scholarly journals Bayesian uncertainty quantification in aerosol optical depth retrieval applied to TROPOMI measurements

2021 ◽  
Author(s):  
Anu Kauppi ◽  
Antti Kukkurainen ◽  
Antti Lipponen ◽  
Marko Laine ◽  
Antti Arola ◽  
...  

Abstract. We present here an aerosol model selection based statistical method in Bayesian framework for retrieving atmospheric aerosol optical depth (AOD) and pixel-level uncertainty. Especially, we focus on to provide more realistic uncertainty estimate by taking into account a model selection problem when searching for the solution by fitting look-up table (LUT) models to a satellite measured top-of-atmosphere reflectance. By means of Bayesian model averaging over the best-fitting aerosol models we take into account an aerosol model selection uncertainty and get also a shared inference about AOD. Moreover, we acknowledge model discrepancy, i.e. forward model error, arising from approximations and assumptions done in forward model simulations. We have estimated the model discrepancy empirically by a statistical approach utilizing residuals of model fits. We use the measurements from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor in ultraviolet and visible bands, and in one wavelength band 675 nm in near-infrared, in order to study the functioning of the retrieval in a broad wavelength range. We exploit a fundamental classification of the aerosol models as weakly absorbing, biomass burning and desert dust aerosols. For experimental purpose we have included some dust type of aerosols having non-spherical particle shapes. For this study we have created the aerosol model LUTs with radiative transfer simulations using the libRadtran software package. It is reasonably straightforward to experiment with different aerosol types and evaluate the most probable aerosol type by the model selection method. We demonstrate the method in wildfire and dust events in a pixel level. In addition, we have evaluated in detail the results against ground-based remote sensing data from the AErosol RObotic NETwork (AERONET). Based on the case studies the method has ability to identify the appropriate aerosol types, but in some wildfire cases the AOD is overestimated compared to the AERONET result. The resulting uncertainty when accounting for the model selection problem and the imperfect forward modelling is higher compared to uncertainty when only measurement error is included in an observation model, as can be expected.

2020 ◽  
Vol 12 (6) ◽  
pp. 991 ◽  
Author(s):  
Yang Wang ◽  
Liangfu Chen ◽  
Jinyuan Xin ◽  
Xinhui Wang

The Visible Infrared Imaging Radiometer Suite (VIIRS) has been observing aerosol optical depth (AOD), which is a critical parameter in air pollution and climate change, for more than 7 years since 2012. Due to limited and uneven distribution of the Aerosol Robotic Network (AERONET) station in China, the independent data from the Campaign on Atmospheric Aerosol Research Network of China (CARE-China) was used to evaluate the National Oceanic and Atmospheric Administration (NOAA) VIIRS AOD products in six typical sites and analyze the influence of the aerosol model selection process in five subregions, particularly for dust. Compared with ground-based observations, the performance of all retrievals (except the Shapotou (SPT) site) is similar to other previous studies on a global scale. However, the results illustrate that the AOD retrievals with the dust model showed poor consistency with a regression equation as y = 0.312x + 0.086, while the retrievals obtained from the other models perform much better with a regression equation as y = 0.783x + 0.119. The poor AOD retrieval with the dust model was also verified by a comparison with the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol product. The results show they have a lower correlation coefficient (R) and a higher mean relative error (MRE) when the aerosol model used in the retrieval is identified as dust. According to the Ultraviolet Aerosol Index (UVAI), the frequency of dust type over southern China is inconsistent with the actual atmospheric condition. In addition, a comparison of ground-based Ångström exponent (α) values yields an unexpected result that the dust model percentage exceed 40% when α < 1.0, and the mean α shows a high value of ~0.75. Meanwhile, the α peak value (~1.1) of the “dust” model determined by a satellite retravel algorithm indicate there is some problem in the dust model selection process. This mismatching of the aerosol model may partly explain the low accuracy at the SPT and the systemic biases in regional and global validations.


2018 ◽  
Vol 10 (11) ◽  
pp. 1838 ◽  
Author(s):  
Yang Zhang ◽  
Zhengqiang Li ◽  
Zhihong Liu ◽  
Juan Zhang ◽  
Lili Qie ◽  
...  

