• Title/Summary/Keyword: Impact Forecast

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Impact of SAPHIR Data Assimilation in the KIAPS Global Numerical Weather Prediction System (KIAPS 전지구 수치예보모델 시스템에서 SAPHIR 자료동화 효과)

  • Lee, Sihye;Chun, Hyoung-Wook;Song, Hyo-Jong
    • Atmosphere
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    • v.28 no.2
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    • pp.141-151
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    • 2018
  • The KIAPS global model and data assimilation system were extended to assimilate brightness temperature from the Sondeur $Atmosph{\acute{e}}rique$ du Profil $d^{\prime}Humidit{\acute{e}}$ Intertropicale par $Radiom{\acute{e}}trie$ (SAPHIR) passive microwave water vapor sounder on board the Megha-Tropiques satellite. Quality control procedures were developed to assess the SAPHIR data quality for assimilating clear-sky observations over the ocean, and to characterize observation biases and errors. In the global cycle, additional assimilation of SAPHIR observation shows globally significant benefits for 1.5% reduction of the humidity root-mean-square difference (RMSD) against European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) analysis. The positive forecast impacts for the humidity and temperature in the experiment assimilating SAPHIR were predominant at later lead times between 96- and 168-hour. Even though its spatial coverage is confined to lower latitudes of $30^{\circ}S-30^{\circ}N$ and the observable variable is humidity, the assimilation of SAPHIR has a positive impact on the other variables over the mid-latitude domain. Verification showed a 3% reduction of the humidity RMSD with assimilating SAPHIR, and moreover temperature, zonal wind and surface pressure RMSDs were reduced up to 3%, 5% and 7% near the tropical and mid-latitude regions, respectively.

Impact of Snow Depth Initialization on Seasonal Prediction of Surface Air Temperature over East Asia for Winter Season (겨울철 동아시아 지역 기온의 계절 예측에 눈깊이 초기화가 미치는 영향)

  • Woo, Sung-Ho;Jeong, Jee-Hoon;Kim, Baek-Min;Kim, Seong-Joong
    • Atmosphere
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    • v.22 no.1
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    • pp.117-128
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    • 2012
  • Does snow depth initialization have a quantitative impact on sub-seasonal to seasonal prediction skill? To answer this question, a snow depth initialization technique for seasonal forecast system has been implemented and the impact of the initialization on the seasonal forecast of surface air temperature during the wintertime is examined. Since the snow depth observation can not be directly used in the model simulation due to the large systematic bias and much smaller model variability, an anomaly rescaling method to the snow depth initialization is applied. Snow depth in the model is initialized by adding a rescaled snow depth observation anomaly to the model snow depth climatology. A suite of seasonal forecast is performed for each year in recent 12 years (1999-2010) with and without the snow depth initialization to evaluate the performance of the developed technique. The results show that the seasonal forecast of surface air temperature over East Asian region sensitively depends on the initial snow depth anomaly over the region. However, the sensitivity shows large differences for different timing of the initialization and forecast lead time. Especially, the snow depth anomaly initialized in the late winter (Mar. 1) is the most effective in modulating the surface air temperature anomaly after one month. The real predictability gained by the snow depth initialization is also examined from the comparison with observation. The gain of the real predictability is generally small except for the forecasting experiment in the early winter (Nov. 1), which shows some skillful forecasts. Implications of these results and future directions for further development are discussed.

