• Journal of the Korean earth science society
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• v.40 no.5
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• pp.476-486
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• 2019

This study examines the controlling role of synoptic disturbances on $PM_{10}$ spring variability in the Korean Peninsula by using empirical orthogonal function (EOF) and back trajectory analyses. Three leading EOF modes are identified, and a lead-lag analysis suggests that $PM_{10}$ variabilities be closely related to the synoptic weather systems. The first EOF shows the spatially homogeneous distribution of $PM_{10}$, which is influenced by travelling anticyclonic disturbance with negative precipitation and descending motion. The second and third modes exhibit the dipole structures of $PM_{10}$, being associated with propagating cyclones. Furthermore, the back-trajectory analysis suggests that the transport of pollutants by anomalous winds associated with synoptic disturbances also contribute to the altered $PM_{10}$ concentration. Hence, a substantial synoptic control should be considered in order to fully understand the $PM_{10}$ spatiotemporal variability.

• Atmosphere
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• v.30 no.2
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• pp.183-193
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• 2020

In this study, Yeongdong cold air damming (YCAD) cases that occur in winters have been selected using automatic weather station data of the Yeongdong region of Korea. The vertical and horizontal scales of YCAD were analyzed using rawinsonde and numerical weather model. YCAD occurred in two typical synoptic patterns such that low pressure and trough systems crossing and passing over Korea (low crossing type: LC and low passing type: LP). When the Siberian high does not expand enough to the Korean peninsula, low pressure and trough systems are likely to move over Korea. Eventually this could lead to surface temperature (3.1℃) higher during YCAD than the average in the winter season (1.6℃). The surface temperature during YCAD, however, was decrease by 1.3℃. The cold air layer was elevated around 120 m~450 m for LP-type. For LC-type, the cold layer were found at less than approximately 400 m and over 1,000 m, which could be thought of combined phenomena with synoptic and local weather forcing. The cross-sectional analysis results indicate the accumulation of cold air on the east mountain slope. Additionally, the north or northeasterly winds turned to the northwesterly wind near the coast in all cases. The horizontal wind turning point of LC-type was farther from the top of the mountain (52.2 km~71.5 km) than that of LP-type (20.0 km~43.0 km).

• Journal of Environmental Science International
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• v.23 no.12
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• pp.1999-2014
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• 2014

A meteo-tsunami occurred along the coastline of South Korea on 31 March 2007, with an estimated maximum amplitude of 240 cm in Yeonggwang (YG). In this study, we investigated the synoptic weather systems around the Yellow sea including the Bohai Bay and Shandong Peninsula using a weather research and forecast model and weather charts of the surface pressure level, upper pressure level and auxiliary analysis. We found that 4-lows passed through the Yellow sea from the Shandung Peninsula to Korea during 5 days. Moreover, the passage of the cold front and the locally heavy rain with a sudden pressure change may make the resonance response in the near-shore and ocean with a regular time-lag. The sea-level pressure disturbance and absolute vorticity in 500 hPa projected over the Yellow sea was propagated with a similar velocity to the coastline of South Korea at the time that meteo-tsunami occurred.

• Water Engineering Research
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• v.3 no.2
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• pp.123-134
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• 2002

A developed Quantitative Flood Forecasting (QFF) model was applied to the mid-Atlantic region of the United States. The model incorporated the evolving structure and frequency of intense weather systems of the study area for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters associated with synoptic atmospheric conditions as Input. Here, we present results from the application of the Quantitative Flood Forecasting (QFF) model in 2 small watersheds along the leeward side of the Appalachian Mountains in the mid-Atlantic region. Threat scores consistently above 0.6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 40% and up to 55 % were obtained.

• Journal of the Korean Geographical Society
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• v.45 no.3
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• pp.319-341
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• 2010

The purposes of this study are to classify heavy snowfall types in the Republic of Korea based on fresh snowfall data and atmospheric circulation data during the last 36(1973/74-2008/09) snow seasons and to identify typical surface synoptic climate patterns that characterize each heavy snowfall type. Four synoptic climate categories and seventeen regional heavy snowfall types are classified based on sea level pressure/surface wind vector patterns in East Asia and frequent spatial clustering patterns of heavy snowfall in the Republic of Korea, respectively. Composite analyses of multiple surface synoptic weather charts demonstrate that the locations and intensity of pressure/wind vector mean and anomaly cores in East Asia differentiate each regional heavy snowfall type in Korea. These differences in synoptic climatic fields are primarily associated with the surge of the Siberian high pressure system and the appearance of low pressure systems over the Korean Peninsula. In terms of hemispheric atmospheric circulation, synoptic climatic patterns in the negative mode of winter Arctic Oscillation (AO) are also associated with frequent heavy snowfall in the Republic of Korea at seasonal scales. These results from long-term synoptic climatic data could contribute to improvement of short-range or seasonal prediction of regional heavy snowfall.