The fine-mode aerosol optical depth (AODf) is an important parameter for the environment and climate change study, which mainly represents the anthropogenic aerosols component. The Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar (PARASOL) instrument can detect polarized signal from multi-angle observation and the polarized signal mainly comes from the radiation contribution of the fine-mode aerosols, which provides an opportunity to obtain AODf directly. However, the currently operational algorithm of Laboratoire d’Optique Atmosphérique (LOA) has a poor AODf retrieval accuracy over East China on high aerosol loading days. This study focused on solving this issue and proposed a grouped residual error sorting (GRES) method to determine the optimal aerosol model in AODf retrieval using the traditional look-up table (LUT) approach and then the AODf retrieval accuracy over East China was improved. The comparisons between the GRES retrieved and the Aerosol Robotic Network (AERONET) ground-based AODf at Beijing, Xianghe, Taihu and Hong_Kong_PolyU sites produced high correlation coefficients (r) of 0.900, 0.933, 0.957 and 0.968, respectively. The comparisons of the GRES retrieved AODf and PARASOL AODf product with those of the AERONET observations produced a mean absolute error (MAE) of 0.054 versus 0.104 on high aerosol loading days (AERONET mean AODf at 865 nm = 0.283). An application using the GRES method for total AOD (AODt) retrieval also showed a good expandability for multi-angle aerosol retrieval of this method.


2020 ◽  
Vol 13 (2) ◽  
pp. 893-905 ◽  
Author(s):  
Elina Giannakaki ◽  
Panos Kokkalis ◽  
Eleni Marinou ◽  
Nikolaos S. Bartsotas ◽  
Vassilis Amiridis ◽  
...  

Abstract. A new method, called ElEx (elastic extinction), is proposed for the estimation of extinction coefficient lidar profiles using only the information provided by the elastic and polarization channels of a lidar system. The method is applicable to lidar measurements both during daytime and nighttime under well-defined aerosol mixtures. ElEx uses the particle backscatter profiles at 532 nm and the vertically resolved particle linear depolarization ratio measurements at the same wavelength. The particle linear depolarization ratio and the lidar ratio values of pure aerosol types are also taken from literature. The total extinction profile is then estimated and compared well with Raman retrievals. In this study, ElEx was applied in an aerosol mixture of marine and dust particles at Finokalia station during the CHARADMExp campaign. Any difference between ElEx and Raman extinction profiles indicates that the nondust component could be probably attributed to polluted marine or polluted continental aerosols. Comparison with sun photometer aerosol optical depth observations is performed as well during daytime. Differences in the total aerosol optical depth are varying between 1.2 % and 72 %, and these differences are attributed to the limited ability of the lidar to correctly represent the aerosol optical properties in the near range due to the overlap problem.


2010 ◽  
Vol 3 (6) ◽  
pp. 1589-1598 ◽  
Author(s):  
D. Martynenko ◽  
T. Holzer-Popp ◽  
H. Elbern ◽  
M. Schroedter-Homscheidt

Abstract. An information content analysis for multi-wavelength SYNergetic AErosol Retrieval algorithm SYNAER was performed to quantify the number of independent pieces of information that can be retrieved. In particular, the capability of SYNAER to discern various aerosol types is assessed. This information content depends on the aerosol optical depth, the surface albedo spectrum and the observation geometry. The theoretical analysis is performed for a large number of scenarios with various geometries and surface albedo spectra for ocean, soil and vegetation. When the surface albedo spectrum and its accuracy is known under cloud-free conditions, reflectance measurements used in SYNAER is able to provide for 2–4° of freedom that can be attributed to retrieval parameters: aerosol optical depth, aerosol type and surface albedo. The focus of this work is placed on an information content analysis with emphasis to the aerosol type classification. This analysis is applied to synthetic reflectance measurements for 40 predefined aerosol mixtures of different basic components, given by sea salt, mineral dust, biomass burning and diesel aerosols, water soluble and water insoluble aerosols. The range of aerosol parameters considered through the 40 mixtures covers the natural variability of tropospheric aerosols. After the information content analysis performed in Holzer-Popp et al. (2008) there was a necessity to compare derived degrees of freedom with retrieved aerosol optical depth for different aerosol types, which is the main focus of this paper. The principle component analysis was used to determine the correspondence between degrees of freedom for signal in the retrieval and derived aerosol types. The main results of the analysis indicate correspondence between the major groups of the aerosol types, which are: water soluble aerosol, soot, mineral dust and sea salt and degrees of freedom in the algorithm and show the ability of the SYNAER to discern between this aerosol types. The results of the work will be further used for the development of the promising methodology of the construction error covariance matrices in the assimilation system.


2019 ◽  
Vol 145 (721) ◽  
pp. 1571-1588
Author(s):  
Sammy Metref ◽  
Alexis Hannart ◽  
Juan Ruiz ◽  
Marc Bocquet ◽  
Alberto Carrassi ◽  
...  

2015 ◽  
Vol 8 (8) ◽  
pp. 3117-3133 ◽  
Author(s):  
D. Pérez-Ramírez ◽  
I. Veselovskii ◽  
D. N. Whiteman ◽  
A. Suvorina ◽  
M. Korenskiy ◽  
...  

