随着城市化、工业化的快速发展,空气污染已经成为了公众最关注的问题之一。为了提高空气质量预报的准确度,以多尺度空气质量模型(Community Multi-Scale Air Quality,CMAQ)为工具,结合中尺度WRF(Weather Research and Forecast Model)...随着城市化、工业化的快速发展,空气污染已经成为了公众最关注的问题之一。为了提高空气质量预报的准确度,以多尺度空气质量模型(Community Multi-Scale Air Quality,CMAQ)为工具,结合中尺度WRF(Weather Research and Forecast Model)气象预报数据、气象观测数据、污染物浓度观测数据,基于极端随机树方法建立了WRF-CMAQ-MOS(Weather Research and Forecast Model-Community Multi-Scale Air Quality-Model Output Statistics)统计修正模型。结果表明,结合WRF气象预报的CMAQ-MOS方法明显修正了由于模型非客观性产生的模式预报偏差,提高了预报效果。使用线性回归方法不能获得较好的优化效果,选取极端随机树方法和梯度提升回归树方法对模型进行改进和比较,发现极端随机树方法对结合WRF气象要素的CMAQ-MOS模型有较大的提升。针对徐州地区空气质量预报,进一步使用基于极端随机树方法的WRF-CMAQ-MOS模型对2016年1、2、3月的空气质量指数(AQI)及PM_(2.5)、PM_(10)、NO_2、SO_2、O_3、CO六种污染物优化试验进行验证,发现优化效果最为明显的两种污染物分别是NO_2及O_3,2016年1、2、3月整体相关系数NO_2由0.35升至0.63,O_3由0.39升至0.79,均方根误差NO_2由0.0346减至0.0243 mg/m^3,O_3由0.0447减至0.0367 mg/m^3。文中发展的WRFCMAQ-MOS统计修正模型可以有效提升预报精度,在空气质量预报中具有很好的应用前景。展开更多
Studies of offshore wave climate based on satellite altimeter significant wave height（SWH） have widespread application value. This study used a calibrated multi-altimeter SWH dataset to investigate the wave climate ...Studies of offshore wave climate based on satellite altimeter significant wave height（SWH） have widespread application value. This study used a calibrated multi-altimeter SWH dataset to investigate the wave climate characteristics in the offshore areas of China. First, the SWH measurements from 28 buoys located in China＇s coastal seas were compared with an Ifremer calibrated altimeter SWH dataset. Although the altimeter dataset tended to slightly overestimate SWH, it was in good agreement with the in situ data in general. The correlation coefficient was 0.97 and the root-mean-square（RMS） of differences was 0.30 m. The validation results showed a slight difference in different areas. The correlation coefficient was the maximum（0.97） and the RMS difference was the minimum（0.28 m） in the area from the East China Sea to the north of the South China Sea.The correlation coefficient of approximately 0.95 was relatively low in the seas off the Changjiang（Yangtze River） Estuary. The RMS difference was the maximum（0.32 m） in the seas off the Changjiang Estuary and was0.30 m in the Bohai Sea and the Yellow Sea. Based on the above evidence, it is confirmed that the multialtimeter wave data are reliable in China＇s offshore areas. Then, the characteristics of the wave field, including the frequency of huge waves and the multi-year return SWH in China＇s offshore seas were analyzed using the23-year altimeter wave dataset. The 23-year mean SWH generally ranged from 0.6-2.2 m. The greatest SWH appeared in the southeast of the China East Sea, the Taiwan Strait and the northeast of the South China Sea.Obvious seasonal variation of SWH was found in most areas; SWH was greater in winter and autumn than in summer and spring. Extreme waves greater than 4 m in height mainly occurred in the following areas： the southeast of the East China Sea, the south of the Ryukyu Islands, the