scholarly journals Impact of the Dust Aerosol Model on the VIIRS Aerosol Optical Depth (AOD) Product across China

2020 ◽  
Vol 12 (6) ◽  
pp. 991 ◽  
Author(s):  
Yang Wang ◽  
Liangfu Chen ◽  
Jinyuan Xin ◽  
Xinhui Wang
Keyword(s):  
Model Selection ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Southern China ◽  
Selection Process ◽  
Atmospheric Condition ◽  
Regression Equation ◽  
Research Network ◽  
Unexpected Result ◽  
Aerosol Model

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.

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 ◽  
...  
Keyword(s):  
Model Selection ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Bayesian Model Averaging ◽  
Forward Model ◽  
Selection Problem ◽  
Aerosol Model ◽  
Model Discrepancy ◽  
Aerosol Types ◽  
Model Selection Problem

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.

scholarly journals Retrieval of the Fine-Mode Aerosol Optical Depth over East China Using a Grouped Residual Error Sorting (GRES) Method from Multi-Angle and Polarized Satellite Data

2018 ◽  
Vol 10 (11) ◽  
pp. 1838 ◽  
Author(s):  
Yang Zhang ◽  
Zhengqiang Li ◽  
Zhihong Liu ◽  
Juan Zhang ◽  
Lili Qie ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Residual Error ◽  
East China ◽  
Anthropogenic Aerosols ◽  
Aerosol Model ◽  
Retrieval Accuracy ◽  
Aerosol Loading ◽  
Fine Mode ◽  
Fine Mode Aerosol

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.

scholarly journals Near-Real-Time Application of SEVIRI Aerosol Optical Depth Algorithm

2020 ◽  
Vol 12 (9) ◽  
pp. 1481
Author(s):  
Olga Zawadzka-Manko ◽  
Iwona S. Stachlewska ◽  
Krzysztof M. Markowicz
Keyword(s):  
Real Time ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Interpolation Method ◽  
Research Network ◽  
Optimal Interpolation ◽  
Infrared Imager ◽  
Uncertainty Calculation ◽  
Extended Area ◽  
Southern Norway

Within the framework of the Satellite-based Monitoring Initiative for Regional Air quality (SAMIRA) project, the near-real-time (NRT) operation has been documented for an in-house developed algorithm used for the retrieval of aerosol optical depth (AOD) maps from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the Meteosat Second Generation (MSG). With the frequency of 15 min at a spatial resolution of roughly 5.5 × 5.5 km the AOD maps are provided for the country domains of Poland, the Czech Republic, Romania, and Southern Norway. A significant improvement has been reported in terms of modification of the existing prototype algorithm that it suits the operational NRT AOD retrieval for an extended area. This is mainly due to the application of the optimal interpolation method for the AOD estimation on reference days with the use of ground-based measurements of the Aerosol Robotic Network (AERONET) and the Aerosol Research Network (PolandAOD-NET) as well as simulations of the Copernicus Atmosphere Monitoring Service (CAMS). The main issues that have been addressed regarding surface reflectance estimation, cloud screening and uncertainty calculation. Exemplary maps of the NRT retrieval have been presented.

scholarly journals Effect of aerosol sub-grid variability on aerosol optical depth and cloud condensation nuclei: Implications for global aerosol modelling

2016 ◽  
Author(s):  
N. Weigum ◽  
N. Schutgens ◽  
P. Stier
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Spatial Scales ◽  
Cloud Condensation Nuclei ◽  
Convective Transport ◽  
Condensation Nuclei ◽  
Gaseous Species ◽  
Climate Effects ◽  
Aerosol Model ◽  
The Impact

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.

scholarly journals Comparison of AERONET and SKYRAD4.2 inversion products retrieved from a Cimel CE318 sunphotometer

2012 ◽  
Vol 5 (3) ◽  
pp. 569-579 ◽  
Author(s):  
V. Estellés ◽  
M. Campanelli ◽  
M. P. Utrillas ◽  
F. Expósito ◽  
J. A. Martínez-Lozano
Keyword(s):  
Refractive Index ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Asymmetry Parameter ◽  
Single Scattering ◽  
Single Scattering Albedo ◽  
Research Network ◽  
High Turbidity ◽  
The Individual ◽  
Good Agreement

