• Title/Summary/Keyword: severe weather

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Predictability of Northern Hemisphere Teleconnection Patterns in GloSea5 Hindcast Experiments up to 6 Weeks (GloSea5 북반구 대기 원격상관패턴의 1~6주 주별 예측성능 검증)

  • Kim, Do-Kyoung;Kim, Young-Ha;Yoo, Changhyun
    • Atmosphere
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    • v.29 no.3
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    • pp.295-309
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    • 2019
  • Due to frequent occurrence of abnormal weather, the need to improve the accuracy of subseasonal prediction has increased. Here we analyze the performance of weekly predictions out to 6 weeks by GloSea5 climate model. The performance in circulation field from January 1991 to December 2010 is first analyzed at each grid point using the 500-hPa geopotential height. The anomaly correlation coefficient and mean-square skill score, calculated each week against the ECWMF ERA-Interim reanalysis data, illustrate better prediction skills regionally in the tropics and over the ocean and seasonally during winter. Secondly, we evaluate the predictability of 7 major teleconnection patterns in the Northern Hemisphere: North Atlantic Oscillation (NAO), East Atlantic (EA), East Atlantic/Western Russia (EAWR), Scandinavia (SCAND), Polar/Eurasia (PE), West Pacific (WP), Pacific-North American (PNA). Skillful predictability of the patterns turns out to be approximately 1~2 weeks. During summer, the EAWR and SCAND, which exhibit a wave pattern propagating over Eurasia, show a considerably lower skill than the other 5 patterns, while in winter, the WP and PNA, occurring in the Pacific region, maintain the skill up to 2 weeks. To account for the model's bias in reproducing the teleconnection patterns, we measure the similarity between the teleconnection patterns obtained in each lead time. In January, the model's teleconnection pattern remains similar until lead time 3, while a sharp decrease of similarity can be seen from lead time 2 in July.

Real-time Wave Overtopping Detection and Measuring Wave Run-up Heights Based on Convolutional Neural Networks (CNN) (합성곱 신경망(CNN) 기반 실시간 월파 감지 및 처오름 높이 산정)

  • Seong, Bo-Ram;Cho, Wan-Hee;Moon, Jong-Yoon;Lee, Kwang-Ho
    • Journal of Navigation and Port Research
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    • v.46 no.3
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    • pp.243-250
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    • 2022
  • The purpose of this study was to propose technology to detect the wave in the image in real-time, and calculate the height of the wave-overtopping through image analysis using artificial intelligence. It was confirmed that the proposed wave overtopping detection system proposed in this study could detect the occurring of wave overtopping, even in severe weather and at night in real-time. In particular, a filtering algorithm for determining if the wave overtopping event was used, to improve the accuracy of detecting the occurrence of wave overtopping, based on a convolutional neural networks to catch the wave overtopping in CCTV images in real-time. As a result, the accuracy of the wave overtopping detection through AP50 was reviewed as 59.6%, and the speed of the overtaking detection model was 70fps based on GPU, confirming that accuracy and speed are suitable for real-time wave overtopping detection.

Influence of Delaying Winter Pruning on Shoot Growth and Fruit Quality of 'Fuji'/M.9 Apple Tree (동계전정 지연이 '후지'/M.9 사과나무의 신초생장 및 과실품질에 미치는 영향)

