Evaluation of Different Bias Correction Methods for Dynamical Downscaled Future Projections of the California Current Upwelling System

Abstract

Abstract Biases in global Earth System Models (ESMs) are an important source of errors when used to obtain boundary conditions for regional models. Here we examine historical and future conditions in the California Current System (CCS) using three different methods to force the regional model: (a) interpolation of ESM output to the regional grid with no bias correction; (b) a “seasonally‐varying” delta method that obtains a season‐dependent mean climate change signal from the ESM for a 30‐year future period; and (c) a “time‐varying” delta method that includes the interannual variability of the ESM over the 1980–2100 period. To compare these methods, we use a high‐resolution (0.1°) physical‐biogeochemical regional model to dynamically downscale an ESM projection under the RCP8.5 emission scenario. Using different downscaling methods, the sign of future changes agrees for most of the physical and ecosystem variables, but the spatial patterns and magnitudes of these changes differ, with the seasonal‐ and time‐varying delta simulations showing more similar changes. Not correcting the ESM forcing leads to amplification of biases in some ecosystem variables as well as misrepresentation of the California Undercurrent and CCS source waters. In the non‐bias corrected and time‐varying delta simulations, most of the ecosystem variables inherit trends and decadal variability from the ESM, while in the seasonally‐varying delta simulation the future variability reflects the observed historical variability (1980–2010). Our results demonstrate that bias correcting the forcing prior to downscaling improves historical simulations, and that the bias correction method may impact the spatial and temporal variability of the future projections.

Keywords

• dynamical downscaling
• bias correction
• California current system
• California undercurrent
• climate future projections