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

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.

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Aerosol optical depth in the European Brewer Network

10.5194/acp-2017-1003 ◽

2017 ◽

Author(s):

Javier López-Solano ◽

Alberto Redondas ◽

Thomas Carlund ◽

Juan J. Rodriguez-Franco ◽

Henri Diémoz ◽

...

Keyword(s):

Real Time ◽

Aerosol Optical Depth ◽

Optical Depth ◽

Temporal Variability ◽

Input Data ◽

Spatial And Temporal Variability ◽

Ultraviolet Range ◽

Using Data ◽

Better Than

Abstract. The high spatial and temporal variability of aerosols make networks capable of measuring their properties in near real time of high scientific interest. In this work we present and discuss results of an aerosol optical depth algorithm to be used in the European Brewer Network, which provides data in near real time of more than 30 spectrophotometers located from Tamanrasset (Algeria) to Kangerlussuaq (Greenland). Using data from the Brewer Intercomparison Campaigns in the years 2013 and 2015, and the period in between, plus comparisons with Cimel sunphotometers and UVPFR instruments, we check the precision, stability, and uncertainty of the Brewer AOD in the ultraviolet range from 300 to 320 nm. Our results show a precision better than 0.01, an uncertainty of less than 0.05, and a stability similar to that of the ozone measurements for well-maintained instruments. We also discuss future improvements to our algorithm with respect to the input data, their processing, and the characterization of the Brewer instruments for the measurement of aerosols.

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Preliminary investigations toward nighttime aerosol optical depth retrievals from the VIIRS day/night band

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-6-587-2013 ◽

2013 ◽

Vol 6 (1) ◽

pp. 587-612 ◽

Cited By ~ 4

Author(s):

R. S. Johnson ◽

J. Zhang ◽

E. J. Hyer ◽

S. D. Miller ◽

J. S. Reid

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Temporal Resolution ◽

Cape Verde ◽

New Method ◽

Coefficient Of Determination ◽

Infrared Imager ◽

Before And After ◽

Artificial Surface ◽

Grand Forks

Abstract. A great need exists for reliable nighttime aerosol products at high spatial and temporal resolution. In this concept demonstration study, using Visible/Infrared Imager/Radiometer Suite (VIIRS) Day/Night Band (DNB) observations on the Suomi National Polar-orbiting Partnership (NPP) satellite, a new method is proposed for retrieving nighttime aerosol optical depth (τ) using the contrast between regions with and without artificial surface lights. Evaluation of the retrieved τ values against daytime AERONET data from before and after the overpass of the VIIRS satellite over the Cape Verde, Grand Forks, and Alta Floresta AERONET stations yields a coefficient of determination (r2) of 0.71. This study suggests that the VIIRS DNB has the potential to provide useful nighttime aerosol detection and property retrievals.

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Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin

Atmospheric Chemistry and Physics ◽

10.5194/acp-14-12031-2014 ◽

2014 ◽

Vol 14 (22) ◽

pp. 12031-12053 ◽

Cited By ~ 32

Author(s):

Y. Wang ◽

K. N. Sartelet ◽

M. Bocquet ◽

P. Chazette ◽

M. Sicard ◽

...

Keyword(s):

Air Quality ◽

Mediterranean Basin ◽

Interpolation Method ◽

Period Length ◽

Research Network ◽

Optimal Interpolation ◽

Aerodynamic Diameter ◽

Western Mediterranean Basin ◽

Ground Based Lidar ◽

The Impact

Abstract. This paper presents a new application of assimilating lidar signals to aerosol forecasting. It aims at investigating the impact of a ground-based lidar network on the analysis and short-term forecasts of aerosols through a case study in the Mediterranean basin. To do so, we employ a data assimilation (DA) algorithm based on the optimal interpolation method developed in the Polair3D chemistry transport model (CTM) of the Polyphemus air quality modelling platform. We assimilate hourly averaged normalised range-corrected lidar signals (PR2) retrieved from a 72 h period of intensive and continuous measurements performed in July 2012 by ground-based lidar systems of the European Aerosol Research Lidar Network (EARLINET) integrated into the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) network and an additional system in Corsica deployed in the framework of the pre-ChArMEx (Chemistry-Aerosol Mediterranean Experiment)/TRAQA (TRAnsport à longue distance et Qualité de l'Air) campaign. This lidar campaign was dedicated to demonstrating the potential operationality of a research network like EARLINET and the potential usefulness of assimilation of lidar signals to aerosol forecasts. Particles with an aerodynamic diameter lower than 2.5 μm (PM2.5) and those with an aerodynamic diameter higher than 2.5 μm but lower than 10 μm (PM10–2.5) are analysed separately using the lidar observations at each DA step. First, we study the spatial and temporal influences of the assimilation of lidar signals on aerosol forecasting. We conduct sensitivity studies on algorithmic parameters, e.g. the horizontal correlation length (Lh) used in the background error covariance matrix (50 km, 100 km or 200 km), the altitudes at which DA is performed (0.75–3.5 km, 1.0–3.5 km or 1.5–3.5 km a.g.l.) and the assimilation period length (12 h or 24 h). We find that DA with Lh = 100 km and assimilation from 1.0 to 3.5 km a.g.l. during a 12 h assimilation period length leads to the best scores for PM10 and PM2.5 during the forecast period with reference to available measurements from surface networks. Secondly, the aerosol simulation results without and with lidar DA using the optimal parameters (Lh = 100 km, an assimilation altitude range from 1.0 to 3.5 km a.g.l. and a 12 h DA period) are evaluated using the level 2.0 (cloud-screened and quality-assured) aerosol optical depth (AOD) data from AERONET, and mass concentration measurements (PM10 or PM2.5) from the French air quality (BDQA) network and the EMEP-Spain/Portugal network. The results show that the simulation with DA leads to better scores than the one without DA for PM2.5, PM10and AOD. Additionally, the comparison of model results to evaluation data indicates that the temporal impact of assimilating lidar signals is longer than 36 h after the assimilation period.