  • Kweon, Hun-Joong;Sagong, Dong-Hoon
    • Korean Journal of Environmental Agriculture
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    • v.41 no.3
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    • pp.199-205
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    • 2022
  • BACKGROUND: The freezing injury by pruning can be reduced by suspending pruning work when severe cold weather (-23 to -49℃) is forecast. Minimum air temperature of the study area, Gunwi region at February 3, 2012 was -21.9℃, and the subzero temperature continued until April 8, 2012. This study was conducted in two years to investigate the effect of delaying winter pruning until full bloom on shoot growth and fruit quality of 'Fuji'/M.9 apple trees. METHODS AND RESULTS: The time of pruning were March 26 for dormant, April 3 for bud break, and May 2 for full bloom. The winter pruning at full bloom significantly reduced fruit weight for two years compared with the control (winter pruning at dormant), and shoot growth was reduced only in the following year. There was no significant effect of delaying winter pruning at bud break on soluble solid content, fruit red color, return bloom, and pruning weight for two years compared with the control. CONCLUSION(S): These results indicated the delaying winter pruning at bud break of 'Fuji'/M.9 apple tree did not offer any disadvantage over comparable dormant pruning, since the fruit quality was not affected. The delayed pruning at full bloom resulted in decreased fruit weight, though shoot growth, fruit quality, and return bloom were not affected by the delayed pruning. So, the delayed pruning should be considered carefully only for the fruit tree orchards in diseases.

Observational analysis of wind characteristics in the near-surface layer during the landfall of Typhoon Mujigae (2015)

  • Lin Xue;Ying Li;Lili Song
    • Wind and Structures
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    • v.37 no.4
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    • pp.315-329
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    • 2023
  • We investigated the wind characteristics in the near-surface layer during the landfall of Typhoon Mujigae (2015) based on observations from wind towers in the coastal areas of Guandong province. Typhoon Mujigae made landfall in this region from 01:00 UTC to 10:00 UTC on October 4, 2015. In the region influenced by the eyewall of the tropical cyclone, the horizontal wind speed was characterized by a double peak, the wind direction changed by >180°, the vertical wind speed increased by three to four times, and the angle of attack increased significantly to a maximum of 7°, exceeding the recommended values in current design criteria. The vertical wind profile may not conform to a power law distribution in the near-surface layer in the region impacted by the eyewall and spiral rainband. The gust factors were relatively dispersed when the horizontal wind speed was small and tended to a smaller value and became more stable with an increase in the horizontal wind speed. The variation in the gust factors was the combined result of the height, wind direction, and circulation systems of the tropical cyclone. The turbulence intensity and the downwind turbulence energy spectrum both increased notably in the eyewall and spiral rainband and no longer satisfied the assumption of isotropy in the inertial subrange and the -5/3 law. This result was more significant in the eyewall area than in the spiral rainband. These results provide a reference for forecasting tropical cyclones, wind-resistant design, and hazard prevention in coastal areas of China to reduce the damage caused by high winds induced by tropical cyclones.

A Framework for Quantifying the Damage to Residential Facilities Caused by Typhoon Changes (태풍 변화로 인한 주거시설 피해 정량화 프레임 워크 제안)

  • Kim, Ji-Myong;Son, Seunghyun
    • Journal of the Korea Institute of Building Construction
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    • v.23 no.6
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    • pp.797-807
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    • 2023
  • This research aims to investigate the alterations in typhoon patterns attributable to climate change and to quantitatively assess the risk of damage to residential structures. The increasing prevalence of climate anomalies and severe weather events, a consequence of global warming, is causing escalating damage globally. Notably, numerous countries are facing substantial devastation due to shifts in typhoon trajectories. Despite this, there exists a gap in empirical research quantifying the impact of these changes on building integrity and the associated risk alterations driven by climate change. In addressing this gap, our study analyzes the frequency and intensity of typhoons impacting Korea, examining the evolution of these meteorological phenomena. Furthermore, we employ the Korean Typhoon Vulnerability Function for residential facilities to quantify the altered risk posed by these changing patterns. The outcomes of this study provide the private sector with essential data to formulate diverse scenarios and business strategies in response to the escalating risks of typhoon-related damage. Additionally, it equips governmental bodies with the necessary insights to develop comprehensive risk management strategies to mitigate the effects of future typhoons.

