Climate change data

  • Many water resources planning decisions require understanding the vulnerability of hydrologic systems to a wide range of different stresses. For many users, this requires developing a set of discrete quantitative hydrologic storylines of climate change impacts that can be used to evaluate adaptation measures. Quantitative hydrologic storylines rely on modern climate downscaling tools and process-based hydrologic models. Each storyline represents key features from the full range of possible climate scenarios, and, taken together, the storylines provide a comprehensive yet concise description of possible climate change impacts. The research community has made substantial scientific advances in understanding impacts of climate variability and change on water resource systems; however, the technologies in climate downscaling and hydrologic modeling have considerable unrealized potential and lack sufficient technical readiness to be used widely for water resources planning.
    The specific work elements in the proposal are: 1. Advance climate downscaling tools to provide climate change scenarios for input to NASA-LIS, including capabilities to explore sensitivities to downscaling methodological choices; 2. Develop watershed-based hydrologic model configurations, and implement them in NASA-LIS, to define land model configurations for water-resource planning; 3. Refine hydrologic models to improve the fidelity of hydrologic model simulations, using a suite of remotely sensed data for diagnostic assessment and improvement as well as bias correction of simulated streamflow time series; 4. Tailor model outputs to increase applicability of hydrologic climate change scenarios for water resources planning, using interactive web-based tools and summary products; and 5. Apply advanced concepts of information theory and machine learning to identify process-level tradeoffs between modeling options, and guide priorities for future research investments.

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