气候变化领域集成服务门户(CCPortal): The retrieval of snow properties from SLSTR Sentinel-3-Part 2: Results and validation

CCPortal

DOI	10.5194/tc-15-2781-2021
	The retrieval of snow properties from SLSTR Sentinel-3-Part 2: Results and validation
	Mei L.; Rozanov V.; Jäkel E.; Cheng X.; Vountas M.; Burrows J.P.
发表日期	2021
ISSN	19940416
起始页码	2781
结束页码	2802
卷号	15 期号:6
英文摘要	To evaluate the performance of the eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) algorithm, presented in the Part 1 companion paper to this paper, we apply the XBAER algorithm to the Sea and Land Surface Temperature Radiometer (SLSTR) instrument on board Sentinel-3. Snow properties-snow grain size (SGS), snow particle shape (SPS) and specific surface area (SSA)-are derived under cloud-free conditions. XBAER-derived snow properties are compared to other existing satellite products and validated by ground-based and aircraft measurements. The atmospheric correction is performed on SLSTR for cloud-free scenarios using Modern-Era Retrospective Analysis for Research and Applications (MERRA) aerosol optical thickness (AOT) and the aerosol typing strategy according to the standard XBAER algorithm. The optimal SGS and SPS are estimated iteratively utilizing a look-up-table (LUT) approach, minimizing the difference between SLSTR-observed and SCIATRAN-simulated surface directional reflectances at 0.55 and 1.6ĝ€¯μm. The SSA is derived for a retrieved SGS and SPS pair. XBAER-derived SGS, SPS and SSA have been validated using in situ measurements from the recent campaign SnowEx17 during February 2017. The comparison shows a relative difference between the XBAER-derived SGS and SnowEx17-measured SGS of less than 4ĝ€¯%. The difference between the XBAER-derived SSA and SnowEx17-measured SSA is 2.7ĝ€¯m2/kg. XBAER-derived SPS can be reasonably explained by the SnowEx17-observed snow particle shapes. Intensive validation shows that (1) for SGS and SSA, XBAER-derived results show high correlation with field-based measurements, with correlation coefficients higher than 0.85. The root mean square errors (RMSEs) of SGS and SSA are around 12ĝ€¯μm and 6ĝ€¯m2/kg. (2) For SPS, aggregate SPS retrieved by XBAER algorithm is likely to be matched with rounded grains while single SPS in XBAER is possibly linked to faceted crystals. The comparison with aircraft measurements, during the Polar Airborne Measurements and Arctic Regional Climate Model Simulation Project (PAMARCMiP) campaign held in March 2018, also shows good agreement (with RCombining double low line0.82 and RCombining double low line0.81 for SGS and SSA, respectively). XBAER-derived SGS and SSA reveal the variability in the aircraft track of the PAMARCMiP campaign. The comparison between XBAER-derived SGS results and the Moderate Resolution Imaging Spectroradiometer (MODIS) Snow-Covered Area and Grain size (MODSCAG) product over Greenland shows similar spatial distributions. The geographic distribution of XBAER-derived SPS over Greenland and the whole Arctic can be reasonably explained by campaign-based and laboratory investigations, indicating a reasonable retrieval accuracy of the retrieved SPS. The geographic variabilities in XBAER-derived SGS and SSA both over Greenland and Arctic-wide agree with the snow metamorphism process. © 2021 Linlu Mei et al.
英文关键词	atmospheric correction; essential oil; model validation; MODIS; Sentinel; snow cover; spatial distribution; Arctic; Bremen; Greenland
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/202382
作者单位	Institute of Environmental Physics, University of Bremen, Bremen, Germany; Leipzig Institute for Meteorology, University of Leipzig, Leipzig, Germany; School of Geospatial Engineering and Science, Sun Yat-Sen University, Zhuhai, 519082, China
推荐引用方式 GB/T 7714	Mei L.,Rozanov V.,Jäkel E.,et al. The retrieval of snow properties from SLSTR Sentinel-3-Part 2: Results and validation[J],2021,15(6).
APA	Mei L.,Rozanov V.,Jäkel E.,Cheng X.,Vountas M.,&Burrows J.P..(2021).The retrieval of snow properties from SLSTR Sentinel-3-Part 2: Results and validation.Cryosphere,15(6).
MLA	Mei L.,et al."The retrieval of snow properties from SLSTR Sentinel-3-Part 2: Results and validation".Cryosphere 15.6(2021).