Impacts of Aerosol−Radiation Interactions on the Wintertime Particulate Pollution under Different Synoptic Patterns in the Guanzhong Basin,China

The effects of aerosol-radiation interactions(ARI)are not only important for regional and global climate,but they can also drive particulate matter(PM)pollution.In this study,the ARI contribution to the near-surface fine PM(PM_(2.5))concentrations in the Guanzhong Basin(GZB)is evaluated under four unfavorable synoptic patterns,including“northlow”,“transition”,“southeast-trough”,and“inland-high”,based on WRF-Chem model simulations of a persistent heavy PM pollution episode in January 2019.Simulations show that ARI consistently decreases both solar radiation reaching down to the surface(SWDOWN)and surface temperature(TSFC),which then reduces wind speed,induces sinking motion,and influences cloud formation in the GZB.However,large differences under the four synoptic patterns still exist.The average reductions of SWDOWN and daytime TSFC in the GZB range from 15.2%and 1.04°C in the case of the“transition”pattern to 26.7%and 1.69°C in the case of the“north-low”pattern,respectively.Furthermore,ARI suppresses the development of the planetary boundary layer(PBL),with the decrease of PBL height(PBLH)varying from 18.7%in the case of the“transition”pattern to 32.0%in the case of the“north-low”pattern.The increase of daytime near-surface PM_(2.5)in the GZB due to ARI is 12.0%,8.1%,9.5%,and 9.7%under the four synoptic patterns,respectively.Ensemble analyses also reveal that when near-surface PM_(2.5)concentrations are low,ARI tends to lower PM_(2.5)concentrations with decreased PBLH,which is caused by enhanced divergence or a transition from divergence to convergence in an area.ARI contributes 15%-25%toward the near-surface PM_(2.5)concentrations during the severe PM pollution period under the four synoptic patterns.

气溶胶对降水影响的现象和机制

Aerosols greatly influence precipitation characteristics,thereby impacting the regional climate and human life.As an indispensable factor for cloud formation and a critical radiation budget regulator,aerosols can affect precipitation intensity,frequency,geographical distribution,area,and time.However,discrepancies exist among current studies due to aerosol properties,precipitation types,the vertical location of aerosols and meteorological conditions.The development of technology has driven advances in current research,but understanding the aerosol effects on precipitation remain complex and challenging.This paper revolves around the following topics from the two perspectives of Aerosol-Radiation Interaction(ARI)and Aerosol-Cloud Interaction(ACI):(1)the influence of different vertical locations of absorbing/scattering aerosols on the atmospheric thermal structure;(2)the fundamental theories of ARI reducing surface wind speed,redistributing water vapour and energy,and then modulating precipitation intensity;(3)different aerosol types(absorbing versus scattering)and aerosol concentrations causing different precipitation diurnal and weekly variations;(4)microphysical processes(cloud water competition,invigoration effect,and evaporation cooling)and observational evidence of different effects of aerosols on precipitation intensity,including enhancing,inhibiting,and transitional effects from enhancement to suppression;and(5)how meteorology,water vapor and dynamics influencing the effect of ACI and ARI on precipitation.In addition,this review lists the existing issues and future research directions for attaining a more comprehensive understanding of aerosol effects on precipitation.Overall,this review advances our understanding of aerosol effects on precipitation and could guide the improvement of weather and climate models to predict complex aerosol-precipitation interactions more accurately.

Aerosol as a critical factor causing forecast biases of air temperature in global numerical weather prediction models

Weather prediction is essential to the daily life of human beings. Current numerical weather prediction models such as the Global Forecast System(GFS) are still subject to substantial forecast biases and rarely consider the impact of atmospheric aerosol, despite the consensus that aerosol is one of the most important sources of uncertainty in the climate system. Here we demonstrate that atmospheric aerosol is one of the important drivers biasing daily temperature prediction. By comparing observations and the GFS prediction, we find that the monthly-averaged bias in the 24-h temperature forecast varies between ± 1.5 ℃ in regions influenced by atmospheric aerosol. The biases depend on the properties of aerosol, the underlying land surface, and aerosol–cloud interactions over oceans. It is also revealed that forecast errors are rapidly magnified over time in regions featuring high aerosol loadings. Our study provides direct ‘‘observational" evidence of aerosol’s impacts on daily weather forecast, and bridges the gaps between the weather forecast and climate science regarding the understanding of the impact of atmospheric aerosol.