The retreival of snow properties from SLSTR/Sentinel-3 – part 2: results and validation

To evaluate the performance of eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) algorithm, presented in part 1 of the companion paper, this manuscript applies the XBAER algorithm on the Sea and Land Surface Temperature Radiometer (SLSTR) and Ocean and Land Colour Instrument (...

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Main Authors: Mei, Linlu, Rozanov, Vladimir, Jäkel, Evelyn, Cheng, Xiao, Vountas, Marco, Burrows, John P.
Format: Text
Language:English
Published: 2020
Subjects:
Online Access:https://doi.org/10.5194/tc-2020-270
https://tc.copernicus.org/preprints/tc-2020-270/
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spelling ftcopernicus:oai:publications.copernicus.org:tcd89740 2023-05-15T14:59:04+02:00 The retreival of snow properties from SLSTR/Sentinel-3 – part 2: results and validation Mei, Linlu Rozanov, Vladimir Jäkel, Evelyn Cheng, Xiao Vountas, Marco Burrows, John P. 2020-10-07 application/pdf https://doi.org/10.5194/tc-2020-270 https://tc.copernicus.org/preprints/tc-2020-270/ eng eng doi:10.5194/tc-2020-270 https://tc.copernicus.org/preprints/tc-2020-270/ eISSN: 1994-0424 Text 2020 ftcopernicus https://doi.org/10.5194/tc-2020-270 2020-10-12T16:22:14Z To evaluate the performance of eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) algorithm, presented in part 1 of the companion paper, this manuscript applies the XBAER algorithm on the Sea and Land Surface Temperature Radiometer (SLSTR) and Ocean and Land Colour Instrument (OLCI) instruments onboard 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/aircraft measurements. Cloud screening is performed by standard XBAER algorithm synergistically using OLCI and SLSTR instruments both onboard Sentinel-3. 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 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 1.6 μm. The SSA is derived for a given 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 of the retrieved SGS with the in-situ data shows a relative difference between XBAER-derived SGS and SnowEx17 measured SGS of less than 4 %. The difference between XBAER-derived SSA and SnowEx17 measured SSA is 2.7 m 2 /kg. XBAER-derived SPS can be reasonable-explained by the SnowEx17 observed snow particle shapes. 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 R = 0.82 and R = 0.81 for SGS and SSA, respectively). XBAER-derived SGS and SSA reveal the variability of the aircraft track of PAMARCMiP campaign. The comparison between XBAER-derived SGS results and 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 reasonable-explained by campaign-based and laboratory investigations, indicating reasonable retrieval accuracy of the retrieved SPS. The geographic variabilities of XBAER-derived SGS and SSA over both Greenland and Arctic-wide agree with the snow metamorphism process. Text Arctic Greenland Copernicus Publications: E-Journals Arctic Greenland Merra ENVELOPE(12.615,12.615,65.816,65.816)
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description To evaluate the performance of eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) algorithm, presented in part 1 of the companion paper, this manuscript applies the XBAER algorithm on the Sea and Land Surface Temperature Radiometer (SLSTR) and Ocean and Land Colour Instrument (OLCI) instruments onboard 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/aircraft measurements. Cloud screening is performed by standard XBAER algorithm synergistically using OLCI and SLSTR instruments both onboard Sentinel-3. 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 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 1.6 μm. The SSA is derived for a given 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 of the retrieved SGS with the in-situ data shows a relative difference between XBAER-derived SGS and SnowEx17 measured SGS of less than 4 %. The difference between XBAER-derived SSA and SnowEx17 measured SSA is 2.7 m 2 /kg. XBAER-derived SPS can be reasonable-explained by the SnowEx17 observed snow particle shapes. 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 R = 0.82 and R = 0.81 for SGS and SSA, respectively). XBAER-derived SGS and SSA reveal the variability of the aircraft track of PAMARCMiP campaign. The comparison between XBAER-derived SGS results and 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 reasonable-explained by campaign-based and laboratory investigations, indicating reasonable retrieval accuracy of the retrieved SPS. The geographic variabilities of XBAER-derived SGS and SSA over both Greenland and Arctic-wide agree with the snow metamorphism process.
format Text
author Mei, Linlu
Rozanov, Vladimir
Jäkel, Evelyn
Cheng, Xiao
Vountas, Marco
Burrows, John P.
spellingShingle Mei, Linlu
Rozanov, Vladimir
Jäkel, Evelyn
Cheng, Xiao
Vountas, Marco
Burrows, John P.
The retreival of snow properties from SLSTR/Sentinel-3 – part 2: results and validation
author_facet Mei, Linlu
Rozanov, Vladimir
Jäkel, Evelyn
Cheng, Xiao
Vountas, Marco
Burrows, John P.
author_sort Mei, Linlu
title The retreival of snow properties from SLSTR/Sentinel-3 – part 2: results and validation
title_short The retreival of snow properties from SLSTR/Sentinel-3 – part 2: results and validation
title_full The retreival of snow properties from SLSTR/Sentinel-3 – part 2: results and validation
title_fullStr The retreival of snow properties from SLSTR/Sentinel-3 – part 2: results and validation
title_full_unstemmed The retreival of snow properties from SLSTR/Sentinel-3 – part 2: results and validation
title_sort retreival of snow properties from slstr/sentinel-3 – part 2: results and validation
publishDate 2020
url https://doi.org/10.5194/tc-2020-270
https://tc.copernicus.org/preprints/tc-2020-270/
long_lat ENVELOPE(12.615,12.615,65.816,65.816)
geographic Arctic
Greenland
Merra
geographic_facet Arctic
Greenland
Merra
genre Arctic
Greenland
genre_facet Arctic
Greenland
op_source eISSN: 1994-0424
op_relation doi:10.5194/tc-2020-270
https://tc.copernicus.org/preprints/tc-2020-270/
op_doi https://doi.org/10.5194/tc-2020-270
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