scholarly journals Reducing cloud contamination in aerosol optical depth (AOD) measurements

2021 ◽  
Vol 14 (4) ◽  
pp. 2787-2798
Author(s):  
Verena Schenzinger ◽  
Axel Kreuter
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Screening Method ◽  
Nearest Neighbour ◽  
Cloud Detection ◽  
Simple Method ◽  
Scanning Time ◽  
Filter Radiometer ◽  
Cloud Screening

Abstract. We propose a new cloud screening method for sun photometry that is designed to effectively filter thin clouds. Our method is based on a k-nearest-neighbour algorithm instead of scanning time series of aerosol optical depth. Using 10 years of data from a precision filter radiometer in Innsbruck, we compare our new method and the currently employed screening technique. We exemplify the performance of the two routines in different cloud conditions. While both algorithms agree on the classification of a data point as clear or cloudy in a majority of the cases, the new routine is found to be more effective in flagging thin clouds. We conclude that this simple method can serve as a valid alternative for cloud detection, and we discuss the generalizability to other observation sites.

scholarly journals Reducing cloud contamination in AOD measurements

2020 ◽  
Author(s):  
Verena Schenzinger ◽  
Axel Kreuter
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Screening Method ◽  
New Method ◽  
Nearest Neighbour ◽  
Cloud Detection ◽  
Simple Method ◽  
Filter Radiometer ◽  
Cloud Screening

Abstract. We propose a new cloud screening method for sun photometry that is designed to effectively filter thin clouds. Our method is based on a k-nearest neighbour algorithm instead of scanning timeseries of aerosol optical depth. Using ten years of data from a precision filter radiometer in Innsbruck, we compare our new method and the currently employed screening technique. We exemplify the performance of the two routines in different cloud conditions. While both algorithms agree on the classification of a datapoint as clear or cloudy in a majority of the cases, the new routine is found to be more effective in flagging thin clouds. We conclude that this simple method can serve as a valid alternative for cloud detection, and discuss the generalizability to other observation sites.

scholarly journals Aerosol Optical Depth comparison between GAW-PFR and AERONET-Cimel radiometers from long term (2005–2015) 1-minute synchronous measurements

2018 ◽  
Author(s):  
Emilio Cuevas ◽  
Pedro Miguel Romero-Campos ◽  
Natalia Kouremeti ◽  
Stelios Kazadzis ◽  
Rosa Delia García ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Rayleigh Scattering ◽  
Field Of View ◽  
Filter Radiometer ◽  
The World ◽  
Comprehensive Comparison ◽  
Cloud Screening ◽  
Fixed Period

Abstract. A comprehensive comparison of more than 70000 synchronous 1-minute aerosol optical depth (AOD) data from three Global Atmosphere Watch-Precision Filter Radiometer (GAW-PFR) and 15 Aerosol Robotic Network-Cimel (AERONET-Cimel) radiometers was performed for the four nearby wavelengths (380, 440, 500 and 870 nm) in the period 2005–2015. The goal of this study is to assess whether, despite the marked differences between both networks and the number of instruments used, their long term AOD data are comparable and consistent. AOD traceability established by the World Meteorological Organization (WMO) consists in determining the percentage of synchronous data within specific limits. If, at least, 95 % of the AOD differences of an instrument compared to the WMO standards lie within these limits, both data populations are considered equivalent. The percentage of traceable data is 92.7 % (380 nm), 95.7 % (440 nm), 95.8 % (500 nm) and 98.0 % (870 nm). When small misalignments in GAW-PFR sun-pointing were fixed (period 2010–2015), the percentage of traceable data increased. The contribution of calibration related aspects to comparison outside the 95 % traceability limits is insignificant in all channels, except in 380 nm. The simultaneous failure of both cloud screening algorithms might occur only under the presence of cirrus, or altostratus clouds on the top of a dust-laden Saharan air layer. Differences in the calculation of the optical depth contribution due to Rayleigh scattering, and O3 and NO2 absorption have a negligible impact. For AOD > 0.1, a non-negligible percentage (≈ 1.9 %) of the AOD data outside the 95 % traceability limits at 380 nm can be partly assigned to the different field of view of the instruments. The comparison of the Angström exponent (AE) shows that under non-pristine conditions (AOD > 0.03 and AE

scholarly journals Aerosol optical depth retrievals at the Izaña Atmospheric Observatory from 1941 to 2013 by using artificial neural networks

2016 ◽  
Vol 9 (1) ◽  
pp. 53-62 ◽  
Author(s):  
R. D. García ◽  
O. E. García ◽  
E. Cuevas ◽  
V. E. Cachorro ◽  
A. Barreto ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Artificial Neural Networks ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Mineral Dust ◽  
Dust Particles ◽  
Filter Radiometer ◽  
Artificial Neural

