academy of Sciences, Beijing 100049, Key Laboratory of Computational Geodynamics, Chinese Academy of Sciences, Beijing 100049

Abstract: Using the Simple Biosphere Model (SiB2), soil thermal properties (STP) were examined in a Tibetan prairie during the monsoon period to investigate ground surface temperature prediction. We improved the SiB2 model by incorporating a revised force-restore method (FRM) to take the vertical heterogeneity of soil thermal diffusivity (k) into account. The results indicate that (1) the revised FRM alleviates daytime overestimation and nighttime underestimation in modeled ground surface temperature (Tg), and (2) its role in little rainfall events is significant because the vertical gradient of k increases with increasing surface evaporation. Since the original formula of thermal conductivity (λ) in the SiB2 greatly underestimates soil thermal conductivity, we compared five algorithms of λ involving soil moisture to investigate the cause of overestimation during the day and underestimation at night on the basis of the revised FRM. The results show that (1) the five algorithms significantly improve Tg prediction, especially in daytime, and (2) taking one of these five algorithms as an example, the simulated Tg values in the daytime are closer to the field measurements than those in the nighttime. The differences between modeled Tg and field measurements are mostly within the margin of error of ±2 K during 3 August to 4 September 1998.

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return