• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.

• Journal of the Korean earth science society
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• v.39 no.3
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• pp.228-240
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• 2018

Solar energy is calculated using meteorological (14 station), ceilometer (2 station) and microwave radiometer (MWR, 7 station)) data observed from the Weather Information Service Engine (WISE) on the Seoul metropolitan area. The cloud optical thickness and the cloud fraction are calculated using the back-scattering coefficient (BSC) of the ceilometer and liquid water path of the MWR. The solar energy on the surface is calculated using solar radiation model with cloud fraction from the ceilometer and the MWR. The estimated solar energy is underestimated compared to observations both at Jungnang and Gwanghwamun stations. In linear regression analysis, the slope is less than 0.8 and the bias is negative which is less than $-20W/m^2$. The estimated solar energy using MWR is more improved (i.e., deterministic coefficient (average $R^2=0.8$) and Root Mean Square Error (average $RMSE=110W/m^2$)) than when using ceilometer. The monthly cloud fraction and solar energy calculated by ceilometer is greater than 0.09 and lower than $50W/m^2$ compared to MWR. While there is a difference depending on the locations, RMSE of estimated solar radiation is large over $50W/m^2$ in July and September compared to other months. As a result, the estimation of a daily accumulated solar radiation shows the highest correlation at Gwanghwamun ($R^2=0.80$, RMSE=2.87 MJ/day) station and the lowest correlation at Gooro ($R^2=0.63$, RMSE=4.77 MJ/day) station.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.31 no.2
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• pp.272-277
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• 1998

Filtering rates of two farming ascidians Styela clava and S. plicata, and of a farming mussel Mytilus edulis were experimentally investigated with reference to effects of water temperature and size. Absorptiometric determinations of filtering rates were carried out in a closed system with experimental animals being decreased indicate dyes neutral red. Optical density (OD) of 440 nm in path length 22 mm cell used as the indication of food particles absorption was appeared directly in proportion with the concentration of neutral red dyes. The filtering rate F is calculated by Kim's equation $F\;=\;V(1-e^{-z})$, where V is the water volume ($\ell$) in the experimental jar, and Z is the decreasing coefficient of OD as meaning of instantaneous removal speed as In $C_t\;=\;In\;C_{o}-Z{\cdot}t$, in this formula $C_t$ is OD at the time t. Filtering rate of S. clava increased as exponential function with increasing temperature while not over critical limit, and the critical temperature for filtering rate was assumed to be between $28^{\circ}C$ and $29^{\circ}C$. In case of S. plicata, the critical temperature was to be below $13^{\circ}C$, and through the temperature range $15\~25^{\circ}C$ appeared a little difference in level even though with significant. M. edulis was not appear any significant effects by water temperature less than $29^{\circ}C$. The model formula derived from the results is as below, where F is filtering rate (${\ell}/hr/animal$), T is water temperature ($^{\circ}C$), and DW is dry meat weight (g) of experimental animal. $$S.\;Clava;\;F\;=\;e xp\;(0.119\;T-4.540)\;(DW)^{0.6745},\;T<29^{\circ}C$$) $$S.\;plicata;\;F\;=\;e xp\;(A_t)\;(DW)^{0.5675},\;(13^{\circ}C $$[A_t =-8.56+0.6805\;T-0.0153\;T^2]$$ $$M.\;edulis;\;F\;=\;0.3844\;(DW)^{0.4952},\;<29^{\circ}C$$)