| YU Tan,HE Yijun,ZHA Guozhen,SONG Jinbao,LIU Guoqiang,GUO Jie. 2013. Global air-sea surface carbon-dioxide transfer velocity and flux estimated using ERS-2 data and a new parametric formula. Acta Oceanologica Sinica, 32(7):78－87 |
| Global air-sea surface carbon-dioxide transfer velocity and flux estimated using ERS-2 data and a new parametric formula |
| Global air-sea surface carbon-dioxide transfer velocity and flux estimated using ERS-2 data and a new parametric formula |
| Received:June 04, 2012 Revised:September 28, 2012 |
| DOI：10.1007/s13131-013-0334-0 |
| Key words:gas transfer velocity carbon dioxide flux wave steepness European remote sensing scatterometer |
| 中文关键词: gas transfer velocity carbon dioxide flux wave steepness European remote sensing scatterometer |
| 基金项目:Public Science and Technology Research Funds Projects of Ocean under contract No. 200905012; a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) of China. |
| Author Name | Affiliation | E-mail | | YU Tan | Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China
Key Laboratory of Chinese Academy of Sciences for Ocean Circulation andWaves (KLOCAW), Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
School ofMarine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
College ofMarine Sciences, Shanghai Ocean University, Shanghai 201306, China | | | HE Yijun | School ofMarine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China | yjhe@nuist.edu.cn | | ZHA Guozhen | Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China
Key Laboratory of Chinese Academy of Sciences for Ocean Circulation andWaves (KLOCAW), Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China | | | SONG Jinbao | Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
Key Laboratory of Chinese Academy of Sciences for Ocean Circulation andWaves (KLOCAW), Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China | | | LIU Guoqiang | Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China
Key Laboratory of Chinese Academy of Sciences for Ocean Circulation andWaves (KLOCAW), Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China | | | GUO Jie | Key Laboratory of Chinese Academy of Sciences for Coastal Zone Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China
Key Laboratory of Shandong Province for Coastal Zone Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China | |
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| Abstract: |
| Using data from the European remote sensing scatterometer (ERS-2) from July 1997 to August 1998, global distributions of the air-sea CO2 transfer velocity and flux are retrieved. A new model of the air-sea CO2 transfer velocity with surface wind speed and wave steepness is proposed. The wave steepness (δ) is retrieved using a neural network (NN) model fromERS-2 scatterometer data, while the wind speed is directly derived by the ERS-2 scatterometer. The new model agrees well with the formulations based on the wind speed and the variation in the wind speed dependent relationships presented inmany previous studies can be explained by this proposed relationwith variationinwave steepness effect. Seasonally globalmaps of gas transfer velocity and flux are shown on the basis of the newmodel and the seasonal variations of the transfer velocity and flux during the 1 a period. The globalmean gas transfer velocity is 30 cm/h after area-weighting and Schmidt number correction and its accuracy remains calculation with in situ data. The highest transfer velocity occurs around 60°N and 60°S, while the lowest on the equator. The total air to sea CO2 flux (calculated by carbon) in that year is 1.77 Pg. The strongest source of CO2 is in the equatorial east Pacific Ocean, while the strongest sink is in the 68°N. Full exploration of the uncertainty of this estimate awaits further data. An effectual method is provided to calculate the effect of waves on the determination of air-sea CO2 transfer velocity and fluxes with ERS-2 scatterometer data. |
| 中文摘要: |
| Using data from the European remote sensing scatterometer (ERS-2) from July 1997 to August 1998, global distributions of the air-sea CO2 transfer velocity and flux are retrieved. A new model of the air-sea CO2 transfer velocity with surface wind speed and wave steepness is proposed. The wave steepness (δ) is retrieved using a neural network (NN) model fromERS-2 scatterometer data, while the wind speed is directly derived by the ERS-2 scatterometer. The new model agrees well with the formulations based on the wind speed and the variation in the wind speed dependent relationships presented inmany previous studies can be explained by this proposed relationwith variationinwave steepness effect. Seasonally globalmaps of gas transfer velocity and flux are shown on the basis of the newmodel and the seasonal variations of the transfer velocity and flux during the 1 a period. The globalmean gas transfer velocity is 30 cm/h after area-weighting and Schmidt number correction and its accuracy remains calculation with in situ data. The highest transfer velocity occurs around 60°N and 60°S, while the lowest on the equator. The total air to sea CO2 flux (calculated by carbon) in that year is 1.77 Pg. The strongest source of CO2 is in the equatorial east Pacific Ocean, while the strongest sink is in the 68°N. Full exploration of the uncertainty of this estimate awaits further data. An effectual method is provided to calculate the effect of waves on the determination of air-sea CO2 transfer velocity and fluxes with ERS-2 scatterometer data. |
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