Lili Qie

Retrieval of Aerosol Fine-Mode Fraction from Intensity and Polarization Measurements by PARASOL over East Asia

The fine-mode fraction (FMF) of aerosol optical depth (AOD) is a key optical parameter that represents the proportion of fine particles relative to total aerosols in the atmosphere. However, in comparison to ground-based measurements, the FMF is still difficult to retrieve from satellite observations, as attempted by a Moderate-resolution Imaging Spectroradiometer (MODIS) algorithm. In this paper, we introduce the retrieval of FMF based on Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar (PARASOL) data. This method takes advantage of the coincident multi-angle intensity and polarization measurements from a single satellite platform. In our method, we use intensity measurements to retrieve the total AOD and polarization measurements to retrieve the fine-mode AOD. The FMF is then calculated as the ratio of the retrieved fine-mode AOD to the total AOD. The important processes in our method include the estimation of the surface intensity and polarized reflectance by using two semi-empirical models, and the building of two sets of aerosol retrieval lookup tables for the intensity and polarized measurements via the 6SV radiative transfer code. We apply this method to East Asia, and comparisons of the retrieved FMFs for the Beijing, Xianghe and Seoul_SNU sites with those of the Aerosol Robotic Network (AERONET) ground-based observations produce correlation coefficients (R2) of 0.838, 0.818, and 0.877, respectively. However, the comparison results are relatively poor (R2 = 0.537) in low-AOD areas, such as the Osaka site, due to the low signal-to-noise ratio of the satellite observations.

Improving Remote Sensing of Aerosol Optical Depth over Land by Polarimetric Measurements at 1640 nm: Airborne Test in North China

An improved aerosol retrieval algorithm based on the Advanced Multi-angular Polarized Radiometer (AMPR) is presented to illustrate the utility of additional 1640-nm observations for measuring aerosol optical depth (AOD) over land using look-up table approaches. Spectral neutrality of the polarized surface reflectance over visible to short-wavelength infrared bands is verified, and the 1640-nm measurements corrected for atmospheric effects are used to estimate the polarized surface reflectance at shorter wavelengths. The AMPR measurements over the Beijing-Tianjin-Hebei region in north China reveal that the polarized surface reflectance of 670, 865 and 1640 nm are highly correlated with correlation slopes close to one (0.985 and 1.03) when the scattering angle is less than 145°. The 1640-nm measurements are then employed to estimate polarized surface reflectance at shorter wavelengths for each single viewing direction, which are then used to improve the retrieval of AOD over land. The comparison between AMPR retrievals and ground-based Sun-sky radiometer measurements during three experimental flights illustrates that this approach retrieves AOD at 865 nm with uncertainties ranging from 0.01 to 0.06, while AOD varies from 0.05 to 0.17.

Retrieval of Aerosol Optical Depth Using the Empirical Orthogonal Functions (EOFs) Based on PARASOL Multi-Angle Intensity Data

Aerosol optical depth (AOD) is a widely used aerosol optical parameter in atmospheric physics. To obtain this parameter precisely, many institutions plan to launch satellites with multi-angle measurement sensors, but one important step in aerosol retrieval, the estimation of surface reflectance, is still a pressing issue. This paper presents an AOD retrieval method based on the multi-angle intensity data from the Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar (PARASOL) platform using empirical orthogonal functions (EOFs), which can be universally applied to multi-angle observations. The function of EOFs in this study is to estimate surface intensity contributions, associated with aerosol lookup tables (LUTs), so that the retrieval of AOD can be implemented. A comparison of the retrieved AODs for the Beijing, Xianghe, Taihu, and Hongkong_PolyU sites with those from the Aerosol Robotic Network (AERONET) ground-based observations produced high correlation coefficients (r) of 0.892, 0.915, 0.831, and 0.897, respectively, while the corresponding root mean square errors (RMSEs) are 0.095, 0.093, 0.099, and 0.076, respectively.

