Advances in Disaster Modeling, Simulation and Visualization for Sandstorm Risk Management in North China

Remote Sensing

Zhaohui Lin¹  Jason K. Levy²  Hang Lei³ 

[1]Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

[2]L. Douglas Wilder School of Government and Public Affairs, Virginia Commonwealth University, Richmond, VA 23284, USA

[3] E-Mail:

[4]Department of Atmospheric Sciences, University of Illinois, Urbana, IL 61801, USA

[5] E-Mail:

关键词: remote sensing;    dust storm modeling;    land surface processes;    soil moisture;    dust-emission;    numerical simulation;   

DOI  :  10.3390/rs4051337

来源: mdpi

【 摘 要 】

Dust storms in North China result in high concentrations of airborne dust particles, which cause detrimental effects on human health as well as social and economic losses and environmental degradation. To investigate the impact of land surface processes on dust storms, we simulate two dust storm events in North China during spring 2002 using two versions of a dust storm prediction system developed by the Institute for Atmospheric Physics (IAP) in Beijing, China. The primary difference between the IAP Sandstorm Prediction System (IAPS 1.0) and more recent version (IAPS 2.0) is the land surface modeling. IAPS 1.0 is based on the Oregon State University (OSU) land surface model, whereas the latest version of the dust storm prediction (IAPS 2.0) uses NOAH land surface schemes for land surface modeling within a meteorological model, MM5. This work investigates whether the improved land surface modeling affects modeling of sandstorms. It is shown that an integrated sandstorm management system can be used to aid the following tasks: ensure sandstorm monitoring and warning; incorporate weather forecasts; ascertain the risk of a sandstorm disaster; integrate multiple technologies (for example, GIS, remote sensing, and information processing technology); track the progress of the storm in real-time; exhibit flexibility, accuracy and reliability (by using multiple sources of data, including in-situ meteorological observations); and monitor PM₁₀ and PM_2.5 dust concentrations in airborne dustfalls. The results indicate that with the new land surface scheme, the simulation of soil moisture is greatly improved, leading to a better estimate of the threshold frictional velocity, a key parameter for the estimating surface dust emissions. In this study, we also discuss specific mechanisms by which land surface processes affect dust storm modeling and make recommendations for further improvements to numerical dust storm simulations.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.