An Approach to Link Climate Model Tropical Cyclogenesis Bias to Large‐Scale Wind Circulation Modes

Abstract

Attributing sources of tropical cyclogenesis (TCG) bias to large‐scale circulation in global circulation models is challenging. Here, we propose the use of empirical orthogonal functions as an approach to understand model bias of TCG. Two leading modes of large‐scale wind circulations in the West Pacific can explain the TCG frequency and location in both climate reanalysis and the MetUM model. In the reanalysis, the two modes distinguish the summer monsoon trough position and the strength of the north Pacific subtropical high. However, in the model, the wind circulations are biased toward the positive phase of simulated modes thus overestimating TCG in the entire Main Development Region. This bias is further related to the north‐eastward shifted monsoon trough and a weakened subtropical high, and overly strong tropics‐subtropics connections. This approach could be deployed more widely to other basins and models to diagnose the causes of TCG bias.

Seasonal Cycle Delay of the Western North Pacific Tropical Cyclone Genesis Frequency in CMIP6 Simulations

“…For instance, Zhao et al (2023) suggest that there is a large uncertainty in the TC genesis simulation over western WNP, which originates from the Gill-type response (Gill, 1980) and Pacific-Japan wave train (Nitta, 1989) excited by diabatic heating associated with the precipitation simulation bias, which in turn triggers a series of anomalies in the large-scale atmospheric circulation. Feng et al (2023) pointed out that the anomalous cyclonic circulation at 850 hPa and the weakening of the WNPSH, including the stronger connection between the tropics and the subtropics, are responsible for the bias in the simulation of the location of TC genesis over the WNP in high-resolution atmosphere-only models.…”

“…Many studies employed climate models to predict future climate changes (Kossin et al, 2016;Murakami & Wang, 2022;Nakamura et al, 2017). Meanwhile, climate models' ability to simulate and predict TC activity is also evaluated by many previous studies (Bell et al, 2019;Camargo, 2013;Camargo et al, 2020;Feng et al, 2023;Shaevitz et al, 2014;Sharmila et al, 2020;Tory et al, 2013). As the latest generation of the Coupled Model Intercomparison Project (CMIP), CMIP6 includes a large number of climate models on various resolutions that can provide valuable opportunities for TC research (Eyring et al, 2016).…”