Study the polarization and depolarization properties of atmospheric aerosol multiple scattering based on the successive order of scattering

With the polynomial fitting of source function in each order of scattering calculation and the effective process of aerosol forward scattering peak, a polarized radiative transfer (RT) model based on the improved successive order of scattering (SOS) method has been developed to solve the vector radiative transfer equation. By our RT model, not only the total Stokes parameters [I, Q, U] measured by the satellite (aircraft) and ground-based sensors with linear polarization could be approximately simulated, but also the results of parameters for each scattering order event could conveniently calculated, which are very helpful to study the polarization properties for the atmospheric aerosol multiple scattering. In this study, the synchronous measured aerosol results including aerosol optical depth, complex refractive index and particle size distribution from AERONET under different air conditions, are considered as the input parameters for the successive scattering simulations. With our polarized RT model and the Mie code combined, the Stokes parameters as well as the degree of polarization for each scattering order are simulated and presented; meanwhile, the polarization (depolarization) properties of multiply scattering are preliminary analyzed and compared with different air quality (clear and pollution). Those results could provide a significant support for the further research of polarized aerosol remote sensing and inversion. Polarization properties of aerosol, successive order of scattering, vector radiative transfer equation, polynomial fitting of source function , multiply scattering

Improving Remote Sensing of Aerosol Microphysical Properties by Near‐Infrared Polarimetric Measurements Over Vegetated Land: Information Content Analysis

While polarimetric measurements contain valuable information regarding aerosol microphysical properties, polarization data in the near-infrared (NIR) bands have not been widely utilized. This paper evaluates whether the aerosol property information contents from single-viewing satellite polarimetric measurements at 1,610 and 2,250 nm can be used to improve the retrieval of aerosol parameters over vegetated land, in combination with shorter-wavelength bands (490, 670, and 870 nm). The a priori information and errors for the analysis are derived by assuming that the surface reflectance at visible wavelengths can be derived from the top of atmosphere at 2,250 nm. The information content in the synthetic data set is investigated for 10 aerosol parameters characterizing the columnar aerosol volumes (V f 0 and V0), particle size distributions (r f eff, v f eff, r c eff, and v c eff), and refractive indices (m f r , m f i , m c r , and m c i ) for the fineand coarse-mode aerosol models, respectively, and one parameter C characterizing the surface polarization. The results indicate that the degrees of freedom for signal can be increased by at least 2 with the addition of NIR measurements and that one to three additional parameters could be further retrieved with significantly decreased uncertainties. In addition, the 1,610 nm band is necessary for the simultaneous retrieval of V f 0, m f r , and r f eff for the fine mode dominated aerosols, while the 1,610 and 2,250 nm bands are both indispensable for retrieving V f 0, V c 0, m c r , r f eff , and r c eff in tandem for the coarse mode dominated aerosols. The analysis also reveals that C could be further retrieved by including scalar radiance and that measurement errors have significantly larger influences on the retrieval uncertainties than model errors.

A parallel method of atmospheric correction for multispectral high spatial resolution remote sensing images

The remote sensing image is usually polluted by atmosphere components especially like aerosol particles. For the quantitative remote sensing applications, the radiative transfer model based atmospheric correction is used to get the reflectance with decoupling the atmosphere and surface by consuming a long computational time. The parallel computing is a solution method for the temporal acceleration. The parallel strategy which uses multi-CPU to work simultaneously is designed to do atmospheric correction for a multispectral remote sensing image. The parallel framework’s flow and the main parallel body of atmospheric correction are described. Then, the multispectral remote sensing image of the Chinese Gaofen-2 satellite is used to test the acceleration efficiency. When the CPU number is increasing from 1 to 8, the computational speed is also increasing. The biggest acceleration rate is 6.5. Under the 8 CPU working mode, the whole image atmospheric correction costs 4 minutes.

Water vapor retrieval from near-IR measurements of polarized scanning atmospheric corrector

Water vapor and aerosol are two key atmospheric factors effecting the remote sensing image quality. As water vapor is responsible for most of the solar radiation absorption occurring in the cloudless atmosphere, accurate measurement of water content is important to not only atmospheric correction of remote sensing images, but also many other applications such as the study of energy balance and global climate change, land surface temperature retrieval in thermal remote sensing. A multi-spectral, single-angular, polarized radiometer called Polarized Scanning Atmospheric Corrector (PSAC) were developed in China, which are designed to mount on the same satellite platform with the principle payload and provide essential parameters for principle payload image atmospheric correction. PSAC detect water vapor content via measuring atmosphere reflectance at water vapor absorbing channels (i.e. 0.91 μm) and nearby atmospheric window channel (i.e. 0.865μm). A near-IR channel ratio method was implemented to retrieve column water vapor (CWV) amount from PSAC measurements. Field experiments were performed at Yantai, in Shandong province of China, PSAC aircraft observations were acquired. The comparison between PSAC retrievals and ground-based Sun-sky radiometer measurements of CWV during the experimental flights illustrates that this method retrieves CWV with relative deviations ranging from 4% ~ 13%. This method retrieve CWV more accurate over land than over ocean, as the water reflectance is low.

