恒河流域和蒙古国南部AERONET站沙尘气溶胶光学物理特性对比分析

沙尘气溶胶作为气溶胶的重要类型之一,对全球和区域水分循环以及亚洲季风系统有着重要影响.利用气溶胶自动观测网(AERONET)印度Kanpur和蒙古国Dalanzadgad两个站点数据,采用阈值法提取了沙尘和人为气溶胶信息并进行了对比分析.结果表明,Kanpur站受印度夏季风影响较大,沙尘气溶胶和人为源气溶胶的排放具有叠加效应,远源输送可能是Kanpur站沙尘气溶胶的主要来源.Dalanzadgad站受东亚夏季风影响较小,春季大风带来了大量的沙尘,这可能与大风天气和植被覆盖度低等因素有关,是春季气溶胶光学厚度显著升高的主要影响因素之一,沙尘具有局地起源特征;在其他时段,人为源气溶胶是当地大气气溶胶的主要来源,但总排放量相对较低.此外,Kanpur站所在的恒河流域大气颗粒物绝对含量远远高于Dalanzadgad所在的蒙古国南部地区.在沙尘天气中,两站颗粒物的光学物理特性相似.     

Study on Probability Distributions of Multi-Timescale Aerosol Optical Depth Using AERONET Data

The probability distribution analysis is per-formed for multi-timescale aerosol optical depth (AOD) using AErosol RObotic NETwork (AERONET) level 2.0 data.The maximum likelihood estimation is employed to determine the best-fit probability density function (PDF),and the statement that the fitting Weibull distribution will be light-tailed is proved true for these AOD samples.The best-fit PDF results for multi-site data show that the PDF of AOD samples with longer timescale in most sites tends to be stably represented by lognormal distribution,while Weibull distribution is a better fit for AOD samples with short timescales.The reason for this difference is ana-lyzed through tail characteristics of the two distributions,and an indicator for the selection between Weibull and lognormal distributions is suggested and validated.The result of this research is helpful for determining the most accurate AOD statistics for a given site and a given time-scale and for validating the retrieved AOD through its PDF.     

A synergic algorithm for retrieval of aerosol optical depth over land

In this paper, a novel algorithm for aerosol optical depth(AOD) retrieval with a 1 km spatial resolution over land is presented using the Advanced Along Track Scanning Radiometer (AATSR) dual-view capability at 0.55, 0.66 and 0.87 μm, in combination with the Bi-directional Reflectance Distribution Function (BRDF) model, a product of the Moderate Resolution Imaging Spectroradiometer (MODIS). The BRDF characteristics of the land surface, i.e. prior input parameters for this algorithm, are computed by extracti...     

Statistical data fusion of multi-sensor AOD over the Continental United States

This article illustrates two techniques for merging daily aerosol optical depth (AOD) measurements from satellite and ground-based data sources to achieve optimal data quality and spatial coverage. The first technique is a traditional Universal Kriging (UK) approach employed to predict AOD from multi-sensor aerosol products that are aggregated on a reference grid with AERONET as ground truth. The second technique is spatial statistical data fusion (SSDF); a method designed for massive satellite data interpolation. Traditional kriging has computational complexity O(N³), making it impractical for large datasets. Our version of UK accommodates massive data inputs by performing kriging locally, while SSDF accommodates massive data inputs by modelling their covariance structure with a low-rank linear model. In this study, we use aerosol data products from two satellite instruments: the moderate resolution imaging spectrometer and the geostationary operational environmental satellite, covering the Continental United States.     

Can MODIS Detect Trends in Aerosol Optical Depth over Land?

The Moderate Resolution Imaging Spectroradiometer(MODIS) sensor onboard NASA's Aqua satellite has been collecting valuable data about the Earth system for more than 14 years, and one of the benefits of this is that it has made it possible to detect the long-term variation in aerosol loading across the globe. However, the long-term aerosol optical depth(AOD)trends derived from MODIS need careful validation and assessment, especially over land. Using AOD products with at least 70 months' worth of measurements collected during 2002–15 at 53 Aerosol Robotic Network(AERONET) sites over land,Mann–Kendall(MK) trends in AOD were derived and taken as the ground truth data for evaluating the corresponding results from MODIS onboard Aqua. The results showed that the AERONET AOD trends over all sites in Europe and North America, as well as most sites in Africa and Asia, can be reproduced by MODIS/Aqua. However, disagreement in AOD trends between MODIS and AERONET was found at a few sites in Australia and South America. The AOD trends calculated from AERONET instantaneous data at the MODIS overpass times were consistent with those from AERONET daily data, which suggests that the AOD trends derived from satellite measurements of 1–2 overpasses may be representative of those from daily measurements.     

