CAS FGOALS-f3-L Model Datasets for CMIP6 Historical Atmospheric Model Intercomparison Project Simulation

He, Bian; Bao, Qing; Wang, Xiaocong; Zhou, Linjiong; Wu, Xiaofei; Liu, Yimin; Wu, Guoxiong; Chen, Kangjun; He, Sicheng; Hu, Wenting; Li, Jiandong; Li, Jinxiao; Nian, Guokui; Wang, Lei; Yang, Jing; Zhang, Minghua; Zhang, Xiaoqi

doi:10.1007/s00376-019-9027-8

Cited by 119 publications

(57 citation statements)

References 40 publications

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“…All experiments are integrated from 1970 to 2014, where the first nine years are considered as the spin-up time, and the results from 1979 to 2014 are provided for analysis. These experimental settings are the same as those for the AMIP r1i1p1f1 experiment in DECK (the Diagnostic, Evaluation and Characterization of Klima), as documented in He et al (2019).…”

Section: Methodsmentioning

confidence: 99%

“…To understand the possible influence of TIP thermal and mechanical forcings on extreme events and its use in downscaling studies, potential uses may need to compare these experiments to the reference run. We recommend the CMIP6 DECK AMIP r1i1p1f1 experiment by using the CAS FGOALS-f3-L model as the reference run since these experiments share the same model and have a consistent integration method and initial state (He et al, 2019). Here, we show the climate mean responses of the TIP thermal and dynamical effect on the Asian summer monsoon in Fig.…”

Section: Usage Notesmentioning

confidence: 99%

“…The configuration of the CMIP6 version of the CAS FGOALS-f3-L model is introduced in the description paper of the AMIP datasets (He et al, 2019). For convenience for those using only the GMMIP datasets, we briefly reintro-duce the model here.…”

Section: Model Introductionmentioning

confidence: 99%

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CAS FGOALS-f3-L Model Datasets for CMIP6 GMMIP Tier-1 and Tier-3 Experiments

Liu

et al. 2019

Adv. Atmos. Sci.

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The Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System (FGOALS-f3-L) model datasets prepared for the sixth phase of the Coupled Model Intercomparison Project (CMIP6) Global Monsoons Model Intercomparison Project (GMMIP) Tier-1 and Tier-3 experiments are introduced in this paper, and the model descriptions, experimental design and model outputs are demonstrated. There are three simulations in Tier-1, with different initial states, and five simulations in Tier-3, with different topographies or surface thermal status. Specifically, Tier-3 contains four orographic perturbation experiments that remove the Tibetan-Iranian Plateau, East African and Arabian Peninsula highlands, Sierra Madre, and Andes, and one thermal perturbation experiment that removes the surface sensible heating over the Tibetan-Iranian Plateau and surrounding regions at altitudes above 500 m. These datasets will contribute to CMIP6's value as a benchmark to evaluate the importance of long-term and short-term trends of the sea surface temperature in monsoon circulations and precipitation, and to a better understanding of the orographic impact on the global monsoon system over highlands.

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Section: Methodsmentioning

confidence: 99%

Section: Usage Notesmentioning

confidence: 99%

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CAS FGOALS-f3-L Model Datasets for CMIP6 GMMIP Tier-1 and Tier-3 Experiments

Liu

et al. 2019

Adv. Atmos. Sci.

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“…In addition, integrations of Tier 3 also provide another potential way for decadal predictions. These two models have the same atmospheric and land components: FAMIL (Bao et al 2019;He et al 2019;Li et al 2019;He et al 2020) and CLM4. Regarding the Tier 1 and 3 experiments, the sea-ice and ocean components are data models.…”

Section: Fgoals-f3-h and Fgoals-f3-lmentioning

confidence: 99%

“…The high-resolution and low-resolution (standard) versions of the Chinese Academy of Science FGOALS climate system model, CAS FGOALS-f3-H (FGOALS-f3-H for short) and CAS FGOALS-f3-L (FGOALS-f3-L for short) respectively, were developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Beijing, China (Bao et al 2019;He et al 2019;Li et al 2019;Bao and Li 2020). The model completed the simulations of HighResMIP Tier 1 in early 2019, and finished the projection of HighResMIP Tier 3 in early 2020.…”

