It is very important in accurately estimating the forests＇ carbon stock and spatial distribution in the regional scale because they possess a great rate in the carbon stock of the terrestrial ecosystem. Yet the curre...It is very important in accurately estimating the forests＇ carbon stock and spatial distribution in the regional scale because they possess a great rate in the carbon stock of the terrestrial ecosystem. Yet the current estimation of forest carbon stock in the regional scale mainly depends on the forest inventory data, and the whole process consumes too much labor, money and time. And meanwhile it has many negative influences on the forest carbon storage updating. In order to figure out these problems, this paper, based on High Accuracy Surface Modeling （HASM）, proposes a forest vegetation carbon storage simulation method. This new method employs the output of LPJ-GUESS model as initial values of HASM and uses the inventory data as sample points of HASM to simulate the distribution of forest carbon storage in China. This study also adopts the seventh forest resources statistics of China as the data source to generate sample points, and it also works as the simulation accuracy test. The HASM simulation shows that the total forest carbon storage of China is 9.2405 Pg, while the calculated value based on forest resources statistics are 7.8115 Pg. The forest resources statistics is taken based on a forest canopy closure, and the result of HASM is much more suitable to the real forest carbon storage. The simulation result also indicates that the southwestern mountain region and the northeastern forests are the important forest carbon reservoirs in China, and they account for 39.82% and 20.46% of the country＇s total forest vegetation carbon stock respectively. Compared with the former value （1975-1995）, it mani- fests that the carbon storage of the two regions do increase clearly. The results of this re- search show that the large-scale reforestation in the last decades in China attains a signifi- cant carbon sink.展开更多
准确理解地质历史时期气候变化的现象和机制,对预测未来气候变化有重要的启示意义。末次间冰期早期是研究未来气候变化可参考的典型暖期。目前,基于气候模式模拟的末次间冰期早期温度低于气候记录重建的结果。这一现状的一个潜在原因在...准确理解地质历史时期气候变化的现象和机制,对预测未来气候变化有重要的启示意义。末次间冰期早期是研究未来气候变化可参考的典型暖期。目前,基于气候模式模拟的末次间冰期早期温度低于气候记录重建的结果。这一现状的一个潜在原因在于,这些气候模拟研究中采用的植被数据为工业革命前水平,忽略了植被动态对气候的反馈作用。本研究利用iLOVECLIM气候模式耦合植被模块VECODE和LPJ-GUESS开展末次间冰期早期(125 ka B. P.)植被动态对气候反馈作用的模拟分析。模拟结果显示,相比基于工业革命前植被条件模拟得到的温度水平,耦合动态植被模拟的全球气候更温暖,但仍略低于记录重建的温度。在大陆/亚大陆尺度,高纬和北非地区模拟的125 ka B. P.植被覆盖度明显高于工业革命前水平,增温幅度也显著高于其他地区;此外,末次间冰期早期北非植被覆盖对区域气温的正反馈通过增强的大气环流使低纬地区输送到高纬地区热量增加,从而表现出对全球气温的正反馈作用。展开更多
基金National High-tech R&D Program of the Ministry of Science and Technology of the People's Republic of China,No.2013AA122003National Key Technologies R&D Program of the Ministry of Science and Tech-nology of China,No.2013BACO3B05
文摘It is very important in accurately estimating the forests＇ carbon stock and spatial distribution in the regional scale because they possess a great rate in the carbon stock of the terrestrial ecosystem. Yet the current estimation of forest carbon stock in the regional scale mainly depends on the forest inventory data, and the whole process consumes too much labor, money and time. And meanwhile it has many negative influences on the forest carbon storage updating. In order to figure out these problems, this paper, based on High Accuracy Surface Modeling （HASM）, proposes a forest vegetation carbon storage simulation method. This new method employs the output of LPJ-GUESS model as initial values of HASM and uses the inventory data as sample points of HASM to simulate the distribution of forest carbon storage in China. This study also adopts the seventh forest resources statistics of China as the data source to generate sample points, and it also works as the simulation accuracy test. The HASM simulation shows that the total forest carbon storage of China is 9.2405 Pg, while the calculated value based on forest resources statistics are 7.8115 Pg. The forest resources statistics is taken based on a forest canopy closure, and the result of HASM is much more suitable to the real forest carbon storage. The simulation result also indicates that the southwestern mountain region and the northeastern forests are the important forest carbon reservoirs in China, and they account for 39.82% and 20.46% of the country＇s total forest vegetation carbon stock respectively. Compared with the former value （1975-1995）, it mani- fests that the carbon storage of the two regions do increase clearly. The results of this re- search show that the large-scale reforestation in the last decades in China attains a signifi- cant carbon sink.
文摘准确理解地质历史时期气候变化的现象和机制,对预测未来气候变化有重要的启示意义。末次间冰期早期是研究未来气候变化可参考的典型暖期。目前,基于气候模式模拟的末次间冰期早期温度低于气候记录重建的结果。这一现状的一个潜在原因在于,这些气候模拟研究中采用的植被数据为工业革命前水平,忽略了植被动态对气候的反馈作用。本研究利用iLOVECLIM气候模式耦合植被模块VECODE和LPJ-GUESS开展末次间冰期早期(125 ka B. P.)植被动态对气候反馈作用的模拟分析。模拟结果显示,相比基于工业革命前植被条件模拟得到的温度水平,耦合动态植被模拟的全球气候更温暖,但仍略低于记录重建的温度。在大陆/亚大陆尺度,高纬和北非地区模拟的125 ka B. P.植被覆盖度明显高于工业革命前水平,增温幅度也显著高于其他地区;此外,末次间冰期早期北非植被覆盖对区域气温的正反馈通过增强的大气环流使低纬地区输送到高纬地区热量增加,从而表现出对全球气温的正反馈作用。
