The Thermocline Biases in the Tropical North Pacific and Their Attributions

Abstract

The tropical thermocline plays an important role in regulating equatorial sea surface temperature (SST); at present, it is still poorly simulated in the state-of-the-art climate models. In this paper, thermocline biases in the tropical North Pacific are investigated using the newly released CMIP6 historical simulations. It is found that CMIP6 models tend to produce an overly shallow thermocline in the northwestern tropics, accompanied by a deep thermocline in the northeastern tropics. A pronounced thermocline strength bias arises in the tropical northeastern Pacific, demonstrating a dipole structure with a sign change at about 8°N. These thermocline biases are accompanied with biases in the simulations of oceanic circulations, including a too weak North Equatorial Countercurrent (NECC), a reduction in water exchanges between the subtropics and the equatorial regions, and an eastward extension of the equatorward interior water transport. The causes of these thermocline biases are further analyzed. The thermocline bias is primarily caused by the model deficiency in simulating the surface wind stress curl, which can be further attributed to the longstanding double-ITCZ bias in the tropical North Pacific. Besides, thermocline strength bias can be partly attributed to the poor prescription of oceanic background diffusivity. By constraining the diffusivity to match observations, the thermocline strength in the tropical northeastern Pacific is greatly increased.

Historical changes in wind-driven ocean circulation drive pattern of Pacific warming

“…1a-c). Internal climate variability could potentially explain a part of the observation-model mismatch, but the mismatch may also originate from model biases in the tropical Pacific [55][56][57][58][59][60] . For example, our heat budget analysis reveals a CP cooling effect by the climatological upwelling in FC (supplementary Fig.…”

Ocean Futures for the World’s Largest Yellowfin Tuna Population Under the Combined Effects of Ocean Warming and Acidification

“…Dueri et al, 2014;Lehodey et al, 2015a;Bianucci et al, 2016;Gailbraith et al, 2017), we have used projections of physical and biogeochemical forcings derived from earth climate models such as those associated with the World Climate Research Programme's Coupled Model Intercomparison Project (Meehl, 1995;Meehl et al, 2000). However, the CMIP models have known biases when applied at local and regional scales (Li et al, 2019;Mckenna et al, 2020;Tian and Dong, 2020;Samuels et al, 2021;Tang et al, 2021;Zhu et al, 2021) and without corrections these biases can lead to spurious correlations when estimating habitat parameters over the historical period (Lehodey et al, 2013). Although we applied both bias-correction (as described in Bell et al, 2021) and ensemble simulations (Semenov and Stratonovitch, 2010;Tittensor et al, 2018;Eddy, 2019), there remains considerable uncertainty in our understanding of how the dynamics of the Western Pacific warm-pool will be altered due to climate change (Brown et al, 2014) and how dissolved oxygen availability within the Pacific will change (Ganachaud et al, 2013).…”

A Shallow Thermocline Bias in the Southern Tropical Pacific in CMIP5/6 Models Linked to Double‐ITCZ Bias

“…The Pacific southern thermocline bias is spatially coincident with precipitation biases south of the equator (Figure 1c) that originate from the SH rainy season (Adam, Schneider, & Brient, 2018; Li & Xie, 2014)–a link we later explore. Precipitation biases north of the equator in the western Pacific, seen year‐round (Adam et al., 2016; Lin, 2007), have been partially attributed to deficits in the reference GPCP data (compare GPCP and CMAP in Figure 3c; Schlosser & Houser, 2007; Stephens et al., 2012; Trenberth et al., 2009), and partially locally linked to the mild shallow thermocline bias north of the equator through wind stress curl (Zhu et al., 2021).…”

“…CMIP3/5 models are known to systematically produce a too shallow equatorial thermocline (e.g., Castaño‐Tierno et al., 2018; Li & Xie, 2012, 2014; Zheng et al., 2012). Furthermore, CCSM model studies revealed biases in the meridional structure of the tropical mid‐Pacific thermocline associated with the DIB (Zhang et al., 2007; Zhang & Song, 2010); and tropical north Pacific thermocline biases have been reported in CMIP6 models (Zhu et al., 2021). But tropical‐wide thermocline representation across CMIP models has not been systematically investigated.…”