本文利用普林斯顿大学全球大气强迫场资料,驱动公用陆面过程模式(Community Land Model version 4.0,CLM4.O)模拟了中国区域1961-2010年土壤湿度的时空变化。将模拟结果与观测结果、美国国家环境预报中心再分析数据(Naional Cent...本文利用普林斯顿大学全球大气强迫场资料,驱动公用陆面过程模式(Community Land Model version 4.0,CLM4.O)模拟了中国区域1961-2010年土壤湿度的时空变化。将模拟结果与观测结果、美国国家环境预报中心再分析数据(Naional Centers for Environmental Prediction Reanalysis,NCEP)和高级微波扫描辐射计(Advanced Microwave Scanning Radiometer-EOS,AMSR-E)反演的土壤湿度进行了对比分析,结果表明CLM4.0模拟结果可以反映出中国区域观测土壤湿度的空间分布和时空变化特征,但东北、江淮和河套三个地区模拟值相对于观测值在各层次均系统性偏大。模拟与NCEP再分析土壤湿度的空间分布基本一致,与AMSR-E的反演值在35°N以北的分布也基本一致;从1961-2010年土壤湿度模拟结果分析得出,各层土壤湿度空间分布从西北向东南增加。低值区主要分布在新疆、青海、甘肃和内蒙古西部地区。东北平原、江淮地区和长江流域为高值区。土壤湿度数值总体上从浅层向深层增加。不同深度土壤湿度变化趋势基本相同。除新疆西部和东北部分地区外,土壤湿度在35°N以北以减少趋势为主,30°N以南的长江流域、华南及西南地区以增加为主。在全球气候变暖的背景下,CLM4.0模拟的夏季土壤湿度在不同程度上响应了降水的变化。中国典型干旱区和半干旱区土壤湿度减小,湿润区增加。其中湿润区土壤湿度对降水的响应最为显著,其次是半干旱区和干旱区。展开更多
植被总初级生产力(Gross Primary Productivity,GPP)决定进入陆地生态系统的初始物质和能量,是陆地碳循环与大气碳库的重要联系纽带.利用陆面过程模式CLM4-CN(Community Land Model version 4 with Carbon- Nitrogen interactions)...植被总初级生产力(Gross Primary Productivity,GPP)决定进入陆地生态系统的初始物质和能量,是陆地碳循环与大气碳库的重要联系纽带.利用陆面过程模式CLM4-CN(Community Land Model version 4 with Carbon- Nitrogen interactions)模拟和分析中国区域1982~2004年GPP(CLM4_GPP)时空变化特征,并通过与基于观测数据升尺度所得到的MTE_GPP(Model Tree Ensemble,MTE)进行比较,评估CLM4在中国区域GPP的模拟能力,同时探讨了不同土地覆盖资料对GPP的影响.结果表明:(1)CLM4-CN能够较好地刻画中国区域GPP空间分布格局,表现为由东南向西北递减,但在量值上大部分区域尤其是30°N以南地区存在高估,CLM4-CN模拟的GPP多年平均值为13.7 PgC a^-1,而MTE_GPP仅为6.9 PgC a^-1;(2)CLM4-CN可以合理模拟GPP的季节变化(与MTE_GPP相关系数大于0.9),在量值上对温带阔叶落叶林、寒带阔叶落叶林、寒带阔叶落叶灌木、C3极地草地、C3非极地草地和农作物模拟较好(均方根偏差RMSD 〈 100 gC m^-2 month^-1);(3)不同植物功能型CLM4_GPP表现出的年际变率均大于MTE_GPP,仅热带针叶常绿林、寒带阔叶落叶林和C3极地草地的CLM4_GPP与MTE_GPP变化趋势一致;(4)降水是研究时段内控制整个中国区域GPP的主要气候因子,但不同地区存在较大差异;(5)两种不同土地覆盖资料GPP模拟结果的显著差异表明,精确的土地覆盖是准确模拟GPP的重要基础.展开更多
In this study, the high-accuracy multisource integrated Chinese land cover(MICLCover) dataset was used in version 4 of the Community Land Model(CLM4) to assess how the new land cover information affected land surface ...In this study, the high-accuracy multisource integrated Chinese land cover(MICLCover) dataset was used in version 4 of the Community Land Model(CLM4) to assess how the new land cover information affected land surface simulation over China. Compared to the default land cover dataset in CLM4, the MICL data indicated lower values for bare soil(14.6% reduction), needleleaf tree(3.6%), and broadleaf tree(1.9%); higher values for shrub cover(1.8% increase), grassland(9.9%), cropland(5.0%), glaciers(0.5%), lakes(1.6%), and wetland(1.1%); and unchanged for urban areas. Two comparative CLM4 simulations were conducted for the 33-yr period from 1972 to 2004, one using the MICL dataset and the other using the default dataset. The results revealed that the MICL data produced a 0.3% lower mean annual surface albedo over China than the original data. The largest contributor to the reduced value was semiarid regions(2.1% reduction). The MICL-data albedo value agreed more closely with observations(MODIS broadband black-sky albedo products) over arid and semiarid regions than for the original data to some extent. The simulated average sensible heat flux over China increased by only 0.1 W m–2 owing to the reduced values in arid and semiarid regions, as opposed to increases in humid and semihumid regions, while an increased latent heat flux of 1 W m–2 was reflected in almost identical changes over the whole region. In addition, the mean annual runoff simulated by CLM4 using MICL data decreased by 6.8 mm yr–1, primarily due to large simulated decreases in humid regions.展开更多
