Objective Wildfires have a great impact on the environment and can pose a threat to property and human lives and health. The occurrence of fire in natural vegetation is dependent on human activities and climate variability. In tropical areas such as the Amazon basin and Indonesia, wildfires are greatly affected by inter-annual fluctuations in tropical Sea Surface Temperatures (SSTs). During the El Niño events of 1997-1998 and 2015-2016, uncontrolled wildfires caused record impacts on health, transportation and the economy. The European countries of the Mediterranean basin are frequently plagued by drought episodes (e.g. during the summer of 2016), causing dangerous wildfires which result in deaths, health problems and economic losses.Seasonal climate prediction is a field which typically forecasts seasonal average precipitation and temperature anomalies with a few months lead time. The main sources of predictability are SSTs, soil moisture, snow cover and teleconnections with the tropics. Seasonal climate predictions are performed operationally in Europe and globally, and are used in fields such as agriculture, health, water management and energy. While some effort has been put into short-term forecasts of fire danger in Europe, there is currently no operational seasonal wildfire forecasting system for Europe and only a few for other continents. The goal of this project is to develop and assess seasonal fire prediction capability through a variety of complementary and innovative methods, with a focus on Europe, the Amazonian basin and Indonesia. Fields of science agricultural sciencesagriculture, forestry, and fisheriesagriculturenatural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changesel niñoengineering and technologyenvironmental engineeringenergy and fuelsengineering and technologyenvironmental engineeringnatural resources managementwater managementagricultural sciencesagricultural biotechnologybiomass Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Topic(s) MSCA-IF-2016 - Individual Fellowships Call for proposal H2020-MSCA-IF-2016 See other projects for this call Funding Scheme MSCA-IF-EF-ST - Standard EF Coordinator BARCELONA SUPERCOMPUTING CENTER CENTRO NACIONAL DE SUPERCOMPUTACION Net EU contribution € 170 121,60 Address CALLE JORDI GIRONA 31 08034 Barcelona Spain See on map Region Este Cataluña Barcelona Activity type Research Organisations Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 170 121,60