Collaborative Research: EaSM3 Integration of Decision-Making with Predictive Capacity for Decadal Climate Impacts

Colorado State University, Fort Collins CO

Investigators

Abstract

The need for climate impact predictions on regional and decadal scales is widely recognized. Industry, government and society increasingly require predictive information in decision-relevant terms to enable appropriate planning and adaptation to future hazards arising from climate variability and change, both to mitigate future costs and maximize potential benefits. Climate scientists are engaged in significant effort to understand the decadal predictability of the climate system and to develop models to predict the climate on 5-30 year timescales. However, parallel efforts to understand predictive capacity of climate impacts and realize the full societal value of decadal prediction science has received little attention. This collaborative project will utilize existing and developing dynamical models combined with observed data using advanced statistical methods to understand our predictive capacity for climate impacts on decadal timescales, and integrate predictive methods so that they more directly meet the societal needs for predictive information. The overarching goal is to transform how scientists from multiple disciplines and practitioners conceptualize decadal climate prediction, by enabling decadal predictions in decision relevant terms to improve planning and adaptive capacity for climate variability and change. The approach follows in two concurrent parts. Understanding of current predictive information needs and usage will be developed in Part I across multiple high-impact weather and climate phenomena and across multiple stakeholder groups. The core research will take place in Part II and will identify our predictive capacity for the needed information through development of new combined statistical-dynamical modeling approaches that incorporate and are robust to uncertainty. An iterative process between information needs and information provision will promote effective integration of skillful predictive information with decision-making. A key project contribution is the development of a prototype generalized interdisciplinary research framework to integrate predictive capacity with decision-making.