Home > Introduction

• Introduction
• Thematic description of CGMS level 1
• Thematic description of CGMS level 2
• Additional functionality in the CGMS software for yield forecast
• Overview of different CGMS versions
• CGMS 9.2 database
• CGMS User Interface
• References
• Annex A Using CGMS in batch mode
• Contacts
• Legal Notice

Introduction

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The following report gives detailed information on the CGMS version 9.2 which is used in an operational context for the MARS Crop Yield Forecasting System. This report is the follow-up of the CGMS version 8.0 User manual and technical documentation (Savin et. al, 2004, EUR 21379 EN) and follows the same structure.

Historically, the MARS Crop Yield Forecasting System (MCYFS) has been developed in Europe around the Crop Growth Monitoring System (CGMS). The CGMS is the combination of the WOFOST crop growth model, a relational database and a statistical yield prediction module.

Nowadays the MARS Crop Yield Forecasting System (MCYFS) is fully operational for the European countries. The decisions n0 1445/2000/EC and 2066/2003/EC on the application of area frame survey and remote sensing techniques to the agricultural statistics for 1999 to 2007 of the European Parliament moved the MCYFS into the operational phase. The main customers of the system are DG-AGRI and EUROSTAT. Part of the operational service to run MCYFS is outsourced through the MARSOP project (MARS-OPerational), which started in the middle of 2000. The AGRI4CAST action (Crop forecasts/Estimates and Climate Change impact on agriculture) of the AGRICULTURE unit of the Joint Research Centre supervises this project and concentrates on yield forecast analysis and synthesis of all information in a bulletin.

In the context of the Global Monitoring for Environment and Security initiative (GMES), JRC formed in 2001 the MARS-FOOD action (Crop monitoring for food security). This action aims at supporting the European Union Food Security and Food Aid Policy through an improved assessment of the crop status in regions/countries stricken by food shortage problems. Accurate and timely information on crop status is needed to properly calibrate and direct European Food Aid, in order to prevent food shortages and consequent human suffering, and to avoid possible market disruptions due to unnecessary food aid distributions. DG AIDCO and RELEX, are the main European Commission customers for this work.

For agro-meteorological monitoring in Russia, Central Asia and the Mediterranean Basin CGMS was extended with different functions as described in the CGMS version 8.0. User Manual and Technical Documentation. This extension was made possible by the contract N 20268-2002-12-FIED ISP NL. As a main result CGMS version 8.0 was developed.

During the years 2004-2007 the development of CGMS continued in the framework of the contracts MARSOP-2 (contractno 21508-2003-12 F1SC ISP NL) and ASEMARS (contractno 22550-2004-12 F1SC ISP NL) leading to a new version CGMS 9.2. The underlying document describes this latest version. New functionality was added or existing functions were changed:

- Weather interpolation for the current year is changed using long term average data from reliable stations in case data for the current day is missing
- The possibility to simulate frost damage (or winterkill) has been implemented
- Several bugs have been solved with regard to the LINGRA model. The LINGRA model is now ready to be used
- CGMS is adapted so that it can be used by the CALPLAT tool:

• Adjustment of CROP_YIELD (extra column crop, date in stead of decade/year, extra output columns)
• Adjustment of GRID_YIELD and NUTS_YIELD (date in stead of decade/year, extra output columns)
• Potential and water limited can be run separately
• Introduced CALPLAT mode (store data at daily level and write additional output)

In the near future it is expected that part of the current functionality of CGMS, the spatial aggregation and the data preparation for yield forecast, will be replaced by another tool. Then the CGMS software will be the tool responsible for weather processing and interpolation and crop growth simulation. Next, the data engine of the CGMS viewer, which has been built to generate on-the-fly maps of CGMS level 1 and 2 for the web site, will be responsible for retrieving and aggregating CGMS weather and crop indicators in a fast way, and additionally creating compound meteorological indicators like rainfall around a crop development stage. The tool will read region, crop and decade specific settings from a database for instance the group of indicators that have to be aggregated to regional level so that they can be used in the third tool which is responsible for the regional crop yield forecast: CGMS Statistical Tool (CST). On top of these tools a manage console will exists responsible for running the tools in an operational production line. In addition there is the CGMS viewer (using the same data engine to generate data) to view the data at EMU or grid level.

We hope this information will be useful for the CGMS users, as well as for the specialists in the field of crop growth simulation, agronomists, agro-meteorologists and will lead to fruitful discussion on further CGMS development, and crop growth monitoring methods improvement.