Agri4Cast Data

External Data Spec Published 22 Jun 2016
information.png Provider:
Joint Research Centre (JRC)
information.png Dataset URL:
http://agri4cast.jrc.ec.europa.eu/DataPortal/Index.aspx?o=d

Related content

Indicators using this data

Produced figures

Trend in crop water deficit of grain maize during the growing season Trend in crop water deficit of grain maize during the growing season Annual rate of change of the crop water deficit of grain maize during the growing season for the period 1985-2014 in Europe. The crop water deficit is the difference between the crop-specific water requirement (in this case grain maize) and available water through precipitation. The simulation is based on the JRC-MARS gridded meteorological data at 25 km resolution. Red colours show an increase of the gap between crop water requirement and the available water, blue colours indicate a reduction of the deficit. Areas where the seasonal crop water requirement exceeds regularly (i.e. in more than 90 % of the years) the available water (through precipitation) have been marked by hatches. Areas without hatches experience both deficit and surplus or only a surplus of water in their crop water balance. In this case, red colours refer to a reduced surplus, while blue colours indicate an increasing surplus of available water.
Projected annual rate of change of the crop water deficit of grain maize during the growing season in Europe for the period 2015-2045 for two climate scenarios. Projected annual rate of change of the crop water deficit of grain maize during the growing season in Europe for the period 2015-2045 for two climate scenarios. Projected annual rate of change of the crop water deficit of grain maize during the growing season in Europe for the period 2015-2045 for two climate scenarios. The crop water deficit is the difference between the crop-specific water requirement (in this case grain maize) and the water available through precipitation. The climate forcing of the two simulations is based on the two global climate models HadGEM2 and MIROC, taken from CMIP5 and bias-corrected by the ISI-MIP project (Warszawski et al., 2014). Crop model simulations have been done with the crop model WOFOST at 25 km resolution. Red colours show an increase of the gap between crop water requirement and water availability, blue colours indicate a reduction of the deficit. Areas where the seasonal crop water requirement exceeds regularly (i.e. in more than 90 % of the years) the water available through precipitation have been marked by hatches. Areas without hatches experience both deficit and surplus or only a surplus of water. In this case, red colours refer to a reduced surplus, while blue colours indicate an increasing surplus of water.
Trend in flowering date of winter wheat Trend in flowering date of winter wheat This figure shows the rate of change of the flowering date for winter wheat. The annual rate of change of the flowering date represents the trend coefficient for long-term changes in the occurrence of flowering of winter wheat in Europe. For example, a value -0.6 indicates that in last 30 years the winter wheat flowering date has been anticipated on average by 0.6 days per year (6 days in 10 years). The flowering date is derived from crop growth models simulating crop development of winter wheat as a function of the temperature sum. The simulation is based on the JRC-MARS gridded meteorological data at 25 km resolution.
Trend in the number of frost-free days Trend in the number of frost-free days The annual rate of change of frost-free days represents the trend coefficient for long-term changes in the annual number of days with a minimum daily temperature above 0 °C. For example, a value of 1 indicates that the number of frost-free days has increased on average by 1 day per year in last 30 years (period 1985-2014). The analysis is based on the JRC-MARS gridded meteorological data at 25 km resolution.
Estimated soil erosion by wind on European arable land Estimated soil erosion by wind on European arable land Soil loss rates by wind (tonnes per hectare per year) on arable land, estimated by the GIS-RWEQ model for 1.17 million cells (of ca. 1 km spatial resolution, into which the arable land of the 28 European Union Member States was subdivided) (Borrelli et al., 2016).

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For references, please go to https://www.eea.europa.eu/data-and-maps/data/external/jrc-mars-gridded-agro-meteorological or scan the QR code.

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