气候变化领域集成服务门户(CCPortal): Mapping of sea ice concentration using the NASA NIMBUS 5 Electrically Scanning Microwave Radiometer data from 1972-1977

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DOI	10.5194/essd-16-1247-2024
	Mapping of sea ice concentration using the NASA NIMBUS 5 Electrically Scanning Microwave Radiometer data from 1972-1977
	Kolbe, Wiebke Margitta; Tonboe, Rasmus T.; Stroeve, Julienne
发表日期	2024
ISSN	1866-3508
EISSN	1866-3516
起始页码	16
结束页码	3
卷号	16 期号:3
英文摘要	The Electrically Scanning Microwave Radiometer (ESMR) instrument onboard the NIMBUS 5 satellite was a one-channel microwave radiometer that measured the 19.35 GHz horizontally polarized brightness temperature ( T-B ) from 11 December 1972 to 16 May 1977. The original tape archive data in swath projection have recently been made available online by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Even though the ESMR was a predecessor of modern multi-frequency radiometers, there are still parts of modern processing methodologies which can be applied to the data to derive the sea ice extent globally. Here, we have reprocessed the entire dataset using a modern processing methodology that includes the implementation of pre-processing filtering, dynamical tie points, and a radiative transfer model (RTM) together with numerical weather prediction (NWP) for atmospheric correction. We present the one-channel sea ice concentration (SIC) algorithm and the model for computing temporally and spatially varying SIC uncertainty estimates. Post-processing steps include resampling to daily grids, land-spillover correction, the application of climatological masks, the setting of processing flags, and the estimation of sea ice extent, monthly means, and trends. This sea ice dataset derived from the NIMBUS 5 ESMR extends the sea ice record with an important reference from the mid-1970s. To make it easier to perform a consistent analysis of sea ice development over time, the same grid and land mask as used for EUMETSAT's OSI-SAF SMMR-based sea-ice climate data record (CDR) were used for our ESMR dataset. SIC uncertainties were included to further ease comparison to other datasets and time periods. We find that our sea ice extent in the Arctic and Antarctic in the 1970s is generally higher than those available from the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC), which were derived from the same ESMR dataset, with mean differences of 240 000 and 590 000 km 2 , respectively. When comparing monthly sea ice extents, the largest differences reach up to 2 million km 2 . Such large differences cannot be explained by the different grids and land masks of the datasets alone and must therefore also result from the differences in data filtering and algorithms, such as the dynamical tie points and atmospheric correction. The new ESMR SIC dataset has been released as part of the ESA Climate Change Initiative (ESA CCI) program and is publicly available at 10.5285/34a15b96f1134d9e95b9e486d74e49cf .(Tonboe et al., 2023)
语种	英语
WOS研究方向	Geology ; Meteorology & Atmospheric Sciences
WOS类目	Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:001192125900001
来源期刊	EARTH SYSTEM SCIENCE DATA
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/305761
作者单位	Technical University of Denmark; Danish Meteorological Institute DMI; University of Manitoba; University of London; University College London; University of Colorado System; University of Colorado Boulder
推荐引用方式 GB/T 7714	Kolbe, Wiebke Margitta,Tonboe, Rasmus T.,Stroeve, Julienne. Mapping of sea ice concentration using the NASA NIMBUS 5 Electrically Scanning Microwave Radiometer data from 1972-1977[J],2024,16(3).
APA	Kolbe, Wiebke Margitta,Tonboe, Rasmus T.,&Stroeve, Julienne.(2024).Mapping of sea ice concentration using the NASA NIMBUS 5 Electrically Scanning Microwave Radiometer data from 1972-1977.EARTH SYSTEM SCIENCE DATA,16(3).
MLA	Kolbe, Wiebke Margitta,et al."Mapping of sea ice concentration using the NASA NIMBUS 5 Electrically Scanning Microwave Radiometer data from 1972-1977".EARTH SYSTEM SCIENCE DATA 16.3(2024).