east of Taiwan-Luzon Island, and the Dongsha Islands extending to the Zhongsha Islands, and the frequency of extreme waves was 3%-6%. Extreme waves occurred most frequently in autumn and rarely in spring. The 100-year return wave height was greatest from the northwest Pacific seas extending to southeast of the Ryukyu Islands（9-12 m）, and the northeast of the South China Sea and the East China Sea had the second largest wave heights（7-11 m）. For inshore areas, the100-year return wave height was the greatest in the waters off the east coast of Guangdong Province and the south coast of Zhejiang Province（7-8 m）, whereas it was at a minimum in the area from the Changjiang Estuary to the Bohai Sea（4-6 m）. An investigation of sampling effects indicates that when using the 1°×1°grid dataset, although the combination of nine altimeters obviously enhanced the time and space coverage of sampling, the accuracy of statistical results, particularly extreme values obtained from the dataset, still suffered from undersampling problems because the time sampling percent in each 1°×1°grid cell was always less than33%.展开更多
作物生长与气候的互馈是当前气候变化研究的热点之一。陆面模型作为一项重要的研究工具,其模型框架、算法设计及参数化方案的不同会直接导致模拟结果的不确定性。为探究陆面模型DLM(dynamic land model)和CLM5(community land model)在...作物生长与气候的互馈是当前气候变化研究的热点之一。陆面模型作为一项重要的研究工具,其模型框架、算法设计及参数化方案的不同会直接导致模拟结果的不确定性。为探究陆面模型DLM(dynamic land model)和CLM5(community land model)在作物生长及农田热通量模拟方面的差异及原因,评估2个模型在华北平原作物研究中的适用程度,论文开展了冬小麦—夏玉米轮作站点的模拟对比研究。结果显示,DLM的夏玉米叶面积指数和生态系统总初级生产力的模拟值更高,与观测值更为接近;CLM5模型则在冬小麦模拟中略优。DLM的潜热模拟值与观测值的相关性普遍更高,可能反映了DLM采用的彭曼公式、双叶策略比CLM5采用基于水势梯度质量守恒、大叶策略的潜热计算方法更具优势。对于产量,模型当前的估测能力并不理想。总的来说,在默认设定下,2个模型的模拟结果能基本反映研究区农田站点内夏玉米和冬小麦的生长规律,但与实测值存在一定偏差。模型在该区域的适用性可能需要通过添加农田管理措施、算法优化和参数本地化等方式进一步提高。展开更多
文摘随着城市化、工业化的快速发展,空气污染已经成为了公众最关注的问题之一。为了提高空气质量预报的准确度,以多尺度空气质量模型(Community Multi-Scale Air Quality,CMAQ)为工具,结合中尺度WRF(Weather Research and Forecast Model)气象预报数据、气象观测数据、污染物浓度观测数据,基于极端随机树方法建立了WRF-CMAQ-MOS(Weather Research and Forecast Model-Community Multi-Scale Air Quality-Model Output Statistics)统计修正模型。结果表明,结合WRF气象预报的CMAQ-MOS方法明显修正了由于模型非客观性产生的模式预报偏差,提高了预报效果。使用线性回归方法不能获得较好的优化效果,选取极端随机树方法和梯度提升回归树方法对模型进行改进和比较,发现极端随机树方法对结合WRF气象要素的CMAQ-MOS模型有较大的提升。针对徐州地区空气质量预报,进一步使用基于极端随机树方法的WRF-CMAQ-MOS模型对2016年1、2、3月的空气质量指数(AQI)及PM_(2.5)、PM_(10)、NO_2、SO_2、O_3、CO六种污染物优化试验进行验证,发现优化效果最为明显的两种污染物分别是NO_2及O_3,2016年1、2、3月整体相关系数NO_2由0.35升至0.63,O_3由0.39升至0.79,均方根误差NO_2由0.0346减至0.0243 mg/m^3,O_3由0.0447减至0.0367 mg/m^3。文中发展的WRFCMAQ-MOS统计修正模型可以有效提升预报精度,在空气质量预报中具有很好的应用前景。
基金The National Natural Science Foundation of China under contract No.41276009
文摘Studies of offshore wave climate based on satellite altimeter significant wave height（SWH） have widespread application value. This study used a calibrated multi-altimeter SWH dataset to investigate the wave climate characteristics in the offshore areas of China. First, the SWH measurements from 28 buoys located in China＇s coastal seas were compared with an Ifremer calibrated altimeter SWH dataset. Although the altimeter dataset tended to slightly overestimate