Climate variability challenges agricultural production, particularly in developing countries. Agricultural resilience requires understanding the impacts of climate variability AND the dynamics of farmer adaptation. Seasonal climate forecasting allows models to predict yields and to explore adaptation strategies, but the challenge lies in translating low-to-moderate skill climate information into useful information for farmers. How will farmers use that information, and how will agro-ecological and socio-economic contexts affect decisions under climate variability? Can in-situ data and remote sensing (UAV, satellite), improve the quality of information on agro-ecological impacts? How do agent-based models and other tools combine with these bio-physical tools to understand the dynamics of farmer adaptation? We seek conceptual, evidence-based research, and case studies on: 1) linking multi-scale climate and RS/environmental information to improve decision support in agriculture; 2) characterizing climate variability and its agro-ecological impacts, 3) how farmer adaptation varies across systems; and 4) attributing farmer decisions to climate variability