Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble
Abstract 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...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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American Geophysical Union (AGU)
2023-07-01
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| Series: | Journal of Advances in Modeling Earth Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2023MS003653 |
| _version_ | 1797647711269289984 |
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| author | Samantha Stevenson Xingying Huang Yingying Zhao Emanuele Di Lorenzo Matthew Newman Luke vanRoekel Tongtong Xu Antonietta Capotondi |
| author_facet | Samantha Stevenson Xingying Huang Yingying Zhao Emanuele Di Lorenzo Matthew Newman Luke vanRoekel Tongtong Xu Antonietta Capotondi |
| author_sort | Samantha Stevenson |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-03-11T15:21:28Z |
| format | Article |
| id | doaj.art-c01f7491c58f4347b01899bccd705d36 |
| institution | Directory Open Access Journal |
| issn | 1942-2466 |
| language | English |
| last_indexed | 2024-03-11T15:21:28Z |
| publishDate | 2023-07-01 |
| publisher | American Geophysical Union (AGU) |
| record_format | Article |
| series | Journal of Advances in Modeling Earth Systems |
| spelling | doaj.art-c01f7491c58f4347b01899bccd705d362023-10-28T13:31:25ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662023-07-01157n/an/a10.1029/2023MS003653Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large EnsembleSamantha Stevenson0Xingying Huang1Yingying Zhao2Emanuele Di Lorenzo3Matthew Newman4Luke vanRoekel5Tongtong Xu6Antonietta Capotondi7University of California, Santa Barbara Santa Barbara CA USANational Center for Atmospheric Research Boulder CO USAPilot National Laboratory for Marine Science and Technology Deep‐Sea Research Center Qingdao ChinaGeorgia Institute of Technology Atlanta GA USAUniversity of Colorado Boulder CO USALos Alamos National Laboratory Los Alamos NM USANOAA Physical Sciences Laboratory Boulder CO USAUniversity of Colorado Boulder CO USAAbstract 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.https://doi.org/10.1029/2023MS003653large ensemblesclimate modelingocean heat content |
| spellingShingle | Samantha Stevenson Xingying Huang Yingying Zhao Emanuele Di Lorenzo Matthew Newman Luke vanRoekel Tongtong Xu Antonietta Capotondi Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble Journal of Advances in Modeling Earth Systems large ensembles climate modeling ocean heat content |
| title | Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble |
| title_full | Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble |
| title_fullStr | Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble |
| title_full_unstemmed | Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble |
| title_short | Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble |
| title_sort | ensemble spread behavior in coupled climate models insights from the energy exascale earth system model version 1 large ensemble |
| topic | large ensembles climate modeling ocean heat content |
| url | https://doi.org/10.1029/2023MS003653 |
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