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Proceedings Paper

Validation of the MODIS albedo product and improving the snow albedo retrieval with additional AMSR-E data in Qinghai-Tibet Plateau
Author(s): Huazhu Xue; Jindi Wang; Huaan Jin; Jian Bi
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Paper Abstract

Land surface albedo is crucial for land surface radiation and energy budgets. In this study we compared the MODIS 16-day albedo product (MCD43A3) with field-measured data in Qinghai-Tibet Plateau. The validation data were used from 4 automatic weather stations(AWS) locations, spanning the year 2002-2008. Results indicate that MCD43A3 albedo product in snow-free seasons is in good agreement with ground-based observations, with a bias of ±0.02-0.05. But in snow season of Qinghai-Tibet Plateau, the MCD43A3 albedo product reaches a high bias. One of the possible reasons is that the amount of bidirectional reflectance observations may not be sufficient for getting the high quality surface albedo retrieval because of cloudy weather during the snowing days. Another reason may be that the heterogeneity of snow surface and complexity of snow grain. It is well known that the snow albedo is influenced by many parameters. However, the accumulated daily maximum temperature is shown to be a good predictor of the snow albedo. And also the snow albedo may effected by snow depth and snow water equivalent. In this paper, we improved a snow albedo retrieval model through daily maximum temperature from AWS and SWE from AMSR-E which can provide time series observations during snowing and snowmelt period. Also the AMSR-E SWE product has a coarse-resolution (25km) and has some uncertainties, the results show better correlation with the field-measured snow surface albedo. The 16-day average value of this algorithm performs well when there is snow in spring.

Paper Details

Date Published: 12 August 2010
PDF: 9 pages
Proc. SPIE 7811, Atmospheric and Environmental Remote Sensing Data Processing and Utilization VI: Readiness for GEOSS IV, 781108 (12 August 2010); doi: 10.1117/12.860099
Show Author Affiliations
Huazhu Xue, State Key Lab. of Remote Sensing Science (China)
Henan Polytechnic Univ. (China)
Beijing Normal Univ. (China)
Jindi Wang, State Key Lab. of Remote Sensing Science (China)
Beijing Normal Univ. (China)
Huaan Jin, State Key Lab. of Remote Sensing Science (China)
Beijing Normal Univ. (China)
Jian Bi, State Key Lab. of Remote Sensing Science (China)
Beijing Normal Univ. (China)


Published in SPIE Proceedings Vol. 7811:
Atmospheric and Environmental Remote Sensing Data Processing and Utilization VI: Readiness for GEOSS IV
Mitchell D. Goldberg; Hal J. Bloom, Editor(s)

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