• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1295-1305
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• 2021

Satellite-derived ocean color products are required to effectively monitor clear open ocean and coastal water regions for various research fields. For this purpose, accurate correction of atmospheric effect is essential. Currently, the Geostationary Ocean Color Imager (GOCI)-II ground segment uses the reanalysis of meteorological fields such as European Centre for Medium-Range Weather Forecasts (ECMWF) or National Centers for Environmental Prediction (NCEP) to correct gas absorption by water vapor and ozone. In this process, uncertainties may occur due to the low spatiotemporal resolution of the meteorological data. In this study, we develop water vapor absorption correction model for the GK-2 combined GOCI-II atmospheric correction using Advanced Meteorological Imager (AMI) total precipitable water (TPW) information through radiative transfer model simulations. Also, we investigate the impact of the developed model on GOCI products. Overall, the errors with and without water vapor absorption correction in the top-of-atmosphere (TOA) reflectance at 620 nm and 680 nm are only 1.3% and 0.27%, indicating that there is no significant effect by the water vapor absorption model. However, the GK-2A combined water vapor absorption model has the large impacts at the 709 nm channel, as revealing error of 6 to 15% depending on the solar zenith angle and the TPW. We also found more significant impacts of the GK-2 combined water vapor absorption model on Rayleigh-corrected reflectance at all GOCI-II spectral bands. The errors generated from the TOA reflectance is greatly amplified, showing a large error of 1.46~4.98, 7.53~19.53, 0.25~0.64, 14.74~40.5, 8.2~18.56, 5.7~11.9% for from 620 nm to 865 nm, repectively, depending on the SZA. This study emphasizes the water vapor correction model can affect the accuracy and stability of ocean color products, and implies that the accuracy of GOCI-II ocean color products can be improved through fusion with GK-2A/AMI.

• Journal of Astronomy and Space Sciences
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• v.24 no.1
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• pp.55-68
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• 2007

We carried out a validation study on AURIC FUV/EUV dayglow calculation with $OII\;834{\AA},\;OI\;989{\AA},\;OI\;1027{\AA},\;NII\;1085{\AA},\;NI\;1134{\AA},\;NI\;1200{\AA},\;OI\;1304{\AA},\;OI\;1356{\AA}$ dayglows observed by STP78-1 satellite. Comparison between calculated and observed values indicates that they are in agreement within about 20% for dayglows of $OII\;834{\AA},\;OI\;1027{\AA},\;NI\;1200{\AA},\;OI\;1304{\AA}$. However, the calculated intensities of $OI\;989{\AA},\;NII\;1085{\AA},\;NI\;1134{\AA}$ are only 42, 74 and 45% of the observed values, respectively, showing serious differences from the observation. It was surmised that the differences in $OI\;989{\AA}\;and\;NI\;1134{\AA}$ are due to incomplete calculation of radiative transfer and uncertain photochemical processes in AURIC model, respectively. The difference in $NII\;1085{\AA}$ is conjectured to be due to variation of the input solar EUV flux rather than due to AURIC model itself. For up-looking dayglows from the satellite, the calculated values from AURIC are all less than those of STP78-1, which may imply that AURIC model does not include dayglow contribution from regions below the satellite altitude when it computes dayglows in up-looking direction. The differences are particularly serious for $OI\;989{\AA},\;NI\;1134{\AA},\;NI\;1200{\AA}$ dayglows. The calculated latitudinal variation of $OII\;834{\AA}$ dayglow is also significantly different from the observed one, especially at mid-latitude regions. This may be due to inability of MSISE-90 (in input of AURIC) to simulate oxygen atom densities at mid-latitudes during auroral storms at those days of STP78-1 observations. Our findings of the validation study should be resolved when AURIC model is revised in future.

