Author:
Baek Ji-Yeon,Park Jinku,Kim Dae-Won,Lee Jong-Seok,Lee Jae-Yong,Lee Seung-Jae,Jo Young-Heon
Abstract
Reduced amounts of aerosols blowing into the Yellow Sea (YS), owing to the temporary lockdown of factories in China during COVID-19, resulted in a 15% decrease in spring chlorophyll-a concentration (CHL) in March 2020 compared to its mean March values from 2003 to 2021. Particularly, the effect of land-based AOD is insignificant compared with that of atmospheric aerosols flowing into the YS, as indicated by the currents and wind directions. Hence, the main objective of this study was to understand the relationship between atmospheric aerosols and CHL by quantitatively considering relevant environmental changes using a Random Forest (RF) algorithm. Various input physical forcing variables to RF were employed, including aerosol optical depth (AOD), sea surface temperature (SST), mixed layer depth (MLD), wind divergence (WD), and total precipitation (TP). From the RF-based analysis, we estimated the relative contribution of each physical forcing variable to the difference in CHL during and after the COVID-19 lockdown period. The sensitivity of the RF model to changes in aerosol levels indicated positive effects of increased amounts of aerosols during spring blooms. Additionally, we calculated the quantitative contribution of aerosols to CHL changes. When SST was warmer and TP was lower than their climatology in March 2020, CHL increased by 0.22 mg m-3 and 0.02 mg m-3, respectively. Conversely, when MLD became shallower and AOD was lower than their climatology, CHL decreased as much as 0.01 mg m-3 and 0.20 mg m-3. Variations in WD caused no significant change in CHL. Overall, the specific estimations for reduced spring blooms were caused by a reduction in aerosols during the COVID-19 lockdown period. Furthermore, the RF developed in this study can be used to examine CHL changes and the relative role of significant environmental changes in biological blooms in the ocean for any normal year.
Funder
National Research Foundation of Korea
Subject
Ocean Engineering,Water Science and Technology,Aquatic Science,Global and Planetary Change,Oceanography
Reference79 articles.
1. Random Forests and Decision Trees;Ali;Int. J. Comput. Sci. Issues (IJCSI),2012
2. Modeled Chl: C Ratio and Derived Estimates of Phytoplankton Carbon Biomass and its Contribution to Total Particulate Organic Carbon in the Global Surface Ocean;Arteaga;Global Biogeochemical Cycles,2016
3. Impact of Coronavirus Outbreak on NO2 Pollution Assessed Using TROPOMI and OMI Observations;Bauwens;Geophysical Res. Lett.,2020
4. Active calculus 2.1. (Allendale, MI. United State of America: Grand Valley State University Libraries)
BoelkinsM.
AustinD.
SchlickerS.
2018
5. Random Forests;Breiman;Mach. Learn.,2001
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献