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Full-Text Articles in Meteorology
Relative Importance Of Radar Variables For Nowcasting Heavy Rainfall: A Machine Learning Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos
Relative Importance Of Radar Variables For Nowcasting Heavy Rainfall: A Machine Learning Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos
Institute for ECHO Articles and Research
Highly short-term forecasting, or nowcasting, of heavy rainfall due to rapidly evolving mesoscale convective systems (MCSs) is particularly challenging for traditional numerical weather prediction models. To overcome such a challenge, a growing number of studies have shown significant advantages of using machine learning (ML) modeling techniques with remote sensing data, especially weather radar data, for high-resolution rainfall nowcasting. To improve ML model performance, it is essential first and foremost to quantify the importance of radar variables and identify pertinent predictors of rainfall that can also be associated with domain knowledge. In this study, a set of MCS types consisting of …
Comparing Past And Future Drought And Surplus Periods In The Colorado River Basin, Rama Bedri
Comparing Past And Future Drought And Surplus Periods In The Colorado River Basin, Rama Bedri
Student Scholar Symposium Abstracts and Posters
The Colorado River Basin is crucial to the Western United States, providing water for seven states and Mexico. Historical and future periods of drought and surplus are analyzed in 17 Colorado River stations. Unimpaired streamflow data are evaluated from the U.S. Geological Survey, Bureau of Reclamation, and Coupled Modeled Intercomparison Projection 5 from 1950-2099. Future projections are based on eight climate scenarios. Four climate models (HadGEM2-ES, CNRM-CM5, CanESM2, MI-ROC5) are observed at Representative Concentration Pathways (RCP) 4.5 and 8.5 emission scenarios. Furthermore, the ensemble water year means of the four models are analyzed. The durations of drought or surplus, magnitudes, …
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 …