• Journal of Environmental Science International
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• v.25 no.6
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• pp.853-864
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• 2016

Meteo-tsunamis are tsunamis that are typically caused by strong atmospheric instability (e.g., pressure jumps) in low pressure systems, but some meteo-tsunamis in winter can be caused by local atmospheric instability in high pressure systems (e.g., the Siberian High). In this study, we investigated a meteo-tsunami event related to a high pressure system that occurred during winter on the Yellow Sea in 2005. Sea level data from tidal stations were analyed with a high-pass filter, and we also performed synoptic weather analyses by using various synoptic weather data (e.g., surface weather charts) collected during the winter season(DJF) of 2005. A numerical weather model (WRF) was used to analyze the atmospheric instability on the day of the selected event (21 Dec. 2005). On the basis of the results, we suggest that the meteo-tsunami triggered by the high pressure system occurred because of dynamic atmospheric instability induced by the expansion and contraction of the Siberian High.

• Atmosphere
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• v.27 no.2
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• pp.235-249
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• 2017

This paper describes methodology verifying near-surface predictability of numerical weather prediction models against the surface synoptic weather station network (SYNOP) observation. As verification variables, temperature, wind, humidity-related variables, total cloud cover, and surface pressure are included in this tool. Quality controlled SYNOP observation through the pre-processing for data assimilation is used. To consider the difference of topographic height between observation and model grid points, vertical inter/extrapolation is applied for temperature, humidity, and surface pressure verification. This verification algorithm is applied for verifying medium-range forecasts by a global forecasting model developed by Korea Institute of Atmospheric Prediction Systems to measure the near-surface predictability of the model and to evaluate the capability of the developed verification tool. It is found that the verification of near-surface prediction against SYNOP observation shows consistency with verification of upper atmosphere against global radiosonde observation, suggesting reliability of those data and demonstrating importance of verification against in-situ measurement as well. Although verifying modeled total cloud cover with observation might have limitation due to the different definition between the model and observation, it is also capable to diagnose the relative bias of model predictability such as a regional reliability and diurnal evolution of the bias.

• Journal of the Korean Geographical Society
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• v.50 no.1
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• pp.1-21
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• 2015

The present study aims to characterize the synoptic climatic patterns of winter extreme low temperature events occurred in different regions of Korea based on daily temperature data observed at 61 weather stations under the supervision of the Korea Meteorological Administation and NCEP/NCAR reanalysis I data for the recent 40 years (1973~2012) period. Analyses of daily maximum and minimum temperatures below 10th percentile thresholds show that high frequencies of winter extreme low temperature events appear across the entire regions of Korea or in either the western or eastern half region divided by major mountain ridges at the 2~7 dayintervals particularly in the first half of the winter period (before mid-January). Composite analyses of surface synoptic climatic data including sea level pressure and wind vector reveal that 13 regional types of winter extreme low temperature events in Korea are closely associated with the relative location and intensity of both the Siberian high pressure and the Aleutian low pressure systems as well as major mountain ridges. Investigations of mid-troposphere (500 hPa) synoptic climatic charts demonstrate that the blocking-like upper troposphere low pressure system advecting the cold air from the Arctic toward the Korean Peninsula may provide favorable synoptic conditions for the outbreaks of winter extreme low temperature events in Korea. These results indicate that the monitoring of synoptic scale climatic systems in East Asia including the Siberian high pressure system, the Aleutian low pressure system and upper level blocking system is critical to the improvement of the predictability of winter extreme low temperature events in Korea.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.85-96
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• 2023

The number of traffic accidents caused by wet or icy road surface conditions is on the rise every year. Car crashes in such bad road conditions can increase fatalities and serious injuries. Historical data (from the year 2016 to the year 2020) on weather-related traffic accidents show that the fatality rates are fairly high in Korea. This requires accurate prediction and identification of hazardous road conditions. In this study, a forecasting model is developed to predict the chances of traffic accidents that can occur on roads affected by weather and road surface conditions. Multiple deep learning algorithms taking into account AlexNet and 2D-CNN are employed. Data on orthophoto images, automatic weather systems, automated synoptic observing systems, and road surfaces are used for training and testing purposes. The orthophotos images are pre-processed before using them as input data for the modeling process. The procedure involves image segmentation techniques as well as the Z-Curve index. Results indicate that there is an acceptable performance of prediction such as 65% for dry, 46% for moist, and 33% for wet road conditions. The overall accuracy of the model is 53%. The findings of the study may contribute to developing comprehensive measures for enhancing road safety.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.23-30
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• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.