Optimizing the parameters of a land surface process model(LSPM) through data assimilation(DA) can not only improve and perfect the parameterization schemes in the LSPM through the physical mechanism, but also increase...Optimizing the parameters of a land surface process model(LSPM) through data assimilation(DA) can not only improve and perfect the parameterization schemes in the LSPM through the physical mechanism, but also increase its regional adaptability and simulation capability. This has practical importance for improving simulation results and the climate-prediction capability of general circulation models(GCMs) and regional climate models(RCMs). This paper presents a DA-based method for optimizing the parameterization schemes in LSPMs. We optimize the unsaturated-soil water flow(Un SWF) model as an example by developing a soil-moisture assimilation scheme based on the Un SWF model and the extended Kalman filter(EKF) algorithm, and then combining them with the Variable Infiltration Capacity(VIC) model. Using a month as the assimilation window, we used the Shuffled Complex Evolution–University of Arizona(SCE-UA) algorithm to minimize the objective function through simulated and assimilated soil moisture, achieved the best fit with the given objective function measurement, and optimized the parameters of the Un SWF model, including the saturated-soil hydraulic conductivity, moisture content, matrix potential, and the Clapp and Hornberger constant. The optimal values of the model parameters were obtained during the DA period(the year 1986), and then the optimized parameters were used to improve the Un SWF model. Finally, numerical simulation experiments were carried out from 1986 to 1993 to evaluate the simulation capability of the improved model and to explore and realize the DA-based method for optimizing the soil water parameterization scheme in LSPMs. The experimental results indicated that the optimized model parameters improved and perfected the model based on the physical mechanism, and increased its simulation capability; the optimized model parameters had good temporal portability and their adaptability was stronger, achieving the aim of improving the model. Therefore, this method is reasonable and feasible. This paper provides a good reference for DA-based optimization of the parameterization schemes in LSPMs.展开更多
In order to examine and analyze the effects of integration of land surface models with TOPMODEL and different approaches for the integration on the model simulation of water and energy balances,the coupled models have...In order to examine and analyze the effects of integration of land surface models with TOPMODEL and different approaches for the integration on the model simulation of water and energy balances,the coupled models have been developed,which incorporate TOPMODEL into the Simplified Biosphere Model(SSiB) with different approaches(one divides a basin into a number of zones according to the distribution of topographic index,and the other only divides the basin into saturated and unsaturated zones).The coupled models are able to(but SSiB is not able to) take into account the impacts of topography variation and vertical heterogeneity of soil saturated hydraulic conductivity on horizontal distribution of soil moisture and in turn on water and energy balances within the basin(or a grid cell).By using the coupled models and SSiB model itself,the daily hydrological components such as runoffs are simulated and final results are analyzed carefully.Simulated daily results of hydrological components produced by both SSiB and coupled models show that(i) There is significant difference between results of soil wetness,its vertical distribution and seasonal variation,water and energy balance,and daily runoff in the basin predicted by SSiB and by the coupled models.The land surface model currently used such as SSiB is likely to misrepresent real feature of water and energy balances in the basin.(ii) Compared with the results for the basin predicted by SSiB,the coupled models predict more strong vertical and seasonal changes in soil wetness,higher evaporation and lower runoff,and improve the base flow simulation obviously.(iii) Comparing the results for the basin predicted by two coupled models with different integration approach and SSiB one by one,the results of daily runoffs and soil wetness predicted by the two coupled models are quite similar.It means,for the coupled models,the approach by dividing a region being considered into more subzones may have limited effects on improving runoff simulation results.The scheme only to divide the region into saturated and unsaturated zones may be a convenient and effective scheme.But then,if the results from the two coupled models for the basin are carefully compared,the simulated results by the coupled model with dividing the basin into more subzones will show higher evaporation and surface runoff but lower subsurface flow,lower total runoff,and lower ground water level averaged for five years.展开更多
