Rectifying low-frequency variability in future climate sea surface temperature simulations: are corrections for extreme change scenarios realistic?

Abstract

Most procedures for redressing systematic bias in climate modeling are calibrated using current climate observations, and perform well. However, their performance in the future climate remains uncertain as no observations exist to compare against. In this context, we use the current and future climate outputs of an ultra-high resolution of Community Earth System Model (UHR-CESM) as the representative truth and bias correct monthly sea surface temperature (SST) simulations of eight Coupled Model Intercomparison Project 6 models over the Niño 3.4 region. A time-frequency bias correction approach is used to correct for bias in distributional, trend, and spectral attributes present in the models. This results in a near perfect power spectrum of the bias corrected current climate model simulations. Considering all correction procedures remain unchanged into the future, the overall representation of the corrected SST simulations shows improvement with consistency across models for the doubled CO _2 scenario, but higher variability and lower consistency in the quadrupled CO _2 concentration scenario.

Keywords

• low-frequency variability bias
• bias correction
• Niño 3.4
• sea surface temperature
• ultra-high resolution climate model