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** Input and output are easily visualized. ** Input and output are easily visualized.
[[Image:graph6.jpg|thumb|'''Modelling type 2. Grid example for Afghanistan (0.5 degree distance)'''|400px|right]] [[Image:graph6.jpg|thumb|'''Modelling type 2. Grid example for Afghanistan (0.5 degree distance)'''|400px|right]]
-: '''Worldwide grid data for free'''. Meteorological data with a worldwide extend are offered by the MARS FOOD (European Union) based on outputs of the ECMWF (European Centre for Medium-Range Weather Forecast) atmospherical model. A time series for more than 40 years is now available thanks to the ERA40 reanalysis project. The data can be downloaded in ASCII Grid format. A tool is available to convert the grids into IDA images. This tool (JRC2IDA) can be downloaded here.+: '''Worldwide grid data for free'''. Meteorological data with a worldwide extend are offered by the MARS FOOD (European Union) based on outputs of the ECMWF (European Centre for Medium-Range Weather Forecast) atmospherical model. A time series for more than 40 years is now available thanks to the ERA40 reanalysis project. The data can be downloaded in ASCII Grid format. A tool is available to convert the grids into IDA images. This tool (JRC2IDA) can be downloaded here: http://www.hoefsloot.com/Downloads/jrc2ida_install.exe.
: The following parameters are available: : The following parameters are available:

Revision as of 09:19, 16 June 2006

Two basic modelling options

A crop monitoring program has to be based on data from different locations inside the country of region that needs to be monitored.

Technically these monitoring locations are points. Points can be pinpointed at the earth’s surface with coordinates. The coordinate system that is used in crop forecasting is called a geographic coordinate system whereby the coordinates are expressed in Longitude - Latitude pairs.

Example : the geographic coordinates of Pnom Penn (Cambodia) are:

  • Longitude: 104.917445
  • Latitude : 11.558831

Normally expressed as 104.917445, 11.558831 (longitude always first). Read more: Geographic Coordinates

Depending on the circumstances, the crop forecasting network can be based on:

Modelling type 1. Monitoring stations in Africa
Enlarge
Modelling type 1. Monitoring stations in Africa
  • An irregularly spaced network based on real-world stations (Modelling type 1). As an example below part of the rainfall recording stations in Africa. This type of network has a preference over the second type whenever station data (to run the water balance) are available. The main advantages of this type of monitoring network are:
    • Input and output of the water balance model can be checked against the real situation in the field.
    • Station weather data are more accurate than gridded data in the vicinity of the stations themselves.
    • Usually requires less computer power due to lower number of monitoring points.
Although the water balance is calculated on a irregularly spaced network, output data can be transformed into grids or images using interpolation techniques. This enables the estimation of water balance parameters for all corners of the monitoring area.
  • A regularly spaced grid (Modelling type 2). In this case, grid points do not coincide with meteorological stations. This type of monitoring network is particularly useful if ground data are scarce or inaccurate and weather data with sufficient accuracy are available on a grid or image basis. The advantages of this type of modeling approach are:
    • Complete coverage of the country/region is possible.
    • Data are relatively easy to get.
    • Input and output are easily visualized.
Modelling type 2. Grid example for Afghanistan (0.5 degree distance)
Enlarge
Modelling type 2. Grid example for Afghanistan (0.5 degree distance)
Worldwide grid data for free. Meteorological data with a worldwide extend are offered by the MARS FOOD (European Union) based on outputs of the ECMWF (European Centre for Medium-Range Weather Forecast) atmospherical model. A time series for more than 40 years is now available thanks to the ERA40 reanalysis project. The data can be downloaded in ASCII Grid format. A tool is available to convert the grids into IDA images. This tool (JRC2IDA) can be downloaded here: http://www.hoefsloot.com/Downloads/jrc2ida_install.exe.
The following parameters are available:
    • average temperature
    • maximum temperature
    • minimum temperature
    • precipitation sum
    • evapo-transpiration sum (ES0, bare soil)
    • evapo-transpiration sum (E0, over water)
    • evapo-transpiration sum (ET0, Penman-Monteith)
    • global radiation sum

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