气候变化领域集成服务门户(CCPortal): A Bayesian approach towards daily pan-Arctic sea ice freeboard estimates from combined CryoSat-2 and Sentinel-3 satellite observations

CCPortal

DOI	10.5194/tc-15-2857-2021
	A Bayesian approach towards daily pan-Arctic sea ice freeboard estimates from combined CryoSat-2 and Sentinel-3 satellite observations
	Gregory W.; Lawrence I.R.; Tsamados M.
发表日期	2021
ISSN	19940416
起始页码	2857
结束页码	2871
卷号	15 期号:6
英文摘要	Observations of sea ice freeboard from satellite radar altimeters are crucial in the derivation of sea ice thickness estimates, which in turn provide information on sea ice forecasts, volume budgets, and productivity rates. Current spatio-temporal resolution of radar freeboard is limited as 30ĝ€¯d are required in order to generate pan-Arctic coverage from CryoSat-2 and 27ĝ€¯d are required from Sentinel-3 satellites. This therefore hinders our ability to understand physical processes that drive sea ice thickness variability on sub-monthly timescales. In this study we exploit the consistency between CryoSat-2, Sentinel-3A, and Sentinel-3B radar freeboards in order to produce daily gridded pan-Arctic freeboard estimates between December 2018 and April 2019. We use the Bayesian inference approach of Gaussian process regression to learn functional mappings between radar freeboard observations in space and time and to subsequently retrieve pan-Arctic freeboard as well as uncertainty estimates. We also employ an empirical Bayesian approach towards learning the free (hyper)parameters of the model, which allows us to derive daily estimates related to radar freeboard spatial and temporal correlation length scales. The estimated daily radar freeboard predictions are, on average across the 2018-2019 season, equivalent to CryoSat-2 and Sentinel-3 freeboards to within 1ĝ€¯mm (standard deviationsĝ€¯<6ĝ€¯cm), and cross-validation experiments show that errors in predictions are, on average, ≤ĝ€¯4ĝ€¯mm across the same period. We also demonstrate the improved temporal variability of a pan-Arctic daily product by comparing time series of the predicted freeboards, with 31ĝ€¯d running means from CryoSat-2 and Sentinel-3 freeboards, across nine sectors of the Arctic, as well as making comparisons with daily ERA5 snowfall data. Pearson correlations between daily radar freeboard anomalies and snowfall are as high as +0.52 over first-year ice and +0.41 over multi-year ice, suggesting that the estimated daily fields are able to capture real physical radar freeboard variability at sub-weekly timescales. © Author(s) 2021.
英文关键词	Satellites
语种	英语
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/202318
作者单位	Centre for Polar Observation and Modelling, Earth Sciences, University College London, London, United Kingdom; Centre for Polar Observation and Modelling, University of Leeds, Leeds, United Kingdom
推荐引用方式 GB/T 7714	Gregory W.,Lawrence I.R.,Tsamados M.. A Bayesian approach towards daily pan-Arctic sea ice freeboard estimates from combined CryoSat-2 and Sentinel-3 satellite observations[J],2021,15(6).
APA	Gregory W.,Lawrence I.R.,&Tsamados M..(2021).A Bayesian approach towards daily pan-Arctic sea ice freeboard estimates from combined CryoSat-2 and Sentinel-3 satellite observations.Cryosphere,15(6).
MLA	Gregory W.,et al."A Bayesian approach towards daily pan-Arctic sea ice freeboard estimates from combined CryoSat-2 and Sentinel-3 satellite observations".Cryosphere 15.6(2021).