Atmospheric aerosol affects electromagnetic radiation transmission through scattering and absorption, which has great influence on optical satellite remote sensing, environmental monitoring, climate forcing and aerosol-cloud interaction. In2021, based on the data collected in the Yellow Sea and the South China Sea near the coast, we developed the coast aerosol model (CAM) to predict the aerosols size distribution under coastal environments. This work makes a comprehensive model evaluation for the CAM with the atmospheric aerosol observation results at the South China Sea coastal station (Maoming) in November 2023. The comparison results show that the CAM can effectively describe the characteristics of aerosol (number concentration, particle size distribution and extinction coefficient) in this area. During the observation period, the average error of prediction results of aerosol concentration is around 20.6%, indicating that the CAM is promising in prediction coastal aerosol microphysical and optical properties.
As an important part of the atmospheric environment, aerosols play a critical role in the study of the relationship between light and radiation. However, due to the complex spatiotemporal distribution of aerosols, it is much difficult to measure their microphysical properties and to determine their optical properties in coastal areas. In this paper, basic meteorological elements (e.g., wind speed, temperature, humidity) are simulated with the numerical weather forecasting (WRF) model. Then, the coastal aerosol model (CAM) together with the observation data is used to simulate the aerosol particle size distribution (APSD) and extinction coefficient for the coastal environment of Qingdao. Finally, data measured by the automatic weather station and particle counter in the coastal area are compared to their corresponding simulations. According to the comparisons results, temperature simulations were higher from an overall perspective (<2°C) with the correlation coefficient larger than 0.96; humidity simulations were comparatively lower on the 11th and 12th day (<10%) than those onthe 13th day (<20%), but the correlation coefficient was still larger than 0.8. With the meterological parameters simulations, the CAM model was used to predict the APSDs. It is founded that simulations for large particles are generally larger, while those for giant particles are generally smaller, but the simulated temperature, humidity, APSD and extinction coefficient are very consistent with their corresponding measurements. The method established in this paper is promising for the simulation and forecast of both the meteorological elements and aerosol microphysical properties.
In order to facilitate scientific applications of aerosol products from geostationary satellite such as Himawari-8 (H-8), the H-8 Level 3 version 030 aerosol data sets from coastal areas were evaluated in this work. Level 2.0 aerosol products from January 2017 to December 2017 collected from 10 Aerosol Robotic Network (AERONET) sites, located in the offshore areas of the South China Sea and the Taiwan Strait, were selected for comparisons. The results showed that the H-8 aerosol product is mostly underestimated when aerosol optical thickness (AOT) is larger then 0.2, while overestimated when AOT is less than 0.2. And that the trends shown by H-8 AOT are basically consistent with the ground observations from AERONET.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.