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| Titel |
Leaf Area Index specification for use in mesoscale weather prediction systems |
| VerfasserIn |
G. Bonafe', C. Knote, F. Di Giuseppe |
| Konferenz |
EGU General Assembly 2009
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 11 (2009) |
| Datensatznummer |
250027870
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| Zusammenfassung |
| The energy budget at the surface is strongly influenced by the presence of vegetation which
alters the partitioning of thermal energy between sensible and latent heat fluxes. Despite its
relevance, Numerical Weather Prediction (NWP) systems only use two parameters to describe
the vegetation cover: the fractional area of vegetation occupying a given pixel and the leaf
area index (LAI). In this study a limited area forecast model (COSMO) is used to investigate
the sensitivity of regional predictions to LAI assumptions over the Italian peninsula. Three
different approaches are compared: a space and time invariant LAI data set, a LAI
specification based on CORINE land classes and a MODIS satellite retrieved data
set.
The three approaches resolve increasingly higher moments both in time and space of LAI
probability density functions. Forecast scores employing the three datasets can therefore be
used to assess the required degree of accuracy needed for this parameter. The MODIS
dataset is the only one able to capture the expected vegetative cycle typical of the
Mediterranean soil and sensibly improves the 850 hPa temperature and humidity
forecast scores up to + 72 hrs forecast time. This suggests that accounting for LAI
temporal and spatial variability could potentially improve the prevision of lower level
variables. Nevertheless, model biases of 2m screen temperatures are not substantially
reduced by the more detailed LAI specification when comparison to synop stations
is performed. Using long term measurements collected by the CARBOEUROPE
project, a detailed verification of sensible and latent heat fluxes predictions is also
presented. It shows that the desirable positive impact arising from a better LAI
specification is nullified by the large uncertainties in the initialization of the soil
moisture which remains a crucial parameter for the reduction of screen level biases. |
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