CLM5.0陆面模式不同土壤分层方案对黄河源区玛多站土壤温湿的数值模拟
Numerical Simulation of Soil Temperature and Humidity at Maduo Station in the Source Area of the Yellow River by Different Soil Stratification Schemes of CLM5.0 Land Surface Model
包逸群 1吕世华 1刘子莎 1游辉奇 1杨凡1
作者信息
- 1. 成都信息工程大学大气科学学院/高原大气与环境四川省重点实验室,成都 610225
- 折叠
摘要
选取 2015年 6月—2018年 8月玛多站观测资料作为驱动CLM5.0(Community Land Model)模式的强迫场数据,应用CLM5.0模式中不同土壤分层方案,对这一时段玛多站土壤温湿变化特征进行模拟,并检验了模拟效果.结果表明:(1)对于土壤温度,CLM5.0 模式的 4种土壤分层方案均能很好地模拟出一年中玛多站不同深度土壤温度的季节变化趋势,浅层土壤温度模拟值与观测值相关性更高,深层土壤温度模拟值的变化幅度相对较小且曲线较光滑.4种分层方案中,20层方案对土壤温度的模拟效果最好,平均相关系数为 0.942.(2)对于土壤湿度,4种土壤分层方案均能较好地模拟出各层土壤湿度的季节变化和日变化趋势,但较观测值都有不同程度的偏差.20层方案对土壤湿度的模拟效果更好,平均相关系数为0.730.
Abstract
The observation data of Maduo station from June 2015 to August 2018 were used as the forcing field data to drive CLM5.0(Community Land Model)model,and the soil temperature and humidity changes of Maduo station from June 2017 to August 2018 were simulated by using different soil stratification schemes in the CLM5.0 model,and compared with the observations.The results show:(1)For the simulation of soil temperature,the four soil stratification schemes of CLM5.0 model could well simulate the seasonal variation trend of soil temperature at different depths of Maduo Station in a year,the shallow simulation value was more correlated with the ob-served value,the temperature change amplitude of the deep soil was relatively small,the curve was smoother,and the 20-layer scheme of the four stratification schemes had the best simulation effect on soil temperature,with an average correlation coefficient of 0.942.(2)For the simulation of soil moisture,the four soil stratification schemes could better simulate the seasonal changes and diurnal trends of soil moisture in each layer,but there were different degrees of deviation from the observed values.The 20-layer scheme had a better simula-tion effect on soil moisture,and the average correlation coefficient was 0.730.
关键词
CLM5.0陆面模式/土壤温度/土壤湿度/数值模拟Key words
CLM5.0 land surface model/Soil temperature/Soil moisture/Numerical simulation引用本文复制引用
出版年
2024
NETL
NSTL
万方数据