Trends in aerosol optical properties over Eastern Europe based on MODIS-Aqua

This study provides characteristics of aerosol columnar properties, measured over ten countries in Eastern Europe from 2002 to 2019. Aerosol optical depth (AOD) and Ångström exponent (AE) were obtained with the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 merged Dark Target and Deep Blue aerosol product. The product is validated using ground-based Aerosol Robotic Network (AERONET) situated at Minsk, Belsk, Moldova and Kyiv. The results showed that 76.15% of retrieved AOD data are within the expected error. It was established that 64.2% of AOD points are between 0 and 0.2 and 79.3% of all AE points are over 1. Mean AOD values in the region vary from 0.130 ​± ​0.04 (Moldova) to 0.193 ​± ​0.03 (Czech Republic) with mean value in the region 0.162 ​± ​0.05. Seasonal mean AOD (AE) values were at the maximum during the summer from 0.231 ​± ​0.05 (1.482 ​± ​0.09 in winter) to minimum 0.087 ​± ​0.04 during the winter (1.363 ​± ​0.17 in summer). Gradual AOD reduction is observed in all countries with annual trend from −0.0050 (Belarus) to −0.0029 (Russia). Finally, the relationship between AOD and AE was studied to classify various aerosol types and showed seasonal non-uniformity of their contribution depending on variation in sources. The entire region is under significant impact of various aerosol types, including clean continental (СС), mixed (MX) and anthropogenic/burning (AB) aerosols types that are at 59.77%, 24.72%, and 12.97% respectively. These results form an important basis for further regional studies of air quality and distribution of sources of pollution.     

MODIS MAIAC高分辨率气溶胶光学厚度产品在干旱区的适用性研究

The Multiangle Implementation of Atmospheric Correction (MAIAC) is a new generic algorithm applied to MODIS measurements to retrieve Aerosol Optical Depth (AOD) over land at high spatial resolution (1 km). It is expected to have good potential in improving the AOD inversion of dark and bright surfaces of land. The high spatial resolution of the MAIAC retrievals enhances the capability to distinguish aerosol sources and determine subtle aerosol features. Retrieval of satellite aerosol properties is therefore often challenging due to considerable seasonal variations in surface reflectance and aerosol properties. To date, MAIAC AOD over arid regions under data-scarce environments has been evaluated. Considering these uncertainties, a systematic effort was made to evaluate the MAIAC AOD over arid areas using Aerosol Robotic Network (AERONET) ground-based AOD from 2000 to 2019. Considerable MAIAC-AERONET AOD matchups demonstrate the capability of MAIAC to retrieve AOD over varied ground surfaces and temporal scales. We employed a broader perspective and evaluated MAIAC performance under varying aerosol loading, aerosol types, surface coverage, and viewing geometry. The results show that (1) MAIAC performed well over various temporal scales, including monthly, seasonal and annual scales. Although underestimation is prevalent, MAIAC AOD in the spring and winter months correspond to the highest and lowest retrieval accuracies, respectively. (2) MAIAC performed well over four different typical land surface land surfaces, showing the highest retrieval accuracy over grassland, yet it slightly overestimated AOD. Construction land is most affected by the aerosol model, and farmland is strongly disturbed by surface reflectance and underestimated most obviously (Below EE = 46.5%). (3) The accuracies of the MAIAC AOD observations of Terra and Aqua are similar; R2 is more than 0.75, but both are underestimated, especially for Aqua. In general, MAIAC’s ability to provide AOD at high spatial resolution appears promising over arid areas and is expected to be helpful to study the characteristics of fine aerosols in arid areas and promote the study of local air quality. © 2023 Science Press. All rights reserved.     

Grid-cell Aerosol Direct Shortwave Radiative Forcing Calculated Using the SBDART Model with MODIS and AERONET Observations:An Application in Winter and Summer in Eastern China

Taking winter and summer in eastern China as an example application, a grid-cell method of aerosol direct radiative forcing(ADRF) calculation is examined using the Santa Barbara DISORT Atmospheric Radiative Transfer(SBDART) model with inputs from MODIS and AERONET observations and reanalysis data. Results show that there are significant seasonal and regional differences in climatological mean aerosol optical parameters and ADRF. Higher aerosol optical depth(AOD)occurs in summer and two prominent high aerosol loading centers are observed. Higher single scattering albedo(SSA) in summer is likely associated with the weak absorbing secondary aerosols. SSA is higher in North China during summer but higher in South China during winter. Aerosols induce negative forcing at the top of the atmosphere(TOA) and surface during both winter and summer, which may be responsible for the decrease in temperature and the increase in relative humidity.Values of ADRF at the surface are four times stronger than those at the TOA. Both AOD and ADRF present strong interannual variations; however, their amplitudes are larger in summer. Moreover, patterns and trends of ADRF do not always correspond well to those of AOD. Differences in the spatial distributions of ADRF between strong and weak monsoon years are captured effectively. Generally, the present results justify that to calculate grid-cell ADRF at a large scale using the SBDART model with observational aerosol optical properties and reanalysis data is an effective approach.     

基于AERONET的西亚地区气溶胶光学特性

利用AERONET 10个站点的Level2数据分析得到2010-2017年西亚地区多个气溶胶参数(光学厚度(Aerosol Optical Depth,AOD)、吸收光学厚度(Absorption Aerosol Optical Depth,AAOD)、波长指数α、粒子体积谱和单次散射反照率(Single Scatt...