Observing Sensitivity Experiment Based on Convective Scale Model for Upper-air Observation Data on GISANG 1 (KMA Research Vessel) in Summer 2018 (현업 국지모델기반 2018년 여름철 기상 1호 특별 고층관측자료의 관측 민감도 실험)

  • Choi, Dayoung;Hwang, Yoonjeong;Lee, Yong Hee
    • Atmosphere
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    • v.30 no.1
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    • pp.17-30
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    • 2020
  • KMA performed the special observation program to provide information about severe weather and to monitor typhoon PRAPIROON using the ship which called the Gisang 1 from 29 June 2018 to 4 July 2018 (UTC). For this period, upper-air was observed 21 times with 6 hour intervals using rawinsonde in the Gisang 1. We investigated the impact of upper-air observation data from the Gisang 1 on the performance of the operational convective scale model (we called LDAPS). We conducted two experiments that used all observation data including upper-air observation data from the Gisang 1 (OPER) and without it (EXPR). For a typhoon PRAPIROON case, track forecast error of OPER was lower than EXPR until forecast 24 hours. The intensity forecast error of OPER for minimum sea level pressure was lower than EXPR until forecast 12 hours. The intensity forecast error of OPER for maximum wind speed was mostly lower than EXPR until forecast 30 hours. OPER showed good performance for typhoon forecast compared with EXPR at the early lead time. Two precipitation cases occurred in the south of the Korean peninsula due to the impact of Changma on 1 July and typhoon on 3 July. The location of main precipitation band predicted from OPER was closer to observations. As assimilating upper-air data observed in the Gisang 1 to model, it showed positive results in typhoon and precipitation cases.

Analysis on Vertical Structure of Sea Fog in the West Coast of the Korean Peninsula by Using Drone (드론을 활용한 한반도 서해 연안의 해무 연직구조 분석)

  • Jeon, Hye-Rim;Park, Mi Eun;Lee, Seung Hyeop;Park, Mir;Lee, Yong Hee
    • Atmosphere
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    • v.32 no.4
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    • pp.307-322
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    • 2022
  • A drone has recently got attention as an instrument for weather observation in lower atmosphere because it can produce the high spatiotemporal resolution weather data even though the weather phenomenon is inaccessible. Sea fog is a weather phenomenon occurred in lower atmosphere, and has observational limitations because it occurs on the sea. Therefore, goal of this study is to analyze the vertical structures about inflow, development and dispersion of sea fog using the high-resolution weather data with the meteorological sensor-equipped drone. This study observed sea fogs in the west coast of the Korean peninsula from March to October 2021 and investigated one sea fog inflowed into the coast on June 8th 2021. θe - qv diagrams (θe: equivalent potential temperature, qv: water vapor ratio) and vertical wind structures were analyzed. At inflow of sea fog, moist adiabatically stable layer was formed in 0-300 m and prevailing wind was switched from south-southwesterly to west-southwesterly under 120 m. Both changes are favorable for sea fog on the location. θe and qv plummeted in a layer 0-183 m. The inflowed sea fog developed from 183 m to 327 m by mixing with ambient atmosphere on top of sea fog. Also, strong mechanical turbulence near ground drove a vertical mixing under stable layer. At dispersion of sea fog, as θe on ground gradually increased, air condition was changed to neutral. Evaporation occurred on both bottom and top in sea fog. These results induced dissipation of sea fog.

A Study on the Synoptic Structural Characteristics of Heavy Snowfall Event in Yeongdong Area that Occurred on 20 January, 2017 (2017년 1월 20일 발생한 강원 영동대설 사례에 대한 대기의 구조적 특성 연구)

  • Ahn, Bo-Young;Lee, Jeong-sun;Kim, Baek-Jo;Kim, Hui-won
    • Journal of Environmental Science International
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    • v.28 no.9
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    • pp.765-784
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    • 2019
  • The synoptic structural characteristics associated with heavy snowfall (Bukgangneung: 31.3 cm) that occurred in the Yeongdong area on 20 January 2017 was investigated using surface and upper-level weather charts, European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data, radiosonde data, and Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product. The cold dome and warm trough of approximately 500 hPa appeared with tropopause folding. As a result, cold and dry air penetrated into the middle and upper levels. At this time, the enhanced cyclonic potential vorticity caused strong baroclinicity, resulting in the sudden development of low pressure at the surface. Under the synoptic structure, localized heavy snowfall occurred in the Yeongdong area within a short time. These results can be confirmed from the vertical analysis of radiosonde data and the characteristics of the MODIS cloud product.

