The Super-large Ensemble Experiments of CAS FGOALS-g3

Lin, Pengfei; Zhao, Bowen; Wei, Jilin; Liu, Hailong; Zhang, Wenxia; Chen, Xiaolong; Jiang, Jie; Ding, Mengrong; Man, Wenmin; Jiang, Junguang; Zhang, Xu; Ding, Yuewen; Bai, Wenrong; Jin, Chenyang; Yu, Zhenzhen; Li, Yiwen; Zheng, Weipeng; Zhou, Tianjun

doi:10.1007/s00376-022-1439-1

Cited by 18 publications

(8 citation statements)

References 72 publications

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“…There are 30 vertical levels for the ocean model component. The horizontal resolution of FGOALS-g3 used for the super-large ensemble is comparable to other CMIP6 models with large ensembles, coarser than that of CESM2, and finer than that of CanESM5 (Lin et al, 2022).…”

Section: Methodsmentioning

confidence: 78%

“…The super‐large ensemble has been proven to be capable of reproducing the historical evolution of average SAT and land precipitation over the globe well during 1850–2014. The large‐scale spatial features of SAT are well simulated, and the ensemble can reproduce the Asian monsoonal circulation and associated precipitation (Lin et al, 2022). Therefore, we can use this ensemble dataset to explore the change in the connections of the summertime NWPSA to the preceding ENSO under global warming.…”

Section: Methodsmentioning

confidence: 99%

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Increasing connections of the leading internal mode of the summertime Northwest Pacific subtropical anticyclone with preceding ENSO under greenhouse warming in FGOALS‐g3 super‐large ensemble

Lin

Wang

et al. 2023

Intl Journal of Climatology

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While much progress has been made in understanding how anthropogenic forcing influences the climate mean state, less attention has been paid to how it may modulate the internal variability of air–sea coupled mode. This study investigates forced changes of the leading internal mode of the summertime Northwest Pacific subtropical anticyclone (NWPSA) and the related sea surface temperature (SST) anomalies based on the 110‐member FGOALS‐g3 super‐large ensemble for the period of 1850–2099. The leading internal mode of the NWPSA variability is obtained by applying snapshot‐empirical orthogonal function analyses across the ensemble dimension each year. It is shown that the connection between the NWPSA and the preceding El Niño–Southern Oscillation (ENSO) strengthens in response to anthropogenic forcing, and the precipitation along the northwestern flank of the NWPSA increases correspondingly due to stronger water vapour transport. The SST anomalies corresponding to the change invoke a rapid transition from El Niño to La Niña in a warming world, which induces a zonal SST contrast between the Indian Ocean warming and the equatorial Pacific cooling, favouring a strengthening of the NWPSA. The stronger influence of ENSO on the NWPSA in the ensuing summer under greenhouse warming may result from the pronounced increase in the internal variability of the central deep‐equatorial Pacific SST and precipitation over the western‐central equatorial Pacific in winter. The stronger influence indicates that ENSO may serve as a stronger predictor of the summertime NWPSA in a warming climate, and may improve the skills of the seasonal forecast of the climate over East and South Asia in summer.

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Section: Methodsmentioning

confidence: 78%

Section: Methodsmentioning

confidence: 99%

Increasing connections of the leading internal mode of the summertime Northwest Pacific subtropical anticyclone with preceding ENSO under greenhouse warming in FGOALS‐g3 super‐large ensemble

Lin

Wang

et al. 2023

Intl Journal of Climatology

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“…The impact of aerosols on ENSO amplitude is also detectable in MIROC6. However, it is still challenging to distinguish these changes between high-emission scenarios or between low-emission scenarios, implying the importance of implementing spatiotemporal analysis methods (e.g., Wills et al, 2020) or generating larger ensembles (e.g., Maher et al, 2019;Rodgers et al, 2021;Lin et al, 2022). The mechanisms underlying the clearly detected changes in this study and the changes in other internal variability will be reported in future works.…”

Section: Changes In Internal Variabilitymentioning

confidence: 85%

“…The Swedish Meteorological and Hydrological Institute used the EC-Earth3 model to generate 50-member ensembles over the historical interval and four shared socioeconomic pathway simulations (2015-2100; SSP1-1.9, SSP3-3.4, SSP5-3.4-OS, and SSP5-8.5) (SMHI-LENS; Wyser et al, 2021). Lin et al (2022) computed 110-member ensemble simulations for the historical period and SSP5-8.5 scenario using the FGOALS-g3 CGCM.…”

Section: Introductionmentioning

confidence: 99%

MIROC6 Large Ensemble (MIROC6-LE): experimental design and initial analyses

Shiogama,

Tatebe,

Hayashi

et al. 2023

Earth Syst. Dynam.

