DOI: 10.5194/tc-12-247-2018
Scopus记录号: 2-s2.0-85041176614
论文题名: Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites
作者: Aalstad K ; , Westermann S ; , Schuler T ; V ; , Boike J ; , Bertino L
刊名: Cryosphere
ISSN: 19940416
出版年: 2018
卷: 12, 期: 1 起始页码: 247
结束页码: 270
语种: 英语
英文关键词: albedo
; data assimilation
; data set
; Gaussian method
; hydrometeorology
; MODIS
; mountain region
; satellite data
; snow cover
; snow water equivalent
; surface energy
; thermal conductivity
; time series analysis
; water budget
; Arctic
; Ny-Alesund
; Spitsbergen
; Svalbard
; Svalbard and Jan Mayen
英文摘要: With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE) is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD) at the 1 km scale by assimilating fractional snow-covered area (fSCA) satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products) to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation) ensemble smoother with multiple data assimilation (ES-MDA) scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79°, Svalbard, Norway) where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE) for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20%, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e.) and 0.13, respectively. The ES-MDA either outperforms or at least nearly matches the performance of other ensemble-based batch smoother schemes with regards to various evaluation metrics. Given the modularity of the method, it could prove valuable for a range of satellite-era hydrometeorological reanalyses. © 2018 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75433
Appears in Collections: 影响、适应和脆弱性 气候变化与战略
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作者单位: Department of Geosciences, University of Oslo, P.O. Box 1047, Blindern, Oslo, Norway; Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Telegrafenberg A43, Potsdam, Germany; Nansen Environmental and Remote Sensing Center, Thormøhlens gate 47, Bergen, Norway
Recommended Citation:
Aalstad K,, Westermann S,, Schuler T,et al. Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites[J]. Cryosphere,2018-01-01,12(1)