Yonsei University · 環境科学
Professor Sujung Go's research lab specializes in atmospheric remote sensing, with a focus on aerosol and dust characterization using satellite-based hyperspectral and broadband radiometric measurements. The lab develops advanced retrieval algorithms to quantify aerosol optical properties, particularly the iron-oxide composition of mineral dust—such as hematite and goethite—critical for understanding light absorption and radiative forcing. Key research directions include the synergistic use of UV–visible and infrared sensors for improved aerosol detection, innovative single-channel UV aerosol index methods, and the application of instruments like OMI, GEMS, MODIS, and DSCOVR-EPIC for atmospheric monitoring. The lab's work contributes significantly to improving climate models and environmental assessments through precise aerosol and radiative effect characterization.
Figures are computed from collected data and may differ slightly.
The retrieval of optimal aerosol datasets by the synergistic use of hyperspectral ultraviolet (UV)–visible and broadband meteorological imager (MI) techniques was investigated. The Aura Ozone Monitoring Instrument (OMI) Level 1B (L1B) was used as a proxy for hyperspectral UV–visible instrument data to which the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol algorithm was applied. Moderate-Resolution Imaging Spectroradiometer (MODIS) L1B and dark target aerosol Level 2 (L2) data
The Ultra-Violet Aerosol Index (UVAI) is a practical parameter for detecting aerosols that absorb UV radiation, especially where other aerosol retrievals fail, such as over bright surfaces (e.g., deserts and clouds). However, typical UVAI retrieval requires at least two UV channels, while several satellite instruments, such as the Thermal And Near infrared Sensor for carbon Observation Cloud and Aerosol Imager (TANSO-CAI) instrument onboard a Greenhouse gases Observing SATellite (GOSAT), provide
Abstract. The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (α-Fe2O3) and goethite (α-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere UV radiances used for dust monitoring, and ultimately shortwave dust direct radiative effects (DRE). Hematite and goethite column mass concentrations and iron-oxide mass fractions of total dust mass concentration were retrieved from the Deep Space Climate Observatory (DSCO
<strong class="journal-contentHeaderColor">Abstract.</strong> The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (<span class="inline-formula"><i>α</i></span>-Fe<span class="inline-formula"><sub>2</sub></span>O<span class="inline-formula"><sub>3</sub></span>) and goethite (<span class="inline-formula"><i>α</i></span>-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere ultraviolet (UV) radiances used for dus
<strong class="journal-contentHeaderColor">Abstract.</strong> The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (<span class="inline-formula"><i>α</i></span>-Fe<span class="inline-formula"><sub>2</sub></span>O<span class="inline-formula"><sub>3</sub></span>) and goethite (<span class="inline-formula"><i>α</i></span>-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere ultraviolet (UV) radiances used for dus
<strong class="journal-contentHeaderColor">Abstract.</strong> The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (<span class="inline-formula"><i>α</i></span>-Fe<span class="inline-formula"><sub>2</sub></span>O<span class="inline-formula"><sub>3</sub></span>) and goethite (<span class="inline-formula"><i>α</i></span>-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere ultraviolet (UV) radiances used for dus
This study investigates the vertical distribution and seasonal climatology of absorbing iron-oxide minerals, specifically hematite and goethite, in atmospheric dust using the updated MAIAC EPIC version 3 algorithm. Leveraging data from July 2015 to December 2023, the key innovation is the improved Level 2 product which now incorporates Aerosol Layer Height (ALH), enabling the first-ever long-term characterization of their vertical and seasonal distribution globally. Our analysis reveals distinct
Aerosol optical depth (AOD) data fusion for aerosol datasets obtained from the Geostationary Korea Multi-Purpose Satellite (GEO-KOMPSAT; GK) series was conducted through the application of both statistical and deep neural network (DNN)-based methodologies. The GK mission incorporates the Advanced Meteorological Imager (AMI) on GK-2A, as well as the Geostationary Environment Monitoring Spectrometer (GEMS) and Geostationary Ocean Color Imager-II (GOCI-II) on GK-2B. The statistical fusion approach
<strong class="journal-contentHeaderColor">Abstract.</strong> Wildfires and agricultural burning generate seemingly increasing smoke aerosol emissions, impacting societal and natural ecosystems. To understand smoke’s effects on climate and public health, we analyzed the spatiotemporal distribution of smoke aerosols, focusing on two major light-absorbing components, black carbon (BC) and brown carbon (BrC) aerosols. Using NASA’s Earth Polychromatic Imaging Camera (EPIC) instrument abo
The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (α-Fe2O3) and goethite (α-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere UV radiances used for dust monitoring, and ultimately shortwave dust direct radiative effects (DRE). Hematite and goethite column mass concentrations and iron-oxide mass fractions of total dust mass concentration were retrieved from the Deep Space Climate Observatory (DSCOVR) Earth
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