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Abstract. Single model initial-condition large ensembles (LEs) are a useful approach to understand the roles of forced responses and internal variability in historical and future climate change. Here, we produce one of the largest ensembles thus far using the MIROC6 coupled atmosphere–ocean global climate model (MIROC6-LE). The total experimental period of MIROC6-LE is longer than 76 000 years. MIROC6-LE consists of a long preindustrial control run, 50-member historical simulations, 8 single forcing historical experiments with 10 or 50 members, 5 future scenario experiments with 50 members and 3 single forcing future experiments with 50 members. Here, we describe the experimental design. The output data of most of the experiments are freely available to the public. This dataset would be useful to a wide range of research communities. We also demonstrate some examples of initial analyses. Specifically, we confirm that the linear additivity of the forcing-response relationship holds for the 1850–2020 trends of the annual mean values and extreme indices of surface air temperature and precipitation by analyzing historical fully forced runs and the sum of single forced historical runs. To isolate historical anthropogenic signals of annual mean and extreme temperature for 2000–2020 relative to 1850–1900, ensemble sizes of 4 and 15, respectively, are sufficient in most of the world. Historical anthropogenic signals of annual mean and extreme precipitation are significant with the 50-member ensembles in 76 % and 69 % of the world, respectively. Fourteen members are sufficient to examine differences in changes in annual mean values and extreme indices of temperature and precipitation between the shared socioeconomic pathways (ssp), ssp585 and ssp126, in most of the world. Ensembles larger than 50 members are desirable for investigations of differences in annual mean and extreme precipitation changes between ssp126 and ssp119. Historical and future changes in internal variability, represented by departures from the ensemble mean, are analyzed with a focus on the El Niño/Southern Oscillation (ENSO) and global annual mean temperature and precipitation. An ensemble size of 31 is large enough to detect ENSO intensification from preindustrial conditions to 1951–2000, from 1951–2000 to 2051–2100 in all future experiments, and from low- to high-emission future scenario experiments. The single forcing historical experiments with 27 members can isolate ENSO intensification due to anthropogenic greenhouse gas and aerosol forcings. Future changes in the global mean temperature variability are discernible with 23 members under all future experiments, while 50 members are not sufficient for detecting changes in the global mean precipitation variability in ssp119 and ssp126. We also confirm that these temperature and precipitation variabilities are not precisely analyzed when detrended anomalies from the long-term averages are used due to interannual climate responses to the historical natural forcing, which highlights the importance of large ensembles for assessing internal variability.

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“…Many of these SMILEs are listed in the Multi‐Model Large Ensemble Archive (https://www.cesm.ucar.edu/community-projects/mmlea; Deser et al., 2020). Next to MPI‐GE CMIP6, currently available SMILEs with CMIP6 forcing and at least 30 realizations for both the historical and future period are ACCESS‐ESM1.5 (Ziehn et al., 2020), CanESM5 (Swart et al., 2019), FGOALS (Lin et al., 2022), LENS2 (Rodgers et al., 2021), SMHI‐LENS (Wyser et al., 2021), SPEAR‐MED (Delworth et al., 2020), and MIROC6 (Tatebe et al., 2019). In comparison to the other CMIP6 SMILEs, MPI‐GE CMIP6 provides the most extensive high‐frequency output for the historical period and five different emission scenarios (Table 1).…”

Section: Introductionmentioning

confidence: 99%

The New Max Planck Institute Grand Ensemble With CMIP6 Forcing and High‐Frequency Model Output

Olonscheck,

Suarez‐Gutierrez,

Milinski

et al. 2023

J Adv Model Earth Syst

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Single‐model initial‐condition large ensembles are powerful tools to quantify the forced response, internal climate variability, and their evolution under global warming. Here, we present the CMIP6 version of the Max Planck Institute Grand Ensemble (MPI‐GE CMIP6) with currently 30 realizations for the historical period and five emission scenarios. The power of MPI‐GE CMIP6 goes beyond its predecessor ensemble MPI‐GE by providing high‐frequency output, the full range of emission scenarios including the highly policy‐relevant low emission scenarios SSP1‐1.9 and SSP1‐2.6, and the opportunity to compare the ensemble to complementary high‐resolution simulations. First, we describe MPI‐GE CMIP6, evaluate it with observations and reanalyzes and compare it to MPI‐GE. Then, we demonstrate with six application examples how to use the power of the ensemble to better quantify and understand present and future climate extremes, to inform about uncertainty in approaching Paris Agreement global warming limits, and to combine large ensembles and artificial intelligence. For instance, MPI‐GE CMIP6 allows us to show that the recently observed Siberian and Pacific North American heatwaves would only avoid reaching 1–2 years return periods in 2071–2100 with low emission scenarios, that recently observed European precipitation extremes are captured only by complementary high‐resolution simulations, and that 3‐hourly output projects a decreasing activity of storms in mid‐latitude oceans. Further, the ensemble is ideal for estimates of probabilities of crossing global warming limits and the irreducible uncertainty introduced by internal variability, and is sufficiently large to be used for infilling surface temperature observations with artificial intelligence.

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The Super-large Ensemble Experiments of CAS FGOALS-g3

Cited by 18 publications

References 72 publications

Increasing connections of the leading internal mode of the summertime Northwest Pacific subtropical anticyclone with preceding ENSO under greenhouse warming in FGOALS‐g3 super‐large ensemble

Increasing connections of the leading internal mode of the summertime Northwest Pacific subtropical anticyclone with preceding ENSO under greenhouse warming in FGOALS‐g3 super‐large ensemble

MIROC6 Large Ensemble (MIROC6-LE): experimental design and initial analyses

The New Max Planck Institute Grand Ensemble With CMIP6 Forcing and High‐Frequency Model Output

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