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| Titel |
JULES-crop: a parametrisation of crops in the Joint UK Land Environment Simulator |
| VerfasserIn |
T. Osborne, J. Gornall, J. Hooker, K. Williams, A. Wiltshire, R. Betts, T. Wheeler |
| 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 ; 8, no. 4 ; Nr. 8, no. 4 (2015-04-22), S.1139-1155 |
| Datensatznummer |
250116282
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| Publikation (Nr.) |
 copernicus.org/gmd-8-1139-2015.pdf |
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| Zusammenfassung |
| Studies of climate change impacts on the terrestrial biosphere have
been completed without recognition of the integrated nature of the biosphere.
Improved assessment of the impacts of climate change on food and water
security requires the development and use of models not only representing
each component but also their interactions. To meet this requirement the
Joint UK Land Environment Simulator (JULES) land surface model has been
modified to include a generic parametrisation of annual crops. The new model,
JULES-crop, is described and evaluation at global and site levels for the
four globally important crops; wheat, soybean, maize and rice. JULES-crop
demonstrates skill in simulating the inter-annual variations of yield for
maize and soybean at the global and country levels, and for wheat for major
spring wheat producing countries. The impact of the new parametrisation,
compared to the standard configuration, on the simulation of surface heat
fluxes is largely an alteration of the partitioning between latent and
sensible heat fluxes during the later part of the growing season. Further
evaluation at the site level shows the model captures the seasonality of leaf
area index, gross primary production and canopy height better than in the
standard JULES. However, this does not lead to an improvement in the
simulation of sensible and latent heat fluxes. The performance of JULES-crop
from both an Earth system and crop yield model perspective is encouraging.
However, more effort is needed to develop the parametrisation of the model
for specific applications. Key future model developments identified include
the introduction of processes such as irrigation and nitrogen limitation
which will enable better representation of the spatial variability in yield. |
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