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The target satellite-derived snow parameters are snow surface temperature, mass fraction of soot, and two types of snow grain size retrieved from different spectral channels. The retrieved satellite products were compared with in-situ measured snow parameters based on snow pit work and snow sampling. The satellite-derived snow surface temperatures agreed well with in-situ measured values with a correlation coefficient (R-c) of 0.900 and a root-mean-square error (RMSE) of 1.1 K. The satellite-derived mass fractions of soot were close to in-situ measured mass fractions of snow impurities for the snow layer between the surface and down to 7 or 10 cm rather than between 0 and 2 cm, while the satellite-derived absolute values were lower than the in-situ measured ones (R-c=0.506 and RMSE=5.0 parts per million by weight (ppmw)). This discrepancy is due primarily to the difference in the composition of snow impurities assumed in the satellite algorithm (soot) and measured in-situ (mineral dust) suggesting that the satellite retrieval of soot is not producing soot concentrations in many cases but rather dust. Snow grain sizes retrieved from two satellite channels lambda = 0.460 and 0.865 pm had better accuracy (R-c =0.840 and RMSE = 125 mu m) than those from a satellite channel at lambda = 1.64 mu m (R-c=0.524 and RMSE = 123 mu m) from the comparison with simply depth-averaged snow grain size. When similar comparisons are made with the depth-averaged measured grain size by a 1/e weighting using flux transmittance, the results for R-c and RMSE are not improved due to some difficulties in calculating the depth-averaging by a 1/e weighting. For all our satellite products, the possible causes of errors are (1) satellite sensor calibration and (2) the bidirectional reflectance model (directional emissivity model for surface temperature) used in the algorithm together with the atmospheric correction. Two ways to improve the in-situ measurements are (1) the representativeness of the measured values and (2) the measuring methods. Field measurements also indicated that the increased reflectance due to \"sun crust\" observed at wet snow surfaces under clear sky could cause an underestimation of satellite-derived snow grain size. This problem will be more severe for the grain size retrieved from the channel at lambda = 1.64 mu m. (c) 2007 Elsevier Inc. 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  1. 防災科研関係論文

ADEOS-II/GLI snow/ice products - Part II: Validation results using GLI and MODIS data

https://nied-repo.bosai.go.jp/records/4366
https://nied-repo.bosai.go.jp/records/4366
db4421df-1260-44e5-a52e-05f259e9db44
Item type researchmap(1)
公開日 2023-03-30
タイトル
言語 en
タイトル ADEOS-II/GLI snow/ice products - Part II: Validation results using GLI and MODIS data
言語
言語 eng
著者 Teruo Aoki

× Teruo Aoki

en Teruo Aoki

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Masahiro Hori

× Masahiro Hori

en Masahiro Hori

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Hiroki Motoyoshi

× Hiroki Motoyoshi

en Hiroki Motoyoshi

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Tomonori Tanikawa

× Tomonori Tanikawa

en Tomonori Tanikawa

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Akihiro Hachikubo

× Akihiro Hachikubo

en Akihiro Hachikubo

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Konosuke Sugiura

× Konosuke Sugiura

en Konosuke Sugiura

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Teppel J. Yasunari

× Teppel J. Yasunari

en Teppel J. Yasunari

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Rune Storvold

× Rune Storvold

en Rune Storvold

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Hans A. Eide

× Hans A. Eide

en Hans A. Eide

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Knut Stamnes

× Knut Stamnes

en Knut Stamnes

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Wei Li

× Wei Li

en Wei Li

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Jens Nieke

× Jens Nieke

en Jens Nieke

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Yukinori Nakajima

× Yukinori Nakajima

en Yukinori Nakajima

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Fumihiro Takahashi

× Fumihiro Takahashi

en Fumihiro Takahashi

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抄録
内容記述タイプ Other
内容記述 For the validation of snow/ice products of the Advanced Earth Observing Satellite-II/Global Imager (ADEOS-II/GLI), several field campaigns were performed for various types of snow conditions with the Moderate Resolution Imaging Spectroradiometer (MODIS) and GLI overpasses at four sites in Alaska and eastern Hokkaido, Japan from 2001 to 2005. The target satellite-derived snow parameters are snow surface temperature, mass fraction of soot, and two types of snow grain size retrieved from different spectral channels. The retrieved satellite products were compared with in-situ measured snow parameters based on snow pit work and snow sampling. The satellite-derived snow surface temperatures agreed well with in-situ measured values with a correlation coefficient (R-c) of 0.900 and a root-mean-square error (RMSE) of 1.1 K. The satellite-derived mass fractions of soot were close to in-situ measured mass fractions of snow impurities for the snow layer between the surface and down to 7 or 10 cm rather than between 0 and 2 cm, while the satellite-derived absolute values were lower than the in-situ measured ones (R-c=0.506 and RMSE=5.0 parts per million by weight (ppmw)). This discrepancy is due primarily to the difference in the composition of snow impurities assumed in the satellite algorithm (soot) and measured in-situ (mineral dust) suggesting that the satellite retrieval of soot is not producing soot concentrations in many cases but rather dust. Snow grain sizes retrieved from two satellite channels lambda = 0.460 and 0.865 pm had better accuracy (R-c =0.840 and RMSE = 125 mu m) than those from a satellite channel at lambda = 1.64 mu m (R-c=0.524 and RMSE = 123 mu m) from the comparison with simply depth-averaged snow grain size. When similar comparisons are made with the depth-averaged measured grain size by a 1/e weighting using flux transmittance, the results for R-c and RMSE are not improved due to some difficulties in calculating the depth-averaging by a 1/e weighting. For all our satellite products, the possible causes of errors are (1) satellite sensor calibration and (2) the bidirectional reflectance model (directional emissivity model for surface temperature) used in the algorithm together with the atmospheric correction. Two ways to improve the in-situ measurements are (1) the representativeness of the measured values and (2) the measuring methods. Field measurements also indicated that the increased reflectance due to "sun crust" observed at wet snow surfaces under clear sky could cause an underestimation of satellite-derived snow grain size. This problem will be more severe for the grain size retrieved from the channel at lambda = 1.64 mu m. (c) 2007 Elsevier Inc. All rights reserved.
言語 en
書誌情報 en : REMOTE SENSING OF ENVIRONMENT

巻 111, 号 2-3, p. 274-290
出版者
言語 en
出版者 ELSEVIER SCIENCE INC
ISSN
収録物識別子タイプ EISSN
収録物識別子 1879-0704
DOI
関連識別子 10.1016/j.rse.2007.02.035
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