Abstract. SKYNET is an international research network of ground based sky – sunphotometers for the observation and monitoring of columnar aerosol properties. The algorithm developed by SKYNET is called SKYRAD.pack, and it is used on Prede instruments only. In this study, we have modified the SKYRAD.pack software in order to adapt it to Cimel sunphotometers. A one month database of Cimel data obtained at Burjassot (Valencia, Spain) has been processed with this program and the obtained inversion products have been compared with AERONET retrievals. In general, the differences found were consistent with the individual error assessments for both algorithms. Although the aerosol optical depth compared well for any aerosol burden situation (rmsd of 0.002–0.013 for all wavelengths), inversion products such as the single scattering albedo, refractive index and asymmetry parameter compared better for higher turbidity situations. The comparison performed for cases with an aerosol optical depth at 440 nm over 0.2 showed rms differences of 0.025–0.049 for single scattering albedo, 0.005–0.034 for the real part of refractive index, 0.004–0.007 for the imaginary part of the refractive index and 0.006–0.009 for the asymmetry parameter. With respect to the volume distributions, the comparison also showed a good agreement for high turbidity cases (mainly within the 0.01–7 μm interval) although the already known discrepancy in the extremes of the distribution was still found in 40% of the cases, in spite of eliminating data and instrumental differences present in previous studies.

scholarly journals Aerosol water parameterization: long-term evaluation and importance

2018 ◽  
Author(s):  
Swen Metzger ◽  
Mohamed Abdelkader ◽  
Benedikt Steil ◽  
Klaus Klingmüller
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Water Uptake ◽  
Climate Model ◽  
Climate Modeling ◽  
Mixed Solution ◽  
Hygroscopic Growth ◽  
Aerosol Model ◽  
Term Evaluation

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.

scholarly journals Quantifying the response of the ORAC aerosol optical depth retrieval for MSG SEVIRI to aerosol model assumptions

2011 ◽  
Vol 116 (D5) ◽  
Author(s):  
Claire E. Bulgin ◽  
Paul I. Palmer ◽  
Christopher J. Merchant ◽  
Richard Siddans ◽  
Siegfried Gonzi ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Aerosol Model

scholarly journals Recovery of the first ever multi-year lidar dataset of the stratospheric aerosol layer, from Lexington, MA, and Fairbanks, AK, January 1964 to July 1965

2021 ◽  
Vol 13 (9) ◽  
pp. 4407-4423
Author(s):  
Juan-Carlos Antuña-Marrero ◽  
Graham W. Mann ◽  
John Barnes ◽  
Albeht Rodríguez-Vega ◽  
Sarah Shallcross ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Coupled Model ◽  
Stratospheric Aerosol ◽  
Aerosol Layer ◽  
Large Variability ◽  
Aerosol Model ◽  
Intercomparison Project ◽  
Relative Errors ◽  
The Tropics

