Final Report: Characterizing Uncertainties in Climate Projections to Support Regional Decision-Making
Dates
Publication Date
2019
Citation
Adrienne Wooten, 2019, Final Report: Characterizing Uncertainties in Climate Projections to Support Regional Decision-Making: .
Summary
In recent years, climate projections have been used to research the climate system as well as provide guidance for climate adaptation decisions and impact assessments. There are numerous methods to produce the locally relevant climate projections for use in impact assessments. Since there are no standard methods to derive locally relevant projections, one must consider multiple approaches. In order to provide additional clarity regarding the use of available climate projections, this project assessed how the inputs that define the projections (e.g., historical climate data, downscaling method, etc.) contribute to the variability among different climate projections for temperature and precipitation variables. This project used projections [...]
Summary
In recent years, climate projections have been used to research the climate system as well as provide guidance for climate adaptation decisions and impact assessments. There are numerous methods to produce the locally relevant climate projections for use in impact assessments. Since there are no standard methods to derive locally relevant projections, one must consider multiple approaches. In order to provide additional clarity regarding the use of available climate projections, this project assessed how the inputs that define the projections (e.g., historical climate data, downscaling method, etc.) contribute to the variability among different climate projections for temperature and precipitation variables. This project used projections created specifically for the south-central United States and a statistical method to determine the contribution from four known sources of variability in the climate projections: (1) the variability associated with human actions (societal), (2) unknowns associated with the physics of the global climate models, (3) the varying approaches to translate global change to local regions, and (4) natural climate variability. Findings from this project suggest that a significant portion of the variability among the climate projections is associated with downscaling technique (>20% of the variability between projections) for projections of temperature and precipitation extremes in the south-central U.S. While the number of projections used was only a fraction of those currently available, this study highlights the importance of carefully considering the inputs into the downscaled climate projections when choosing how many and which to use for climate impact assessments, management decisions, or other applications.