Title: Developing Quantitative Future Climate Scenarios to Inform Ecological Impact Assessments and Climate Adaptation Planning
Speaker: Imtiaz Rangwala, CIRES, NC CASC

Abstract:
In recent years, Scenario Planning is being increasingly practiced to inform future ecological responses and planning for adaptation under climate change. This presentation will discuss some of the advancements in developing scale-appropriate quantitative climate-projections information desired by the natural resource management community. I will discuss the issues of (a) big data associated with future climate projections from Global Climate Models (now increasingly being developed as Earth System Models) and their downscaled derivatives, (b) climate projections uncertainty and use of the “scenarios” approach to incorporate that uncertainty into impact assessment and adaptation planning, and (c) some of the tools developed to provide various desired quantitative information to generate climate scenarios for applications in the real world. I will conclude by talking about a current effort at the North Central CASC to advance the development of future Ecological Scenarios for natural resources management decision making (e.g., Resist-Accept-Direct Framework) by more robustly considering the uncertainties in ecological processes.

Speaker Bio: 
Imtiaz Rangwala is a Research Scientist in CIRES and the Lead Climate Scientist at the North Central Climate Adaptation Science Center. He is a climate scientist engaged in advancing the understanding of changing water balance and climate extremes driven by anthropogenic climate change, and its relevance to ecosystem response. His work includes understanding, and working with, uncertainty in future climate change and ecological responses, and developing relevant tools and data to inform resource management and climate adaptation. He has extensive experience in working with the natural resource management community in the Intermountain West and Great Plains region in the development and communication of useful and usable climate science and data.