Abstract. We report the recovery and processing methodology of the first ever multi-year lidar dataset of the stratospheric aerosol layer. A Q-switched ruby lidar measured 66 vertical profiles of 694 nm attenuated backscatter at Lexington, Massachusetts, between January 1964 and August 1965, with an additional nine profile measurements conducted from College, Alaska, during July and August 1964. We describe the processing of the recovered lidar backscattering ratio profiles to produce mid-visible (532 nm) stratospheric aerosol extinction profiles (sAEP532) and stratospheric aerosol optical depth (sAOD532) measurements, utilizing a number of contemporary measurements of several different atmospheric variables. Stratospheric soundings of temperature and pressure generate an accurate local molecular backscattering profile, with nearby ozone soundings determining the ozone absorption, which are used to correct for two-way ozone transmittance. Two-way aerosol transmittance corrections are also applied based on nearby observations of total aerosol optical depth (across the troposphere and stratosphere) from sun photometer measurements. We show that accounting for these two-way transmittance effects substantially increases the magnitude of the 1964/1965 stratospheric aerosol layer's optical thickness in the Northern Hemisphere mid-latitudes, then ∼ 50 % larger than represented in the Coupled Model Intercomparison Project 6 (CMIP6) volcanic forcing dataset. Compared to the uncorrected dataset, the combined transmittance correction increases the sAOD532 by up to 66 % for Lexington and up to 27 % for Fairbanks, as well as individual sAEP532 adjustments of similar magnitude. Comparisons with the few contemporary measurements available show better agreement with the corrected two-way transmittance values. Within the January 1964 to August 1965 measurement time span, the corrected Lexington sAOD532 time series is substantially above 0.05 in three distinct periods, October 1964, March 1965, and May–June 1965, whereas the 6 nights the lidar measured in December 1964 and January 1965 had sAOD values of at most ∼ 0.03. The comparison with interactive stratospheric aerosol model simulations of the Agung aerosol cloud shows that, although substantial variation in mid-latitude sAOD532 are expected from the seasonal cycle in the stratospheric circulation, the Agung cloud's dispersion from the tropics would have been at its strongest in winter and weakest in summer. The increasing trend in sAOD from January to July 1965, also considering the large variability, suggests that the observed variations are from a different source than Agung, possibly from one or both of the two eruptions that occurred in 1964/1965 with a Volcanic Explosivity Index (VEI) of 3: Trident, Alaska, and Vestmannaeyjar, Heimaey, south of Iceland. A detailed error analysis of the uncertainties in each of the variables involved in the processing chain was conducted. Relative errors for the uncorrected sAEP532 were 54 % for Fairbanks and 44 % Lexington. For the corrected sAEP532 the errors were 61 % and 64 %, respectively. The analysis of the uncertainties identified variables that with additional data recovery and reprocessing could reduce these relative error levels. Data described in this work are available at https://doi.org/10.1594/PANGAEA.922105 (Antuña-Marrero et al., 2020a).

Validation of JAXA Himawari-8 Aerosol Optical Depth Products over China with AERONET and CARSNET Observations

2020 ◽  
Author(s):  
Ling Gao ◽  
Chengcai Li ◽  
Lin Chen ◽  
Jun Li ◽  
Huizheng Che
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Southern China ◽  
Correlation Coefficients ◽  
Northern China ◽  
Temporal Variations ◽  
Retrieval Algorithm ◽  
High Temporal Resolution ◽  
Surface Reflectance ◽  
Modis Aod

&lt;p&gt;The performance of JAXA Himawari-8 Advanced Himawari Imager (AHI) aerosol optical depth (AOD) products over China is evaluated with ground-based AErosol&amp;#160;RObotic&amp;#160;NETwork (AERONET) and Sun-Sky Radiometer Observation Network (CARSNET) observations as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products. Considering the quality and quantity of valid data, the study was limited to AOD products from AHI with a Quality Assurance Flag (QA_Flag) of &amp;#8220;good&amp;#8221; and &amp;#8220;very good.&amp;#8221; The spatial distribution of the AHI AOD product is similar to that of the MODIS AOD product. The AOD correlation between AHI and MODIS is better in the morning than in the afternoon after March, however, using MODIS AOD as a reference resulted in underestimation in the morning and overestimation in the afternoon. The bias is also larger in spring and autumn than in summer and winter. Validation with sun-photometer observations indicates good correlation between AHI AOD and ground-based observations with correlation coefficients larger than 0.75 (N&gt;1000) when barren and sparsely vegetated surfaces are excluded. At 02:30 UTC, 53% of the collocated AHI AOD observations fall in the expected error (EE) range and at 5:30 UTC, 59.3% fall above the EE. The AHI AOD overestimation was apparent at the Northern China stations in April and after October, whereas the underestimation was apparent in southern China throughout the year. The temporal variations of AHI and AERONET AOD also show that the overestimation occurred in the afternoon and underestimation occurred in the morning.&lt;/p&gt;&lt;p&gt;The assumption that the solar geometries were nearly identical and the surface reflectance unchanged for a month causes the surface reflectance underestimation and leads to the AOD overestimation for barren surfaces in autumn and winter. Because background aerosols were neglected, the surface reflectance was overestimated, leading to AOD underestimation in vegetated surfaces.&lt;/p&gt;&lt;p&gt;Overall, the JAXA AOD provides a reliable and high temporal resolution aerosol product for environmental and climate research and the aerosol retrieval algorithm requires improvement.&lt;/p&gt;

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