TY - JOUR
T1 - Ensemble Spread Behavior in Coupled Climate Models
T2 - Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble
AU - Stevenson, Samantha
AU - Huang, Xingying
AU - Zhao, Yingying
AU - Di Lorenzo, Emanuele
AU - Newman, Matthew
AU - van Roekel, Luke
AU - Xu, Tongtong
AU - Capotondi, Antonietta
N1 - Publisher Copyright:
© 2023 The Authors. Journal of Advances in Modeling Earth Systems published by Wiley Periodicals LLC on behalf of American Geophysical Union.
PY - 2023/7
Y1 - 2023/7
N2 - Assessing uncertainty in future climate projections requires understanding both internal climate variability and external forcing. For this reason, single-model initial condition large ensembles (SMILEs) run with Earth System Models (ESMs) have recently become popular. Here we present a new 20-member SMILE with the Energy Exascale Earth System Model version 1 (E3SMv1-LE), which uses a “macro” initialization strategy choosing coupled atmosphere/ocean states based on inter-basin contrasts in ocean heat content (OHC). The E3SMv1-LE simulates tropical climate variability well, albeit with a muted warming trend over the twentieth century due to overly strong aerosol forcing. The E3SMv1-LE's initial climate spread is comparable to other (larger) SMILEs, suggesting that maximizing inter-basin ocean heat contrasts may be an efficient method of generating ensemble spread. We also compare different ensemble spread across multiple SMILEs, using surface air temperature and OHC. The Community Earth system Model version 1, the only ensemble which utilizes a “micro” initialization approach perturbing only atmospheric initial conditions, yields lower spread in the first ∼30 years. The E3SMv1-LE exhibits a relatively large spread, with some evidence for anthropogenic forcing influencing spread in the late twentieth century. However, systematic effects of differing “macro” initialization strategies are difficult to detect, possibly resulting from differing model physics or responses to external forcing. Notably, the method of standardizing results affects ensemble spread: control simulations for most models have either large background trends or multi-centennial variability in OHC. This spurious disequlibrium behavior is a substantial roadblock to understanding both internal climate variability and its response to forcing.
AB - Assessing uncertainty in future climate projections requires understanding both internal climate variability and external forcing. For this reason, single-model initial condition large ensembles (SMILEs) run with Earth System Models (ESMs) have recently become popular. Here we present a new 20-member SMILE with the Energy Exascale Earth System Model version 1 (E3SMv1-LE), which uses a “macro” initialization strategy choosing coupled atmosphere/ocean states based on inter-basin contrasts in ocean heat content (OHC). The E3SMv1-LE simulates tropical climate variability well, albeit with a muted warming trend over the twentieth century due to overly strong aerosol forcing. The E3SMv1-LE's initial climate spread is comparable to other (larger) SMILEs, suggesting that maximizing inter-basin ocean heat contrasts may be an efficient method of generating ensemble spread. We also compare different ensemble spread across multiple SMILEs, using surface air temperature and OHC. The Community Earth system Model version 1, the only ensemble which utilizes a “micro” initialization approach perturbing only atmospheric initial conditions, yields lower spread in the first ∼30 years. The E3SMv1-LE exhibits a relatively large spread, with some evidence for anthropogenic forcing influencing spread in the late twentieth century. However, systematic effects of differing “macro” initialization strategies are difficult to detect, possibly resulting from differing model physics or responses to external forcing. Notably, the method of standardizing results affects ensemble spread: control simulations for most models have either large background trends or multi-centennial variability in OHC. This spurious disequlibrium behavior is a substantial roadblock to understanding both internal climate variability and its response to forcing.
KW - climate modeling
KW - large ensembles
KW - ocean heat content
UR - https://www.scopus.com/pages/publications/85165788780
U2 - 10.1029/2023MS003653
DO - 10.1029/2023MS003653
M3 - Article
AN - SCOPUS:85165788780
SN - 1942-2466
VL - 15
JO - Journal of Advances in Modeling Earth Systems
JF - Journal of Advances in Modeling Earth Systems
IS - 7
M1 - e2023MS003653
ER -