Lin Su

A comparison of HYSPLIT backward trajectories generated from two GDAS datasets.

The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model is widely used to generate backward trajectories in given starting locations. However, differences exist between trajectories generated from the model with different input datasets. In this study, backward trajectories in Hong Kong in the entire year of 2011 are derived by HYSPLIT model. Two sets of Global Data Assimilation System (GDAS) output data associated with different horizontal and vertical resolutions (GDAS1 and GDAS0P5) are used as drivers in an attempt to quantify the differences between the results and discover the underlying reasons responsible for discrepancy. The results reveal that the significant differences between back trajectories generated from the two GDAS datasets can be mainly attributed to different vertical velocity calculation methods due to the absence of vertical velocity in GDAS0P5 dataset. The HYSPLIT trajectories are also sensitive to the horizontal and vertical resolutions of the input meteorological data, but to lesser extents. Results of cluster analysis indicate that when the air mass is from the north, northeast, or west with a long-to-medium range, the HYSPLIT backward trajectories are sensitive to the vertical advection calculation method and data resolution, whereas when the air mass is from the south or southwest with a long range, the trajectories are more likely to remain unchanged with the shifting of vertical velocity or data resolution. By comparing the vertical velocities with the observations and the performance in retrieving PM contributions from different directions, we conclude that GDAS1 dataset is more plausible in backward trajectory analysis in the Pearl River Delta.

Sensitivities of WRF-Chem to dust emission schemes and land surface properties in simulating dust cycles during springtime over East Asia

The sensitivities of Weather Research and Forecasting model coupled with chemistry (WRF-Chem) to the Air Force Weather Agency (AFWA) and Shao2011 (S11) dust emission schemes, and to various land surface properties generated from United States Geological Survey (USGS) and Beijing Normal University (BNU) soil data over East Asia for spring 2012, are examined in this study. The results show that the dust emissions generated with the S11 scheme are 2–5 times that generated with the AFWA emission scheme, with emissions ranging from 0.2–1 Tg/d over East Asia in the relevant period. The AFWA emission scheme omits almost the entire Gobi desert and produces low dust emissions, whereas large amounts of dust emission in this region are produced with the S11 emission scheme, regardless of whether USGS or BNU soil data are used. The surface particulate matter 10 (PM10) concentrations are reasonably well reproduced by the model with different configurations. However, the S11 emission scheme has better performance in simulating the surface PM10 concentrations than the AFWA scheme, especially near the Gobi desert. Comparisons with satellite-based observations suggest that WRF-Chem gives better performance with S11 emission scheme in reproducing the horizontal and vertical distribution of aerosol optical properties. The discrepancy between the performances of the AFWA and S11 emission schemes is mainly due to the underestimation of the dust emission over the Gobi desert by the AFWA scheme, which scales the dust emission directly based on the erodibility factor, indicating that the erodibility factor over the Gobi desert is highly underestimated and highlighting an urgent need to improve the erodibility data set.

Resolving the impact of stratosphere‐to‐troposphere transport on the sulfur cycle and surface ozone over the Tibetan Plateau using a cosmogenic 35S tracer

The Himalayas were recently identified as a global hot spot for deep stratosphere-to-troposphere transport (STT) in spring. Although the STT in this region may play a vital role in tropospheric chemistry, the hydrological cycle and aquatic ecosystems in Asia, there is no direct measurement of a chemical stratospheric tracer to verify and evaluate its possible impacts. Here we use cosmogenic S-35 as a tracer for air masses originating in the stratosphere and transported downward. We measure concentrations of S-35 in fresh surface snow and river runoff samples collected from Mount Everest in April 2013 to be more than 10 times higher than previously reported by any surface measurement, in support of the Himalayas as a gateway of springtime STT. In light of this result, measurements of (SO2)-S-35 and (SO42-)-S-35 at Nam Co in spring 2011 are reanalyzed to investigate the magnitudes of stratospheric air masses from the Himalayas to the tropospheric sulfur cycle and surface O-3 level over the Tibetan Plateau. A simple one-box model reveals that the oxidative lifetime of SO2 is reduced in aged STT plumes. Triple oxygen isotopic measurements of sulfate samples suggest that enhanced O-3 levels may shift the oxidation pathway of SO2 in the troposphere, which may be constrained by further intensive sampling and measurements. Comparison with surface O-3 measurements and traditional meteorological tracing methods shows that S-35 is a potentially unique and sensitive tracer to quantify the contribution of stratospheric air to surface O-3 levels in fresh or aged STT plumes.