A long-term simulation for the period 1990–2010 is conducted with the latest version of the International Centre for Theoretical Physics' Regional Climate Model(RegCM4), driven by ERA-Interim boundary conditions a...A long-term simulation for the period 1990–2010 is conducted with the latest version of the International Centre for Theoretical Physics' Regional Climate Model(RegCM4), driven by ERA-Interim boundary conditions at a grid spacing of 25 km. The Community Land Model(CLM) is used to describe land surface processes, with updates in the surface parameters,including the land cover and surface emissivity. The simulation is compared against observations to evaluate the model performance in reproducing the present day climatology and interannual variability over the 10 main river basins in China,with focus on surface air temperature and precipitation. Temperature and precipitation from the ERA-Interim reanalysis are also considered in the model assessment. Results show that the model reproduces the present day climatology over China and its main river basins, with better performances in June–July–August compared to December–January–February(DJF).In DJF, we find a warm bias at high latitudes, underestimated precipitation in the south, and overestimated precipitation in the north. The model in general captures the observed interannual variability, with greater skill for temperature. We also find an underestimation of heavy precipitation events in eastern China, and an underestimation of consecutive dry days in northern China and the Tibetan Plateau. Similar biases for both mean climatology and extremes are found in the ERA-Interim reanalysis, indicating the difficulties for climate models in simulating extreme monsoon climate events over East Asia.展开更多
文摘本文利用普林斯顿大学全球大气强迫场资料,驱动公用陆面过程模式(Community Land Model version 4.0,CLM4.O)模拟了中国区域1961-2010年土壤湿度的时空变化。将模拟结果与观测结果、美国国家环境预报中心再分析数据(Naional Centers for Environmental Prediction Reanalysis,NCEP)和高级微波扫描辐射计(Advanced Microwave Scanning Radiometer-EOS,AMSR-E)反演的土壤湿度进行了对比分析,结果表明CLM4.0模拟结果可以反映出中国区域观测土壤湿度的空间分布和时空变化特征,但东北、江淮和河套三个地区模拟值相对于观测值在各层次均系统性偏大。模拟与NCEP再分析土壤湿度的空间分布基本一致,与AMSR-E的反演值在35°N以北的分布也基本一致;从1961-2010年土壤湿度模拟结果分析得出,各层土壤湿度空间分布从西北向东南增加。低值区主要分布在新疆、青海、甘肃和内蒙古西部地区。东北平原、江淮地区和长江流域为高值区。土壤湿度数值总体上从浅层向深层增加。不同深度土壤湿度变化趋势基本相同。除新疆西部和东北部分地区外,土壤湿度在35°N以北以减少趋势为主,30°N以南的长江流域、华南及西南地区以增加为主。在全球气候变暖的背景下,CLM4.0模拟的夏季土壤湿度在不同程度上响应了降水的变化。中国典型干旱区和半干旱区土壤湿度减小,湿润区增加。其中湿润区土壤湿度对降水的响应最为显著,其次是半干旱区和干旱区。
文摘植被总初级生产力(Gross Primary Productivity,GPP)决定进入陆地生态系统的初始物质和能量,是陆地碳循环与大气碳库的重要联系纽带.利用陆面过程模式CLM4-CN(Community Land Model version 4 with Carbon- Nitrogen interactions)模拟和分析中国区域1982~2004年GPP(CLM4_GPP)时空变化特征,并通过与基于观测数据升尺度所得到的MTE_GPP(Model Tree Ensemble,MTE)进行比较,评估CLM4在中国区域GPP的模拟能力,同时探讨了不同土地覆盖资料对GPP的影响.结果表明:(1)CLM4-CN能够较好地刻画中国区域GPP空间分布格局,表现为由东南向西北递减,但在量值上大部分区域尤其是30°N以南地区存在高估,CLM4-CN模拟的GPP多年平均值为13.7 PgC a^-1,而MTE_GPP仅为6.9 PgC a^-1;(2)CLM4-CN可以合理模拟GPP的季节变化(与MTE_GPP相关系数大于0.9),在量值上对温带阔叶落叶林、寒带阔叶落叶林、寒带阔叶落叶灌木、C3极地草地、C3非极地草地和农作物模拟较好(均方根偏差RMSD 〈 100 gC m^-2 month^-1);(3)不同植物功能型CLM4_GPP表现出的年际变率均大于MTE_GPP,仅热带针叶常绿林、寒带阔叶落叶林和C3极地草地的CLM4_GPP与MTE_GPP变化趋势一致;(4)降水是研究时段内控制整个中国区域GPP的主要气候因子,但不同地区存在较大差异;(5)两种不同土地覆盖资料GPP模拟结果的显著差异表明,精确的土地覆盖是准确模拟GPP的重要基础.
基金supported by the National Basic Research Program of China (Grants Nos. 2010CB951101 and 2010CB428403)the National Natural Science Foundation of China (Grant No. 91125016)