Two simulations of five years (2003-2007) were conducted with the Regional Climate models RegCM4, one coupled with Land surface models BATS and the other with CLM4.5 over West Africa, where simulated air temperature a...Two simulations of five years (2003-2007) were conducted with the Regional Climate models RegCM4, one coupled with Land surface models BATS and the other with CLM4.5 over West Africa, where simulated air temperature and precipitation were analyzed. The purpose of this study is to assess the performance of RegCM4 coupled with the new CLM4.5 Land</span><span style="font-family:""> </span><span style="font-family:Verdana;">surface scheme and the standard one named BATS in order to find the best configuration of RegCM4 over West African. This study could improve our understanding of the sensitivity of land surface model in West Africa climate simulation, and provide relevant information to RegCM4 users. The results show fairly realistic restitution of West Africa’s climatology and indicate correlations of 0.60 to 0.82 between the simulated fields (BATS and CLM4.5) for precipitation. The substitution of BATS surface scheme by CLM4.5 in the model configuration, leads mainly to an improvement of precipitation over the Atlantic Ocean, however, the impact is not sufficiently noticeable over the continent. While the CLM4.5 experiment restores the seasonal cycles and spatial distribution, the biases increase for precipitation and temperature. Positive biases already existing with BATS are amplified over some sub-regions. This study concludes that temporal localization (seasonal effect), spatial distribution (grid points) and magnitude of precipitation and temperature (bias) are not simultaneously improved by CLM4.5. The introduction of the new land surface scheme CLM4.5, therefore, leads to a performance of the same order as that of BATS, albeit with a more detailed formulation.展开更多
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...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。展开更多
本文利用中尺度模式Weather Research and Forecasting Model(WRF)3.1版本及National Centers forEnvironmental Prediction(NCEP)分析资料,就2003年6月下旬我国江淮及南方地区的强降水事件,以24h短期天气模拟的方式,研究了模式中四个...本文利用中尺度模式Weather Research and Forecasting Model(WRF)3.1版本及National Centers forEnvironmental Prediction(NCEP)分析资料,就2003年6月下旬我国江淮及南方地区的强降水事件,以24h短期天气模拟的方式,研究了模式中四个不同陆面方案对降水模拟的影响.结果表明,此次暴雨事件模拟对不同陆面方案是比较敏感的,模拟区域内雨量级别越高,不同方案的TS评分差异就越大,较大范围雨量可存在30%的差异,四种方案的暴雨中心值可存在100%～150%的较大差别;不同陆面方案还导致了模拟平均感热通量及潜热通量的系统性差异,这些差异的分布具有地域特点;陆面方案通过两种机理对模拟降水产生重要影响,即主要影响地表蒸发量,以及主要影响低层环流及水汽辐合,从而分别影响模拟的较大范围降水(如,平均约7%、最大约30%的较大范围雨量差异)及包含模拟降水中心的较小范围暴雨(如,方案间暴雨中心雨量可存在100%～150%的较大差别).可见,不同陆面过程可从不同空间尺度、不同程度上影响暴雨天气,改进陆面方案可以提高WRF模式对暴雨的模拟能力.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.4157136840971229&41130528)+1 种基金the Important National Project of High-resolution Earth Observation System(Grant No.05-Y30B02-9001-13/15-8)the Special Foundation for Free Exploration of the State Key Laboratory of Remote Sensing Science(Grant No.14ZY-01)
文摘Optimizing the parameters of a land surface process model(LSPM) through data assimilation(DA) can not only improve and perfect the parameterization schemes in the LSPM through the physical mechanism, but also increase its regional adaptability and simulation capability. This has practical importance for improving simulation results and the climate-prediction capability of general circulation models(GCMs) and regional climate models(RCMs). This paper presents a DA-based method for optimizing the parameterization schemes in LSPMs. We optimize the unsaturated-soil water flow(Un SWF) model as an example by developing a soil-moisture assimilation scheme based on the Un SWF model and the extended Kalman filter(EKF) algorithm, and then combining them with the Variable Infiltration Capacity(VIC) model. Using a month as the assimilation window, we used the Shuffled Complex Evolution–University of Arizona(SCE-UA) algorithm to minimize the objective function through simulated and assimilated soil moisture, achieved the best fit with the given objective function measurement, and optimized the parameters of the Un SWF model, including the saturated-soil hydraulic conductivity, moisture content, matrix potential, and the Clapp and Hornberger constant. The optimal values of the model parameters were obtained during the DA period(the year 1986), and then the optimized parameters were used to improve the Un SWF model. Finally, numerical simulation experiments were carried out from 1986 to 1993 to evaluate the simulation capability of the improved model and to explore and realize the DA-based method for optimizing the soil water parameterization scheme in LSPMs. The experimental results indicated that the optimized model parameters improved and perfected the model based on the physical mechanism, and increased its simulation capability; the optimized model parameters had good temporal portability and their adaptability was stronger, achieving the aim of improving the model. Therefore, this method is reasonable and feasible. This paper provides a good reference for DA-based optimization of the parameterization schemes in LSPMs.
