Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Keguang, Wang"'
Autor:
Keguang Wang, Caixin Wang, Frode Dinessen, Gunnar Spreen, Robert Ricker, Xiangshan Tian-Kunze
Publikováno v:
Frontiers in Marine Science, Vol 11 (2024)
Multisensor data fusion (MDF) is a process/technique of combining observations from multiple sensors to provide a more robust, accurate and complete description of the concerned object, environment or process. In this paper we introduce a new MDF met
Externí odkaz:
https://doaj.org/article/909f249037394cf3854e747685b0301b
Publikováno v:
Journal of Glaciology, Vol 64, Pp 387-396 (2018)
Increasing ship traffic and human activity in the Arctic has led to a growing demand for accurate Arctic weather forecast. High-quality forecasts obtained by models are dependent on accurate initial states achieved by assimilation of observations. In
Externí odkaz:
https://doaj.org/article/d5228c2900cb4263869eb3429ed0ac48
Publikováno v:
Weather and Forecasting.
Simulation of atmosphere-ocean-ice interactions in coupled Earth modelling systems with kilometer-scale resolution is a newchallenge in operational numericalweather prediction. This study presents an assessment of sensitivity experiments performed wi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bbb4e46e03db6c2a60a8f4c6c12df154
https://doi.org/10.1175/waf-d-22-0134.1
https://doi.org/10.1175/waf-d-22-0134.1
A Local Analytical Optimal Nudging (LAON) is introduced and thoroughly evaluated for assimilating the Advanced Microwave Scanning Radiometer 2 (AMSR2) sea ice concentration (SIC) in the Norwegian High-resolution pan-Arctic ocean and sea ice Predictio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7cde8d0172eb776ee7da0e611cf0ad3a
https://tc.copernicus.org/preprints/tc-2023-11/
https://tc.copernicus.org/preprints/tc-2023-11/
Publikováno v:
Polar Research, Vol 34, Iss 0, Pp 1-16 (2015)
Snow ice and superimposed ice formation on landfast sea ice in a Svalbard fjord, Kongsfjorden, was investigated with a high-resolution thermodynamic snow and sea-ice model, applying meteorological weather station data as external forcing. The model s
Externí odkaz:
https://doaj.org/article/86f13ccf13934a4196d717b5817bfe11
Autor:
Keguang Wang, Kai Håkon Christensen, Philip Rostosky, Sindre Markus Fritzner, Rune G. Graversen
Publikováno v:
The Cryosphere, Vol 13, Pp 491-509 (2019)
Source at https://doi.org/10.5194/tc-13-491-2019. The accuracy of the initial state is very important for the quality of a forecast, and data assimilation is crucial for obtaining the best-possible initial state. For many years, sea-ice concentration
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab668bea86e169b979341872624dab80
https://doi.org/10.5194/tc-13-491-2019
https://doi.org/10.5194/tc-13-491-2019
Sea ice is a critical component of the Earth system, playing an important role in high-latitudesurface radiation balance and heat, moisture and momentum exchange between atmosphereand ocean. In recent years, rapid changes have been occurring in Arcti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eeabfa4c74027afcff70522116d9a707
https://doi.org/10.5194/egusphere-egu2020-21935
https://doi.org/10.5194/egusphere-egu2020-21935
The METROMS is a coupled ocean and sea ice model based on the Regional Ocean Modeling System (ROMS) and the Los Alamos sea ice model CICE. It was employed for seasonal forecast of the September Arctic sea ice extent (SIE) in 2019 in the Sea Ice Predi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::12c0afd3c9c98b8204c7ee6254392740
https://doi.org/10.5194/egusphere-egu2020-13429
https://doi.org/10.5194/egusphere-egu2020-13429
Publikováno v:
IGARSS
In this study, we show assimilation results from a coupled ocean sea-ice model. The model has a horizontal resolution of 2.5 km. In the assimilation system, we assimilate high-resolution ice charts, structured on a 1 km grid. We compare the assimilat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::33558a6d723e1dbf2d75ace0677c797f
https://doi.org/10.1109/igarss.2019.8898221
https://doi.org/10.1109/igarss.2019.8898221