Thematic description of CGMS level 1
Reasons for Interpolation
To simulate crop growth the CGMS needs to interpolate daily meteorological station data to a regular climatic grid. In theory it is possible to apply the CGMS at station level. However, the problem is that meteorological stations are very far apart and their geographical distribution is irregular. Furthermore, the CGMS not only needs daily meteorological data but also data on soils, crops and land use which are spatially variable too. In order to combine these data layers and simulate their interaction as well as their effects on crop growth it is necessary to know meteorological conditions for any point in between the stations. After interpolation of meteorological data, a representative spatial schematisation of meteorology, soils, crops and land use can be derived.
An additional reason for interpolation is the function of the CGMS as a monitoring and forecasting system in which current results of certain regions are compared to a reference year. Comparison of current weather with the long term average on a station basis is not recommended because the continuity of time series cannot be guaranteed at station level. Stations are sometimes moved to other locations, or they are replaced by others, or new stations do not have historic data. Further, station data may be incomplete because of interruptions in observations or instrument failures. The spatial interpolation procedure of the CGMS secures continuous and complete time series of meteorological data on a fixed geographical grid covering the complete land surface.
