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Titel |
Inferring past land use-induced changes in surface albedo from satellite observations: a useful tool to evaluate model simulations |
VerfasserIn |
J. P. Boisier, N. Noblet-Ducoudré, P. Ciais |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1726-4170
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Digitales Dokument |
URL |
Erschienen |
In: Biogeosciences ; 10, no. 3 ; Nr. 10, no. 3 (2013-03-07), S.1501-1516 |
Datensatznummer |
250018138
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Publikation (Nr.) |
copernicus.org/bg-10-1501-2013.pdf |
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Zusammenfassung |
Regional cooling resulting from increases in surface albedo has been
identified in several studies as the main biogeophysical effect of past land
use-induced land cover changes (LCC) on climate. However, the amplitude of
this effect remains quite uncertain due to, among other factors, (a)
uncertainties in the extent of historical LCC and, (b) differences in the way
various models simulate surface albedo and more specifically its dependency
on vegetation type and snow cover. We derived monthly albedo climatologies
for croplands and four other land cover types from the Moderate Resolution
Imaging Spectroradiometer (MODIS) satellite observations. We then
reconstructed the changes in surface albedo between preindustrial times and
present-day by combining these climatologies with the land cover maps of 1870
and 1992 used by seven land surface models (LSMs) in the context of the LUCID
("Land Use and Climate: identification of robust Impacts") intercomparison
project. These reconstructions show surface albedo increases larger than
10% (absolute) in winter, and larger than 2% in summer between 1870
and 1992 over areas that experienced intense deforestation in the northern
temperate regions. The historical surface albedo changes estimated with MODIS
data were then compared to those simulated by the various climate models
participating in LUCID. The inter-model mean albedo response to LCC shows a
similar spatial and seasonal pattern to the one resulting from the
MODIS-based reconstructions, that is, larger albedo increases in winter than
in summer, driven by the presence of snow. However, individual models show
significant differences between the simulated albedo changes and the
corresponding reconstructions, despite the fact that land cover change maps
are the same. Our analyses suggest that the primary reason for those
discrepancies is how LSMs parameterize albedo. Another reason, of secondary
importance, results from differences in their simulated snow extent. Our
methodology is a useful tool not only to infer observations-based historical
changes in land surface variables impacted by LCC, but also to point out
deficiencies of the models. We therefore suggest that it could be more widely
developed and used in conjunction with other tools in order to evaluate LSMs. |
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