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Xiaoyan Wang
and
Kaicun Wang

Abstract

Boundary layer height (BLH) significantly impacts near-surface air quality, and its determination is important for climate change studies. Integrated Global Radiosonde Archive data from 1973 to 2014 were used to estimate the long-term variability of the BLH based on profiles of potential temperature, relative humidity, and atmospheric refractivity. However, this study found that there was an obvious inhomogeneity in the radiosonde-derived BLH time series because of the presence of discontinuities in the raw radiosonde dataset. The penalized maximal F test and quantile-matching adjustment were used to detect the changepoints and to adjust the raw BLH series. The most significant inhomogeneity of the BLH time series was found over the United States from 1986 to 1992, which was mainly due to progress made in sonde models and processing procedures. The homogenization did not obviously change the magnitude of the daytime convective BLH (CBLH) tendency, but it improved the statistical significance of its linear trend. The trend of nighttime stable BLH (SBLH) is more dependent on the homogenization because the magnitude of SBLH is small, and SBLH is sensitive to the observational biases. The global daytime CBLH increased by about 1.6% decade−1 before and after homogenization from 1973 to 2014, and the nighttime homogenized SBLH decreased by −4.2% decade−1 compared to a decrease of −7.1% decade−1 based on the raw series. Regionally, the daytime CBLH increased by 2.8%, 0.9%, 1.6%, and 2.7% decade−1 and the nighttime SBLH decreased significantly by −2.7%, −6.9%, −7.7%, and −3.5% decade−1 over Europe, the United States, Japan, and Australia, respectively.

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Xiaoyan Wang
and
Renhe Zhang
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Xiaoyan Wang
and
Renhe Zhang
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Xiaoyan Wang
,
Robert E. Dickinson
,
Liangyuan Su
,
Chunlüe Zhou
, and
Kaicun Wang

Abstract

The recent severe and frequent PM2.5 (i.e., fine particles smaller than 2.5 µm) pollution in China has aroused unprecedented public concern. The first two years of PM2.5 measurements in China are reported and compared with those of Europe and the United States. The average PM2.5 concentration in China is approximately 5 times that over Europe and America. The contribution of atmospheric dispersion to such air quality is evaluated in this study. Air stagnation or its absence is a good indicator of the atmosphere’s capability to disperse its pollutants, but the NOAA definition of an air stagnation event is found to not be applicable to China since it depends on vertical mixing that is weakened in China by the effects of terrain. To address this deficiency, a new threshold for air stagnation events is proposed that depends on the 10-m wind speed, boundary layer height, and occurrence of precipitation. This newly defined air stagnation closely tracks the day-to-day variation of PM2.5 concentrations. Such events are more frequent over China than over Europe and the United States during autumn and winter, especially over the Sichuan basin and Jing-Jin-Ji region of China. If China had the same frequency of air stagnation as the United States or Europe, 67% and 82% of its stations would improve their current air quality during autumn and winter (e.g., an average of 12% decrease in PM2.5 concentrations for the Jing-Jin-Ji region in wintertime). Its severe pollution and frequent air stagnation conditions make controls on emission less effective in China than elsewhere.

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Huawu Wu
,
Cicheng Zhang
,
Xiao-Yan Li
,
Congsheng Fu
,
Haohao Wu
,
Pei Wang
, and
Jinzhao Liu

Abstract

The northeastern Tibetan Plateau is located in a climatic junction, which is considered an ideal region to explore the interactions between the summer monsoons and the westerly circulation patterns. However, to date, the needed long-term precipitation-based isotopic dataset is too limited to predict the interactions and patterns. This paper presents an evaluation of hydrometeorological processes and climate dynamics in the northeastern Tibetan Plateau based on a 7-yr precipitation isotope dataset covering the summer monsoon periods from 2012 to 2018. Results illustrated remarkable seasonal isotopic variability, characterized by lower δ 18O and δ 2H values in June with an average of −10‰ and −66.7‰, respectively. Higher δ 18O and δ 2H values in July averaged −6.7‰ and −39.5‰, respectively. This clear isotopic variability is largely related to seasonal changes of moisture sources and hydrometeorological processes. These precipitation isotopic values were primarily determined by the amount of precipitation, relative humidity, and convective activity, but showed no correlation with air temperature. Backward trajectory model results showed that Xinjiang, northern China, the Arctic, central Asia, and the South China Sea (SCS) were the primary sources of precipitation for the study site with varying seasonal contributions. The maritime moisture source of the SCS primarily resulted in the lowest precipitation δ 18O values during the prevailing summer monsoon, which is mainly as a result of the strong convective activity and rainout processes along the air trajectory. The higher average deuterium excess (d-excess) value of precipitation in September indicated continental sources from central Asia (e.g., 75.4%) as land vapor recycling increases d-excess concentration in the atmosphere. These findings provide further insights into the main factors of precipitation isotopic variability related to atmospheric processes along the trajectory and the relevant factors in the monsoon regions.

Significance Statement

Recently, scientists and policy makers have become aware that Tibetan hydroclimate variability provides evidence of changes in regional and global circulation patterns that may result in the intensification of climate-driven extremes. However, these studies largely depend on crucial paleoclimate records of past precipitation isotopes in monsoon regions, which contain great uncertainties because of the complex relationship between climatic variability and precipitation isotopes. This study first presented a 7-yr isotopic dataset to understand the hydrological processes and climate dynamics controlling the isotopic variability in the northeastern Tibetan Plateau. The findings reveal important factors on the isotopic variability associated with atmospheric processes and their key climatic variables, which can enhance our interpretation of the paleoclimate records in monsoon regions.

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Xiaoyan Zhang
,
Jianping Huang
,
Gang Li
,
Yongwei Wang
,
Cheng Liu
,
Kaihui Zhao
,
Xinyu Tao
,
Xiao-Ming Hu
, and
Xuhui Lee

Abstract

The Weather Research and Forecasting (WRF) Model is used in large-eddy simulation (LES) mode to investigate a lake-breeze case occurring on 12 June 2012 over the Lake Taihu region of China. Observational data from 15 locations, wind profiler radar, and the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to evaluate the WRF nested-LES performance in simulating lake breezes. Results indicate that the simulated temporal and spatial variations of the lake breeze by WRF nested LES are consistent with observations. The simulations with high-resolution grid spacing and the LES scheme have a high correlation coefficient and low mean bias when evaluated against 2-m temperature, 10-m wind, and horizontal and vertical lake-breeze circulations. The atmospheric boundary layer (ABL) remains stable over the lake throughout the lake-breeze event, and the stability becomes even stronger as the lake breeze reaches its mature stage. The improved ABL simulation with LES at a grid spacing of 150 m indicates that the non-LES planetary boundary layer parameterization scheme does not adequately represent subgrid-scale turbulent motions. Running WRF fully coupled to a lake model improves lake-surface temperature and consequently the lake-breeze simulations. Allowing for additional model spinup results in a positive impact on lake-surface temperature prediction but is a heavy computational burden. Refinement of a water-property parameter used in the Community Land Model, version 4.5, within WRF and constraining the lake-surface temperature with observational data would further improve lake-breeze representation.

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