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| Titel |
Using MODIS vegetation index data to test land cover parameterisation in a global vegetation model across Europe |
| VerfasserIn |
Jennifer Price, Tristan Quaife, Ian Woodward |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250072094
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| Zusammenfassung |
| The uncertainties associated with assigning a prescribed vegetation fraction from satellite
derived land cover data are explored here by conducting three simulations across Europe
using the Sheffield Dynamic Global Vegetation Model (SDGVM). There were two aims; the
first was to demonstrate the importance of specific crop representation in SDGVM, the
second was to address the effects of assigning different proportions of crops and grasses
to the plant functional types used as inputs to SDGVM. This was tested by first
running a simulation where crops were treated as natural grasses; then two further
simulations were run using different translations of the mosaic land cover classes of the
GLC2000 product into the plant functional types used by SDGVM. These land
cover classes contain a mixture of crops and natural grasses. Validation of SDGVM
outputs of the fraction of absorbed photosynthetically active radiation (fPAR) took
place using satellite observations of the normalized difference vegetation index
(NDVI) from MODIS (moderate resolution imaging spectroradiometer) during the
period 2001-2005. The results revealed that overall the representation of seasonal
phenology across Europe is good. However there are exceptions where the crop model in
SDGVM provides an inadequate representation of phenology and also areas where
prescribed crop cover is too high. The Iberian Peninsula is poorly represented by
current crop parameterisations in SDGVM. This is attributed to the use of a single
plant functional type in SDGVM to represent all crop types which appears to be
inappropriate in this instance. The differences between the highest and lowest crop
fractional coverages result in large differences in vegetation productivity of 0.7 Pg
C yr-1 for GPP (gross primary productivity) and 0.16 Pg C yr-1 for NEP (net
ecosystem productivity). When crops were not included these differences were
as high as 30%. This illustrates the need to represent vegetation cover, in terms
of type and spatial distribution, as accurately as possible in global scale models. |
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