Projected Future Extreme Droughts Based on CMIP6 GCMs under SSP Scenarios (SSP 시나리오에 따른 CMIP6 GCM 기반 미래 극한 가뭄 전망)

  • Kim, Song-Hyun;Nam, Won-Ho;Jeon, Min-Gi;Hong, Eun-Mi;Oh, Chansung
    • Journal of The Korean Society of Agricultural Engineers
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    • v.66 no.4
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    • pp.1-15
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    • 2024
  • In recent years, climate change has been responsible for unusual weather patterns on a global scale. Droughts, natural disasters triggered by insufficient rainfall, can inflict significant social and economic consequences on the entire agricultural sector due to their widespread occurrence and the challenge in accurately predicting their onset. The frequency of drought occurrences in South Korea has been rapidly increasing since 2000, with notably severe droughts hitting regions such as Incheon, Gyeonggi, Gangwon, Chungbuk, and Gyeongbuk in 2015, resulting in significant agricultural and social damage. To prepare for future drought occurrences resulting from climate change, it is essential to develop long-term drought predictions and implement corresponding measures for areas prone to drought. The Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report outlines a climate change scenario under the Shared Socioeconomic Pathways (SSPs), which integrates projected future socio-economic changes and climate change mitigation efforts derived from the Coupled Model Intercomparison Project 6 (CMIP6). SSPs encompass a range of factors including demographics, economic development, ecosystems, institutions, technological advancements, and policy frameworks. In this study, various drought indices were calculated using SSP scenarios derived from 18 CMIP6 global climate models. The SSP5-8.5 scenario was employed as the climate change scenario, and meteorological drought indices such as the Standardized Precipitation Index (SPI), Self-Calibrating Effective Drought Index (scEDI), and Standardized Precipitation Evapotranspiration Index (SPEI) were utilized to analyze the prediction and variability of future drought occurrences in South Korea.

A Foundational Study on Deep Learning for Assessing Building Damage Due to Natural Disasters (자연재해로 인한 건물의 피해 평가를 위한 딥러닝 기초 연구)

  • Kim, Ji-Myong;Yun, Gyeong-Cheol
    • Journal of the Korea Institute of Building Construction
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    • v.24 no.3
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    • pp.363-370
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    • 2024
  • The escalating frequency and intensity of natural disasters and extreme weather events due to climate change have caused increasingly severe damage to societal infrastructure and buildings. Government agencies and private companies are actively working to evaluate these damages, but existing technologies and methodologies often fall short of meeting the practical demands for accurate assessment and prediction. This study proposes a novel approach to assess building damage resulting from natural disasters, focusing on typhoons-one of the most devastating natural hazards experienced in the country. The methodology leverages deep learning algorithms to evaluate typhoon-related damage, providing a comprehensive framework for assessment. The framework and outcomes of this research can provide foundational data for the evaluation of natural disaster-induced damage over the entire life cycle of buildings and can be applied in various other industries and research areas for assessing risk of damage.

A Case Study on Near-Cloud Turbulence around the Mesoscale Convective System in the Korean Peninsula (한반도에서 발생한 중규모 대류계의 구름 주변 난류 발생 메커니즘 사례 연구)

  • Sung-Il Yang;Ju Heon Lee;Jung-Hoon Kim
    • Atmosphere
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    • v.34 no.2
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    • pp.153-176
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    • 2024
  • At 0843 UTC 30 May 2021, a commercial aircraft encountered severe turbulence at z = 11.5 km associated with the rapid development of Mesoscale Convective System (MCS) in the Gyeonggi Bay of Korea. To investigate the generation mechanisms of Near-Cloud Turbulence (NCT) near the MCS, Weather Research and Forecasting model was used to reproduce key features at multiple-scales with four nested domains (the finest ∆x = 0.2 km) and 112 hybrid vertical layers. Simulated subgrid-scale turbulent kinetic energy (SGS TKE) was located in three different regions of the MCS. First, the simulated NCT with non-zero SGS TKE at z = 11.5 km at 0835 UTC was collocated with the reported NCT. Cloud-induced flow deformation and entrainment process on the downstream of the overshooting top triggered convective instability and subsequent SGS TKE. Second, at z = 16.5 km at 0820 UTC, the localized SGS TKE was found 4 km above the overshooting cloud top. It was attributed to breaking down of vertically propagating convectively-induced gravity wave at background critical level. Lastly, SGS TKE was simulated at z = 11.5 km at 0930 UTC during the dissipating stage of MCS. Upper-level anticyclonic outflow of MCS intensified the environmental westerlies, developing strong vertical wind shear on the northeastern quadrant of the dissipating MCS. Three different generation mechanisms suggest the avoidance guidance for the possible NCT events near the entire period of the MCS in the heavy air traffic area around Incheon International Airport in Korea.

