Adrienne Wootten (United States of America) 1; Keith Dixon (United States of America) 2; Dennis Adams-Smith (United States of America) 2; Renee Mcpherson (United States of America) 3
1 - South Central Climate Adaptation Science Center; 2 - NOAA Geophysical Fluid Dynamics Laboratory; 3 - University of Oklahoma
Decision makers who require high-resolution climate projections for adaptation planning often use statistically downscaled projections in areas with high spatial and temporal resolution observations. Statistical downscaling provides a relatively low-cost approach that aims to address climate model shortcomings (e.g., coarse spatial resolution and systematic biases) to create data products more suitable for direct use in climate impacts work. Because these datasets are relatively easy to access, users may apply them without understanding how the underlying statistical methods influence the results, particularly for extreme events (e.g., intense rainfall) that may be of greatest interest in adaptation planning.
This presentation will highlight how the South Central Climate Adaptation Science Center (including the Geophysical Fluid Dynamics Laboratory of the National Oceanic and Atmospheric Administration and the University of Oklahoma) examines the consequences of choices made in the statistical downscaling process and how our science team informs decision makers of those results. Through co-production, our science team determines what variables are critical to decision makers in our region and researches how scenarios (i.e., representative concentration pathways), global climate model, downscaling technique, training observations, and choices made during the downscaling process influence theuncertaintythat stakeholders must incorporate in their planning processes.