• Journal of the Korean earth science society
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• v.23 no.7
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• pp.552-564
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• 2002

The data of satellite-observed Microwave Sounding Unit (MSU) channel 1 (Ch1) brightness temperature and General Circulation Model (GCM) reanalyses over the globe have been used to investigate low tropospheric hydrometeors and microwave surface emissivity during the period from January 1981 to December 1993. The average of GCM Ch1 temperature has been reconstructed from three kinds of reanalyses, based on the MSU weighting function. Since the GCM temperature mainly corresponds to the thermal state of the lower troposphere without the difference in the emissivity between ocean and land, it is higher in summer than in other seasons over the regions. The MSU temperature over the ocean shows its maximum at the ITCZ and the SPCZ due to hydrometeors. Over high latitude ocean, the temperature is enhanced because of sea ice emissivity, while it is reduced over the land. The seasonal displacement of the ITCZ and the SPCZ systematically appeared in the difference of Ch1 temperature between the GCM and the MSU. The difference values decrease in the regions of the ITCZ, the SPCZ, and the sea ice because of the increase of the MSU temperature. According to the local minima of the values, the ITCZ moves norhward to 9 N in fall, and the SPCZ moves southward to 12 S in boreal fall and winter. The sea ice in the northern hemisphere is extended southward to 53 N in winter, while the ice in the southern hemisphere, northward to 58 S in boreal summer. We also have discussed the separated contribution from hydrometeors and surface emissivity to the MSU Ch1 temperature, utilizing radiative transfer theory. The increase of 4-6K in the temperature over the ITCZ is inferred to result from hydrometeors of 1-1.5mm/day, and furthermore the increase of 10-30K over the high latitude ocean, ice emissivity of 0.6-0.9.

• Journal of the Korean earth science society
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• v.39 no.1
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• pp.53-66
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• 2018

The information of surface reflectance ($R_{sfc}$) is important for the heat balance and the environmental/climate monitoring. The $R_{sfc}$ sensitivity to error-induced variables for the Geostationary Environment Monitoring Spectrometer (GEMS) retrieval from geostationary-orbit satellite observations at 300-500 nm was investigated, utilizing polar-orbit satellite data of the MODerate resolution Imaging Spectroradiometer (MODIS) and Ozone Mapping Instrument (OMI), and the radiative transfer model (RTM) experiment. The variables in this study can be cloud, Rayleigh-scattering, aerosol, ozone and surface type. The cloud detection in high-resolution MODIS pixels ($1km{\times}1km$) was compared with that in GEMS-scale pixels ($8km{\times}7km$). The GEMS detection was consistent (~79%) with the MODIS result. However, the detection probability in partially-cloudy (${\leq}40%$) GEMS pixels decreased due to other effects (i.e., aerosol and surface type). The Rayleigh-scattering effect in RGB images was noticeable over ocean, based on the RTM calculation. The reflectance at top of atmosphere ($R_{toa}$) increased with aerosol amounts in case of $R_{sfc}$<0.2, but decreased in $R_{sfc}{\geq}0.2$. The $R_{sfc}$ errors due to the aerosol increased with wavelength in the UV, but were constant or slightly decreased in the visible. The ozone absorption was most sensitive at 328 nm in the UV region (328-354 nm). The $R_{sfc}$ error was +0.1 because of negative total ozone anomaly (-100 DU) under the condition of $R_{sfc}=0.15$. This study can be useful to estimate $R_{sfc}$ uncertainties in the GEMS retrieval.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.155-165
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• 2020

In this present study, the sensitivity of O₄ Air Mass Factor (AMF) to Aerosol Peak Height (APH) has been investigated using radiative transfer model according to various parameters(wavelength (340 nm and 477 nm), aerosol type (smoke, dust, sulfate), aerosol optical depth (AOD), surface reflectance, solar zenith angle, and viewing zenith angle). In general, it was found that O₄ AMF at 477 nm is more sensitive to APH than that at 340 nm and is stably retrieved with low spectral fitting error in Differential Optical Absorption Spectroscopy (DOAS) analysis. In high AOD condition, sensitivity of O₄ AMF on APH tends to increase. O₄ AMF at 340 nm decreased with increasing solar zenith angle. This dependency isthought to be induced by the decrease in length of the light path where O₄ absorption occurs due to the shielding effect caused by Rayleigh and Mie scattering at high solar zenith angles above 40°. At 477 nm, as the solar zenith angle increased, multiple scattering caused by Rayleigh and Mie scattering partly leads to the increase of O₄ AMF in nonlinear function. Based on synthetic radiance, APHs have been retrieved using O₄ AMF. Additionally, the effect of AOD uncertainty on APH retrieval error has been investigated. Among three aerosol types, APH retrieval for sulfate type is found to have the largest APH retrieval error due to uncertainty of AOD. In the case of dust aerosol, it was found that the influence of AOD uncertainty is negligible. It indicates that aerosol types affect APH retrieval error since absorption scattering characteristics of each aerosol type are various.

• 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.