基金supported by National Natural Science Foundation of China(Grant Nos.41075060 and 41030106)
文摘In order to examine and analyze the effects of integration of land surface models with TOPMODEL and different approaches for the integration on the model simulation of water and energy balances,the coupled models have been developed,which incorporate TOPMODEL into the Simplified Biosphere Model(SSiB) with different approaches(one divides a basin into a number of zones according to the distribution of topographic index,and the other only divides the basin into saturated and unsaturated zones).The coupled models are able to(but SSiB is not able to) take into account the impacts of topography variation and vertical heterogeneity of soil saturated hydraulic conductivity on horizontal distribution of soil moisture and in turn on water and energy balances within the basin(or a grid cell).By using the coupled models and SSiB model itself,the daily hydrological components such as runoffs are simulated and final results are analyzed carefully.Simulated daily results of hydrological components produced by both SSiB and coupled models show that(i) There is significant difference between results of soil wetness,its vertical distribution and seasonal variation,water and energy balance,and daily runoff in the basin predicted by SSiB and by the coupled models.The land surface model currently used such as SSiB is likely to misrepresent real feature of water and energy balances in the basin.(ii) Compared with the results for the basin predicted by SSiB,the coupled models predict more strong vertical and seasonal changes in soil wetness,higher evaporation and lower runoff,and improve the base flow simulation obviously.(iii) Comparing the results for the basin predicted by two coupled models with different integration approach and SSiB one by one,the results of daily runoffs and soil wetness predicted by the two coupled models are quite similar.It means,for the coupled models,the approach by dividing a region being considered into more subzones may have limited effects on improving runoff simulation results.The scheme only to divide the region into saturated and unsaturated zones may be a convenient and effective scheme.But then,if the results from the two coupled models for the basin are carefully compared,the simulated results by the coupled model with dividing the basin into more subzones will show higher evaporation and surface runoff but lower subsurface flow,lower total runoff,and lower ground water level averaged for five years.
文摘Two simulations of five years (2003-2007) were conducted with the Regional Climate models RegCM4, one coupled with Land surface models BATS and the other with CLM4.5 over West Africa, where simulated air temperature and precipitation were analyzed. The purpose of this study is to assess the performance of RegCM4 coupled with the new CLM4.5 Land</span><span style="font-family:""> </span><span style="font-family:Verdana;">surface scheme and the standard one named BATS in order to find the best configuration of RegCM4 over West African. This study could improve our understanding of the sensitivity of land surface model in West Africa climate simulation, and provide relevant information to RegCM4 users. The results show fairly realistic restitution of West Africa’s climatology and indicate correlations of 0.60 to 0.82 between the simulated fields (BATS and CLM4.5) for precipitation. The substitution of BATS surface scheme by CLM4.5 in the model configuration, leads mainly to an improvement of precipitation over the Atlantic Ocean, however, the impact is not sufficiently noticeable over the continent. While the CLM4.5 experiment restores the seasonal cycles and spatial distribution, the biases increase for precipitation and temperature. Positive biases already existing with BATS are amplified over some sub-regions. This study concludes that temporal localization (seasonal effect), spatial distribution (grid points) and magnitude of precipitation and temperature (bias) are not simultaneously improved by CLM4.5. The introduction of the new land surface scheme CLM4.5, therefore, leads to a performance of the same order as that of BATS, albeit with a more detailed formulation.
文摘选取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。
文摘本文利用中尺度模式Weather Research and Forecasting Model(WRF)3.1版本及National Centers forEnvironmental Prediction(NCEP)分析资料,就2003年6月下旬我国江淮及南方地区的强降水事件,以24h短期天气模拟的方式,研究了模式中四个不同陆面方案对降水模拟的影响.结果表明,此次暴雨事件模拟对不同陆面方案是比较敏感的,模拟区域内雨量级别越高,不同方案的TS评分差异就越大,较大范围雨量可存在30%的差异,四种方案的暴雨中心值可存在100%～150%的较大差别;不同陆面方案还导致了模拟平均感热通量及潜热通量的系统性差异,这些差异的分布具有地域特点;陆面方案通过两种机理对模拟降水产生重要影响,即主要影响地表蒸发量,以及主要影响低层环流及水汽辐合,从而分别影响模拟的较大范围降水(如,平均约7%、最大约30%的较大范围雨量差异)及包含模拟降水中心的较小范围暴雨(如,方案间暴雨中心雨量可存在100%～150%的较大差别).可见,不同陆面过程可从不同空间尺度、不同程度上影响暴雨天气,改进陆面方案可以提高WRF模式对暴雨的模拟能力.
