Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Yonggwan Shin"'
Publikováno v:
Atmospheric Science Letters, Vol 24, Iss 4, Pp n/a-n/a (2023)
Abstract Non‐stationarity in heavy rainfall time series is often apparent in the form of trends because of long‐term climate changes. We have built non‐stationary (NS) models for annual maximum daily (AMP1) and 2‐day precipitation (AMP2) data
Externí odkaz:
https://doaj.org/article/1a6941c14cb641419b7e5ea9093b657b
Publikováno v:
Atmosphere, Vol 12, Iss 8, p 1052 (2021)
Scientists who want to know future climate can use multimodel ensemble (MME) methods that combine projections from individual simulation models. To predict the future changes of extreme rainfall in Iran, we examined the observations and 24 models of
Externí odkaz:
https://doaj.org/article/f8a67e0b1a7a4625a3d1a9e00b84fc3e
Autor:
Yonggwan Shin, Yire Shin, Juyoung Hong, Maeng-Ki Kim, Young-Hwa Byun, Kyung-On Boo, Il-Ung Chung, Doo-Sun R. Park, Jeong-Soo Park
Publikováno v:
Atmosphere, Vol 12, Iss 1, p 97 (2021)
Scientists occasionally predict projected changes in extreme climate using multi-model ensemble methods that combine predictions from individual simulation models. To predict future changes in precipitation extremes in the Korean peninsula, we examin
Externí odkaz:
https://doaj.org/article/f118535d1aee4f54a2235d7e14ea106f
Publikováno v:
Atmosphere, Vol 11, Iss 8, p 775 (2020)
A model weighting scheme is important in multi-model climate ensembles for projecting future changes. The climate model output typically needs to be bias corrected before it can be used. When a bias-correction (BC) is applied, equal model weights are
Externí odkaz:
https://doaj.org/article/afb20c80a37d46608a89fb551d393c48
Autor:
Yonggwan Shin, Yun Am Seo
Publikováno v:
International Journal on Advanced Science, Engineering & Information Technology; 2024, Vol. 14 Issue 2, p501-506, 6p
Autor:
Sungmin Kim, Jong-Keun Seon, Bonggyun Ko, Jun-Hyuk Lim, Woo-Chan Song, Gyo Rim Kang, Yonggwan Shin, Sung-Taek Jung
Publikováno v:
Journal of Pediatric Orthopaedics; Nov/Dec2023, Vol. 43 Issue 10, p632-639, 8p
Publikováno v:
Atmospheric Science Letters. 24
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ec44ca5e7c60d21fc9f1d4e7a87e8e4
https://doi.org/10.1002/asl.1145
https://doi.org/10.1002/asl.1145
Autor:
Jeong-Soo Park, Maeong-Ki Kim, Juyoung Hong, Yonggwan Shin, Il-Ung Chung, Doo-Sun R. Park, Yire Shin, Kyung-On Boo, Young-Hwa Byun
Projected changes in extreme climate are occasionally predicted through multi-model ensemble methods using a weighted averaging that combines predictions from individual simulation models. To predi...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::15aad5c367b0de61f0c0b3c4a6a95b49
https://doi.org/10.1002/essoar.10504075.1
https://doi.org/10.1002/essoar.10504075.1
Publikováno v:
Atmosphere, Vol 11, Iss 775, p 775 (2020)
Atmosphere
Volume 11
Issue 8
Atmosphere
Volume 11
Issue 8
A model weighting scheme is important in multi-model climate ensembles for projecting future changes. The climate model output typically needs to be bias corrected before it can be used. When a bias-correction (BC) is applied, equal model weights are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c5e98cba70e85dde4a6d665a582e8f3c
https://www.mdpi.com/2073-4433/11/8/775
https://www.mdpi.com/2073-4433/11/8/775
Publikováno v:
Stochastic Environmental Research and Risk Assessment. 33:47-57
Projections of changes in extreme climate are sometimes predicted by using multi-model ensemble methods such as Bayesian model averaging (BMA) embedded with the generalized extreme value (GEV) distribution. BMA is a popular method for combining the f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f1c77ade0678403cb8c4d8dc684673a
https://doi.org/10.1007/s00477-018-1629-7
https://doi.org/10.1007/s00477-018-1629-7