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Hung Ming Cheung, Chang-Hoi Ho, Minhee Chang, Dasol Kim, Jinwon Kim, and Woosuk Choi


Despite tremendous advancements in dynamical models for weather forecasting, statistical models continue to offer various possibilities for tropical cyclone (TC) track forecasting. Herein, a track-pattern-based approach was developed to predict a TC track for a lead time of 6–8 days over the western North Pacific (WNP), utilizing historical tracks in conjunction with dynamical forecasts. It is composed of four main steps: 1) clustering historical tracks similar to that of an operational 5-day forecast in their early phase into track patterns, and calculating the daily mean environmental fields (500-hPa geopotential height and steering flow) associated with each track; 2) deriving the two environmental variables forecasted by dynamical models; 3) evaluating pattern correlation coefficients between the two environmental fields from step 1 and those from dynamical model for a lead times of 6–8 days; and 4) producing the final track forecast based on relative frequency maps obtained from the historical tracks in step 1 and the pattern correlation coefficients obtained from step 3. TCs that formed in the WNP and lasted for at least 7 days, during the 9-yr period 2011–19 were selected to verify the resulting track-pattern-based forecasts. In addition to the performance comparable to dynamical models under certain conditions, the track-pattern-based model is inexpensive, and can consistently produce forecasts over large latitudinal or longitudinal ranges. Machine learning techniques can be implemented to incorporate nonlinearity in the present model for improving medium-range track forecasts.

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Dasol Kim, Chang-Hoi Ho, Doo-Sun R. Park, Johnny C. L. Chan, and Youngsun Jung


In this study, the variation of tropical cyclone (TC) rainfall area over the subtropical oceans is investigated using the Tropical Rainfall Measuring Mission precipitation data collected from 1998 to 2014, with a focus on its relationship with environmental conditions. In the subtropics, higher moving speed and larger vertical wind shear significantly contribute to an increase in TC rainfall area by making horizontal rainfall distribution more asymmetric, while sea surface temperature rarely affects the fluctuation of TC rainfall area. This relationship between TC rainfall area and environmental conditions in the subtropics is almost opposite to that in the tropics. It is suggested that, in the subtropics, unlike the tropics, dynamic environmental conditions are likely more crucial to varying TC rainfall area than thermodynamic environmental ones.

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Dasol Kim, Chang-Hoi Ho, Hiroyuki Murakami, and Doo-Sun R. Park


Understanding the mechanisms related to the variations in the rainfall structure of tropical cyclones (TCs) is crucial in improving forecasting systems of TC rainfall and its impact. Using satellite precipitation and reanalysis data, we examined the influence of along-track large-scale environmental conditions on inner-core rainfall strength (RS) and total rainfall area (RA) for Atlantic TCs during the TC season (July–November) from 1998 to 2019. Factor analysis revealed three major factors associated with variations in RS and RA: large-scale low and high pressure systems [factor 1 (F1)]; environmental flows, sea surface temperature, and humidity [factor 2 (F2)]; and maximum wind speed of TCs [factor 3 (F3)]. Results from our study indicate that RS increases with an increase in the inherent primary circulation of TCs (i.e., F3) but is less affected by large-scale environmental conditions (i.e., F1 and F2), whereas RA is primarily influenced by large-scale low and high pressure systems (i.e., F1) over the entire North Atlantic and partially influenced by environmental flows, sea surface temperature, humidity, and maximum wind speed (i.e., F2 and F3). A multivariable regression model based on the three factors accounted for the variations of RS and RA across the entire basin. In addition, regional distributions of mean RS and RA from the model significantly resembled those from observations. Therefore, our study suggests that large-scale environmental conditions over the North Atlantic Ocean are important predictors for TC rainfall forecasts, particularly with regard to RA.

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Doo-Sun R. Park, Chang-Hoi Ho, Dasol Kim, Nam-Young Kang, Yeojin Han, and Hye-Ryun Oh


Air quality depends as much on large-scale tropospheric circulation as on the amount of pollutant emissions. Many studies have found a relationship between air quality and midlatitude synoptic weather systems. A stable low-level troposphere and airflow from polluted areas are conditions that favor air pollution in a region. However, few studies have focused on the possible remote effect of tropical cyclone (TC) activity in the tropics on air quality in the midlatitude East Asian countries. Here, we found that TCs in the South China Sea (SCS) can increase the concentration of particulate matter with aerodynamic diameters less than 10 μm (PM10) over South Korea through poleward-propagating Rossby waves. According to our analyses, intense divergence due to a TC causes a barotropic Rossby wave train from the SCS to the North Pacific Ocean. Anomalous highs over the Korean Peninsula (part of the Rossby wave train) result in stable air conditions and cause polluted air inflow to increase the PM10 concentration up to 65 μg m−3. Our finding suggests that TC activity in the tropics should be considered for more accurate forecasts of air quality in South Korea.

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