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Assimilation of lidar signals: application to aerosol forecasting in the Mediterranean Basin

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-14-13059-2014 ◽

2014 ◽

Vol 14 (9) ◽

pp. 13059-13107 ◽

Cited By ~ 1

Author(s):

Y. Wang ◽

K. N. Sartelet ◽

M. Bocquet ◽

P. Chazette ◽

M. Sicard ◽

...

Keyword(s):

Transport Model ◽

Interpolation Method ◽

Period Length ◽

Research Network ◽

Optimal Interpolation ◽

Aerodynamic Diameter ◽

Background Error ◽

The Mediterranean ◽

Ground Based Lidar ◽

The Impact

Abstract. This paper presents a new application of assimilating lidar signals to aerosol forecasting. It aims at investigating the impact of a ground-based lidar network on analysis and short-term forecasts of aerosols through a case study in the Mediterranean. To do so, we employ a data assimilation (DA) algorithm based on the optimal interpolation method developed in the chemistry transport model (CTM) {Polair3D of the air quality modelling platform POLYPHEMUS. We assimilate hourly-averaged normalised range corrected lidar signals (PR2) retrieved from a 72 h period of intensive and continuous measurements performed in July 2012 by ground-based lidar systems of the European Aerosol Research Lidar Network (EARLINET) integrated into the Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS) and an additional system in Corsica deployed in the framework of the pre-ChArMEx (Chemistry-Aerosol Mediterranean Experiment)/TRAQA (TRAnsport à longue distance et Qualité de l'Air) campaign. This lidar campaign was dedicated to demonstrating the potential operationality of a research network like EARLINET and the potential usefulness of assimilation of lidar signals to aerosol forecasts. Particles with an aerodynamic diameter lower than 2.5 μm (PM2.5) and those with an aerodynamic diameter higher than 2.5 μm but lower than 10 μm (PM2.5–10) are analysed separately using the lidar observations at each DA step. First, we study the spatial and temporal influences of the assimilation of lidar signals on aerosol forecasting. We conduct sensitivity studies on algorithmic parameters, e.g. the horizontal correlation length (Lh) used in the background error covariance matrix (50 km, 100 km or 200 km), the altitudes at which DA is performed (0.75–3.5 km, 1.0–3.5 km or 1.5–3.5 km a.g.l.) and the assimilation period length (12 h or 24 h). We find that DA with Lh = 100 km and assimilation from 1.0 to 3.5 km a.g.l. during a 12 h assimilation period length leads to the best scores for PM10 and PM2.5 during the forecast period with reference to available measurements from surface networks. Secondly, the aerosol simulation results without and with lidar DA using the optimal parameters (Lh

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

Remote Sensing ◽

10.3390/rs12060991 ◽

2020 ◽

Vol 12 (6) ◽

pp. 991 ◽

Cited By ~ 1

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.

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

Atmospheric Measurement Techniques ◽

10.5194/amt-5-569-2012 ◽

2012 ◽

Vol 5 (3) ◽

pp. 569-579 ◽

Cited By ~ 38

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.

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Validation of new satellite aerosol optical depth retrieval algorithm using Raman lidar observations at radiative transfer laboratory in Warsaw

EPJ Web of Conferences ◽

10.1051/epjconf/201817604008 ◽

2018 ◽

Vol 176 ◽

pp. 04008 ◽

Cited By ~ 1

Author(s):

Olga Zawadzka ◽

Iwona S. Stachlewska ◽

Krzysztof M. Markowicz ◽

Anca Nemuc ◽

Kerstin Stebel

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Weather Conditions ◽

Retrieval Algorithm ◽

High Temporal Resolution ◽

Data Set ◽

Infrared Imager ◽

On Line ◽

The University ◽

Monitoring Service

During an exceptionally warm September of 2016, the unique, stable weather conditions over Poland allowed for an extensive testing of the new algorithm developed to improve the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) aerosol optical depth (AOD) retrieval. The development was conducted in the frame of the ESA-ESRIN SAMIRA project. The new AOD algorithm aims at providing the aerosol optical depth maps over the territory of Poland with a high temporal resolution of 15 minutes. It was tested on the data set obtained between 11-16 September 2016, during which a day of relatively clean atmospheric background related to an Arctic airmass inflow was surrounded by a few days with well increased aerosol load of different origin. On the clean reference day, for estimating surface reflectance the AOD forecast available on-line via the Copernicus Atmosphere Monitoring Service (CAMS) was used. The obtained AOD maps were validated against AODs available within the Poland-AOD and AERONET networks, and with AOD values obtained from the PollyXT-UW lidar. of the University of Warsaw (UW).

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