An Analysis of the Least Observing-Session Duration of GPS for the Retrieval of Precipitable Water Vapor (GPS 가강수량 산출을 위한 최소 관측세션 지속시간에 대한 분석)

  • Kim, Yoo-Jun;Han, Sang-Ok;Kim, Ki-Hoon;Kim, Seon-Jeong;Kim, Geon-Tae;Kim, Byung-Gon
    • Atmosphere
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    • v.24 no.3
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    • pp.391-402
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    • 2014
  • This study investigated the performances of precipitable water vapor (PWV) retrieval from the sets of ground global positioning system (GPS) signals, each of which had different length of observing-session duration, for the purpose of obtaining as short session duration as possible that is required at the least for appropriate retrieval of the PWV for meteorological usage. The shorter duration is highly desirable to make the most use of the GPS instrument on board the mobile observation vehicle making measurements place by place. First, using Bernese 5.0 software the PWV retrieval was conducted with the data sets of GPS signals archived continuously in 30 seconds interval during 2-month period of January and February, 2012 at Bukgangneung site. Each of the PWVs produced independently using different session durations was compared to that of radio-sonde launched at the same GPS location, a Bukgangneung site. Second, the same procedure was done using the data sets obtained from the mobile observation vehicle that was operating at Boseong area in Jeonnam province during Changma observation campaign in 2013, and the results were compared to that at Bukgangneung site. The results showed that as the observing-session duration increased the retrieval errors decreased with the dramatic change happening between 3 and 4 hours of the duration. On average, the root mean square error (RMSE) of the retrieved PWV was around 1 mm for the durations of greater than 4 hours. The results at both the Bukgangneung (fixed site) and Boseong (mobile vehicle) seemed to be fairly comparable with each other. From this study it is believed that at least 4 hours of observing-session duration is needed for the retrieval of PWV from the ground GPS for meteorological usage using Bernese 5.0 software.

Analysis on Inundation Characteristics for Flood Impact Forecasting in Gangnam Drainage Basin (강남지역 홍수영향예보를 위한 침수특성 분석)

  • Lee, Byong-Ju
    • Atmosphere
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    • v.27 no.2
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    • pp.189-197
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    • 2017
  • Progressing from weather forecasts and warnings to multi-hazard impact-based forecast and warning services represents a paradigm shift in service delivery. Urban flooding is a typical meteorological disaster. This study proposes support plan for urban flooding impact-based forecast by providing inundation risk matrix. To achieve this goal, we first configured storm sewer management model (SWMM) to analyze 1D pipe networks and then grid based inundation analysis model (GIAM) to analyze 2D inundation depth over the Gangnam drainage area with $7.4km^2$. The accuracy of the simulated inundation results for heavy rainfall in 2010 and 2011 are 0.61 and 0.57 in POD index, respectively. 20 inundation scenarios responding on rainfall scenarios with 10~200 mm interval are produced for 60 and 120 minutes of rainfall duration. When the inundation damage thresholds are defined as pre-occurrence stage, occurrence stage to $0.01km^2$, 0.01 to $0.1km^2$, and $0.1km^2$ or more in area with a depth of 0.5 m or more, rainfall thresholds responding on each inundation damage threshold results in: 0 to 20 mm, 20 to 50 mm, 50 to 80 mm, and 80 mm or more in the rainfall duration 60 minutes and 0 to 30 mm, 30 to 70 mm, 70 to 110 mm, and 110 mm or more in the rainfall duration 120 minutes. Rainfall thresholds as a trigger of urban inundation damage can be used to form an inundation risk matrix. It is expected to be used for urban flood impact forecasting.

