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Vegetation controls on northern high latitude snow‐albedo feedback: observations and CMIP 5 model simulations
Author(s) -
Loranty Michael M.,
Berner Logan T.,
Goetz Scott J.,
Jin Yufang,
Randerson James T.
Publication year - 2014
Publication title -
global change biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.146
H-Index - 255
eISSN - 1365-2486
pISSN - 1354-1013
DOI - 10.1111/gcb.12391
Subject(s) - albedo (alchemy) , environmental science , snow , vegetation (pathology) , climatology , climate model , boreal , atmospheric sciences , latitude , taiga , climate change , physical geography , ecology , geology , geography , meteorology , oceanography , medicine , art , geodesy , pathology , performance art , biology , art history
The snow‐masking effect of vegetation exerts strong control on albedo in northern high latitude ecosystems. Large‐scale changes in the distribution and stature of vegetation in this region will thus have important feedbacks to climate. The snow‐albedo feedback is controlled largely by the contrast between snow‐covered and snow‐free albedo (Δα), which influences predictions of future warming in coupled climate models, despite being poorly constrained at seasonal and century time scales. Here, we compare satellite observations and coupled climate model representations of albedo and tree cover for the boreal and A rctic region. Our analyses reveal consistent declines in albedo with increasing tree cover, occurring south of latitudinal tree line, that are poorly represented in coupled climate models. Observed relationships between albedo and tree cover differ substantially between snow‐covered and snow‐free periods, and among plant functional type. Tree cover in models varies widely but surprisingly does not correlate well with model albedo. Furthermore, our results demonstrate a relationship between tree cover and snow‐albedo feedback that may be used to accurately constrain high latitude albedo feedbacks in coupled climate models under current and future vegetation distributions.