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| Titel |
Evaluation of a Global Vegetation Model using time series of satellite vegetation indices |
| VerfasserIn |
F. Maignan, F.-M. Bréon, F. Chevallier, N. Viovy, P. Ciais, C. Garrec, J. Trules, M. Mancip |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 4, no. 4 ; Nr. 4, no. 4 (2011-12-05), S.1103-1114 |
| Datensatznummer |
250001922
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| Publikation (Nr.) |
 copernicus.org/gmd-4-1103-2011.pdf |
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| Zusammenfassung |
Atmospheric CO2 drives most of the greenhouse effect increase. One
major uncertainty on the future rate of increase of CO2 in the
atmosphere is the impact of the anticipated climate change on the
vegetation. Dynamic Global Vegetation Models (DGVM) are used to address this
question. ORCHIDEE is such a DGVM that has proven useful for climate change
studies. However, there is no objective and methodological way to accurately
assess each new available version on the global scale. In this paper, we
submit a methodological evaluation of ORCHIDEE by correlating
satellite-derived Vegetation Index time series against those of the modeled
Fraction of absorbed Photosynthetically Active Radiation (FPAR). A perfect
correlation between the two is not expected, however an improvement of the
model should lead to an increase of the overall performance.
We detail two case studies in which model improvements are demonstrated,
using our methodology. In the first one, a new phenology version in ORCHIDEE
is shown to bring a significant impact on the simulated annual cycles, in
particular for C3 Grasses and C3 Crops. In the second case study, we compare the simulations
when using two different weather fields to drive ORCHIDEE. The ERA-Interim
forcing leads to a better description of the FPAR interannual anomalies than
the simulation forced by a mixed CRU-NCEP dataset. This work shows that long
time series of satellite observations, despite their uncertainties, can
identify weaknesses in global vegetation models, a necessary first step to
improving them. |
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