Environmental Engineering Reference
In-Depth Information
The climatic data used in the SEAMLESS project are part of the Joint Research Centre
Monitoring Agriculture with Remote Sensing (JRC MARS) database of the MARS
Crop Yield Forecasting System (Micale and Genovese 2004 ; http://mars.jrc.it/marsstat ;
Genovese et al. 2007) . This database provides daily values that are needed as input data
for the model chain. It contains European wide, quality checked daily data since 1975.
The database is based on observed meteorological station data interpolated to a 50 by
50 km grid (MARS-grid). Daily data of roughly 1,300 stations is interpolated to a 50
by 50 km grid (MARS-grid) (Micale and Genovese 2004) . In the frame of SEAMLESS
a meteorological database has been developed, based on a weighted average of grid
weather values for each Climate Zone (NUTS2/EnZ combination), according to the
surface covered by the NUTS2/EnZ combination within the MARS-grid. The occurring
variability of the parameters within the NUTS2/EnZ combinations, due to the different
grids that are averaged according to their spatial weight, is described via minimum,
maximum values and standard deviation of the parameters. As a result one Climate
Zone is described by the time series of daily rainfall data over the period 1975-2007 for
the assumed representative point (pseudo weather station) of the climate zone.
To test the aggregated data the long term average for the climate zones was
calculated from 1975 until 2004. If the aggregated data at the level of Climate
Zones is compared with the patterns coming from the MARS Meteorological Grid
database they are well reflected for the majority of the countries, depending on the
NUTS2 area variability.
The correlation of the Environmental Stratification with the climatic parameters
from the JRC MARS Climate database can be assessed for example in using the
annual temperature sum as shown by Metzger et al. (2005) . It showed a high
correlation (R 2 of the regression of 0.95).
Figure 7.4 shows the overlay of the annual temperature sum (Tbase = 0) from the
long term average (1975-2004) with Environmental zones of the EnS highlighting the
spatial homogeneity of the zones in terms of temperature sums. Similar patterns are
found when using other relevant climatic parameters based on the long term average.
Climatic gradients that did not lead to additional zones in the EnS, as climatic
factors where only one part of the selection criteria, are partly reflected in the Climate
Zones, for example the rainfall gradient from the west to the east coast in Great
Britain (see Fig. 7.5 ). Climate Zones in Great Britain are well suited to highlight
the specific distribution of weather parameters throughout the country. This is valid
for the majority of the countries and areas, whereas Sweden, Norway, Finland
and the Baltic States show a much coarser pattern due to the large administrative
units averaging partly different climatic situations within the Climate Zones.
For modelling purposes it is needed to provide one soil profile description per
Seamzone. This is a complicated task for two reasons. Firstly, the majority of soil
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