GISS‐E2.1: Configurations and Climatology

This paper describes the GISS‐E2.1 contribution to the Coupled Model Intercomparison Project, Phase 6 (CMIP6). This model version differs from the predecessor model (GISS‐E2) chiefly due to parameterization improvements to the atmospheric and ocean model components, while keeping atmospheric resolut...

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Bibliographic Details
Published in:Journal of Advances in Modeling Earth Systems
Main Authors: Kelley, Maxwell, Schmidt, Gavin A., Nazarenko, Larissa S., Bauer, Susanne E., Pérez García-Pando, Carlos
Other Authors: Barcelona Supercomputing Center
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2020
Subjects:
Online Access:http://hdl.handle.net/2117/339771
https://doi.org/10.1029/2019MS002025
Description
Summary:This paper describes the GISS‐E2.1 contribution to the Coupled Model Intercomparison Project, Phase 6 (CMIP6). This model version differs from the predecessor model (GISS‐E2) chiefly due to parameterization improvements to the atmospheric and ocean model components, while keeping atmospheric resolution the same. Model skill when compared to modern era climatologies is significantly higher than in previous versions. Additionally, updates in forcings have a material impact on the results. In particular, there have been specific improvements in representations of modes of variability (such as the Madden‐Julian Oscillation and other modes in the Pacific) and significant improvements in the simulation of the climate of the Southern Oceans, including sea ice. The effective climate sensitivity to 2 × CO2 is slightly higher than previously at 2.7–3.1°C (depending on version) and is a result of lower CO2 radiative forcing and stronger positive feedbacks. Climate modeling at GISS is supported by the NASA Modeling, Analysis and Prediction program, and resources supporting this work were provided by the NASA High‐End Computing (HEC) Program through the NASA Center for Climate Simulation (NCCS) at Goddard Space Flight Center. We thank Ángel Adames and John Fasullo for providing figures and data from their multimodel comparisons. We also thank the two anonymous reviewers who helped improve the clarity and usefulness of the manuscript. Peer Reviewed "Article signat per 46 autors/es: Maxwell Kelley Gavin A. Schmidt Larissa S. Nazarenko Susanne E. Bauer Reto Ruedy Gary L. Russell Andrew S. Ackerman Igor Aleinov Michael Bauer Rainer Bleck Vittorio Canuto Grégory Cesana Ye Cheng Thomas L. Clune Ben I. Cook Carlos A. Cruz Anthony D. Del Genio Gregory S. Elsaesser Greg Faluvegi Nancy Y. Kiang Daehyun Kim Andrew A. Lacis Anthony Leboissetier Allegra N. LeGrande Ken K. Lo John Marshall Elaine E. Matthews Sonali McDermid Keren Mezuman Ron L. Miller Lee T. Murray Valdar Oinas Clara Orbe Carlos Pérez García‐Pando Jan P. Perlwitz Michael J. Puma David Rind Anastasia Romanou Drew T. Shindell Shan Sun Nick Tausnev Kostas Tsigaridis George Tselioudis Ensheng Weng Jingbo Wu Mao‐Sung Yao" Postprint (published version)