Mapping surface solar radiation over Poland and the Baltic countries

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This case study looks at how new solar climate atlases for Poland and the Baltic Republics were produced using CM SAF data.

Date & Time
1 January 1991–31 December 2014
Satellites
Meteosat-4, 5, 6, 7, 8, 9 and 10
Instruments
MVIRI, SEVIRI
Channels/Products
CM SAF SARAH 1.0/-X monthly mean SIS, SID and DNI

By Jakub Walawender (IMGW-PIB), Zanita Avotniece (LVĢMC), Justinas Kilpys (LHMT), Kairi Vint (ESTEA), Jörg Trentmann (DWD), and Mark Higgins (EUMETSAT).

In the process of developing a climate atlas a number of choices about how to display the data have to be made. This will depend on the purpose the atlas serves for and who will be using it.

Two solar radiation atlases were created within the Baltic Solar Radiation Initiative. Both atlases consist of 2,646 maps and present selected climate characteristics of solar radiation over Poland and the Baltic countries for the period 1991–2014, calculated on the basis of CM SAF SARAH climate data records:

  • Surface incoming shortwave radiation (SIS, Monthly mean),
  • Surface incoming direct radiation (SID, Monthly mean),
  • Surface direct normalised radiation (DNI, Monthly mean).

Two different mapping approaches to develop atlases are shown. The underlying features are identical.

Figure 1 is an example map from the Poland atlas, Figure 2 is an example map from the Baltic atlas.

A dedicated climate mapping tool was used to create maps for the Baltic Republics. For Poland, CM SAF data were integrated with additional geographical datasets in the GIS environment and adjusted to one of the standard mapping layouts of the Polish Weather Service.

The same climate characteristics and coloured legends were used to so both atlases could be compared with each other.

In both cases scripts enabling automatic production of maps were used but the processing environment was different. More technical details on the mapping methods and tools with a short comparative analysis showing some advantages and disadvantages of both quite different mapping approaches are presented below.

Baltic solar radiation atlas can be accessed here:

http://www.meteo.lt/lt/saules-spinduliuotes-atlasas (Lithuanian version)
http://www2.meteo.lv/radiacija/curl_rad.php (Latvian version)
http://www.ilmateenistus.ee/kliima/paikesekiirguse-atlas (Estonian version)
http://www.ilmateenistus.ee/kliima/solar-atlas/?lang=en (English version)

Solar radiation atlas for Poland can be accessed here:

http://klimat.pogodynka.pl/pl/solar-atlas (Polish version)
http://klimat.pogodynka.pl/en/solar-atlas (English version)

Figure 1: Example map of the Poland solar climate atlas
Figure 2: Example map of the Baltic solar atlas

  Baltic Solar Radiation Atlas Poland Solar Radiation Atlas
Mapping tool R scripting ArcGIS + Python (ArcPy) scripting
CM SAF data Coverage Lituania, Latvia, Estonia and the surrounding areas lmmited by lat/long coordinates: 53.5°–60°N and 18°–29°E CM SAF data records clipped to the administrative border of Poland
Coordinate system World Geodetic System 1984 (WGS84) National coordinate system for small scale maps: PUWG-92 Gauss-Krüger projection at PL-ETRF89 spatial reference frame
Additional layers Country boundary Neighbouring countries, Voivodeship borders, 29 major cities, generalized river network (tapered polygons), the largest lakes, mountain ranges enhanced by pseudo-3D effect (shaded relief in the background + 30% transparency of the CM SAF layer)
Characteristic features Applies global mapping standard

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Information on solar radiation levels for the whole mapping domain
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Gives broader context of solar radiation distribution in the region
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Covers territories of neighbouring countries

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Faster map production process
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Country boundary layer helps to identify national territories and the Baltic Sea.
Applies one of the standard layouts for climate mapping used at IMGW-PIB
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Information on solar radiation levels limited to the area of Poland
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Keeps the focus on the main area of interests (territory of Poland)
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Does not interfere in the areas under competence of NMSs of neighbouring countries
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Slower map production process
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Additional layers and graphical effects help to interpret spatial distribution of the solar radiation
 
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