using this cartography for any study or research, please quote
it as indicated in the reference
Here under you can access to the Map Server of the
Digital Climatic Atlas of the Iberian Peninsula whether for its
displaying and querying or for its download.
There you will find interesting
information whether for the Map Server use (displaying, querying
and download) and for other important issues to consider about limitations
and improvements of the Atlas.
Query for an specific coordinate
There exist different displaying tools ()
but, until now, there isn’t any tool to detect
a specific coordiante. However, there is a “trick”
in order to easily detect a specific coordinate. In the Options
if you type the desired coordinate in the blank boxes for the origin
point X,Y; down-left corner of the map will correspond to the desired
Displayed maps have been scaled and reclassified individually.
That means that a same colour holds a different climatic value depending
on the month, which implies that maps are not visually comparable.
However, there is a higher contrast within each individual map.
In case you may wish to compare maps from different months with
a same colour scale you have to click on the Animation Icon .
This will play an animation which enables observing a monthly temporal
sequence. In this case, like stated above, maps show a common colour
palette. In other words, the same colour is always assigned to
the same climatic value for each month.
Obviously, downloaded maps have not the same information
quality (as they are not reclassified) and therefore, user may decide
how to process this information whether it is for displaying purposes
or numerical analysis.
In order not to block the server, maximum allowed download
extent corresponds approximately to the size of a Spanish province.
Once you have downloaded the desired maps in your PC
there are two options:
- If you wish to perform basic operations (such as displaying, querying
and so on), you just simply have to download for free MiraMon Map
Reader (installing through the Map Reader Icon ).
- If you wish to perform advanced GIS operations, you
will have to purchase MiraMon
GIS. In case you might need to use another software, MiraMon
GIS is able to export to other formats (such as LAN/GIS,GRD,TXT,BMP,JPG,
GeoTIFF, IMG Idrisi).
When the maps are queried in the map server, temperature
and precipitation units are expressed, as usual, in Celsius degrees
and mm. However, when downloaded and queried in a GIS the units
would be expressed in tenths of Celsius degrees and tenths of mm.
Tenths allow to deal with integer surfaces (instead of
real ones) which provide smaller file
Access to Web Map Service and Web Coverage Service
You can access to those services through this link
services (WMS and WCS) follow Open Geospatial Consortium (OGM) standards.
If you purchase MiraMon 5 you can display and query maps through
the following sequence: File/ “Navigate through WMS servers
and then add an external server with the address above.
If contextual menus appearing over the icons are not
enough to solve your doubts, by clicking on Help Icon
you will find detailed instructions on how to deeply use the Map
Every downloaded map is related to a file that contains
metadata following ISO 19139 recommendations.
referring to map accuracy (RMS and R2 )is shown.
In the map legend (left side in the map server page),
you can click on the variable name to query the metadata of each
month. Obviously, when a map is downloaded its associated metadata
is downloaded too.
Limitations and improvements. A few considerations.
The case of Portugal
For Portugal, data from meteorological stations have
been obtained from bibliography. Therefore, the cartography obtained
for the Portuguese territory must be cautionly considered because
only 47 stations have been used. However, it is important to take
into account that the generated model for the Spanish territory
is robust enough to be applied to the Portuguese territory, specially
when for some applications it is important to work in a peninsular
scale instead of a state scale. In future updates we will try to
incorporate more Portuguese stations.
- Improve geographical variables modeling (such as
continentality, solar radiation), as well as introducing new variables
(orography, information from remote sensors, etc)
- Series Length: longer series will contribute to enhance
temporal stability and therefore an improvement of climatic information
quality. In addition, new stations will be incorporated in order
to obtain a larger spatial coverage taking into account additional
- Location of the stations: problems of extrapolation and homogeneity:
The set of the meteorological stations used to perform multiple
regression analysis is placed within a range for each geographical
variable. When mapping the model outside this range, it occurs that
we are extrapolating. Regression model does not inform about the
behaviour of the fitted function to these points just because there
is no information. Among all variables used, only the altitude may
present extrapolation problems. Meteorological stations used have
an altitudinal range from 0 to 2263 m. Hence, when modeling areas
higher than 2263 m, incorrect estimations of climatic variables
may arise. A clarifying example is the case of altitude versus precipitation.
For these points of the territory (higher than 2263 m) the relationship
found between both variables might vary from that found for other
altitudes. In fact, for this case it might seem that this relationship
is even inverted for the highest mountain summits where precipitation,
instead of rising, diminishes (Solé Sabarís et al.,
To avoid extrapolation effects there are two options. First, consists
in computing the maps for the entire territory and leave the user
the choice of removing outranged points by applying a boolean mask.
Second option, consists in reclassifying the raster matrices of
geographical variables within the ranges, where stations are placed,
and then proceed to map the model. In the case of the Atlas, we
have chosen the first option because it enables you to keep complete
numerical information for ulterior analysis.
Homogeneity of slopes
The fact that there are only a few stations in steep
areas with contrasted values (north and south aspects) diminishes
contribution of solar radiation to the model. This is a limitation
since, intuitively, solar radiation should always influence air