Large-scale Atmospheric Patterns associated with the 2018 Heatwave Prediction in the Korea-Japan Region using GloSea6

  • Jinhee Kang;Semin Yun;Jieun Wie;Sang-Min Lee;Johan Lee;Baek-Jo Kim;Byung-Kwon Moon
    • Journal of the Korean earth science society
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    • v.45 no.1
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    • pp.37-47
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    • 2024
  • In the summer of 2018, the Korea-Japan (KJ) region experienced an extremely severe and prolonged heatwave. This study examines the GloSea6 model's prediction performance for the 2018 KJ heatwave event and investigates how its prediction skill is related to large-scale circulation patterns identified by the k-means clustering method. Cluster 1 pattern is characterized by a KJ high-pressure anomaly, Cluster 2 pattern is distinguished by an Eastern European high-pressure anomaly, and Cluster 3 pattern is associated with a Pacific-Japan pattern-like anomaly. By analyzing the spatial correlation coefficients between these three identified circulation patterns and GloSea6 predictions, we assessed the contribution of each circulation pattern to the heatwave lifecycle. Our results show that the Eastern European high-pressure pattern, in particular, plays a significant role in predicting the evolution of the development and peak phases of the 2018 KJ heatwave approximately two weeks in advance. Furthermore, this study suggests that an accurate representation of large-scale atmospheric circulations in upstream regions is a key factor in seasonal forecast models for improving the predictability of extreme weather events, such as the 2018 KJ heatwave.

An Analysis of the Hail Damages to Korean Forests in 2017 by Meteorology, Species and Topography (2017년 우박에 의한 산림피해의 기상, 수종 및 지형 특성 분석)

  • Lim, Jong-Hwan;Kim, Eunsook;Lee, Bora;Kim, Sunhee;Jang, Keunchang
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.19 no.4
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    • pp.280-292
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    • 2017
  • Hail is not a frequently occurring weather event, and there are even fewer reports of hail damages to forest stands. Since the 2000s, an increase in hail incidence has been documented in Europe and the United States. In Korea, severe hails occurred in Jeollanam-do province on May 31 and in Gyeongsangbuk-do province on June 1, 2017. Hail size was ranged from 0.5 to 5.0 cm in diameter in Jeollanam-do, and from 1.5 to 3.0 cm in Gyeongsangbuk-do. This study was aimed to analyze the hail damages to forests by species and topography based on damage-categorized maps created by using drones and aerial photographs, and to analyze relationships of the damages with meteorological factors. The total damaged forest area was 1,163.1ha in Jeollanam-do, and 2,942.3ha in Gyeongsangbuk-do. Among the 'severe' damaged area 326.7ha, 91% was distributed in Jeollanam-do, and concentrated in the city of Hwasun which covers 57.2% of the total 'severe' damaged area. The most heavily damaged species was Korean red pine(Pinus densiflora S. & Z.) followed by P. rigida. Most broad-leaved trees species including oaks were recovered without any dead trees found. Liliodendron tulipifera was the most severely damaged in terms of the rate of 'severe' degree individuals which are needed to be checked whether they will die or be recovered. Cause of the death of pines was considered as the combination of physical damage caused by the hail and long-lasting drought with high air temperature that occurred before and after the hail event. No pathogens and insects were found which might have affected to tree deaths. We suggested a dieback mechanism of the pine trees damaged by hail and drought.