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.

Map server

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 Icon , 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 coordinate.

Displaying

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.

Downloads

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).

Units

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 weights.

Access to Web Map Service and Web Coverage Service

You can access to those services through this link (https://www.opengis.grumets.cat/cgi-bin/iberia/MiraMon5_0.cgi). Both 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.

Help

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 Server.


Metadata

Every downloaded map is related to a file that contains metadata following ISO 19139 recommendations.

Next, metadata 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.

Geographic predictors

- Improve geographical variables modeling (such as continentality, solar radiation), as well as introducing new variables (orography, information from remote sensors, etc)

Meteorological stations

- 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 local effects.

- Location of the stations: problems of extrapolation and homogeneity:

Extrapolation

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., 1952).

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 temperature.