DOI: 10.5194/tc-10-761-2016
Scopus记录号: 2-s2.0-84966318460
论文题名: Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation
作者: Yang Q ; , Losch M ; , Losa S ; N ; , Jung T ; , Nerger L ; , Lavergne T
刊名: Cryosphere
ISSN: 19940416
出版年: 2016
卷: 10, 期: 2 起始页码: 761
结束页码: 774
语种: 英语
英文关键词: concentration (composition)
; data assimilation
; general circulation model
; ice thickness
; Kalman filter
; meltwater
; radiometric survey
; satellite data
; sea ice
; sensor
; summer
; uncertainty analysis
; Arctic
英文摘要: Data assimilation experiments that aim at improving summer ice concentration and thickness forecasts in the Arctic are carried out. The data assimilation system used is based on the MIT general circulation model (MITgcm) and a local singular evolutive interpolated Kalman (LSEIK) filter. The effect of using sea ice concentration satellite data products with appropriate uncertainty estimates is assessed by three different experiments using sea ice concentration data of the European Space Agency Sea Ice Climate Change Initiative (ESA SICCI) which are provided with a per-grid-cell physically based sea ice concentration uncertainty estimate. The first experiment uses the constant uncertainty, the second one imposes the provided SICCI uncertainty estimate, while the third experiment employs an elevated minimum uncertainty to account for a representation error. Using the observation uncertainties that are provided with the data improves the ensemble mean forecast of ice concentration compared to using constant data errors, but the thickness forecast, based on the sparsely available data, appears to be degraded. Further investigating this lack of positive impact on the sea ice thicknesses leads us to a fundamental mismatch between the satellite-based radiometric concentration and the modeled physical ice concentration in summer: the passive microwave sensors used for deriving the vast majority of the sea ice concentration satellite-based observations cannot distinguish ocean water (in leads) from melt water (in ponds). New data assimilation methodologies that fully account or mitigate this mismatch must be designed for successful assimilation of sea ice concentration satellite data in summer melt conditions. In our study, thickness forecasts can be slightly improved by adopting the pragmatic solution of raising the minimum observation uncertainty to inflate the data error and ensemble spread. © Author(s) 2016. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75160
Appears in Collections: 影响、适应和脆弱性 气候变化与战略
There are no files associated with this item.
作者单位: Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Beijing, China; Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany; St. Petersburg Department of P. P. Shirshov Institute of Oceanology, St. Petersburg, Russian Federation; University of Bremen, Bremen, Germany; Norwegian Meteorological Institute, Oslo, Norway
Recommended Citation:
Yang Q,, Losch M,, Losa S,et al. Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation[J]. Cryosphere,2016-01-01,10(2)