Assessment of CMIP6 models' skill for tropical Indian Ocean sea surface temperature variability

Abstract

AbstractThe present study examines the ability of Coupled Model Inter‐comparison Project phase 6 (CMIP6) models in representing the dominant modes of tropical Indian Ocean (TIO) sea surface temperature (SST) variability on the interannual and decadal time scale. Historical simulations from 27 CMIP6 models are assessed against Extended Reconstructed SST over the period of 1854 to 2014. Spectrum analysis reveals that many models reproduce interannual and decadal variability of TIO SST but underestimate the amplitude of variability with some disparity in the periodicity. All models can reproduce the dominant basin‐wide mode of interannual and decadal variability of TIO SST reasonably well. Skill score analysis of TIO SST variability reveals that KACE‐1‐0‐G has highest skill, followed by FGOALS‐f3‐L, EC‐Earth3‐Veg‐LR, ACCESS‐ESM1‐5, CanESM5‐CanOE on the interannual timescale and FGOALS‐f3‐L, CanESM5‐CanOE, KACE‐1‐0‐G and CanESM5, respectively, showed highest skills for decadal variability. It is found that variations in radiation and latent heat flux are primarily responsible for interannual variability in TIO SST, the basin‐wide warming, in the observations. Taylor diagram analysis reveals that all the models exhibit better skill for the radiative flux; however, skill for the latent heat and momentum flux varies from model to model. It is important to note that the models in which the latent heat flux and zonal wind are better represented have produced better TIO SST variability compared to other models. A higher discrepancy in latent heat and zonal momentum flux leads to improper wind‐evaporation‐SST and wind‐circulation‐SST feedback, which in turn restricts the model skill. Besides, model that has realistic central and eastern Pacific SST variability show better skill for TIO SST variability in both interannual and decadal time scales. The present study advocates that better representation of latent heat flux and zonal wind in coupled models is important for the accurate simulation of interannual and decadal variability in TIO SST.