气候变化领域集成服务门户(CCPortal): Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation

CCPortal

DOI	10.5194/tc-10-761-2016
	Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation
	Yang Q.; Losch M.; Losa S.N.; Jung T.; Nerger L.; Lavergne T.
发表日期	2016
ISSN	19940416
卷号	10 期号:2
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.
学科领域	concentration (composition); data assimilation; general circulation model; ice thickness; Kalman filter; meltwater; radiometric survey; satellite data; sea ice; sensor; summer; uncertainty analysis; Arctic
语种	英语
scopus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
来源期刊	Cryosphere
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/119664
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
推荐引用方式 GB/T 7714	Yang Q.,Losch M.,Losa S.N.,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],2016,10(2).
APA	Yang Q.,Losch M.,Losa S.N.,Jung T.,Nerger L.,&Lavergne T..(2016).Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation.Cryosphere,10(2).
MLA	Yang Q.,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".Cryosphere 10.2(2016).