1 … Institute for the Protection and Security of the Citizen The grid reference system used for CGMS (MARS-STAT Action) G.Genovese 1st European Workshop on Reference Grids Ispra; October, 2003

2 Rationale of the project The MARS (Monitoring Agriculture with Remote Sensing) project started in 1989 an Agro-meteorological system at European Level based on –Collection of Meteorological data –Collection of Remote Sensing Data –Transformations and Modelling into crop parameters

3 Objective and Users Objective –Provide harmonised European views on the cropping season –Provide quantitative crop yield forecasts Study influence of weather on crop growth Monitoring crop condition Input for the quantitative yield prediction All procedures and data storage are part of the Crop Growth Monitoring System (CGMS)

4 Users DG-Agri (Outlook group); EUROSTAT; DG-Enlarg FAO; National Competent Authorities Other (Trade Organisations, Universities..)

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6 Motivation: spatial schematisation (soil, climate, land use); secures continuous/complete time series Interpolate daily meteorological station data towards centres of a regular climatic grid (50 by 50 kilometres, Lambert-Azimuthal projection, 5625 cells) Simple approach, easy to automate while accuracy is sufficient Spatial interpolation (weather monitoring)

7 DB GRID DB GRID: description Daily data at grid level 5625 cells (50 x 50 km)5625 cells (50 x 50 km) 1906 on the EU-15 countries (34%)1906 on the EU-15 countries (34%) Data stored: Data since 1 January 1975Data since 1 January 1975 Reference period (long term): 1975 – 2002Reference period (long term): 1975 – agrometeorological parameters10 agrometeorological parameters

8  around 4000 stations  quality checked  current day  best spatial and temporal coverage in western Europe

9 Three steps to interpolate to grid cell: –temporal coverage of stations –selection of stations based on distance, similarity in altitude and distance to the coast, climatic barriers, –simple average over one up to four stations, corrected for altitude difference in case of temperature and vapour pressure; rainfall only most similar station Spatial interpolation (weather monitoring)

10 DB GRID: 1.MAXIMUM_TEMPERATURE 2.MINIMUM_TEMPERATURE 3.VAPOUR_PRESSURE 4.WINDSPEED 5.RAINFALL 6.E0 (evaporation from a water surface – Penman method) 7.ES0 (evaporation from a wet bare soil- Penman method) 8.ET0 (evapotranspiration - Penman method) 9.CALCULATED_RADIATION (Ångström, Supit, Hargreaves ) 10.SNOW_DEPTH

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12  homogeneous simulation units in regard to weather and soil  NUTS (administrative) regions for aggregation Spatial schematisation (crop monitoring)

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15 DECEMBER 2002 JANUARY 2003 FEBRUARY 2003 MARCH 2003 APRIL 2003 Frost kill risk Meteo monitoring

16 Agrometeo monitoring

17 Map of meteo events Vs agricultural activities

18 Maps of meteo extreme events

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20 Esternal users LIST OF PROJETS linked TO CGMS 1.B-CGMS ( 2.Eurostat ( 3.Spanish – CGMS (Universidad Politécnica de Madrid - UPM) 4.Modeling Surface Radiation (Physical and Chemical Exposure Unit -(IHCP) ) 5.Registration procedure of pesticide in Italy (International Center for Pesticides and Health Risk Prevention) ) 6.Designing Sustainable plant-protein production systems (Crop and Weed Ecology Group - Department of Plant Sciences - Wageningen University) ) 7.Evaluation of growth and productivity model integrated with remote sensing techniques (Università degli Studi di Milano-Department of Crop Science) ) 8.Crop yield forecasting in Kazakhstan using CGMS and WOFOST (ALTERRA) ) 9.Monitoring weather and crop in Mongolia using CGMS and WOFOST (ALTERRA) 10.DEMETER 11.ENSAMBLES (ECMWF) ) 12.TERRACE project (Cranfield University at Sisloe,Bedfordshire – UK) ) 13.Temperature Correction of Energy Consumption (EI – LMU, DG-EUROSTAT unit Energy Statistics) 14.Forest Fire Information System ( 15.European Phenology Networks

21 projection LAMBERT_AZIMUTH units METERS spheroid SPHERE parameters Centre of projection EU GRID projection and DATUM

22 Achievements 35 countries covered 11 crops monitored 28 years of meteo and agrometeo data 21 years of low resolution satellite information 20 crop’s indicators

23 Score = dist + Δ alt*Walt + Δ dCstcorr + ClbIncexpressed in km where: dist : distance between the weather station and the grid centre. [km] Δ alt : absolute difference in altitude.[m] Walt : weighting factor for Δ alt (= 0.5). dCstcorr : absolute difference in corrected distance to coast [km] ClbInc : climate barrier increment. (1000 km or 0) Interpolation procedure: scoring procedure