• Title/Summary/Keyword: 대기과학

Search Result 1,621, Processing Time 0.032 seconds

GEMS BrO Retrieval Sensitivity Test Using a Radiative Transfer Model (복사전달모델을 이용한 GEMS 일산화브로민 산출 민감도 시험)

  • Chong, Heesung;Kim, Jhoon;Jeong, Ukkyo;Park, Sang Seo;Hong, Jaemin;Ahn, Dha Hyun;Cha, Hyeji;Lee, Won-Jin;Lee, Hae-jung
    • Korean Journal of Remote Sensing
    • /
    • v.37 no.6_1
    • /
    • pp.1491-1506
    • /
    • 2021
  • To estimate errors in GEMS retrievals for bromine monoxide (BrO) total vertical column densities(VCDs), we perform a sensitivity test using synthetic spectra generated by a radiative transfer model. Hourly synthetic data are produced for 00-07 UTC on the first day of every month in Jul 2013- Jun 2014. Solution errors estimated by the optimal estimation method tend to decrease with increasing air mass factors (AMFs) but increase when AMFs are larger than 5. Interference errors induced by formaldehyde (HCHO) absorption appear to be larger with smaller BrO AMFs. Total BrO retrieval errors estimated by combining solution and interference errors show an average of 26.74±30.18% for all data samples and 60.39±133.78% for those with solar zenith angles higher than 80°. Due to interfering spectral features and measurement errors not considered in thisstudy, errorsin BrO retrievals from actual GEMS measurements may have different magnitudes from our estimates. However, the variability of errors assessed in this study is still expected to appear in the actual BrO retrievals.

Introducing SPARTAN Instrument System for PM Analysis (PM 관측을 위한 스파르탄 시스템)

  • Sujin Eom;Sang Seo Park;Jhoon Kim;Seoyoung Lee;Yeseul Cho;Seungjae Lee;Ehsan Parsa Javid
    • Atmosphere
    • /
    • v.33 no.3
    • /
    • pp.319-330
    • /
    • 2023
  • As the need for PM type observation increases, Surface Particulate Matter Network (SPARTAN), PM samplers analyzes aerosol samples for PM mass concentration and chemical composition, were recently installed at two sites: Yonsei University at Seoul and Ulsan Institute of Science and Technology (UNIST) at Ulsan. These SPARTAN filter samplers and nephelometers provide the PM2.5 mass concentration and chemical speciation data with aerosol type information. We introduced the overall information and installation of SPARTAN at the field site in this study. After installation and observation, both Seoul and Ulsan sites showed a similar time series pattern with the daily PM2.5 mass concentration of SPARTAN and the data of Airkorea. In particular, in the case of high concentrations of fine particles, daily average value of PM2.5 was relatively well-matched. During the Yonsei University observation period, high concentrations were displayed in the order of sulfate, black carbon (BC), ammonium, and calcium ions on most measurement days. The case in which the concentration of nitrate ions showed significant value was confirmed as the period during which the fine dust alert was issued. From the data analysis, SPARTAN data can be analyzed in conjunction with the existing urban monitoring network, and it is expected to have a synergetic effect in the research field. Additionally, the possibility of being analyzed with optical data such as AERONET is presented. In addition, the method of installing and operating SPARTAN has been described in detail, which is expected to help set the stage for the observation system in the future.

기후, 인류의 생존을 약속할 것인가

  • O, Jae-Ho
    • The Science & Technology
    • /
    • no.8 s.411
    • /
    • pp.90-93
    • /
    • 2003
  • 현재 우리 주변에서 일어나고 있는 기후학적 사건들은 46억 년 전에 지구와 대기가 처음으로 형성되면서 계속된 지구 역사 대단원의 가장 마지막 부분에 해당한다. 지구가 탄생한 시점에서 대략 10억 년이 지나면서 지구상에는 생명체들이 등장했고, 이 생명체들의 생존의 결과로 대기의 조성성분도 변해왔다. 즉, 생명체가 대기의 조성성분을 조절해 왔다는 것을 말한다.

  • PDF

Analysis of the Relationship of Cold Air Damming with Snowfall in the Yeongdong Region (영동 지역 한기 축적과 강설의 연관성 분석)

  • Kim, Mi-Gyeong;Kim, Byung-Gon;Eun, Seung-Hee;Chae, Yu-Jin;Jeong, Ji-Hoon;Choi, Young-Gil;Park, Gyun-Myeong
    • Atmosphere
    • /
    • v.31 no.4
    • /
    • pp.421-431
    • /
    • 2021
  • The Yeongdong region is frequently vulnerable to heavy snowfall in winter in terms of societal and economical damages. By virtue of a lot of previous efforts, snowfall forecast has been significantly improved, but the performance of light snowfall forecast is still poor since it is very conducive to synoptic and mesoscale interactions, largely attributable to Taeback mountains and East Sea effects. An intensive observation has been made in cooperation with Gangwon Regional Meteorological Office and National Institute of Meteorological Studies in winter seasons since 2019. Two distinctive Cold Air Damming (CAD) events (14 February 2019 and 6 February 2020) were observed for two years when the snowfall forecast was wrong specifically in its location and timing. For two CAD events, lower-level temperature below 2 km ranged to lowest limit in comparisons to those of the previous 6-years (2014~2019) rawinsonde soundings, along with the stronger inversion strength (> 2.0℃) and thicker inversion depth (> 700 m). Further, the northwesterly was predominant within the CAD layer, whereas the weak easterly wind was exhibited above the CAD layer. For the CAD events, strong cold air accumulation along the east side of Taeback Mountains appeared to prevent snow cloud and convergence zone from penetrating into the Yeongdong region. We need to investigate the influence of CAD on snowfall in the Yeongdong region using continuous intensive observation and modeling studies altogether. In addition, the effect of synoptic and mesoscale interactions on snowfall, such as nighttime drainage wind and land breeze, should be also examined.

