Intercomparison of two model climates simulated by a unified weather-climate model system (GRIST), part I: mean state.
Saved in:
| Title: | Intercomparison of two model climates simulated by a unified weather-climate model system (GRIST), part I: mean state. |
|---|---|
| Authors: | Fu, Zhen1,2 (AUTHOR), Zhang, Yi1,2,3 (AUTHOR) zhangyi_fz@piesat.cn, Li, Xiaohan4 (AUTHOR), Rong, Xinyao5 (AUTHOR) |
| Source: | Climate Dynamics. Jul2024, Vol. 62 Issue 7, p6273-6291. 19p. |
| Subjects: | Atmospheric models, Statistical equilibrium, Radiative forcing, Ice clouds, Weather forecasting |
| Abstract: | This study made an intercomparison of two model climates, simulated by a unified weather-climate model system (GRIST), under the Atmospheric Model Intercomparison Project (AMIP) experimental protocol. These two model AMIP simulations with PhysW and PhysC (AMIPW and AMIPC hereafter) are configured with different physics suites, but both generated by a unified dynamical core framework. PhysW and PhysC are originally designed for weather forecasting and climate simulation, respectively. Both AMIPW and AMIPC reach statistical equilibrium in the climate integration. They overall produce comparable model climates, while distinctive bias features also exist. Compared with the AMIP experiments of 54 climate models from CMIP6, both AMIPW and AMIPC demonstrate competitive performances in the mean state simulations. They capture the observed spatial distribution of large-scale circulation and precipitation, as well as replicate the seasonal migration and primary frequency-intensity structures of precipitation. However, due to different parameterization schemes such as convection and microphysics being utilized, the most notable differences between the models lie in processes related to moist physics. For instance, AMIPW tends to overestimate (underestimate) global shortwave (longwave) cloud radiative forcing, while AMIPC provides a more balanced estimation, with a significantly stronger longwave cloud radiative forcing over the tropics. In addition, AMIPC well reproduces cloud fraction and liquid content but underestimates cloud ice water content, whereas AMIPW significantly overestimates all these variables. Overall, the similarity between two model climates is higher than their discrepancy. The results demonstrate that the extent to which the selection of two distinct physics suites can influence the simulated model climate, within a unified model system. [ABSTRACT FROM AUTHOR] |
| Copyright of Climate Dynamics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | This study made an intercomparison of two model climates, simulated by a unified weather-climate model system (GRIST), under the Atmospheric Model Intercomparison Project (AMIP) experimental protocol. These two model AMIP simulations with PhysW and PhysC (AMIPW and AMIPC hereafter) are configured with different physics suites, but both generated by a unified dynamical core framework. PhysW and PhysC are originally designed for weather forecasting and climate simulation, respectively. Both AMIPW and AMIPC reach statistical equilibrium in the climate integration. They overall produce comparable model climates, while distinctive bias features also exist. Compared with the AMIP experiments of 54 climate models from CMIP6, both AMIPW and AMIPC demonstrate competitive performances in the mean state simulations. They capture the observed spatial distribution of large-scale circulation and precipitation, as well as replicate the seasonal migration and primary frequency-intensity structures of precipitation. However, due to different parameterization schemes such as convection and microphysics being utilized, the most notable differences between the models lie in processes related to moist physics. For instance, AMIPW tends to overestimate (underestimate) global shortwave (longwave) cloud radiative forcing, while AMIPC provides a more balanced estimation, with a significantly stronger longwave cloud radiative forcing over the tropics. In addition, AMIPC well reproduces cloud fraction and liquid content but underestimates cloud ice water content, whereas AMIPW significantly overestimates all these variables. Overall, the similarity between two model climates is higher than their discrepancy. The results demonstrate that the extent to which the selection of two distinct physics suites can influence the simulated model climate, within a unified model system. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 09307575 |
| DOI: | 10.1007/s00382-024-07205-2 |
