Identification and physical retrieval of dust storm using three MODIS thermal IR channels

Abstract

In this paper, the dust event on 7 April 2001 in northern China is investigated with three MODIS thermal infrared (IR) bands. It is found that for the dust cloud, the observed 11 μm minus 12 μm brightness temperature difference (BTD) is always negative, while the BTD of 8.5 μm minus 11 μm varies from positive to negative depending on the dust concentration. Based on these distinguishing properties, we develop a dust mask algorithm to identify the dust storm occurrence and spatial extent. The algorithm can be used successfully in both the daytime and nighttime. Using the Mie spherical scattering theory, the thermal radiation transfer through the single dust layer is performed with the widely used forward model DISTORT. Our calculations show that the dust-like aerosols can well explain the observed BTD although both of the complex refractive index and particle size of aerosols will significantly influence the BTD. When the complex refractive index is fixed (dust-like aerosols in this paper), then the dust optical thickness and effective radii of dust particles can be retrieved from the brightness temperature (BT) of the 11 μm channel and the BTD of 11 μm minus 12 μm channels, respectively. The integral dust column density can also be derived from the retrieved dust optical thickness and effective radius.

Introduction

Dust storms often occur in the spring season and influence large areas of northern China. During a dust-storm event, the concentration of dust particles in the atmosphere increases significantly. The increased dust concentration produces air quality hazards along the transportation routes. Dust storms may also have climatic influences on regional and global scales through their interactions with the solar and terrestrial radiative fields (Shi and Zhao, 2003).

Satellite monitoring is a powerful tool for studying the properties of large-scale dust storms. Since the 1970s, scientists have succeeded in identifying the outbreaks of dust storms from satellite images by use of two different techniques, the VIR (visible and near-infrared) technique (Griggs, 1975, Carlson, 1979, Norton et al., 1980) and the TIR (thermal infrared) window technique (Shenk and Curran, 1974, Ackerman, 1989). It has been shown that the TIR technique has the distinct advantage in detecting dust storms over high-albedo surfaces and in nighttimes.

Based on the identification techniques, more recent studies have been carried out to quantitatively determine the physical parameters of dust storms, such as aerosol loading. The aerosol loading is a key parameter for dust-storm assessment, modeling, and forecasting. The VIR technique can be used to retrieve this parameter over ocean (Tanré et al., 1997); but to do so over land remains a major challenge. Because dust storms mostly occur over desert or arid regions with bright surfaces, such as the Sahara Desert and the Gobi Desert, the surface contribution to the satellite signal is quite large and often unknown. As a result, estimates of the properties of dust aerosol are highly uncertain.

Wen and Rose (1994) developed an algorithm based on the TIR technique for the retrieval of particle size, optical thickness and total mass of volcanic cloud by using the AVHRR bands 4 and 5. The concept of their algorithm is similar to that for the retrieval of cirrus using the BTD method (Wu, 1987, Giraud et al., 1997). The principle is applicable to remote sense the properties of the dust storm. In addition, Ackerman (1997) investigated the possibility of detecting volcanic and soil-derived aerosols using infrared observations at wavelengths 8.5 μm together with 11 and 12 μm from theoretical calculations.

In this paper, we develop a dust-storm mask algorithm for identifying the dust-storm outbreak and the spatial extent using the three TIR window channels, as proposed by Ackerman (1997). Because only TIR channels are used, the algorithm is applicable to both daytime and nighttime conditions. Further, if adequate aerosol physical information (complex refractive index and particle size distribution) are determined, satellite observations of the three channels can be explained with the forward model's simulation. The BT of the 11 μm channel shows a quasi-linear relationship with dust optical thickness and the BTD between the 11 and 12 μm channels shows a quasi-linear relationship with particle size. Depending on this physical understanding and a pre-calculated look-up table, an algorithm is also proposed for the retrieval of dust-cloud optical thickness and dust-particle effective radius. The algorithm is applied to studying the severe dust storm that occurred on 7 April 2001 over northern China. Based on the retrieved dust optical thickness and dust-particle effective radius, integral dust columnar density is derived.