Zobrazeno 1 - 7 of 7 pro vyhledávání: '"Ebony Lee"'
3
Optimization of snow-related parameters in the Noah land surface model (v3.4.1) using a micro-genetic algorithm (v1.7a)
Autor: Sujeong Lim, Hyeon-Ju Gim, Ebony Lee, Seungyeon Lee, Won Young Lee, Yong Hee Lee, Claudio Cassardo, Seon Ki Park
Snowfall prediction is important in winter and early spring because snowy conditions generate enormous economic damages. However, there is a lack of previous studies dealing with snow prediction, especially using land surface models (LSMs). Numerical
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d1ca7ac8244601f1b786497a748a3c4
https://gmd.copernicus.org/articles/15/8541/2022/
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4
Classifying Synoptic Patterns and Identifying Sensitive Areas for Targeted Observations to Improve Air Quality Prediction over South Korea
Autor: Seungyeon Lee, Xiaohao Qin, Ji Won Yoon, Ebony Lee, Sujeong Lim, Seon Ki Park
In air quality prediction, initial conditions, based on both atmospheric and aerosol/chemistry observations, are essentially required for a coupled atmosphere-chemistry model. In general, we have more accurate model results with a higher amount and q
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::dffc98a968353a1b533845da58414160
https://doi.org/10.5194/ems2022-346
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5
Combinational Optimization of Physical Parameterization Schemes to Improve Air Quality Prediction Using Intelligent Optimization System
Autor: Ji Won Yoon, Ebony Lee, Sujeong Lim, Seungyeon Lee, Seon Ki Park
The environmental problems related to air pollution have been increasing, especially in East Asia, due to human activities, including high energy consumption and rapid economic growth. In order to address the air pollution problems, it is essential n
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0358711bb6024fa7d5a4e00eec0ed6ec
https://doi.org/10.5194/ems2022-342
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6
New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS)
Autor: Hyeong Ahn Kwon, Ara Cho, Young-Joon Kim, Jintai Lin, Sujung Go, Yong-Sang Choi, G. Gonzalez Abad, Jay R. Herman, Ben Veihelmann, Hyunkee Hong, K. M. Han, Seunghoon Lee, Juseon Bak, Berit Ahlers, Kwon-Ho Lee, Jhoon Kim, Marcel Dobber, Chul H. Song, David P. Edwards, Omar Torres, Dai Ho Ko, Kyung Jung Moon, Mijin Kim, David Haffner, Michael J. Newchurch, Ebony Lee, Haklim Choi, Hanlim Lee, Seon Ki Park, Sang-Kyun Kim, Kelly Chance, Junsung Park, Myoung Hwan Ahn, Mijin Eo, Ukkyo Jeong, Jiwon Yang, Thomas P. Kurosu, James H. Crawford, Chang Keun Song, Mina Kang, Jung Moon Yoo, Jihyo Chong, Pawan K. Bhartia, Hitoshi Irie, Kwang Mog Lee, Won Jun Choi, Glen Jaross, Cheng Liu, Kanghyun Baek, Yasko Kasai, D. K. Nicks, Pepijn Veefkind, Jae H. Kim, Rokjin J. Park, Hee Woo Shin, Myeong Jae Jeong, Jongmin Yoon, Yugo Kanaya, Jung Hun Woo, Robert J. Swap, Kyunghwa Lee, Heesung Chong, Jay Al-Saadi, Alexis K.H. Lau, Seoyoung Lee, Barry Lefer, Ja Ho Koo, Yesol Cha, Yunsoo Choi, Myungje Choi, Xiong Liu, Sang Seo Park, Si-Wan Kim, Sang Woo Kim, Gregory R. Carmichael, Pieternel F. Levelt, Sachiko Hayashida, Hana Lee, C. Chan Miller, C. Thomas McElroy, Bo Ram Kim
Publikováno v: Bulletin of the American Meteorological Society. 101:E1-E22
The Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled for launch in February 2020 to monitor air quality (AQ) at an unprecedented spatial and temporal resolution from a geostationary Earth orbit (GEO) for the first time. With the
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f3f6f449e920e2592f988872c1e4067e
https://doi.org/10.1175/bams-d-18-0013.1
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7
Impact of the OMI aerosol optical depth on analysis increments through coupled meteorology–aerosol data assimilation for an Asian dust storm
Autor: Dusanka Županski, Milija Županski, Seon Ki Park, Ebony Lee
Publikováno v: Remote Sensing of Environment. 193:38-53
In this study, we investigate the possibility of using a coupled meteorology–aerosol data assimilation (DA) to improve the forecast of a dust storm. We interfaced a coupled meteorology–chemistry model (WRF-Chem) with a hybrid variational-ensemble
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ff627cb969c07e4a0158626718751097
https://doi.org/10.1016/j.rse.2017.02.013
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