Detection of deep stratospheric intrusions by cosmogenic 35S

Significance The recently revised stricter US National Ambient Air Quality Standard for ground-level ozone (O3) requires precise methods to screen “exceptional events,” such as naturally occurring deep stratospheric intrusions. However, existing approaches used in detecting stratospheric intrusions and evaluating their contributions to ground-level O3 enhancement are not satisfactory. Here, we introduce the use of cosmogenic 35S to assist in such quantifications. We measured the highest 35S concentration in natural sulfate aerosols ever reported in the literature during deep stratospheric intrusions. The downward transport of stratospheric O3 is confirmed by air quality data and meteorological analysis, showing the high sensitivity of 35S as a stratospheric tracer and its utility to understand atmospheric transport and chemistry processes. The extent to which stratospheric intrusions on synoptic scales influence the tropospheric ozone (O3) levels remains poorly understood, because quantitative detection of stratospheric air has been challenging. Cosmogenic 35S mainly produced in the stratosphere has the potential to identify stratospheric air masses at ground level, but this approach has not yet been unambiguously shown. Here, we report unusually high 35S concentrations (7,390 atoms m−3; ∼16 times greater than annual average) in fine sulfate aerosols (aerodynamic diameter less than 0.95 µm) collected at a coastal site in southern California on May 3, 2014, when ground-level O3 mixing ratios at air quality monitoring stations across southern California (43 of 85) exceeded the recently revised US National Ambient Air Quality Standard (daily maximum 8-h average: 70 parts per billion by volume). The stratospheric origin of the significantly enhanced 35S level is supported by in situ measurements of air pollutants and meteorological variables, satellite observations, meteorological analysis, and box model calculations. The deep stratospheric intrusion event was driven by the coupling between midlatitude cyclones and Santa Ana winds, and it was responsible for the regional O3 pollution episode. These results provide direct field-based evidence that 35S is an additional sensitive and unambiguous tracer in detecting stratospheric air in the boundary layer and offer the potential for resolving the stratospheric influences on the tropospheric O3 level.

Numerical modeling of a strong dust event over the south China region in March 2010

The mesoscale model WRF-Chem was used to simulate a severe dust storm event that occurred in March 2010. The storm affected a vast area of East Asia, including the south China region and Hong Kong. This southern region is rarely affected by dust weather. The performance of the WRF-Chem was evaluated by observational data such as the National Center for Atmospheric Research reanalysis data for atmospheric circulation, PM10 concentration from various ground stations, and satellite images of Moderate Resolution Imaging Spectroradiometer and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations. The dependence of the model’s performance on certain important parameterizations was examined in this study. For this particular dust storm event, the model results suggest that the simulation is not very sensitive to certain key physical parameterizations such as threshold wind speed of dust emission and the choice of land surface model. In general, the WRF-Chem is capable of capturing the key physical processes for this severe dust event. The analysis of the dust transport fluxes suggests that the dust transport to the south China region is mainly from the north, although there is a mountainous region in the northern part of the south China region.

Investigating the role of dust in ice nucleation within clouds and further effects on the regional weather system over East Asia – Part 1: model development and validation

The GOCART–Thompson microphysics scheme coupling the GOCART aerosol model and the aerosol-aware Thompson–Eidhammer microphysics scheme has been implemented in the WRF-Chem to quantify and evaluate the effect of dust on the ice nucleation process in the atmosphere by serving as ice nuclei (IN). The performance of the GOCART–Thompson microphysics scheme in simulating the effect of dust in atmospheric ice nucleation is then evaluated over East Asia during spring, a typical dust-intensive season, in 2012. Based upon the dust emission reasonably reproduced by WRF-Chem, the effect of dust on atmospheric cloud ice water content is well reproduced. With abundant dust particles serving as IN, the simulated ice water mixing ratio and ice crystal number concentration increases by 15 and 7 % on average over the dust source region and downwind areas during the investigated period. The comparison with the ice water path from satellite observations demonstrated that the simulation of the cloud ice profile is substantially improved by considering the indirect effect of dust particles in the simulations. Additional sensitivity experiments are carried out to optimize the parameters in the ice nucleation parameterization in the GOCART–Thompson microphysics scheme. Results suggest that lowering the threshold relative humidity with respect to ice to 100 % for the ice nucleation parameterization leads to further improvement in cloud ice simulation.