{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T02:54:06Z","timestamp":1771469646348,"version":"3.50.1"},"reference-count":125,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,16]],"date-time":"2022-09-16T00:00:00Z","timestamp":1663286400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["XDA20050102"],"award-info":[{"award-number":["XDA20050102"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["XDA23060601"],"award-info":[{"award-number":["XDA23060601"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["41975135"],"award-info":[{"award-number":["41975135"]}]},{"name":"National Natural Science Foundation of China","award":["XDA20050102"],"award-info":[{"award-number":["XDA20050102"]}]},{"name":"National Natural Science Foundation of China","award":["XDA23060601"],"award-info":[{"award-number":["XDA23060601"]}]},{"name":"National Natural Science Foundation of China","award":["41975135"],"award-info":[{"award-number":["41975135"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The \u201cwarm-humid\u201d climate change across the Tibetan Plateau (TP) has promoted grassland growth and an overall greening trend has been observed by remote sensing products. Many of the current generations of Earth System Models (ESMs) incorporate advanced process-based vegetation growth in the land surface module that can simulate vegetation growth, but the evaluation of their performance has not received much attention, especially over hot spots where projections of the future climate and vegetation growth are greatly needed. In this study, we compare the leaf area index (LAI) simulations of 35 ESMs that participated in CMIP6 to a remote-sensing-derived LAI product (GLASS LAI). The results show that about 40% of the models overestimated the Tibetan Plateau\u2019s greening, 48% of the models underestimated the greening, and 11% of the models showed a declining LAI trend. The CMIP6 models generally produced poor simulations of the spatial distribution of LAI trend, and overestimated the LAI trend of alpine vegetation, grassland, and forest, but underestimated meadow and shrub. Compared with other vegetation types, simulations of the forest LAI trend were the worst, the declining trend in forest pixels on the TP was generally underestimated, and the greening of the meadow was underestimated as well. However, the greening of the grassland, was greatly overestimated. For the Tibetan Plateau\u2019s averaged LAI, more than 70% of the models overestimated this during the growing seasons of 1981\u20132014. Similar to the forest LAI trend, the performance of the forest LAI simulation was the worst among the different vegetation types, and the forest LAI was underestimated as well.<\/jats:p>","DOI":"10.3390\/rs14184633","type":"journal-article","created":{"date-parts":[[2022,9,19]],"date-time":"2022-09-19T04:49:22Z","timestamp":1663562962000},"page":"4633","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["How Well Do CMIP6 Models Simulate the Greening of the Tibetan Plateau?"],"prefix":"10.3390","volume":"14","author":[{"given":"Jiafeng","family":"Liu","sequence":"first","affiliation":[{"name":"Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610299, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3791-1727","authenticated-orcid":false,"given":"Yaqiong","family":"Lu","sequence":"additional","affiliation":[{"name":"Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610299, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1444","DOI":"10.1126\/science.1155121","article-title":"Forests and climate change: Forcings, feedbacks, and the climate benefits of forests","volume":"320","author":"Bonan","year":"2008","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"870","DOI":"10.1126\/science.278.5339.870","article-title":"The response of global terrestrial ecosystems to interannual temperature variability","volume":"278","author":"Braswell","year":"1997","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"920","DOI":"10.1126\/science.aan5360","article-title":"Past and future global transformation of terrestrial ecosystems under climate change","volume":"361","author":"Nolan","year":"2018","journal-title":"Science"},{"key":"ref_4","first-page":"1","article-title":"Highlights of the IPCC Working Group I Fifth Assessment Report","volume":"10","author":"Qin","year":"2014","journal-title":"Clim. 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