Influence of model bias on simulating North Atlantic sea surface temperature during the mid-Pliocene, supplement to: Song, Zhaoyang; Latif, Mojib; Park, Wonsun; Zhang, Yuming (2018): Influence of Model Bias on Simulating North Atlantic Sea Surface Temperature During the Mid-Pliocene. Paleoceanography and Paleoclimatology

Climate models generally underestimate the pronounced warming in the sea surface temperature (SST) over the North Atlantic during the mid-Pliocene that is suggested by proxy data. Here, we investigate the influence of the North Atlantic cold SST bias, which is observed in many climate models, on the...

Full description

Bibliographic Details
Main Authors: Song, Zhaoyang, Latif, Mojib, Park, Wonsun, Zhang, Yuming
Format: Dataset
Language:English
Published: PANGAEA - Data Publisher for Earth & Environmental Science 2018
Subjects:
Online Access:https://dx.doi.org/10.1594/pangaea.889380
https://doi.pangaea.de/10.1594/PANGAEA.889380
Description
Summary:Climate models generally underestimate the pronounced warming in the sea surface temperature (SST) over the North Atlantic during the mid-Pliocene that is suggested by proxy data. Here, we investigate the influence of the North Atlantic cold SST bias, which is observed in many climate models, on the simulation of mid-Pliocene surface climate in a series of simulations with the Kiel Climate Model. A surface freshwater-flux correction is applied over the North Atlantic, which considerably enhances simulation of North Atlantic Ocean circulation and SST under present-day conditions. Using reconstructed mid-Pliocene boundary conditions with closed Bering and Arctic Archipelago Straits, the corrected model depicts significantly reduced model-proxy SST discrepancy in comparison to the uncorrected model. A key factor in reducing the discrepancy is the stronger and more sensitive Atlantic Meridional Overturning Circulation and poleward heat transport. We conclude that simulations of mid-Pliocene surface climate over the North Atlantic can considerably benefit from alleviating model biases in this region.