Remote sensing of sea surface pCO2 in coastal ocean using a mechanistic-based semi-analytic method:a case study in the East China Sea
While satellite remote sensing has become a very useful tool for assessing sea surface partial pressure of carbon dioxide (pCO2) and the subsequent qualifying air-sea CO2 flux,the applications of currently available empirical approaches in coastal oceans have proven to be challenging due to the interaction of multiple controlling factors.We put forward a “Mechanistic-based Semi-analytic-Algorithm (MSAA) to estimate sea surface pCO2 in coastal oceans by satellite remote sensing.The observed pCO2 can be analytically expressed as the sum of individual components contributed by major controls that include thermodynamics (or temperature),mixing and biology.First,the temperature effect was predicted by thermodynamic calculation.Second,the mixing effect was predicted by total dissolved inorganic carbon (DIC) and total alkalinity (TA) values according to the mixing ratio of the two end-members (e.g.,the Changjiang River and the Kuroshio water in the East China Sea).The conservative mixing index,salinity,was derived from remotely-sensed absorption coefficient of colored dissolved organic matter (CDOM).Third,an integral expression for pCO2 drawdown by the biological effect was parameterized by satellite-derived chlorophyll a concentration eliminating the overlap of other effects.We demonstrated the validity and applicability of the algorithm in the East China Sea (ECS) during summertime when the river discharge was highest and the plume extension was greatest.The satellite-derived pCO2 distribution compared well with the high resolution underway pCO2 data collected with extensive coverage in the ECS.These two datasets showed correlated,great spatial complexity dictated by the river plume both physically and biologically.Finally,area and directions of MSAA improvements are discussed.This semi-analytic algorithm for satellite-derived pCO2 has more physical and biogeochemical mechanistic interpretations than the empirical methods,and thus should be applicable to the other systems.
Aquatic pCO2 Mechanistic-based Satellite remote sensing Semi-analytic algorithms East China Sea
Yan Bai Wei-Jun Cai Xianqiang He Weidong Zhai Delu Pan Minhan Dai Peisong Yu
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Stat School of Marine Science and Policy, University of Delaware, Newark, Delaware, USA State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
国际会议
The 17th Pacific -Asian Marginal Seas Meeting(第十七届太平洋与亚洲边缘海国际会议)
杭州
英文
802-808
2013-04-23（万方平台首次上网日期，不代表论文的发表时间）