An Analysis of Observed and Simulated Wind in the Snowfall Event in Yeongdong Region on 8 February 2020 (2020년 2월 8일 영동지역 강설 사례 시 관측과 수치모의 된 바람 분석)

  • Kim, Hae-Min;Nam, Hyoung-Gu;Kim, Baek-Jo;Jee, Joon-Bum
    • Atmosphere
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    • v.31 no.4
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    • pp.433-443
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    • 2021
  • The wind speed and wind direction in Yeongdong are one of the crucial meteorological factors for forecasting snowfall in this area. To improve the snowfall forecast in Yeongdong region, Yeongdong Extreme Snowfall-Windstorm Experiment, YES-WEX was designed. We examined the wind field variation simulated with Local Data Assimilation and Prediction System (LDAPS) using observed wind field during YES-WEX period. The simulated wind speed was overestimated over the East Sea and especially 2 to 4 times in the coastal line. The vertical wind in Yeongdong region, which is a crucial factor in the snowfall forecast, was not well simulated at the low level (850 hPa~1000 hPa) until 12 hours before the forecast. The snowfall distribution was also not accurately simulated. Three hours after the snowfall on the East Sea coast was observed, the snowfall was simulated. To improve the forecast accuracy of snowfall in Yeongdong region, it is important to understand the weather conditions using the observed and simulated data. In the future, data in the northern part of the East Sea and the mountain slope of Taebaek observed from the meteorological aircraft, ship, and drone would help in understanding the snowfall phenomenon and improving forecasts.

Text Mining and Network Analysis of News Articles for Deriving Socio-Economic Damage Types of Heat Wave Events in Korea: 2012~2016 Cases (뉴스 기사 텍스트 마이닝과 네트워크 분석을 통한 폭염의 사회·경제적 영향 유형 도출: 2012~2016년 사례)

  • Jung, Jae In;Lee, Kyoungjun;Kim, Seungbum
    • Atmosphere
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    • v.30 no.3
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    • pp.237-248
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    • 2020
  • In order to effectively prepare for damage caused by weather events, it is important to proactively identify the possible impacts of weather phenomena on the domestic society and economy. Text mining and Network analysis are used in this paper to build a database of damage types and levels caused by heat wave. We collect news articles about heat wave from the SBS news website and determine the primary and secondary effects of that through network analysis. In addition to that, based on the frequency with which each impact keyword is mentioned, we estimate how much influence each factor has. As a result, the types of impacts caused by heat wave are efficiently derived. Among these types of impacts, we find that people in South Korea are mainly interested in algae and heat-related illness. Since this technique of analysis can be applied not only to news articles but also to social media contents, such as Twitter and Facebook, it is expected to be used as a useful tool for building weather impact databases.

A Study on Improvement of the Use and Quality Control for New GNSS RO Satellite Data in Korean Integrated Model (한국형모델의 신규 GNSS RO 자료 활용과 품질검사 개선에 관한 연구)

  • Kim, Eun-Hee;Jo, Youngsoon;Lee, Eunhee;Lee, Yong Hee
    • Atmosphere
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    • v.31 no.3
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    • pp.251-265
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    • 2021
  • This study examined the impact of assimilating the bending angle (BA) obtained via the global navigation satellite system radio occultation (GNSS RO) of the three new satellites (KOMPSAT-5, FY-3C, and FY-3D) on analyses and forecasts of a numerical weather prediction model. Numerical data assimilation experiments were performed using a three-dimensional variational data assimilation system in the Korean Integrated Model (KIM) at a 25-km horizontal resolution for August 2019. Three experiments were designed to select the height and quality control thresholds using the data. A comparison of the data with an analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) integrated forecast system showed a clear positive impact of BA assimilation in the Southern Hemisphere tropospheric temperature and stratospheric wind compared with that without the assimilation of the three new satellites. The impact of new data in the upper atmosphere was compared with observations using the infrared atmospheric sounding interferometer (IASI). Overall, high volume GNSS RO data helps reduce the RMSE quantitatively in analytical and predictive fields. The analysis and forecasting performance of the upper temperature and wind were improved in the Southern and Northern Hemispheres.