| 长江三角洲地区净生态系统二氧化碳通量及浓度的数值模拟 |
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| 引用本文： | 刁一伟,黄建平,刘诚,崔健,刘寿东.长江三角洲地区净生态系统二氧化碳通量及浓度的数值模拟[J].大气科学,2015,39(5):849-860. |
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| 作者姓名： | 刁一伟 黄建平 刘诚 崔健 刘寿东 |
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| 作者单位： | 1.耶鲁大学-南京信息工程大学大气环境中心, 南京 210044;南京信息工程大学中国气象局气溶胶-云-降水重点开放实验室, 南京 210044 |
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| 基金项目： | 江苏高校优势学科建设工程项目PAPD,长江学者和创新团队发展计划项目 |
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| 摘 要： | 净生态系统碳通量(NEE)的计算对于准确模拟区域碳通量和大气CO2浓度的时空变化至关重要。本文利用中尺度大气-温室气体耦合模式WRF-GHG(Weather Research and Forecasting Model with Greenhouse Gases Module),对2010年7月28日至2010年8月2日期间影响长江三角洲地区大气CO2浓度及时空分布的各种过程进行了详尽模拟。结果表明,植被光合呼吸模型(VPRM)能模拟不同植被下垫面NEE的日变化;WRF-GHG模拟的大气CO2浓度日变化与观测相吻合,但低估了大气CO2浓度5~15 ppm(ppm表示10-6),这可能与人为排放源的低估、VPRM参数的不确定性以及气象场模拟的不准确性有关。太湖和植被覆盖较好的地区如浙江北部山区是该地区的主要碳汇,而城市为CO2的主要排放源。太湖和陆地生态系统对区域内碳循环起到一定的调节作用,减缓区域大气CO2浓度的升高。此外,局地气象条件如湖陆风对太湖周边地区大气CO2浓度有显著影响。
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| 关 键 词： | 长江三角洲 WRF-GHG耦合模式 二氧化碳浓度 净生态系统碳通量 |
| 收稿时间： | 2014/2/17 0:00:00 |
| 修稿时间： | 2014/9/23 0:00:00 |
A Modeling Study of CO2 Flux and Concentrations over the Yangtze River Delta Using the WRF-GHG Model |
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| DIAO Yiwei,HUANG Jianping,LIU Cheng,CUI Jian and LIU Shoudong.A Modeling Study of CO2 Flux and Concentrations over the Yangtze River Delta Using the WRF-GHG Model[J].Chinese Journal of Atmospheric Sciences,2015,39(5):849-860. |
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| Authors: | DIAO Yiwei HUANG Jianping LIU Cheng CUI Jian and LIU Shoudong |
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| Institution: | Yale-NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044;Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing 210044,Yale-NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044;Jiangsu Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044,Yale-NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044,Yale-NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044 and Yale-NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044;Jiangsu Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044 |
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| Abstract: | Accurate quantification of land-atmosphere exchange is crucial for the simulation of regional scale carbon flux and CO2 concentrations. In this study, a coupling model, WRF-GHG (Weather Research and Forecasting Model with Greenhouse Gases Module) is employed to simulate regional net ecosystem exchange (NEE) and atmospheric CO2 concentrations over the Yangtze River Delta (YRD) from July 28 to August 2, 2010. In the modeling system, several "tagged" species are defined to trace the contribution of various sources to atmospheric CO2 concentrations. The simulated NEE fluxes and CO2 concentrations are evaluated against in-situ measurements. The results show that VPRM can reproduce spatial-temporal variation patterns of NEE over different types of vegetation. Overall, the diurnal patterns in CO2 concentration compared quite well with field measurements, indicating that the model captures the major features in the diurnal variations of CO2. However, the model underestimates CO2 concentrations by 5~15 ppm (10-6). This is most likely due to an underestimation of anthropogenic emissions, the uncertainties of parameters defined in VPRM, and meteorological inputs. Local meteorological conditions, such as land-lake breeze, exert an important impact on CO2 concentrations. While lake-atmospheric interactions over Lake Taihu and vegetation-atmospheric interactions over mountain areas in northern Zhejiang province play a dominate role in carbon sink, urban-related anthropogenic emissions act as a major source of carbon. The WRF-GHG modeling system demonstrated its capability of simulating local and regional variations in CO2 fluxes and concentrations. |
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| Keywords: | Yangtze River Delta WRF-GHG model CO2 concentrations Net ecosystem exchange |
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