Thus far, the decisions made by various stakeholders engaged in disaster risk reduction (DRR) and climate change adaptation (CCA) have largely been based on the quantifiable and economic impacts of climatic events. While this approach has helped to make certain progress in DRR and CCA, the emerging body of evidence, recognizing the losses and damages after adaptation and mitigation, suggest the greater need to understand the non-economic losses and damages associated with climate change and to incorporate this understanding into decision making processes for climate risk reduction. Keeping this in view, the research team intends to study the non-economic losses and damages associated with climate change through case study of recent past climatic extreme events in Bangladesh (floods), India (droughts), Philippines and Japan (Typhoon) and Thailand (urban floods). The research will: develop an assessment framework to identify and measure non-economic losses for key vulnerable sectors (e.g., agriculture, water, livelihood and gender); identify range of best practices for addressing the non-economic loss and damage; and developing policy mainstreaming guidelines addressing non-economic losses and damages targeting the key policy makers and the practitioners. This research will help improve our understanding on the non-economic damages associated with the extreme climatic events (rapid and slow onset) and help introduce necessary changes in the risk reduction, transfer and pooling measures including risk insurance, compensation, microfinance etc. As a result, this research is relevant to Thematic area 4-1 c) Multi-trans disciplinary research and assessment of Impacts of extreme weather events and slow onset events at regional, sub-regional and local levels (what are the gaps; what is the status quo?) and non-economic losses. The project will closely collaborate with CAF2014-RR03-NMY-Pereira led by SEADPRI-UKM and share experiences and expertise through organizing common workshops and exchanging research methodologies and results from Malaysia, Vietnam, Philippines, Cambodia and Myanmar.