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Articles 1 - 6 of 6
Full-Text Articles in Atmospheric Sciences
Kinematic And Dynamic Structure Of The 18 May 2020 Squall Line Over South Korea, Wishnu Agum Swastiko, Chia-Lun Tsai, Seung Hee Kim, Gyuwon Lee
Kinematic And Dynamic Structure Of The 18 May 2020 Squall Line Over South Korea, Wishnu Agum Swastiko, Chia-Lun Tsai, Seung Hee Kim, Gyuwon Lee
Institute for ECHO Articles and Research
The diagonal squall line that passed through the Korean Peninsula on the 18 May 2020 was examined using wind data retrieved from multiple Doppler radar synthesis focusing on its kinematic and dynamic aspects. The low-level jet, along with warm and moist air in the lower level, served as the primary source of moisture supply during the initiation and formation process. The presence of a cold pool accompanying the squall line played a role in retaining moisture at the surface. As the squall line approached the Korean Peninsula, the convective bands in the northern segment (NS) and southern segment (SS) of …
Nowcasting Heavy Rainfall With Convolutional Long Short-Term Memory Networks: A Pixelwise Modeling Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Soorok Ryu, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos
Nowcasting Heavy Rainfall With Convolutional Long Short-Term Memory Networks: A Pixelwise Modeling Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Soorok Ryu, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos
Institute for ECHO Articles and Research
The recent decades have seen an increasing academic interest in leveraging machine learning approaches to nowcast, or forecast in a highly short-term manner, precipitation at a high resolution, given the limitations of the traditional numerical weather prediction models on this task. To capture the spatiotemporal associations of data on input variables, a deep learning (DL) architecture with the combination of a convolutional neural network and a recurrent neural network can be an ideal design for nowcasting rainfall. In this study, a long short-term memory (LSTM) modeling structure is proposed with convolutional operations on input variables. To resolve the issue of …
Feasibility Analysis Of Aeronet Lunar Aod For Nighttime Particulate Matter Estimation, Kwang Nyun Kim, Seung Hee Kim, Sang Seo Park, Yun Gon Lee
Feasibility Analysis Of Aeronet Lunar Aod For Nighttime Particulate Matter Estimation, Kwang Nyun Kim, Seung Hee Kim, Sang Seo Park, Yun Gon Lee
Institute for ECHO Articles and Research
Several studies have attempted to estimate particulate matter (PM) concentrations using aerosol optical depth (AOD), based on AOD and PM relationships. Owing to the limited availability of nighttime AOD data, PM estimation studies using AOD have focused on daytime. Recently, the Aerosol Robotic Network (AERONET) produced nighttime AOD, called lunar AOD, providing an opportunity to estimate nighttime PM. Nighttime AOD measurements are particularly important as they help fill gaps in our understanding of aerosol variability and its impact on the atmosphere, as there are significant variations in AOD between day and night. In this study, the relationship between lunar AOD …
Meteorological Characteristics Of Fog Events In Korean Smart Cities And Machine Learning Based Visibility Estimation, Jaemin Kim, Seung Hee Kim, Hyun Woo Seo, Yi Victor Wang, Yun Gon Lee
Meteorological Characteristics Of Fog Events In Korean Smart Cities And Machine Learning Based Visibility Estimation, Jaemin Kim, Seung Hee Kim, Hyun Woo Seo, Yi Victor Wang, Yun Gon Lee
Institute for ECHO Articles and Research
To address various urban issues such as fine dust, traffic congestion, and water shortage caused by rapid urbanization, a national pilot Smart City is planned in two Korean cities, Sejong and Busan. As weather data is crucial for improving the environment and operating future transportation while constructing a smart city, preparing for future weather disasters by analyzing the characteristics of various meteorological phenomena in the planned development area is necessary. This study analyzed the fog generation characteristics for the period of 2016–2020 at the automatic weather system sites of the Korea Meteorological Administration in Sejong and Busan, and the characteristics …
Murphy Scale: A Locational Equivalent Intensity Scale For Hazard Events, Yi Victor Wang, Antonia Sebastian
Murphy Scale: A Locational Equivalent Intensity Scale For Hazard Events, Yi Victor Wang, Antonia Sebastian
Institute for ECHO Articles and Research
Empirical cross-hazard analysis and prediction of disaster vulnerability, resilience, and risk requires a common metric of hazard strengths across hazard types. In this paper, the authors propose an equivalent intensity scale for cross-hazard evaluation of hazard strengths of events for entire durations at locations. The proposed scale is called the Murphy Scale, after Professor Colleen Murphy. A systematic review and typology of hazard strength metrics is presented to facilitate the delineation of the defining dimensions of the proposed scale. An empirical methodology is introduced to derive equivalent intensities of hazard events on a Murphy Scale. Using historical data on …
Assessment Of Aerosol Optical Depth Under Background And Polluted Conditions Using Aeronet And Viirs Datasets, Mijin Kim, Seung Hee Kim, Woogyung Vincent Kim, Yun Gon Lee, Jhoon Kim, Menas C. Kafatos
Assessment Of Aerosol Optical Depth Under Background And Polluted Conditions Using Aeronet And Viirs Datasets, Mijin Kim, Seung Hee Kim, Woogyung Vincent Kim, Yun Gon Lee, Jhoon Kim, Menas C. Kafatos
Institute for ECHO Articles and Research
We investigated aerosol optical depth (AOD) under background and polluted conditions using Aerosol Robotic Network (AERONET) and Visible Infrared Imaging Radiometer Suite (VIIRS) observations. The AOD data were separated into background, high, and median AOD (BAOD, HAOD, and MAOD, respectively) based on the cumulative AOD distribution at each point and then their spatiotemporal variations were analyzed. Persistent pollutant emissions from industrial activity in South Asia (SUA) and Northeast Asia (NEA) produced the highest BAOD values. Gridded-BAODs obtained from VIIRS Deep Blue AOD products showed widespread high-level BAOD over the oceans associated with transport from dust and biomass burning events. The …