Distinct impacts of humidity profiles on physical properties and secondary formation of aerosols in Shanghai

Liu, Tongqiang; He, Qianshan; Chen, Yonghang; Liu, Jie; Liu, Qiong; Fu, Xinshu; Zhang, Jiating; Huang, Guan; Li, Rui

doi:10.1016/j.atmosenv.2021.118756

Cited by 8 publications

(2 citation statements)

References 85 publications

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“…However, some studies have argued that the above Eq. (7a) should only be applied to calculate the SVP over water surfaces (T>0 C), and a different equation (with over-ice correction) should be used for over-ice surfaces (T<0 C) (e.g., Murray, 1967;Liu et al, 2021). The over-ice form is expressed as below: According to Murray (1967), the combination of Eqs.…”

Section: Tetens's Formulamentioning

confidence: 99%

Brief Communication: Effects of different saturation vapor pressure calculations on simulated surface-subsurface hydrothermal regimes at a permafrost field site

Huang

Abolt

Bennett

2023

Preprint

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Abstract. Air saturation vapor pressure (SVP) can be calculated using different formulas, with or without over-ice correction. These different approaches result in variability that affects the simulation of surface-subsurface thermal-hydrological processes in cold regions; however, this topic has not been well documented to date. In this study, we compared the relative humidity (RH) downloaded and calculated from four data sources in Alaska based on five commonly used SVP formulas. RH, along with other meteorological indicators, was used to drive physically-based land surface models. Results show that RH is a sensitive parameter, and its biases from SVP with or without over-ice correction meaningfully impact model-based predictions of snow depth, sublimation, soil temperature, and active layer thickness.

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Section: Tetens's Formulamentioning

confidence: 99%

Brief Communication: Effects of different saturation vapor pressure calculations on simulated surface-subsurface hydrothermal regimes at a permafrost field site

Huang

Abolt

Bennett

2023

Preprint

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“…Since the calibration constant varies with altitude due to different vertical processes of moisture transportation, the information of the specific humidity for the entire altitude range, including the low values at higher altitudes, was used for the calibration [135][136][137][138][139].…”

Section: Water Vapor Mixing Ratio (Wvmr)mentioning

confidence: 99%

Profiling of Aerosols and Clouds over High Altitude Urban Atmosphere in Eastern Himalaya: A Ground-Based Observation Using Raman LIDAR

et al. 2023

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Profiles of aerosols and cloud layers have been investigated over a high-altitude urban atmosphere in the eastern Himalayas in India, for the first time, using a Raman LIDAR. The study was conducted post-monsoon season over Darjeeling (latitude 27°01′ N longitude 88°36′ E, 2200 masl), a tourist destination in north-eastern India. In addition to the aerosols and cloud characterization and atmospheric boundary layer detection, the profile of the water vapor mixing ratio has also been analyzed. Effects of atmospheric dynamics have been studied using the vertical profiles of the normalized standard deviation of RCS along with the water vapor mixing ratio. The aerosol optical characteristics below and above the Atmospheric Boundary Layer (ABL) region were studied separately, along with the interrelation of their optical and microphysical properties with synoptic meteorological parameters. The backscatter coefficient and the extinction coefficient were found in the range from 7.15×10−10 m−1 sr−1 to 3.01×10−5 m−1 sr−1 and from 1.02×10−5 m−1 to 2.28×10−3 m−1, respectively. The LIDAR ratio varies between 3.9 to 78.39 sr over all altitudes. The variation of the linear depolarization ratio from 0.19 to 0.32 indicates the dominance, of non-spherical particles. The periodicity observed in different parameters may be indicative of atmospheric wave phenomena. Cloud parameters, such as scattering coefficients, top and bottom height, and optical depth for different cloud phases, have been evaluated. A co-located Micro Rain Radar has been used with LIDAR for cloud life cycle study.

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Estimating spatio-temporal variability of aerosol pollution in Yunnan Province, China

Zhou

Yang²,

Wu³

et al. 2022

Atmospheric Pollution Research

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Distinct impacts of humidity profiles on physical properties and secondary formation of aerosols in Shanghai

Cited by 8 publications

References 85 publications

Brief Communication: Effects of different saturation vapor pressure calculations on simulated surface-subsurface hydrothermal regimes at a permafrost field site

Brief Communication: Effects of different saturation vapor pressure calculations on simulated surface-subsurface hydrothermal regimes at a permafrost field site

Profiling of Aerosols and Clouds over High Altitude Urban Atmosphere in Eastern Himalaya: A Ground-Based Observation Using Raman LIDAR

Estimating spatio-temporal variability of aerosol pollution in Yunnan Province, China

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