22 May 2023
 | 22 May 2023
Status: this preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).

Atmospheric bias teleconnections associated with systematic SST errors in the tropical Indian Ocean

Yuan-Bing Zhao, Nedjeljka Žagar, Frank Lunkeit, and Richard Blender

Abstract. State-of-the-art climate models suffer from significant sea surface temperature (SST) biases in the tropical Indian Ocean (TIO), greatly damaging the climate prediction and projection. In this study, we investigate the multidecadal atmospheric bias teleconnections caused by the TIO SST bias and their impacts on the simulated atmospheric variability. A set of century long simulations forced with idealized SST perturbations, resembling various persistent TIO SST biases in coupled climate models, are conducted with an intermediate complexity atmospheric model. Bias analysis is performed using the normal-mode function decomposition which can differentiate between balanced and unbalanced flow regimes across spatial scales. The results show that the atmospheric circulation biases caused by the TIO SST bias have the Gill-Matsuno-type pattern in the tropics and Rossby wave-train distribution in the extratropics, similar to the steady state response to tropical heating. The teleconnection between the tropical and extratropical biases is set up by the Rossby wave-train emanating from the subtropics. Over 90 % of the bias variance is contained in planetary scales (zonal wavenumber k ≤ 5). These biases have great impacts on the simulated energy and interannual variance (IAV). The zonal-mean-flow energy and the extratropical (balanced) wave-flow energy responses are closely related to bias phase (i.e., the covariance between the bias and reference state). In contrast, the tropical (both unbalanced and balanced) wave-flow energy responses are primarily associated with bias amplitude. The response of the IAV is contingent upon the sign of the SST bias. A positive SST bias reduces the IAV, whereas a negative SST bias increases it, regardless of dynamical regimes. Geographically, strong IAV responses are observed in the tropical Indo-west Pacific region, Australia, south and northeast Asia, the Pacific-North America region and Europe, where the background IAVs are strong.

Yuan-Bing Zhao et al.

Status: open (until 03 Jul 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Yuan-Bing Zhao et al.

Yuan-Bing Zhao et al.


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Short summary
Climate models suffer from sea surface temperature (SST) biases, greatly affecting climate prediction. In this study, we show that localized SST bias in the tropical Indian Ocean can cause biases in global circulation, especially at the planetary scales, which impact simulated variability. The spatial variability response can be attributed to bias amplitude or bias phase, depending on regimes and regions, whereas the temporal variability response is contingent upon the sign of the SST bias.