Section: Introductionmentioning

confidence: 99%

CAS FGOALS-f3-H and CAS FGOALS-f3-L outputs for the high-resolution model intercomparison project simulation of CMIP6

Bao

Liu

et al. 2020

Atmospheric and Oceanic Science Letters

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The High Resolution Model Intercomparison Project (HighResMIP) is a unique model intercomparison project in phase 6 of the Coupled Model Intercomparison Project (CMIP6), which is focused on the impact of horizontal resolutions. The outputs of the high-and low-resolution versions of CAS FGOALS-f3-H and CAS FGOALS-f3-L for the experiments of the HighResMIP simulations in CMIP6 are described in this paper. The models and their configurations, experimental settings, and postprocessing methods are all introduced. CAS FGOALS-f3-H, with a 0.25° horizontal resolution, and CAS FGOALS-f3-L, with a 1° horizontal resolution, were forced by the standard external conditions, and two coordinated sets of simulations were conducted for 1950-2014 and 2015-50 with the Experiment IDs of 'highresSST-present' and 'highresSST-future', respectively. The model outputs contain multiple time scales including the required hourly mean, three-hourly mean, six-hourly transient, daily mean, and monthly mean datasets. It is reported that the 0.25° CAS FGOALS-f3-H successfully simulates some of the key challenges in climate modeling, including the average lifetime of tropical cyclones, particularly in the western parts of the northern Pacific Ocean, and the diurnal cycle of hourly precipitation. These datasets will contribute to the benchmarking of current models for CMIP, and studies of the impacts of horizontal resolutions on climate modeling issues.

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How well do forecast models represent observed long‐lived Rossby wave packets during southern hemisphere summer?

Perez

Barreiro

2023

Atmospheric Science Letters

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Rossby wave packets (RWPs), are atmospheric perturbations linked to the occurrence of extreme weather events such as heatwaves, extratropical cyclone development and other equally destructive phenomena. Under certain circumstances, these packets can last from several days to 2–3 weeks in the atmosphere. Therefore, forecast models should be able to correctly predict their formation and development to enhance extreme weather events prediction from 10 to 30 days in advance. In this study, we assess whether the NCEP and IAP‐CAS sub‐seasonal forecast models can predict the evolution of observed RWPs that last more than 8 days (long‐lived RWPs or LLRWPs) during southern hemisphere summer. Results show that the NCEP (IAP‐CAS) model forecasts LLRWPs that appear eastward (westward) from the observed LLRWPs. Both models forecasted LLRWPs that rapidly lose energy after the 6th–7th lead day of simulation, which could limit LLRWPs prediction to the synoptic time scale. Additionally, both models better forecast LLRWPs when the packets manifest in the eastern Pacific. Southern Annular mode (SAM) and El Niño Southern‐Oscillation (ENSO) do not seem to exert a large influence in the representation of LLRWPs. Nevertheless, during the best LLRWPs forecasts, the observed circulation anomalies signal the manifestation of negative SAM events. In contrast, both forecast models struggle at forecasting LLRWPs when a blocking situation develops to the South of Australia. Lastly, an inactive Madden Julian Oscillation (MJO) seems to favor the development of accurate LLRWPs forecasts, whereas during phases 3, 5 in the NCEP model and 3, 8 for IAP‐CAS, the models struggle at forecasting LLRWPs.

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CAS FGOALS-f3-L Model Datasets for CMIP6 Historical Atmospheric Model Intercomparison Project Simulation

Cited by 119 publications

References 40 publications

CAS FGOALS-f3-L Model Datasets for CMIP6 GMMIP Tier-1 and Tier-3 Experiments

CAS FGOALS-f3-L Model Datasets for CMIP6 GMMIP Tier-1 and Tier-3 Experiments

CAS FGOALS-f3-H and CAS FGOALS-f3-L outputs for the high-resolution model intercomparison project simulation of CMIP6

How well do forecast models represent observed long‐lived Rossby wave packets during southern hemisphere summer?

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