WEBINAR – What are the time scales of climate services for agriculture?

WEBINAR – What are the time scales of climate services for agriculture?


According to the WMO 2019 global analysis, many countries highlight agriculture and food security as critical priority sectors for climate change adaptation, with weather and climate services being the foundation element for planning and decision making. However, what is meant by ‘climate services’ is not always clear to users in the agricultural and other sectors. These users often strive for understanding which type of information these services provide, at which time scales, and how it can specifically support the decisions they need to make in the field. This understanding is not trivial, since it is actually what allows the uptake of climate services and makes their use sustainable in the long term. If climate services are available but are not used to support crop management and take any other informed decisions, they are of no value.

In this webinar, MED-GOLD researchers and sector users will explain the difference between the time scales of climate services for agriculture, including weather forecasts, seasonal predictions, decadal predictions and climate change projections. Participants to the webinar will have the opportunity to discover how predictions of climate variables (e.g. temperature, precipitation, etc.) and agro-climatic indices (e.g. total spring rain, etc.) are made for different crops. Speakers will also explain how to interpret probabilistic predictions, their advantages and limitations and how this knowledge translates into concrete actionable advice for the management of crops and food systems, including grapes/wine, olive/olive oil, durum wheat/pasta and coffee.



Questions from the audience and answers provided by speakers after the webinar can be found in the MED-GOLD Forum. You will be able to participate in the discussion and ask additional questions to our speakers.

More information

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2020-05-25T18:18:20+00:00April 24th, 2020|The MED-GOLD project|
This project has received funding from the European Union's Horizon 2020 Research and Innovation programme under Grant agreement No. 776467