{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T06:56:50Z","timestamp":1784271410737,"version":"3.55.0"},"reference-count":54,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2022,8,13]],"date-time":"2022-08-13T00:00:00Z","timestamp":1660348800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["U20A2081"],"award-info":[{"award-number":["U20A2081"]}]},{"name":"National Natural Science Foundation of China","award":["41971325"],"award-info":[{"award-number":["41971325"]}]},{"name":"National Natural Science Foundation of China","award":["42171391"],"award-info":[{"award-number":["42171391"]}]},{"name":"National Natural Science Foundation of China","award":["41975096"],"award-info":[{"award-number":["41975096"]}]},{"name":"National Natural Science Foundation of China","award":["2019YFC1510503"],"award-info":[{"award-number":["2019YFC1510503"]}]},{"name":"National Key Research and Development Program of China","award":["U20A2081"],"award-info":[{"award-number":["U20A2081"]}]},{"name":"National Key Research and Development Program of China","award":["41971325"],"award-info":[{"award-number":["41971325"]}]},{"name":"National Key Research and Development Program of China","award":["42171391"],"award-info":[{"award-number":["42171391"]}]},{"name":"National Key Research and Development Program of China","award":["41975096"],"award-info":[{"award-number":["41975096"]}]},{"name":"National Key Research and Development Program of China","award":["2019YFC1510503"],"award-info":[{"award-number":["2019YFC1510503"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Snow cover phenology (SCP) is critical to the climate system. China has the most comprehensive snow cover distribution in the middle and low latitudes and has shown dramatic changes over the past few decades. However, the spatiotemporal characteristics of SCP parameters and their sensitivity to meteorological factors (temperature and precipitation) under different conditions (altitude, snow cover classification, or season) in China are insufficiently studied. Therefore, using improved daily MODIS cloud-gap-filled (CGF) snow-cover-extent (SCE) products, the spatiotemporal characteristics (distribution and variation) and respond to climate of snow cover area (SCA), snow cover start (SCS), snow cover melt (SCM), and snow cover days (SCD) are explored from 2000 to 2020. The results show that in the past 20 years, snow cover in China has demonstrated a trend of decreasing SCA, decreasing SCD, advancing SCS, and advancing SCM, with SCM advancing faster than SCS. The greatest snowfall occurs in January, mainly in northeastern China, northern Xinjiang, and the Tibet Plateau. Spatially, the slope of SCP was mainly within \u00b10.5 day\/year (d\/y) Statistics indicated that the area proportion where SCD is significantly reduced is greater than increased; SCD, SCS, and SCM are shortened or advanced in three snow-covered area classifications. Moreover, compared with precipitation, the significantly correlated regions (6\u201347.2% more than precipitation) and correlation degree (1.23\u20138.33 times precipitation in significantly correlated snow cover classification) between temperature and SCP in different seasons are larger. For stable snow-covered areas (SSA), SCD are mainly affected by spring temperature below 1500 m and mainly by autumn temperature above 1500 m; the precipitation is more affected in autumn. The correlation of SCP with temperature and precipitation has obvious spatial and seasonal differences and shows characteristic variation with altitude. These results can provide important data support for climate prediction, hydrological research, and disaster warning.<\/jats:p>","DOI":"10.3390\/rs14163936","type":"journal-article","created":{"date-parts":[[2022,8,15]],"date-time":"2022-08-15T23:44:03Z","timestamp":1660607043000},"page":"3936","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Snow Cover Phenology Change and Response to Climate in China during 2000\u20132020"],"prefix":"10.3390","volume":"14","author":[{"given":"Qin","family":"Zhao","sequence":"first","affiliation":[{"name":"Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4636-979X","authenticated-orcid":false,"given":"Xiaohua","family":"Hao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"},{"name":"Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"},{"name":"Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siqiong","family":"Luo","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6681-3640","authenticated-orcid":false,"given":"Donghang","family":"Shao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"},{"name":"Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7583-6003","authenticated-orcid":false,"given":"Hongyi","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"},{"name":"Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3587-734X","authenticated-orcid":false,"given":"Tianwen","family":"Feng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8756-0104","authenticated-orcid":false,"given":"Hongyu","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4261","DOI":"10.5194\/tc-15-4261-2021","article-title":"Evaluation of snow extent time series derived from Advanced Very High Resolution Radiometer global area coverage data (1982\u20132018) in the Hindu Kush Himalayas","volume":"15","author":"Wu","year":"2021","journal-title":"Cryosphere"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3673","DOI":"10.1029\/2000GL012556","article-title":"Recent northern hemisphere snow extent: A comparison of data derived from visible and microwave satellite sensors","volume":"28","author":"Armstrong","year":"2001","journal-title":"Geophys. 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