文摘In this study, the high-accuracy multisource integrated Chinese land cover(MICLCover) dataset was used in version 4 of the Community Land Model(CLM4) to assess how the new land cover information affected land surface simulation over China. Compared to the default land cover dataset in CLM4, the MICL data indicated lower values for bare soil(14.6% reduction), needleleaf tree(3.6%), and broadleaf tree(1.9%); higher values for shrub cover(1.8% increase), grassland(9.9%), cropland(5.0%), glaciers(0.5%), lakes(1.6%), and wetland(1.1%); and unchanged for urban areas. Two comparative CLM4 simulations were conducted for the 33-yr period from 1972 to 2004, one using the MICL dataset and the other using the default dataset. The results revealed that the MICL data produced a 0.3% lower mean annual surface albedo over China than the original data. The largest contributor to the reduced value was semiarid regions(2.1% reduction). The MICL-data albedo value agreed more closely with observations(MODIS broadband black-sky albedo products) over arid and semiarid regions than for the original data to some extent. The simulated average sensible heat flux over China increased by only 0.1 W m–2 owing to the reduced values in arid and semiarid regions, as opposed to increases in humid and semihumid regions, while an increased latent heat flux of 1 W m–2 was reflected in almost identical changes over the whole region. In addition, the mean annual runoff simulated by CLM4 using MICL data decreased by 6.8 mm yr–1, primarily due to large simulated decreases in humid regions.
基金jointly supported by the National Key Research and Development Program of China(Grant No.2016YFA0600704)the National Natural Science Foundation(Grant No.41375104)the Climate Change Specific Fund of China(Grant Nos.CCSF201626 and CCSF201509)
文摘A long-term simulation for the period 1990–2010 is conducted with the latest version of the International Centre for Theoretical Physics' Regional Climate Model(RegCM4), driven by ERA-Interim boundary conditions at a grid spacing of 25 km. The Community Land Model(CLM) is used to describe land surface processes, with updates in the surface parameters,including the land cover and surface emissivity. The simulation is compared against observations to evaluate the model performance in reproducing the present day climatology and interannual variability over the 10 main river basins in China,with focus on surface air temperature and precipitation. Temperature and precipitation from the ERA-Interim reanalysis are also considered in the model assessment. Results show that the model reproduces the present day climatology over China and its main river basins, with better performances in June–July–August compared to December–January–February(DJF).In DJF, we find a warm bias at high latitudes, underestimated precipitation in the south, and overestimated precipitation in the north. The model in general captures the observed interannual variability, with greater skill for temperature. We also find an underestimation of heavy precipitation events in eastern China, and an underestimation of consecutive dry days in northern China and the Tibetan Plateau. Similar biases for both mean climatology and extremes are found in the ERA-Interim reanalysis, indicating the difficulties for climate models in simulating extreme monsoon climate events over East Asia.