Zhongmin Zhu

Cloud amount and aerosol characteristic research in the atmosphere over Hubei province, China

Although the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO) has been widely used in aerosol research, the classification of aerosol and cloud still exist some problems. Tradition classification method used by NASA is probability distribution functions (PDFs), but in reality, when we want to realize this algorithm, we fund it is difficult to describe the multi-modal distribution of cloud backscatter coefficients. Further, because ice cloud and dust aerosol have some similar properties, so it is not easy to identify them. In this paper, we introduce a classification method which based on Support vector machine (SVM), and add another characteristic. Then according to the result of classification inverse the aerosol characteristic, the height of cloud top, at the same time, combine with the CloudSat calculate the other cloud character, these data will be helpful for further climate research.

CALIPSO-AERONET Combined Application for Weather and Climate Research

In this paper, a new method is proposed, which combine CALIPSO lidar data with AERONET data to acquire the unstable aerosol information in Taiwan. First, introduce a CALIPSO retrieval arithmetic to obtain the aerosol optical depth, and then compare the differences between CALIPSO and AERONET. By combining these two techniques we could not only have the precise site data from AERONET, but also own the change information of aerosol in southeast China from CALIPSO. Different from AERONET, we can also display the spatial properties of aerosol from CALIPSO lidar backscatter data, such as, the strength of aerosol in each layer and their change with time in the aerosphere.

Mobile Aerosol Lidar for Earth Observation Atmospheric Correction

A new atmospheric correction method of earth observation images based on the combination of satellite data and lidar data is proposed in this paper. A mobile scanning Mie lidar was developed to detect the aerosols spatial and temporal distribution for the purpose above. To obtain more accurate data, future development plan of a multi-wavelength, multi-channel Raman lidar is discussed. Earth observation images processed by the radiative transfer model and this new method are presented. Also issues to approach the final goal of this new atmospheric correction method are discussed.

Aerosol Character Comparison of CALIPSO and Sunphotometer in Hubei Province, China

The stable aerosol retrieval algorithm needs a prior assumption of lidar ratio (the extinction-to-backscatter ratio), and the known aerosol type that is the prerequisite of this assumption, so how to identify the clouds and aerosol from lidar profile is fundamental to acquire atmospheric optical parameter. In this paper, we first employ the CloudSat to validate the CALISPOs classificatory results, which is released in different versions, after choosing more accurate classification, then start retrieving. Second, sun-photometer is used for verifying the CALIPSOs calibration coefficient and supplies the day time records which are relatively more accurate. Finally, aerosol characteristic in Hubei province is analyzed. All the data will supply more available information for further climate change research.

Retrieval of Aerosol Optical Properties based on Measurements of Lidar, Sun-Photometer, and CALIPSO at Wuhan, China

Studying optical properties of atmospheric aerosol is important because aerosol affects people around the world significantly. These effects strongly depend on the physical and optical properties of aerosol particles. In this paper, we propose to use lidar, sun-photometer, and CALIPSO synchronously, then present combined retrieval to investigate the optical properties of aerosol. The observations were performed at Wuhan during the period of December 2007 to May 2008. The primary results show that the proposed method improved the precision of aerosol optical depth effectively. Furthermore, long-term atmospheric and aerosol data could be obtained by consecutive observations. Also these data will be useful for future understanding about their environmental and climate effects.

Development and new application of Raman/Mie lidar: severe weather research and Earth observation atmospheric correction

Aerosol particles play important role in both global climate system and earth observation application. We have developed a portable scanning Mie lidar, with the combination of spectrograph, active and passive earth observation satellite data, and the ground sensor data, severe weather research and earth observation atmospheric correction work could be conducted. To obtain more accurate aerosol information, we are developing a new multi-channel Raman lidar system. Also we have developed a simulation model for system performance simulation and data simulation. In this paper, the lidar system development, simulation modeling, and primary experimental work result will be described.

The ground-based lidar combined with sunphotometer for aerosol optical depth retrieval

Aerosol particles are important components of the earth-atmosphere system, not only affecting atmospheric visibility of the earths surface from space, but also be an important element to the occurrence of cloud that aerosol particles serve as the primary source of cloud condensation nuclei(CCN). Remote sensing of aerosol properties from space/satellite can reveal the tendency of temporal-spatial distribution in global scale, however, whose precision cant satisfy the request of quantitative remote sensing. Thus, in this paper proposes the method combined sunphotometer (passive measurements) and Lidar (active remote sensing measurements) developed by Wuhan University to retrieve the aerosol optical depth. The primary results show that the proposed method improved the precision of aerosol optical depth effectively. Furthermore, long-term atmospheric and aerosol data could be obtained by consecutive Lidar and sunphotometer observations. Also these data will be used for emending the existing atmospheric model and aerosol type, and make them more compliant for China area application.

The active-passive remote sensing for aerosol optical depth retrieval

In this paper, a hybrid retrieval method of aerosol optical depth based on the combination of active and passive optical remote sensing is proposed. Two methods to retrieve the atmospheric optical depth are introduced: the so-called dark pixel method is used for retrieving the aerosol optical depth from MODIS; the other one is used by CALIPSO lidar data. After analyzing the two methods, the combined MODIS and CALIPSO method is applied for the aerosol optical depth, the primary experimental results show that these data are in agreement with each other in time-space evolvement trend.

An Atmospheric Correction Method Based on Lidar Data

In this paper, a new atmospheric correction method based on the combination of lidar data and satellite data is proposed. Two methods to retrieve the atmospheric optical depth are introduced: one is by method used in 6S model, the other one is by lidar detection data. Earth observation images processed by the above two methods are presented. Future approaches to this new atmospheric correction method are discussed.

A mobile lidar for Earth observation application

Aerosols have large impacts on radiative transfer through scattering and extinction, which distort the satellite signals in earth observation application. In the paper, we apply lidar for measuring aerosol signals simultaneously when earth observation satellite flyover. In this way, the aerosol influence could be removed precisely by the combination of real-time lidar data and atmospheric radiance transmission model. Here, the aerosol optical depth retrieved by lidar data is integrated into the 6S model for satellite image atmospheric correction. The primary results are shown in this paper.