Climatological changes in East Asian winter monsoon circulation in a warmer future

Wu, Chi‐Hua; Shiu, Chengshi; Chen, Yiying; Tsai, I‐Chun; Lee, Shih‐Yu

doi:10.1016/j.atmosres.2022.106593

Cited by 5 publications

(2 citation statements)

References 44 publications

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“…The influence of aerosols on the EAWM, as examined herein, pertains to the effects of aerosols within the context of global warming. Nonetheless, it is imperative to acknowledge that the forcing by greenhouse gases (attributable to global warming) may potentially modify the dynamics of the EAWM (He, 2023; Wu et al, 2023; Xu & Fan, 2021; Xu et al, 2016). For instance, Xu and Fan (2021), through their analysis of CMIP5 data, posited that the circulation associated with the EAWM could exhibit minimal alteration under conditions of global warming, as inferred from the 850 hPa meridional wind patterns.…”

Section: Discussionmentioning

confidence: 99%

Aerosol impacts on the East Asian winter monsoon: Insights from TaiESM1 and CMIP6 simulations

Tsai,

Yang,

Shiu

et al. 2024

Intl Journal of Climatology

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The East Asian winter monsoon (EAWM) is an important climate pattern in Southeast Asia. This study delved into the aerosol effects on the EAWM by analysing simulations conducted with the Taiwan Earth System Model version 1 (TaiESM1) model, part of the Coupled Model Intercomparison Project Phase 6 (CMIP6). Our assessment, validated against observational and reanalysis data, revealed that TaiESM1 effectively replicates the robust circulation of the EAWM and aerosol concentrations, placing its performance above average level among CMIP6 models. Notably, the simulated global mean aerosol optical thickness exhibited an approximately 20% increase from 1850 to 2014. The increased aerosols corresponded to a weakened Aleutian Low and an intensified Siberian High, leading to a weakened EAWM in the lower atmosphere over extratropical areas. In addition, the cooling across the Northern Hemisphere might affect enhanced northerly winds at approximately 10°N, which are situated in the southern part of the EAWM. An analysis of the near‐surface temperature budget indicated that the aerosol‐induced cooling in East China and India was primarily driven by changes in shortwave and longwave radiation fluxes, albeit slightly offset by sensible heat and latent heat fluxes. Furthermore, our study also reveals that while the mechanisms through which anthropogenic aerosols affect the northern portion of the EAWM vary across most CMIP6 models, their impacts on the tropical region remain consistent.

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Section: Discussionmentioning

confidence: 99%

Aerosol impacts on the East Asian winter monsoon: Insights from TaiESM1 and CMIP6 simulations

Tsai,

Yang,

Shiu

et al. 2024

Intl Journal of Climatology

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“…For the definition of the four quarters, this study follows the standard seasonal definition [40]. The average temperature profiles were also calculated.…”

Section: Deadband Regulation Modelmentioning

confidence: 99%

A Microwave Radiometer Residual Inversion Neural Network Based on a Deadband Conditioning Model

Zhao,

Wu,

et al. 2023

JMSE

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Microwave radiometers are passive remote sensing devices that are widely used in marine atmospheric observations. The accuracy of its inversion of temperature and humidity profiles is an important indicator of its performance. Back Propagation (BP) neural networks are widely used in the study of microwave radiometer inversion problems. However, the BP network which is carried by the radiometer inversion suffers from profile data collapse. To address this, this study introduced a residual network to improve the accuracy of water vapor vertical profiles. Aiming at the problem of large inversion temperature error due to the effect of turbulence on the light-travel phase induced by stationary fronts along the seashore in the subtropical monsoon climate region, we used historical data to establish the seasonal a priori mean profile and design a dead-zone residual adjustment model. The accuracy of the residual network and the deadband-adjusted residual network was verified using the meteorological records of the Taizhou region from 2013–2018, with the experimental data and BP hierarchical network as the comparison term. We found no data collapse in the temperature and humidity profile inversion results of the residual network. Relative to the initial BP hierarchical algorithm, where the error of water vapor in the range 6–10 km was reduced by 80%, the dead zone residual adjustment model in the inverse-temperature phenomenon reduced the sum of squares error by 21%, compared with the ordinary residual network inversion results. Our findings provide new insights into the accuracy improvement of radiometer remote sensing.

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Interannual variation of the initial formation of the Siberian High: the role of the North Atlantic sea surface temperatures and the high-latitude Central Eurasia snow-cover conditions

Chen,

et al. 2024

Clim Dyn

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Climatological changes in East Asian winter monsoon circulation in a warmer future

Cited by 5 publications

References 44 publications

Aerosol impacts on the East Asian winter monsoon: Insights from TaiESM1 and CMIP6 simulations

Aerosol impacts on the East Asian winter monsoon: Insights from TaiESM1 and CMIP6 simulations

A Microwave Radiometer Residual Inversion Neural Network Based on a Deadband Conditioning Model

Interannual variation of the initial formation of the Siberian High: the role of the North Atlantic sea surface temperatures and the high-latitude Central Eurasia snow-cover conditions

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