Using Multisource Satellite Data to Assess Recent Snow-Cover Variability and Uncertainty in the Qinghai–Tibet PlateauSource: Journal of Hydrometeorology:;2019:;volume 020:;issue 007::page 1293DOI: 10.1175/JHM-D-18-0220.1Publisher: American Meteorological Society
Abstract: AbstractSnow cover in the Qinghai?Tibet Plateau (QTP) is a critical component in the water cycle and regional climate of East Asia. Fractional snow cover (FSC) derived from five satellite sources [the three satellites comprising the multisensor synergy of FengYun-3 (FY-3A/B/C), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Interactive Multisensor Snow and Ice Mapping System (IMS)] were intercompared over the QTP to examine uncertainties in mean snow cover and interannual variability over the last decade. A four-step cloud removal procedure was developed for MODIS and FY-3 data, which effectively reduced the cloud percentage from about 40% to 2%?3% with an error of about 2% estimated by a random sampling method. Compared to in situ snow-depth observations, the cloud-removed FY-3B data have an annual classification accuracy of about 94% for both 0.04° and 0.01° resolutions, which is higher than other datasets and is recommended for use in QTP studies. Among the five datasets analyzed, IMS has the largest snow extent (22% higher than MODIS) and the highest FSC (4.7% higher than MODIS), while the morning-overpass MODIS and FY-3A/C FSC are similar and are around 5% higher than the afternoon-overpass FY-3B FSC. Contrary to MODIS, IMS shows increasing variability in snow cover and snow duration over the last decade (2006?17). Differences in variabilities of FSC and snow duration between products are greater at 5?6 km than lower elevations, with seasonal snow-cover change showing the largest uncertainty in snowmelt date.
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contributor author | Jiang, Yingsha | |
contributor author | Chen, Fei | |
contributor author | Gao, Yanhong | |
contributor author | Barlage, Michael | |
contributor author | Li, Jianduo | |
date accessioned | 2019-10-05T06:54:21Z | |
date available | 2019-10-05T06:54:21Z | |
date copyright | 5/15/2019 12:00:00 AM | |
date issued | 2019 | |
identifier other | JHM-D-18-0220.1.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4263796 | |
description abstract | AbstractSnow cover in the Qinghai?Tibet Plateau (QTP) is a critical component in the water cycle and regional climate of East Asia. Fractional snow cover (FSC) derived from five satellite sources [the three satellites comprising the multisensor synergy of FengYun-3 (FY-3A/B/C), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Interactive Multisensor Snow and Ice Mapping System (IMS)] were intercompared over the QTP to examine uncertainties in mean snow cover and interannual variability over the last decade. A four-step cloud removal procedure was developed for MODIS and FY-3 data, which effectively reduced the cloud percentage from about 40% to 2%?3% with an error of about 2% estimated by a random sampling method. Compared to in situ snow-depth observations, the cloud-removed FY-3B data have an annual classification accuracy of about 94% for both 0.04° and 0.01° resolutions, which is higher than other datasets and is recommended for use in QTP studies. Among the five datasets analyzed, IMS has the largest snow extent (22% higher than MODIS) and the highest FSC (4.7% higher than MODIS), while the morning-overpass MODIS and FY-3A/C FSC are similar and are around 5% higher than the afternoon-overpass FY-3B FSC. Contrary to MODIS, IMS shows increasing variability in snow cover and snow duration over the last decade (2006?17). Differences in variabilities of FSC and snow duration between products are greater at 5?6 km than lower elevations, with seasonal snow-cover change showing the largest uncertainty in snowmelt date. | |
publisher | American Meteorological Society | |
title | Using Multisource Satellite Data to Assess Recent Snow-Cover Variability and Uncertainty in the Qinghai–Tibet Plateau | |
type | Journal Paper | |
journal volume | 20 | |
journal issue | 7 | |
journal title | Journal of Hydrometeorology | |
identifier doi | 10.1175/JHM-D-18-0220.1 | |
journal fristpage | 1293 | |
journal lastpage | 1306 | |
tree | Journal of Hydrometeorology:;2019:;volume 020:;issue 007 | |
contenttype | Fulltext |