High resolution air temperature climatology for G reece for the period 1971–2000
Climate atlases provide an excellent overview of a region's climate in the form of maps and disclose information about climate change. They constitute a valuable tool for easy access and management of climate information for a wide range of users including scientists, policymakers, resource man...
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Veröffentlicht in: | Meteorological applications 2017-04, Vol.24 (2), p.191-205 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Climate atlases provide an excellent overview of a region's climate in the form of maps and disclose information about climate change. They constitute a valuable tool for easy access and management of climate information for a wide range of users including scientists, policymakers, resource managers and urban planners.
The main aim of this work was the production of high resolution monthly mean air temperature climatology for
G
reece, determined from a high resolution homogeneous mean temperature dataset. Temperature data were obtained from 52 meteorological stations of the
H
ellenic
N
ational
M
eteorological
S
ervice. High resolution temperature maps were obtained by interpolating the homogenized data.
MISH
(
M
eteorological
I
nterpolation based on
S
urface
H
omogenized
D
ata), an interpolation method developed for meteorological purposes, was applied twice, once using as topographic model variables the elevation derived from a 90 m digital elevation model (
DEM
) and the first 15
AURELHY
(
A
nalyse
U
tilisant le
R
elief pour les
B
ésoins de l'
H
ydrométéorologie) principal components, and then using some additional model variables besides the elevation and the 15
AURELHY
principal components: latitude, incoming solar irradiance,
E
uclidean distance from the coastline and land to sea percentage. The spatial interpolation of monthly mean temperature was performed with a 0.5′ resolution (∼730 m at 38 °
N
). The results showed that modelling with only the
AURELHY
variables is not sufficient and the use of additional model variables is necessary. |
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ISSN: | 1350-4827 1469-8080 |
DOI: | 10.1002/met.1617 |