The original application of PESERA was at 1km resolution across Europe. As such PESERA was designed to use data that is more readily available at the continental scale. A number of subsequent applications have considered national or sub-national areas with others applications looking at the catchment scale. In order to apply PESERA the main effort is preparing input data, primarily converting local climatological time series data to monthly statistics and interpolating this point data to produce a raster surface. As well as the climatology other primary data are required, generated from: land-use; soil texture and topography. Specific requirements for each input layer and running the model are detailed in the manual. The dynamic tutorial aims to act as a catalogue of methods used in the preparation of input data for the PESERA_GRID model. This will be achieved through a series of worked examples. Spreadsheets and tables used to calculated climate statistics and convert land use will be uploaded as a resource template which allows others to calculated the required detail from times series data. It is envisaged that the catalogue will grow through time when dealing with new data storage formats from climate stations.
When generating raster surfaces the most stringent requirement is that all data layers have the same projection, coordinates and extents (the number of rows and columns in each raster are the same). Raster surface data are converted to ASCII files prior to running the PESERA model. ASCII files should contain standard header information (ncols, nrows, xllcorner, yllcorner, cellsize, nodata_value).
There are no formal requirements for scale, level of detail or number of climatological station the following are suggested for guidance. However, we do not recommend the use of PESERA with a resolution finer than a 100m (100m x 100m raster cell). (100m, 250m and 1000m are typical of PESERA applications.)
Level of detail:
(land-use, Soil units, topography)
Number of climatological stations:
Site Specific: number of station should describe observed climate gradients.
Format: ASCII files converted from raster/GRID (raster/GRID data is converted to ASCII before executing the model, raster/GRID is used to generate the data and visualise output)
Land use: (reclassified to PESERA land use classes: crop planting dates & cropping cycle details are required in arable areas)
Soil: (soil TEXTURE; this is the minimum required)
Topography: SRTM90 (90m DEM). There is a google earth interface with srtm at: www.kcl.ac.uk/schools/sspp/geography/research/emm/geodata/topoview.html
1) define projection, coordinates, and extent of input data.
2) define boundary of study site
3) extract SRTM data or other source of DEM at appropriate scale
4) create raster/GRID from polygons of land-use and soil texture
5) climatological analysis; the number of climatological stations considered should reflect both the number available (record > 30years) and the climate gradient of the study area. (How many climate stations are available with rainfall records > 30years , do you have a long term average annual rainfall map of the study site)