|Convener: Keith Lambkin | Co-Conveners: Emily Gleeson , Josef Eitzinger|
The population of the world doubled in the 40 year period between 1959 – 1999. This meant that global food production also needed to double, and this trend continues. To increase food production one could farm more land, or farm the same land more efficiently.
Weather conditions are perhaps the greatest uncertainty within the agricultural sector. Hail, disease & drought can all have devastating effects on crops. However meteorological related risks can be reduced through the better timing of harvests, application of pesticides or irrigation systems. A clear picture of the current and future weather conditions, along with appropriate farm actions, can increase the likelihood of improved yields.
Climate change is also influencing crop suitability in certain regions. Where livestock are been negatively affected by migrating diseases and available food. To complicate matters the agricultural sector is also trying to become more sustainable and environmental friendly in an attempt to meet greenhouse gas emission targets.
What is clear is that a greater integration of reliable meteorological and climatological information, in agriculture decision support systems, will be essential to maintain future food demand.
The aim of this session is to highlight current applications and research that integrate meteorological and climatological information in agriculture.
We invite presentations related to all agrometeorology topics including:
• Agrometerological monitoring and forecasting methods
• Providing agrometeorological information to support decision making in agriculture
• Agrometeorological modelling (e.g. modelling agrometeorological related diseases, frost protection warning methods, drought indices etc.)
• Interactions/feedback of farmers and other end users of agrometeorological products and services
• Weather and climatic extremes and their impact on agriculture
• Methods of measurements and observations (e.g. ground based equipment, remote sensing products, citizen science, Big Data and SmartAg etc. )
• Communicating uncertainty and graphical representation for decision makers (e.g. GIS, timelapse, geolocation, ensembles etc.)
• Climate change impacts on agriculture observed and/or predicted
• Agrometeorological networks
• Agrometeorological training and education