Abstract. This work deals with the applicability of the linear estimation technique (LE) to invert spectral measurements of aerosol optical depth (AOD) provided by AERONET CIMEL sun photometers. The inversion of particle properties using only direct-sun AODs allows the evaluation of parameters such as effective radius (reff) and columnar volume aerosol content (V) with significantly better temporal resolution than the operational AERONET algorithm which requires both direct sun and sky radiance measurements. Sensitivity studies performed demonstrate that the constraints on the range of the inversion are very important to minimize the uncertainties, and therefore estimates of reff can be obtained with uncertainties less than 30 % and of V with uncertainties below 40 %. The LE technique is applied to data acquired at five AERONET sites influenced by different aerosol types and the retrievals are compared with the results of the operational AERONET code. Good agreement between the two techniques is obtained when the fine mode predominates, while for coarse mode cases the LE results systematically underestimate both reff and V. The highest differences are found for cases where no mode predominates. To minimize these biases, correction functions are developed using the multi-year database of observations at selected sites, where the AERONET retrieval is used as the reference. The derived corrections are tested using data from 18 other AERONET stations offering a range of aerosol types. After correction, the LE retrievals provide better agreement with AERONET for all the sites considered. Finally, the LE approach developed here is applied to AERONET and star-photometry measurements in the city of Granada (Spain) to obtain day-to-night time evolution of columnar aerosol microphysical properties.


2016 ◽  
Author(s):  
N. Weigum ◽  
N. Schutgens ◽  
P. Stier

Abstract. A fundamental limitation of grid-based models is their inability to resolve variability on scales smaller than a grid box. Past research has shown that significant aerosol variability exists on scales smaller than these grid-boxes, which can lead to discrepancies in simulated aerosol climate effects between high and low resolution models. This study investigates the impact of neglecting sub-grid variability in present-day global microphysical aerosol models on aerosol optical depth (AOD) and cloud condensation nuclei (CCN). We introduce a novel technique to isolate the effect of aerosol variability from other sources of model variability by varying the resolution of aerosol and trace gas fields while maintaining a constant resolution in the rest of the model. We compare WRF-Chem runs in which aerosol and gases are simulated at 80 km and again at 10 km resolutions; in both simulations the other model components, such as meteorology and dynamics, are kept at the 10 km baseline resolution. We find that AOD is underestimated by 13 % and CCN is overestimated by 27 % when aerosol and gases are simulated at 80 km resolution compared to 10 km. Processes most affected by neglecting aerosol sub-grid variability are gas-phase chemistry and aerosol uptake of water through aerosol/gas equilibrium reactions. The inherent non-linearities in these processes result in large changes in aerosol parameters when aerosol and gaseous species are artificially mixed over large spatial scales. These changes in aerosol and gas concentrations are exaggerated by convective transport, which transports these altered concentrations to altitudes where their effect is more pronounced. These results demonstrate that aerosol variability can have a large impact on simulating aerosol climate effects, even when meteorology and dynamics are held constant. Future aerosol model development should focus on accounting for the effect of sub-grid variability on these processes at global scales in order to improve model predictions of the aerosol effect on climate.


2018 ◽  
Author(s):  
Swen Metzger ◽  
Mohamed Abdelkader ◽  
Benedikt Steil ◽  
Klaus Klingmüller

Abstract. We scrutinize the importance of aerosol water for the aerosol optical depth (AOD) calculations by a long-term evaluation of the EQuilibrium Simplified Aerosol Model V4 for climate modeling, which was introduced by Metzger et al. (2016a). EQSAM4clim is based on a sin-gle solute coefficient approach that efficiently parameterizes hygroscopic growth, account- ing for aerosol water uptake from the deliquescence relative humidity up to supersaturation. EQSAM4clim extends the single solute coefficient approach to treat water uptake of multi- component mixtures. The gas-aerosol partitioning and the mixed solution water uptake can be solved analytically, preventing the need for iterations, which is computationally efficient. EQSAM4clim has been implemented in the global chemistry climate model EMAC and com- pared to ISORROPIA II (Fountoukis and Nenes, 2007) at climate time-scales. Our global modeling results show that (I) our EMAC results of the aerosol optical depth (AOD) are comparable to independent results of Pozzer et al. (2015) for the period 2000–2010, (II) the results of various aerosol properties of EQSAM4clim and ISORROPIA II are similar and in agreement with AERONET and EMEP observations for the period 2000–2013, and (III) that the underlying assumptions on the aerosol water uptake limitations are important for derived AOD calculations. Sensitivity studies of different levels of chemical aging and associated water uptake show larger effects on AOD calculations for the year 2005 compared to the differences associated with the application of the two gas-liquid-solid partitioning schemes. Altogether, our study reveals the importance of the aerosol water for climate applications.


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