Estimation of Atmosphere-Ocean CO2 Flux in the East Sea using Geostationary Ocean Color Imager Data

Title
Estimation of Atmosphere-Ocean CO2 Flux in the East Sea using Geostationary Ocean Color Imager Data
Author(s)
장은나; 임정호; 박근하; 박영규
KIOST Author(s)
Park, Young Gyu(박영규)
Alternative Author(s)
박근하; 박영규
Publication Year
2018-04-09
Abstract
The ocean plays an important role in controlling the Earth’s climate by regulating the concentration of CO2 through air-sea carbon cycle while storing more than 50 times as much CO2 as the atmosphere. With the on-going climate change, as the atmospheric CO2 increases, the ocean CO2 also increases. Oceanic acidification dissolves the shells which consist of calcium carbonate to increase CO2. Thus, the monitoring of CO2 and the flux between the atmosphere and ocean are important to analyze regional/global carbon cycle and climate change. In situ observations are difficult to monitor spatiotemporal changes because of weather, equipment, and budget problems. But satellite data can be used to cover vast areas at high temporal resolution. The purpose of this study is to first estimate surface seawater fugacity of CO2 (fCO2) in the East Sea of Korea and then to determine the CO2 fluxes between the atmosphere and ocean. To estimate fCO2, we used random forest (RF) and support vector regression (SVR) machine learning approaches. Geostationary Ocean Color Imager (GOCI) and Hybrid Coordinate Ocean Model (HYCOM) reanalysis data were used as main input data in this study. GOCI is the world first geostationary ocean color observation sensor, and it collects 8 images hourly per

day from 9 am to 4 pm in local time with 8 bands from visible to near-infrared regions at 500 m resolution. Five ocean related parameters— sea surface temperature (SST), sea surface salinity (SSS), mixed layer depth (MLD), chlorophyll-a (Chl-a), and colored dissolved organic matter (CDOM)— and 4 band reflectance (400 – 565 nm) and their ratios were used as input variables to the machine learning models. RF performed better than SVR, and SST, SSS, and MLD were most contributing parameters to estimate surface seawater fCO2 in the East Sea. It might be related with an environment of the East Sea, an active deep convection and various currents that bring warm and salty water. We also calculated and analyzed sea-air CO2 flux in the East Sea using analytical equations and the estimated surface seawater fCO2 based on the RF model. The results showed that the East Sea absorbs CO2 from the atmosphere throughout the whole region, acts as a sink for atmospheric CO2.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/23438
Bibliographic Citation
European Geosciences Union General Assembly 2018, 2018
Publisher
European Geosciences Union
Type
Conference
Language
English
Publisher
European Geosciences Union
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