SWH, it was in good agreement with the in situ data in general. The correlation coefficient was 0.97 and the root-mean-square（RMS） of differences was 0.30 m. The validation results showed a slight difference in different areas. The correlation coefficient was the maximum（0.97） and the RMS difference was the minimum（0.28 m） in the area from the East China Sea to the north of the South China Sea.The correlation coefficient of approximately 0.95 was relatively low in the seas off the Changjiang（Yangtze River） Estuary. The RMS difference was the maximum（0.32 m） in the seas off the Changjiang Estuary and was0.30 m in the Bohai Sea and the Yellow Sea. Based on the above evidence, it is confirmed that the multialtimeter wave data are reliable in China＇s offshore areas. Then, the characteristics of the wave field, including the frequency of huge waves and the multi-year return SWH in China＇s offshore seas were analyzed using the23-year altimeter wave dataset. The 23-year mean SWH generally ranged from 0.6-2.2 m. The greatest SWH appeared in the southeast of the China East Sea, the Taiwan Strait and the northeast of the South China Sea.Obvious seasonal variation of SWH was found in most areas; SWH was greater in winter and autumn than in summer and spring. Extreme waves greater than 4 m in height mainly occurred in the following areas： the southeast of the East China Sea, the south of the Ryukyu Islands, the east of Taiwan-Luzon Island, and the Dongsha Islands extending to the Zhongsha Islands, and the frequency of extreme waves was 3%-6%. Extreme waves occurred most frequently in autumn and rarely in spring. The 100-year return wave height was greatest from the northwest Pacific seas extending to southeast of the Ryukyu Islands（9-12 m）, and the northeast of the South China Sea and the East China Sea had the second largest wave heights（7-11 m）. For inshore areas, the100-year return wave height was the greatest in the waters off the east coast of Guangdong Province and the south coast of Zhejiang Province（7-8 m）, whereas it was at a minimum in the area from the Changjiang Estuary to the Bohai Sea（4-6 m）. An investigation of sampling effects indicates that when using the 1°×1°grid dataset, although the combination of nine altimeters obviously enhanced the time and space coverage of sampling, the accuracy of statistical results, particularly extreme values obtained from the dataset, still suffered from undersampling problems because the time sampling percent in each 1°×1°grid cell was always less than33%.
文摘作物生长与气候的互馈是当前气候变化研究的热点之一。陆面模型作为一项重要的研究工具,其模型框架、算法设计及参数化方案的不同会直接导致模拟结果的不确定性。为探究陆面模型DLM(dynamic land model)和CLM5(community land model)在作物生长及农田热通量模拟方面的差异及原因,评估2个模型在华北平原作物研究中的适用程度,论文开展了冬小麦—夏玉米轮作站点的模拟对比研究。结果显示,DLM的夏玉米叶面积指数和生态系统总初级生产力的模拟值更高,与观测值更为接近;CLM5模型则在冬小麦模拟中略优。DLM的潜热模拟值与观测值的相关性普遍更高,可能反映了DLM采用的彭曼公式、双叶策略比CLM5采用基于水势梯度质量守恒、大叶策略的潜热计算方法更具优势。对于产量,模型当前的估测能力并不理想。总的来说,在默认设定下,2个模型的模拟结果能基本反映研究区农田站点内夏玉米和冬小麦的生长规律,但与实测值存在一定偏差。模型在该区域的适用性可能需要通过添加农田管理措施、算法优化和参数本地化等方式进一步提高。
