• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.227-236
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• 2009

This study investigates the characteristics of cloud top brightness temperature (CTBT) of WV and IR1 from MTSAT-1R when lightning strikes in South Korea. For temporal and spatial collocations, lightnings, occurred only within ${\pm}5$ minutes from the six minutes added official satellite observation time (e.g., not 0600 UTC but 0606 UTC, considering the real scan time over South Korea), were selected. And the CTBTs corresponding to lightning spots were determined using the nearest pixel within 5 km. The brightness temperature difference (BTD, defined as WV - IR1) between two channels is negatively large when no lightning occurrs, whereas it increases up to positive values (sometimes, +5 K) and the largest frequency distributes around 225 K and 205 K in lightning cases. The probablistic approach for lightning frequency forecast, presented by Machado et al. (2008) in Southern America, was applied over South Korea and new exponential equations, with high coefficients of determination around 0.95 to 0.99, were developed using two channels' BTDs when lightning strikes. Moreover, a case study on 10th June, 2006, the largest number of lightning occurred between 2002 and 2006, was made. The major finding is that lightning activity is closely related to the dramatic decreases in BT and the increases in BTD (esp., equal to or larger than 0 K). Lightning frequency increases exponentially when BTD increases up to 0 K. Therefore, lightning forecast skill will be improved when the integrated strategy (synoptic background and satellite-based CTBT and BTD) is applied. It is believed that this study contributes to the application of the Korean first geostationary satellite (COMS), scheduled to launch at the end of this year, to severe weather detections.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1653-1667
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• 2020

In this study, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. We investigated the characteristics of fine particulate matter (PM2.5) distributions in a building-congested district. To analyze the effects of road emission on the PM2.5 concentrations, we calculated road emissions based on the monthly, daily, and hourly emission factors and the total amount of PM2.5 emissions established from the Clean Air Policy Support System (CAPSS) of the Ministry of Environment. We validated the simulated PM2.5 concentrations against those measured at the PKNU-AQ Sensor stations. In the cases of no road emission, the LDAPS-CFD model underestimated the PM2.5 concentrations measured at the PKNU-AQ Sensor stations. The LDAPS-CFD model improved the PM2.5 concentration predictions by considering road emission. At 07 and 19 LST on 22 June 2020, the southerly wind was dominant at the target area. The PM2.5 distribution at 07 LST were similar to that at 19 LST. The simulated PM2.5 concentrations were significantly affected by the road emissions at the roadside but not significantly at the building roof. In the road-emission case, the PM2.5 concentration was high at the north (wind speeds were weak) and west roads (a long street canyon). The PM2.5 concentration was low in the east road where the building density was relatively low.