On the origin of equatorial Atlantic biases in coupled general circulation models

By Ingo Richter, Shang-Ping Xie. 2008

323 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change, Oceanography

View Paper: https://www.semanticscholar.org/paper/f47db8b3941a483180e8e55a52a9d8d6b2ca7aa7

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Citations in the corpus

Challenges and Prospects for Reducing Coupled Climate Model SST Biases in the Eastern Tropical Atlantic and Pacific Oceans: The U.S. CLIVAR Eastern Tropical Oceans Synthesis Working Group (2016, methodology): “Although the process(es) linking the precipitation and SST biases is (are) still under debate (Richter and Xie 2008; Zermeno-Diaz and Zhang 2013; Richter et al. 2014a), it is self-evident that models with better precipitation representations can more accurately capture realistic air–sea coupling.”
Impact of ocean model resolution on CCSM climate simulations (2012, background): “Here we highlight two uncoupled atmosphere-only and Several studies demonstrate that the EEA SST bias is connected to a springtime westerly equatorial trade wind bias (DeWitt 2005) that erroneously deepens the thermocline, inhibiting the summer cold tongue development (Chang et al. 2007; Richter and”
The GFDL Earth System Model Version 4.1 (GFDL‐ESM 4.1): Overall Coupled Model Description and Simulation Characteristics (2020, background): “To further highlight this improvement across generations of models, we focus in on the Amazon region, which has remained one of the main recalcitrant biases in climate models (e.g., Richter & Xie, 2008).”
Tropical Atlantic biases and their relation to surface wind stress and terrestrial precipitation (2012, background): “This suggests that improving the representation of land surface processes in GCMs offers a way of improving their performance in the tropical Atlantic.”
Improved Climate Simulation by MIROC5: Mean States, Variability, and Climate Sensitivity (2010, background): “The model showed mean states that were relatively close to the average of CGCMs participating in the Coupled Model Intercomparison Project phase 3 (CMIP3).”
Potential of equatorial Atlantic variability to enhance El Niño prediction (2012, background): “Thus, some of the deficiencies of state-of-the-art climate models 190 in simulating and predicting ENSO variability could be related to the strong systematic model 191 error in the Tropical Atlantic [Richter and Xie, 2008; Wahl et al., 2011].”