No abstract

No abstract

No abstract

The use of Global Climate Model (GCM) precipitation simulations typically requires corrections for precipitation biases at sub-grid spatial scales, typically at daily or monthly timescales. However, over many regions GCMs underestimate of the magnitudes of multi-year precipitation extremes in the observed climate, resulting in a likely underestimation of the magnitudes of multi-year precipitation extremes in future scenarios. The objective of this study is to propose a method to extract from GCMs more realistic scenarios of multi-year precipitation extremes over time horizons of decades to one century. This proposed correction method is analogous to widely used bias correction methods, except that it is applied to variability at longer time scales than previous implementations (i.e. multi-year rather than daily or monthly). A case study of precipitation over a basin from the New York City water supply system demonstrates the potential magnitude of the underestimation of multi-year precipitation using uncorrected GCM scenarios, and the potential impact of the correction on multi-year hydrological extremes. Overall, it is a practical, conceptually simple approach meant for water supply system impact studies, but can be used for any impact studies that require more realistic multi-year extreme precipitation extreme scenarios.

No abstract