A varied and growing group of users now require accurate climate projections, particularly high-resolution projections and projections incorporating meteorological and hydrologic extremes, for all manner of impacts, adaptation, and vulnerability assessments. There has recently been explosive growth in the number of regional climate datasets to address these needs, with varied accuracy in different metrics and incomplete validation.  However, with little guidance on how to choose among them, a usability gap continues to exist between their production and their use in addressing outstanding questions in climate science. Decision makers often have difficulty using these datasets as well, and have loudly called for "actionable science" and "co-production" of science: The core idea being that stakeholders and scientists should be engaged in a two-way exchange about each others' needs and capabilities.  These circumstances have arisen largely because no standardized procedure exists for validating regional climate datasets. The primary objective of this proposal is the development of a comprehensive regional hydroclimate data assessment capability focused on feature-specific metrics and stakeholder-relevant outcomes.  The secondary objective of this proposal is to leverage this assessment capability to improve our ability to predict these outcomes, by identifying the process-level drivers of outcome biases and evaluating the most appropriate and efficient ways to couple climate models, hydrologic models, and models of human impacts.

The key components of this proposal are as follows: (1) continuous outreach and engagement to ensure a focus on stakeholder needs, (2) development and accumulation of metrics associated with processes, features, and outcomes, (3) a software suite capable of directly evaluating the quality of regional climate and hydrological datasets, (4) production of high-quality regional climate and hydrological data that can be used for broader applications, including future projections, (5) model optimization and sensitivity experiments so as to maximize their capability to credibly compute hydroclimate metrics, (6) an assessment of uncertainty linking process-based representations, model coupling, and resolution to stakeholder-relevant outcomes and (7) sensitivity experiments to characterize the magnitude and scale of irrigation influences on the climate system.

This proposal incorporates broad coverage of the continental US (CONUS), along with four diverse case studies that include the Sacramento-San Joaquin watersheds, Colorado River headwaters, Susquehanna River and the Kissimmee River, where water management systems are complex and highly influenced by climatic variability at fine spatial and temporal scales.  A rich diversity of meteorological, hydrologic and anthropogenic features will be considered, including atmospheric rivers, mesoscale convective complexes, sea breeze, coastal storms, the North American monsoon, streamflow, flooding and water demand.  Focusing on the CONUS, and (to varying degrees) its diverse climatological regions, allows for a sufficiently compact region of study to support regional modeling at high spatial resolution.