• 关键词：Carbon Tracker模式  数值模拟  CO₂浓度  影响因子

• 基金项目：广东省自然科学基金项目（No.S2012040007057）；国家重点基础研究发展计划（No.2010CB950601）；中国气象局气候变化基础能力建设项目（No.CCSF201306，CCSF201405）；广东省气象局科学技术研究项目（No.2012B10，2011B02）；广东科技计划项目（No.2012A061400012，2011A032100006）；广州热带海洋气象研究所博士启动基金（No.220037）

• 麦博儒
• 中国气象局广州热带海洋气象研究所/广东省区域数值天气预报重点实验室, 广州 510080

• 邓雪娇
• 中国气象局广州热带海洋气象研究所/广东省区域数值天气预报重点实验室, 广州 510080

• 安兴琴
• 中国气象科学研究院, 北京 100081

• 周凌晞
• 中国气象科学研究院, 北京 100081

• 谭浩波
• 中国气象局广州热带海洋气象研究所/广东省区域数值天气预报重点实验室, 广州 510080

• 李菲
• 中国气象局广州热带海洋气象研究所/广东省区域数值天气预报重点实验室, 广州 510080

• 李楠
• 中国气象局气象探测中心, 北京 100081

• 摘要：利用瓦里关全球本底站和番禺气象局站地面观测的CO₂浓度资料对改进的Carbon Tracker-2010（CT-2010）模式系统进行了验证.结果显示，CT-2010能较好地反映近地层CO₂浓度的分布状况，在瓦里关地区，模拟值与观测值的决定系数（R²）为0.584，残差为4.49 μmol·mol^-1，相对误差为1.18%；在珠三角地区，上述3个参数值分别为0.430、13.89 μmol·mol^-1和3.63%.利用CT-2010模式对广东地区近地层典型CO₂过程及其影响因素进行了模拟和分析研究.结果表明：在典型高、低浓度CO₂过程中，以广州为中心的珠三角区域始终为CO₂浓度高值区，从东北至西南方向的梅州、河源、广州、肇庆和云浮等区域存在明显的CO₂聚集带.在典型高浓度CO₂过程中，珠三角和粤北区域的CO₂浓度上升最明显， 而粤东和粤西地区的CO₂浓度变化较小；在典型低浓度过程中，珠三角、粤北及粤东的CO₂浓度波动明显小于过程前和过程后，而粤西地区的CO₂浓度波动较大.这些变化主要是受到了风场、下垫面植被、相对湿度及气温等因子的显著影响.

• Abstract：Measurements of surface CO₂ concentrations from a background site on the Tibetan Plateau (Waliguan, WLG) and a meteorological observatory in Guangdong (Panyu, PYQXJ) were used to validate the newly-improved Carbon Tracker (CT-2010) numerical model. The model captures well the distribution of surface CO₂ concentrations. Determination coefficients(R²), residuals, and relative errors from a linear regression of model-simulated surface CO₂ concentrations as a function of ground measurements are 0.584, 4.49 μmol·mol^-1, and 1.18%, respectively, at the WLG site and 0.430, 13.89 μmol·mol^-1, and 3.63%, respectively, at the PYQXJ site. Based upon time series of mean surface CO₂ concentrations measured at Shenzhen City, two cases were identified: a low CO₂ concentration case (18-20 March 2007) and a high CO₂ concentration case (16-21 December 2007). Mean simulated CO₂ concentrations over Guangdong for these two cases were then analyzed. Overall, the highest CO₂ concentrations were centered over the Pearl River Delta (PRD) region, especially over Guangzhou City, and spread over a zone from the northeast to the southeast of Guangdong. The increase in CO₂ concentration was relatively lower in eastern and western Guangdong, but higher over the PRD region and northern Guangdong in the high CO₂ concentration case. Less change in the distribution of CO₂ concentrations over the PRD region and in northern and eastern Guangdong before and after the period selected for the low CO₂ concentration case was seen. In general, changes in CO₂ concentrations over Guangdong were influenced significantly by the wind field, vegetation, relative humidity, and temperature.

• Key words：Carbon Tracker model  numerical simulation  CO₂ concentration  influential factors

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