2023

High spatial resolution agro-climatic projections to 2023

Weather Measures

Country – France

Objectives of agro-climatic projections

Agriculture, which is highly dependent on climatic conditions, is facing unprecedented upheavals linked to climate change. Anticipating these impacts and providing tools to guide agronomic decisions is becoming a strategic priority. The aim of this project, carried out for Weenat, is to produce high spatial resolution agro-climatic indicators for the French territory, to feed an operational tool dedicated to supporting agricultural practices in the context of climate change.

Based on a rigorous methodology, this study combines the analysis of historical meteorological data, future projections and the generation of specific indicators. It aims to meet the needs of players in the agricultural sector to ensure the resilience of their activities.

Phase 1: Creation of a historical weather database

The first step in this agro-climatic projection is to create a high spatial resolution historical weather database for France. This database will incorporate key variables such as temperature, precipitation, humidity and wind, providing an accurate picture of past climatic conditions. These data serve as a reference for assessing future climate variations and identifying trends likely to influence agricultural activities.

Phase 2: Future weather forecasts

The second phase focuses on the production of a set of meteorological variables projected over a “typical year” and three future time horizons. These horizons, generally located in the short, medium and long term, make it possible to anticipate the impacts of RCP (Representative Concentration Pathways) climate scenarios on the different regions of France.

Projections include data such as the frequency and intensity of heat waves, periods of drought and frost, and rainfall variability, to identify the main challenges facing crops.

Phase 3: Production of agro-climatic indicators

Finally, the last phase consists of producing specific agro-climatic indicators, such as drought indices and critical frost periods. These indicators are crucial for farmers, as they will enable them to improve their crop cycle planning systems, optimize resources and minimize losses linked to extreme weather conditions.

A proactive approach to tomorrow's agriculture

Faced with the growing impacts of climate change, agro-climatic projections are an essential lever for anticipating future challenges and developing robust adaptation strategies. This project, conducted as part of our climate change data service, offers innovative solutions to support the agricultural sector in its transition to sustainable, resilient management. By combining a rigorous analysis of historical data, precise future climate projections and adapted agro-climatic indicators, this study provides a solid basis for ensuring the sustainability of agricultural activities, even in an uncertain climate context.

Applications and benefits of agro-climatic indicators

The results of this project are intended to feed an operational agronomic support tool, providing decision-makers and farmers with valuable information to help them adapt their practices. This tool will enable :

  • Improve crop management, taking into account the specific climatic constraints of each region.
  • Strengthen the resilience of farms in the face of climatic hazards by anticipating risks.
  • Optimize the use of natural resources, such as water and agricultural inputs, for more sustainable agriculture.

These indicators will also help guide public policies on agriculture and regional planning, by identifying the areas most vulnerable to climate change.

Understanding agro-climatic projections

Agro-climatic projections involve analyzing and modeling weather and climate data to produce indicators tailored to specific agricultural situations. These indicators are designed to meet the challenges posed by phenomena such as rainfall variability, rising temperatures, frost periods and intensifying drought.

Thanks to their high spatial resolution (1 km), the results of this study offer unrivalled precision, enabling direct application on a local scale. This level of detail is essential for guiding agronomic practices and developing targeted adaptation strategies for each region.