What is the Atlas?
We could define this Atlas as a “set of digital
climatic maps of mean air temperature (minimum, mean and maximum),
precipitation and solar radiation”. With these maps we are
able to find, for every 200m of the Iberian Peninsula, which is
the mean annual temperature, the precipitation of June or any of
the variables mentioned before in climatic terms. In other words,
you can query the mean value based on the average from all years
where data is available. Furthermore, these values may be queried
for the whole year (mean for temperature and solar radiation or
accumulated for precipitation) or for a certain month.
-Completeness: 65 digital
climatic maps of air mean temperature (minimum, mean and maximum),
precipitation and solar radiation.
- High quality base data:
2285 meteorological stations have been used containing data from
the 1951-1999 period (a range of 15 up to 50 years depending on
the case) and a Digital Elevation Model with 200 m resolution.
- Detailed resolution
(specially if we consider largeness of the Iberian Peninsula): spatial
resolution of 200 m and monthly and annual temporal resolution.
- Integration of techniques:
These maps have been processed using statistical techniques (such
as multiple regression with residual correction), Geographic Information
Systems (GIS) and spatial interpolation of meteorological stations
quality (known error) computed and documented for every map. Error
level and their spatial distribution are crucial aspects whether
for cartography assessment or for assessment of models generated
from this cartography.
enables these maps to be overlaid with other sources of information.
- Accessibility: Queriable
and downloadable in GIS format freely on Internet.
Why has it been made?
It is well-known that the Iberian Peninsula presents
interesting characteristics, as well as complex, in climatological
and biogeographical terms. In addition, from geosciences and biosciences
(hydrology, ecology, biogeography, etc) as well as from land managers
(conservation agencies, etc) there is an obvious interest for climatology.
Despite this interest, just data coming from meteorological stations
is relevant enough. Even though, these stations present an irregular
spatial distribution throughout the territory and hence, some questions
arise: How making climatological maps? How generating information
where no data is available? To sum up: How interpolating?
First approaches used expert knowledge and intuition
for drawing maps but...
- Nobody can deal with several meteorological stations
and variables (altitude, continentality, etc.) at the same time.
- Lack of objectivity in the resultant cartography
- Classical methods did not inform about quality parameters (relevant
- Those maps did not offer a truly continuous variation over terrain
- Complex data, such as solar radiation, was not included
New technological (computers) and scientific progress (GIS), specially
during last decade, make possible that today we are able to develop
cartography based on numerical methods.
Who has developed the Atlas?
The Atlas started in 2000 as an initiative of the Unit
of Botany in the BABVE Department (Animal Biology, Vegetal Biology
and Ecology) as well as the Department of Geography, both in the
Autonomous University of Barcelona.
A research was developed in order to deepen into issues
relating to spatial interpolation of discrete climatological data
spread over a territory (meteorological stations). First of all,
this research was directed to climatological and vegetation data
to obtain suitability maps of plant species, but later we focused
our research in climatological aspects.
How has it been made?
The Atlas has been made through a combination of different
techniques such us statistical analysis, spatial interpolation and
Geographic information Systems.
As starting data we used 3528 meteorological stations
for thermometric measures and 7293 stations for rain gauge measures.
These stations were filtered in order to achieve a compromise between
length of the series (temporal stability) and density (spatial coverage).
Finally, following the statistical tests, we decided to work with
series of 15 or more years for temperature data and 20 or more years
for precipitation. Once this filtering process was finished, there
remained 286 thermometric meteorological stations, 1217 rain gauge
stations and 782
In addition to these stations, it is important to state
that we also used the Digital Elevation Model (DEM) of the Iberian
Peninsula with a spatial resolution of 200m.
DEM and derived geographical variables (altitude,
latitude, continentality, solar radiation and terrain curvature)
have been introduced in statistical analysis to predict mean climatological
values of temperature and precipitation.
This information has been completely implemented in
a GIS (MiraMon)
which enabled us to:
- Objective interpolation by considering geographic
- Repeatability (new data, new models, etc)
- Data accessibility: through WMS Server based in OGC standards
is possible to perform basic queries as well as download data for
more complex analysis.
- High-quality print maps can be obtained
- Integration to other systems
- Process steps:
- filtering meteorological stations
- modeling geographical variables
- database enrichment
- map algebra
- statistical tests to assess map quality
In the methodology section of the booklet, there are
reflected the technical aspects considered in the making of the
Atlas. From here you can download the PDF
For further information over scientific matters and
related techniques for the making of this Atlas, you can check Methodology
section in this web or check References.
What are our future goals?
Our aim is to improve quality of present cartography
and generate new derived maps (evapotranspiration for example).
In order to get better maps we can follow two strategies:
1) Increase the quality of the current data. Basically, this may
be achieved by increasing length series of the stations and also
by increasing the number of meteorological stations, which is completely
an institutional competence.
2) Improve the used methodology by testing new
spatial interpolation techniques or incorporating new geographical
Sergi Gumà, Núria Julià and Joan
Masó for technical support.
Guadalupe Barea for the web design.
Pep Serra and Pedro Pinto for english and portuguese
Roberto Vallejo (Inventario Forestal Nacional) for
the supplied data.
Javier Martín Vide (Departament de Geografia
Física i Anàlisi Geogràfica), Ángel
M. Felicísimo (Departamento de Expresión Gráfica,UNEX)
for althruistic academic support.