Validation and accuracy assessment of a Simplified Aerosol Retrieval Algorithm (SARA) over Beijing under low and high aerosol loadings and dust storms

2014 ◽  
Vol 153 ◽  
pp. 50-60 ◽  
Author(s):  
Muhammad Bilal ◽  
Janet E. Nichol ◽  
Pak W. Chan
2022 ◽  
Vol 14 (2) ◽  
pp. 373
Author(s):  
Muhammad Bilal ◽  
Alaa Mhawish ◽  
Md. Arfan Ali ◽  
Janet E. Nichol ◽  
Gerrit de Leeuw ◽  
...  

The SEMARA approach, an integration of the Simplified and Robust Surface Reflectance Estimation (SREM) and Simplified Aerosol Retrieval Algorithm (SARA) methods, was used to retrieve aerosol optical depth (AOD) at 550 nm from a Landsat 8 Operational Land Imager (OLI) at 30 m spatial resolution, a Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) at 500 m resolution, and a Visible Infrared Imaging Radiometer Suite (VIIRS) at 750 m resolution over bright urban surfaces in Beijing. The SEMARA approach coupled (1) the SREM method that is used to estimate the surface reflectance, which does not require information about water vapor, ozone, and aerosol, and (2) the SARA algorithm, which uses the surface reflectance estimated by SREM and AOD measurements obtained from the Aerosol Robotic NETwork (AERONET) site (or other high-quality AOD) as the input to estimate AOD without prior information on the aerosol optical and microphysical properties usually obtained from a look-up table constructed from long-term AERONET data. In the present study, AOD measurements were obtained from the Beijing AERONET site. The SEMARA AOD retrievals were validated against AOD measurements obtained from two other AERONET sites located at urban locations in Beijing, i.e., Beijing_RADI and Beijing_CAMS, over bright surfaces. The accuracy and uncertainties/errors in the AOD retrievals were assessed using Pearson’s correlation coefficient (r), root mean squared error (RMSE), relative mean bias (RMB), and expected error (EE = ± 0.05 ± 20%). EE is the envelope encompassing both absolute and relative errors and contains 68% (±1σ) of the good quality retrievals based on global validation. Here, the EE of the MODIS Dark Target algorithm at 3 km resolution is used to report the good quality SEMARA AOD retrievals. The validation results show that AOD from SEMARA correlates well with AERONET AOD measurements with high correlation coefficients (r) of 0.988, 0.980, and 0.981; small RMSE of 0.08, 0.09, and 0.08; and small RMB of 4.33%, 1.28%, and -0.54%. High percentages of retrievals, i.e., 85.71%, 91.53%, and 90.16%, were within the EE for Landsat 8 OLI, MODIS, and VIIRS, respectively. The results suggest that the SEMARA approach is capable of retrieving AOD over urban areas with high accuracy and small errors using high to medium spatial resolution satellite remote sensing data. This approach can be used for aerosol monitoring over bright urban surfaces such as in Beijing, which is frequently affected by severe dust storms and haze pollution, to evaluate their effects on public health.


2021 ◽  
Vol 658 (1) ◽  
pp. 012039
Author(s):  
Jiabao Yue ◽  
Donghai Xie ◽  
Jie Yu ◽  
Lin Zhu ◽  
Zhengyang He

2020 ◽  
Vol 13 (2) ◽  
pp. 553-573 ◽  
Author(s):  
Guangliang Fu ◽  
Otto Hasekamp ◽  
Jeroen Rietjens ◽  
Martijn Smit ◽  
Antonio Di Noia ◽  
...  

Abstract. In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON – the Netherlands Institute for Space Research. The campaign took place in October–November 2017 over the western part of the United States. During ACEPOL six different instruments were deployed on the NASA ER-2 high-altitude aircraft, including four multi-angle polarimeters (MAPs): SPEX airborne, the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI), and the Research Scanning Polarimeter (RSP). Also, two lidars participated: the High Spectral Resolution Lidar-2 (HSRL-2) and the Cloud Physics Lidar (CPL). Flights were conducted mainly for scenes with low aerosol load over land, but some cases with higher AOD were also observed. We perform aerosol retrievals from SPEX airborne, RSP (410–865 nm range only), and AirMSPI using the SRON aerosol retrieval algorithm and compare the results against AERONET (AErosol RObotic NETwork) and HSRL-2 measurements (for SPEX airborne and RSP). All three MAPs compare well against AERONET for the aerosol optical depth (AOD), with a mean absolute error (MAE) between 0.014 and 0.024 at 440 nm. For the fine-mode effective radius the MAE ranges between 0.021 and 0.028 µm. For the comparison with HSRL-2 we focus on a day with low AOD (0.02–0.14 at 532 nm) over the California Central Valley, Arizona, and Nevada (26 October) as well as a flight with high AOD (including measurements with AOD>1.0 at 532 nm) over a prescribed forest fire in Arizona (9 November). For the day with low AOD the MAEs in AOD (at 532 nm) with HSRL-2 are 0.014 and 0.022 for SPEX and RSP, respectively, showing the capability of MAPs to provide accurate AOD retrievals for the challenging case of low AOD over land. For the retrievals over the smoke plume a reasonable agreement in AOD between the MAPs and HSRL-2 was also found (MAE 0.088 and 0.079 for SPEX and RSP, respectively), despite the fact that the comparison is hampered by large spatial variability in AOD throughout the smoke plume. A good comparison is also found between the MAPs and HSRL-2 for the aerosol depolarization ratio (a measure of particle sphericity), with an MAE of 0.023 and 0.016 for SPEX and RSP, respectively. Finally, SPEX and RSP agree very well for the retrieved microphysical and optical properties of the smoke plume.


2009 ◽  
Vol 2 (2) ◽  
pp. 679-701 ◽  
Author(s):  
G. E. Thomas ◽  
C. A. Poulsen ◽  
A. M. Sayer ◽  
S. H. Marsh ◽  
S. M. Dean ◽  
...  

Abstract. The aerosol component of the Oxford-Rutherford Aerosol and Cloud (ORAC) combined cloud and aerosol retrieval scheme is described and the theoretical performance of the algorithm is analysed. ORAC is an optimal estimation retrieval scheme for deriving cloud and aerosol properties from measurements made by imaging satellite radiometers and, when applied to cloud free radiances, provides estimates of aerosol optical depth at a wavelength of 550 nm, aerosol effective radius and surface reflectance at 550 nm. The aerosol retrieval component of ORAC has several incarnations – this paper addresses the version which operates in conjunction with the cloud retrieval component of ORAC (described by Watts et al., 1998), as applied in producing the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) data-set. The algorithm is described in detail and its performance examined. This includes a discussion of errors resulting from the formulation of the forward model, sensitivity of the retrieval to the measurements and a priori constraints, and errors resulting from assumptions made about the atmospheric/surface state.


2013 ◽  
Vol 136 ◽  
pp. 135-145 ◽  
Author(s):  
Muhammad Bilal ◽  
Janet E. Nichol ◽  
Max P. Bleiweiss ◽  
David Dubois

Sign in / Sign up

Export Citation Format

Share Document