An Enhancement of Low-Frequency Variability in the Kuroshio–Oyashio Extension in CCSM3 owing to Ocean Model Biases

Abstract

Enhanced decadal variability in sea surface temperature (SST) centered on the Kuroshio Extension (KE) has been found in the Community Climate System Model version 3 (CCSM3) as well as in other coupled climate models. This decadal peak has higher energy than is found in nature, almost twice as large in some cases. While previous analyses have concentrated on the mechanisms for such decadal variability in coupled models, an analysis of the causes of excessive SST response to changes in wind stress has been missing. Here, a detailed comparison of the relationships between interannual changes in SST and sea surface height (SSH) as a proxy for geostrophic surface currents in the region in both CCSM3 and observations, and how these relationships depend on the mean ocean circulation, temperature, and salinity, is made. We use observationally based climatological temperature and salinity fields as well as satellite-based SSH and SST fields for comparison. The primary cause for the excessive SST variability is the coincidence of the mean KE with the region of largest SST gradients in the model. In observations, these two regions are separated by almost 500 km. In addition, the too shallow surface oceanic mixed layer in March north of the KE in the subarctic Pacific contributes to the biases. These biases are not unique to CCSM3 and suggest that mean biases in current, temperature, and salinity structures in separated western boundary current regions can exert a large influence on the size of modeled decadal SST variability.

Seasonal Evolutions of Atmospheric Response to Decadal SST Anomalies in the North Pacific Subarctic Frontal Zone: Observations and a Coupled Model Simulation

“…This overestimation of the simulated anomalies is consistent with the overestimation of the frontal gradient in the climatological-mean SST (purple contour; see also excursion of the SAFZ in the model that is in realistic magnitude (Fig. Thompson and Kwon 2010). In fact, both the SST anomalies and climatological-mean SST gradient in the model are nearly twice as large as their observational counterpart ( Fig.…”

Ocean Circulation Signatures of North Pacific Decadal Variability

“…Like the traditional PDO index (PC-PDO), computed as the leading principal component of North Pacific SST anomalies (20-70 • N, Figure 1b), its warm (positive) phase is associated with cooling in the Kuroshio-Oyashio Extension (KOE) concurrent with warming along the west coast of North America. The LFC-PDO pattern is similar to the PDO-like anomaly pattern obtained from LFCA of observed Pacific SSTs over the twentieth century , with the biggest difference being the larger amplitude of KOE SST anomalies in the CMIP5 models, a known bias of low-resolution climate models (Thompson & Kwon, 2010). The warming associated with LFC-PDO is about half as strong as that associated with PC-PDO but extends farther west into the Bering Sea and Sea of Okhotsk.…”

“…The steady state Sverdrup balance governing the oceanic response to wind stress forcing is well resolved, though nonlinear and eddy dynamics in the KOE are not, leading to mean state biases in the KOE system and stronger and larger-scale KOE SST variability in low-resolution models than in observations and high-resolution models (Thompson & Kwon, 2010). The steady state Sverdrup balance governing the oceanic response to wind stress forcing is well resolved, though nonlinear and eddy dynamics in the KOE are not, leading to mean state biases in the KOE system and stronger and larger-scale KOE SST variability in low-resolution models than in observations and high-resolution models (Thompson & Kwon, 2010).…”

Spatial Patterns and Intensity of the Surface Storm Tracks in CMIP5 Models

“…6b, which shows no overlap in the location of the KOE based on altimetry data (which captures the current) and the maximum in j=SSTj. Because our analysis examines the SST, we cannot comment directly on the ocean currents, but previous research has shown that coarse-resolution models like those used in this study produce a single, merged front that has both the strong ocean current and the SST front rather than having separate Kuroshio and Oyashio Extension fronts (e.g., Thompson and Kwon 2010). In the analysis presented here, the strong collocation of the T DIFF , j=SSTj, and s BI may be a result of the merged locations of the SST gradient and the ocean currents in the CMIP5 models, and for ERA-I it relates to the reduced spatial resolution we use for the analysis.…”