Efforts associated with this project has been categorized into five interwoven tasks: (1) continuous outreach and engagement to better understand fundamental regional knowledge gaps, (2) application of a storyline framework for understanding model performance in light of events and period of stakeholder interest, (3) use of new and existing use-inspired metrics that connect process understanding with regional needs, (4) use of diffential crediblity analysis to understand and intercompare Earth system datasets, (5) development of a deeper understanding of multi-sector interactions, the interplay between global and regional climate forcings, and implications for the energy supply. These tasks are addressed in detail below.
Task 1: Regional Engagement
Through the HyperFACETS project we are engaging Earth system scientists and regional collaborators within working groups to build common understanding and strategy for achieving these goals. Our regional collaborators are drawn primarily from water and energy management agencies, with broad geographical coverage of the continental United States. This project proposes to refine past engagement efforts and understand how climate datasets are being used for specific decision applications.
Case study narratives developed under the HyperFACETS projects:
Task 2: Storylines
HyperFACETS has developed a storyline context to frame our analysis activities and provide a means to effectively interface our scientific pursuits with stakeholder interests. Formally, a storyline is a physically self-consistent unfolding of a past event, or of a plausible future event or pathway (Shepherd et al., 2018). They may also be thought of as test cases for assessing if regional models can reproduce an event consistent with observations. These storylines are chosen to be representative of major climatic events that have impacted, or would impact, the policy or decision context.
Learn more about our storylines.
Task 3: Metric Development and Process Understanding
HyperFACETS will develop new metrics and leverage existing metrics to evaluate and understand modeled processes. This procedure will subsequently inform credibility and uncertainty in light of a nonstationary climate system. This work encapsulates the key scientific tasks that will lead to a better understanding of the Earth system. We will perform deep dives into natural hazards, low flow and flood regimes in rivers, water availability in groundwater and snowpack, and implications for human systems. A key outcome is the identification of process biases and errors that are most responsible for uncertainties in available products.
Task 4: Differential Credibility Analysis
Differential credibility analysis (DCA) will be performed to better understand Earth system model behavior and how differences between data production methods. This process involves a broad assessment of model performance, and will target the validity of Earth system datasets for decision making.
Task 5: Model Sensitivity Studies
HyperFACETS will develop a deeper understanding of intersectoral dynamics (those at the atmosphere-water-energy-land interface), the interplay between global and regional climate forcings and implications for key aspects of energy supply using Earth system simulations conducted at a range of spatial scales for scenarios of changing land use, irrigation and energy mix.
