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; 27-29 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

UsersDG-Agri (Outlook group); EUROSTAT; DG-EnlargFAO; National Competent Authorities Other (Trade Organisations, Universities..)

5

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

DBDBGRIDGRID

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 1906 on the EU-15 countries (34%)countries (34%)

Data stored:

• Data since 1 January 1975 Data since 1 January 1975

• Reference period (long Reference period (long term): 1975 – 2002term): 1975 – 2002

• 10 agrometeorological 10 agrometeorological parametersparameters

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around 4000

stations

quality checked

1933 - 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. RAINFALL6. 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

11

12

GIS-OVER-

LAY

NUTS A

SMU 2

SMU 1

NUTS B

EMU 1

EMU 2

EMU 3EMU 4

EMU1 = GRID 1, SMU 2, NUTS B EMU2 = GRID 1, SMU 1, NUTS B EMU3 = GRID 1, SMU 1, NUTS A EMU4 = GRID 1, SMU 2, NUTS A

GRID 1

homogeneous

simulation units in

regard to weather and

soil

NUTS

(administrative)

regions for

aggregation

Spatial schematisation (crop monitoring)

13

14

15

DECEMBER 2002

JANUARY 2003

FEBRUARY 2003

MARCH 2003

APRIL 2003

-30

-20

-10

0

10

20

30

40

1-Jan 1-Mar 1-May

°C T max T min

POLAND - Western

0

5

10

15

20

25

30

35

1-Jan 1-Feb 1-Mar 1-Apr 1-May

mmsnowrain

Frost kill risk

Meteo monitoring

16

Agrometeo monitoring

17

Map of meteo events Vs agricultural activities

18

Maps of meteo extreme events

19

http://www.marsop.info

20

Esternal usersLIST OF PROJETS linked TO CGMS1. B-CGMS (http://b-cgms.cragx.fgov.be/)

2. Eurostat (http://www.aris.sai.jrc.it/cgi-bin/eurostat.pl)

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. DEMETER11. 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 (http://natural-hazards.jrc.it/fires/)

15. European Phenology Networks

21

• projection LAMBERT_AZIMUTHunits METERSspheroid SPHEREparameters6378388

• Centre of projection EU129 0 0.0 48 0 0.0

0 0

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 + Δalt*Walt + ΔdCstcorr + ClbInc expressed in km

where:

dist : distance between the weather station and the grid centre. [km]

Δalt : absolute difference in altitude. [m]

Walt : weighting factor for Δalt (= 0.5).

dCstcorr : absolute difference in corrected distance to coast [km]

ClbInc : climate barrier increment. (1000 km or 0)

Interpolation procedure: scoring procedure