Study on pixel matching method of the multi-angle observation from airborne AMPR measurements

For the along-track scanning mode, the same place along the ground track could be detected by the Advanced Multi-angular Polarized Radiometer (AMPR) with several different scanning angles from -55 to 55 degree, which provides a possible means to get the multi-angular detection for some nearby pixels. However, due to the ground sample spacing and spatial footprint of the detection, the different sizes of footprints cannot guarantee the spatial matching of some partly overlap pixels, which turn into a bottleneck for the effective use of the multi-angular detected information of AMPR to study the aerosol and surface polarized properties. Based on our definition and calculation of t he pixel coincidence rate for the multi-angular detection, an effective multi-angle observation’s pixel matching method is presented to solve the spatial matching problem for airborne AMPR. Assuming the shape of AMPR’s each pixel is an ellipse, and the major axis and minor axis depends on the flying attitude and each scanning angle. By the definition of coordinate system and origin of coordinate, the latitude and longitude could be transformed into the Euclidian distance, and the pixel coincidence rate of two nearby ellipses could be calculated. Via the traversal of each ground pixel, those pixels with high coincidence rate could be selected and merged, and with the further quality control of observation data, thus the ground pixels dataset with multi-angular detection could be obtained and analyzed, providing the support for the multi-angular and polarized retrieval algorithm research in t he next study.

A sensitivity study of atmospheric reflectance to aerosol layer height based on multi-angular polarimetric measurements

The reflected Solar radiance at top of atmosphere (TOA) are, to some degree, sensitive to the vertical distribution of absorbing aerosols, especially at short wavelengths (i.e. blue and UV bands). If properly exploited, it may enable the extraction of basic information on aerosol vertical distribution. In recent years, rapid development of the advanced spectral multi-angle polarimetric satellite observation technology and aerosol inversion algorithm makes the extraction of more aerosol information possible. In this study, we perform a sensitivity analysis of the reflection function at TOA to the aerosol layer height, to explore the potential for aerosol height retrievals by using multi-angle total and polarized reflectance passive observations at short wavelength. Employing a vector doubling-adding method radiative transfer code RT3, a series of numerical experiments were conducted considering different aerosol model, optical depth (AOD), single-scattering albedo (SSA), and scale height (H), also the wavelength, solar-viewing geometry, etc. The sensitivity of both intensity and polarization signals to the aerosol layer height as well as the interacted impactions with SSA and AOD are analyzed. It’s found that the sensitivity of the atmospheric reflection function to aerosol scale height increase with aerosol loading (i.e. AOD) and aerosol absorption (i.e. SSA), and decrease with wavelength. The scalar reflectance is sensitive to aerosol absorption while the polarized reflectance is more influenced by the altitude. Then the aerosol H and SSA may be derived simultaneously assuming that the total and polarized radiances in UV bands deconvolve the relative influences of height and absorption. Aerosol layer height, Atmospheric reflection function, Sensitivity, Ultraviolet (UV) band.

Retrieval of absorptive gas columnar amounts using atmospheric hyper-spectral irradiance measurements within visible spectrum

A hyper spectral ground-based instrument named Atmosphere-Surface Radiation Automatic Instrument (ASRAI) has been developed for the purpose of in-situ calibration of satellites. The apparatus has both upward and downward looking views, and thus can observe both the atmosphere and land surface. The solar transmitted irradiance can be derived from the measured full spectral irradiance and diffused spectral irradiance of atmosphere within visible spectrum (0.4-1.0μm). A method similar to that of King et al. which originally intended to apply to multi-wavelength measurements, is adopted to determine absorptive gaseous columnar amount from hyper spectrum. The solar irradiance at top of atmosphere and absorption coefficients of water vapor (H2O), ozone (O3), oxygen (O2) and nitrogen dioxide (NO2) are recalculated at an instrumental spectral resolution by convolution method. Based on the gaseous characteristics of absorption, the total columnar amounts of water vapor and oxygen are first inferred from solar transmitted irradiance at strong absorption wavelength of 0.934μm and 0.763μm respectively. The total columnar amounts of ozone and nitrogen dioxide, together with aerosol optical depth, are determined by a nonlinear least distance fitting method which minimizes a χ2 statistic to obtain optimal solutions. ASRAI was deployed for observation in Dunhuang site in China in August of 2014. Our results demonstrate that the algorithm is reasonable. Although the validation is preliminary, the hyper spectrum measured by ASRAI exhibits good ability to retrieve the abundance of absorptive gases and aerosols.