Effect of Model Domain on Summer Precipitation Predictions over the Korean Peninsula in WRF Model (WRF 모형에서 한반도 여름철 강수 예측에 모의영역이 미치는 영향)

  • Kim, Hyeong-Gyu;Lee, Hye-Young;Kim, Joowan;Lee, Seungwoo;Boo, Kyung On;Lee, Song-Ee
    • Atmosphere
    • /
    • v.31 no.1
    • /
    • pp.17-28
    • /
    • 2021
  • We investigated the impact of domain size on the simulated summer precipitation over the Korean Peninsula using the Weather Research and Forecasting (WRF) model. Two different domains are integrated up to 72-hours from 29 June 2017 to 28 July 2017 when the Changma front is active. The domain sizes are adopted from previous RDAPS (Regional Data Assimilation and Prediction System) and current LDAPS (Local Data Assimilation and Prediction System) operated by the Korea Meteorological Administration, while other model configurations are fixed identically. We found that the larger domain size showed better prediction skills, especially in precipitation forecast performance. This performance improvement is particularly noticeable over the central region of the Korean Peninsula. Comparisons of physical aspects of each variable revealed that the inflow of moisture flux from the East China Sea was well reproduced in the experiment with a large model domain due to a more realistic North Pacific high compared to the small domain experiment. These results suggest that the North Pacific anticyclone could be an important factor for the precipitation forecast during the summer-time over the Korean Peninsula.

Development of Surface Weather Forecast Model by using LSTM Machine Learning Method (기계학습의 LSTM을 적용한 지상 기상변수 예측모델 개발)

  • Hong, Sungjae;Kim, Jae Hwan;Choi, Dae Sung;Baek, Kanghyun
    • Atmosphere
    • /
    • v.31 no.1
    • /
    • pp.73-83
    • /
    • 2021
  • Numerical weather prediction (NWP) models play an essential role in predicting weather factors, but using them is challenging due to various factors. To overcome the difficulties of NWP models, deep learning models have been deployed in weather forecasting by several recent studies. This study adapts long short-term memory (LSTM), which demonstrates remarkable performance in time-series prediction. The combination of LSTM model input of meteorological features and activation functions have a significant impact on the performance therefore, the results from 5 combinations of input features and 4 activation functions are analyzed in 9 Automated Surface Observing System (ASOS) stations corresponding to cities/islands/mountains. The optimized LSTM model produces better performance within eight forecast hours than Local Data Assimilation and Prediction System (LDAPS) operated by Korean meteorological administration. Therefore, this study illustrates that this LSTM model can be usefully applied to very short-term weather forecasting, and further studies about CNN-LSTM model with 2-D spatial convolution neural network (CNN) coupled in LSTM are required for improvement.

Academic Development Status of Climate Dynamics in Korean Meteorological Society (한국기상학회 기후역학 분야 학술 발전 현황)

  • Soon-Il An;Sang-Wook Yeh;Kyong-Hwan Seo;Jong-Seong Kug;Baek-Min Kim;Daehyun Kim
    • Atmosphere
    • /
    • v.33 no.2
    • /
    • pp.125-154
    • /
    • 2023
  • Since the Korean Meteorological Society was organized in 1963, the climate dynamics fields have been made remarkable progress. Here, we documented the academic developments in the area of climate dynamics performed by members of Korean Meteorological Society, based on studies that have been published mainly in the Journal of Korean Meteorological Society, Atmosphere, and Asia-Pacific Journal of Atmospheric Sciences. In these journals, the fundamental principles of typical ocean-atmosphere climatic phenomena such as El Niño, Madden-Julian Oscillation, Pacific Decadal Oscillation, and Atlantic Multi-decadal Oscillation, their modeling, prediction, and its impact, are being conducted by members of Korean Meteorological Society. Recently, research has been expanded to almost all climatic factors including cryosphere and biosphere, as well as areas from a global perspective, not limited to one region. In addition, research using an artificial intelligence (AI), which can be called a cutting-edge field, has been actively conducted. In this paper, topics including intra-seasonal and Madden-Julian Oscillations, East Asian summer monsoon, El Niño-Southern Oscillation, mid-latitude and polar climate variations and some paleo climate and ecosystem studies, of which driving mechanism, modeling, prediction, and global impact, are particularly documented.