Abstract. This paper presents the reconstruction of a 73-year time series of the aerosol optical depth (AOD) at 500 nm at the subtropical high-mountain Izaña Atmospheric Observatory (IZO) located in Tenerife (Canary Islands, Spain). For this purpose, we have combined AOD estimates from artificial neural networks (ANNs) from 1941 to 2001 and AOD measurements directly obtained with a Precision Filter Radiometer (PFR) between 2003 and 2013. The analysis is limited to summer months (July–August–September), when the largest aerosol load is observed at IZO (Saharan mineral dust particles). The ANN AOD time series has been comprehensively validated against coincident AOD measurements performed with a solar spectrometer Mark-I (1984–2009) and AERONET (AErosol RObotic NETwork) CIMEL photometers (2004–2009) at IZO, obtaining a rather good agreement on a daily basis: Pearson coefficient, R, of 0.97 between AERONET and ANN AOD, and 0.93 between Mark-I and ANN AOD estimates. In addition, we have analysed the long-term consistency between ANN AOD time series and long-term meteorological records identifying Saharan mineral dust events at IZO (synoptical observations and local wind records). Both analyses provide consistent results, with correlations  >  85 %. Therefore, we can conclude that the reconstructed AOD time series captures well the AOD variations and dust-laden Saharan air mass outbreaks on short-term and long-term timescales and, thus, it is suitable to be used in climate analysis.

scholarly journals Cloud screening in AVHRR digital data over Arctic regions

1993 ◽  
Vol 17 ◽  
pp. 386-390 ◽  
Author(s):  
Sonia C. Gallegos ◽  
Jeffrey D. Hawkins ◽  
Chiu Fu Cheng
Keyword(s):  
Single Channel ◽  
Screening Method ◽  
Detection Algorithm ◽  
Digital Data ◽  
Cloud Detection ◽  
Arctic Regions ◽  
Identification Technique ◽  
Multiple Band ◽  
Cloud Screening ◽  
Very High

A cloud screening method initially generated to mask cloud contaminated pixels over the ocean in visible/infrared imagery, has been revised and adapted to detect clouds over Arctic regions with encouraging results. Although the method is quite successful in eliminating very cold clouds, it underestimates low level clouds. However, this does not appear to interfere with monitoring of ice related features such as leads or the ice edge in Advanced Very High Resolution Radiometer (AVHRR) scenes. The method uses: a multiple-band approach to produce signatures not readily available in single channel data, an edge detection/dilation technique to locate features in the clouds and to join isolated edges, and a polygon identification technique to remove noise in the form of isolated pixels and separate clear regions from cloud contaminated areas. The method has been tested over a limited set of data with consistent results. Initial evaluation of the usefulness of this cloud-detection algorithm in data-fusion experiments indicate a potential in locating areas in AVHRR data which are cloud contaminated and which could yield a far superior representation of the ice features if replaced with data from a different sensor such as the Special Sensor Microwave/lmager (SSM/I).

scholarly journals Measurement of aerosol optical depth and sub-visual cloud detection using the optical depth sensor (ODS)

2016 ◽  
Vol 9 (2) ◽  
pp. 455-467 ◽  
Author(s):  
D. Toledo ◽  
P. Rannou ◽  
J.-P. Pommereau ◽  
A. Sarkissian ◽  
T. Foujols
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Diffuse Radiation ◽  
Dust Storms ◽  
Saharan Dust ◽  
Cloud Detection ◽  
Depth Sensor ◽  
Data Set ◽  
Good Agreement

Abstract. A small and sophisticated optical depth sensor (ODS) has been designed to work in the atmosphere of Mars. The instrument measures alternatively the diffuse radiation from the sky and the attenuated direct radiation from the Sun on the surface. The principal goals of ODS are to retrieve the daily mean aerosol optical depth (AOD) and to detect very high and optically thin clouds, crucial parameters in understanding the Martian meteorology and climatology. The detection of clouds is undertaken at twilight, allowing the detection and characterization of clouds with opacities below 0.03 (sub-visual clouds). In addition, ODS is capable to retrieve the aerosol optical depth during nighttime from moonlight measurements. Recently, ODS has been selected at the METEO meteorological station on board the ExoMars 2018 Lander. In order to study the performance of ODS under Mars-like conditions as well as to evaluate the retrieval algorithms for terrestrial measurements, ODS was deployed in Ouagadougou (Africa) between November 2004 and October 2005, a Sahelian region characterized by its high dust aerosol load and the frequent occurrence of Saharan dust storms. The daily average AOD values retrieved by ODS were compared with those provided by a CIMEL sunphotometer of the AERONET (Aerosol Robotic NETwork) network localized at the same location. Results represent a good agreement between both ground-based instruments, with a correlation coefficient of 0.77 for the whole data set and 0.94 considering only the cloud-free days. From the whole data set, a total of 71 sub-visual cirrus (SVC) were detected at twilight with opacities as thin as 1.10−3 and with a maximum of occurrence at altitudes between 14 and 20 km. Although further optimizations and comparisons of ODS terrestrial measurements are required, results indicate the potential of these measurements to retrieve the AOD and detect sub-visual clouds.

scholarly journals Daytime and nighttime aerosol optical depth implementation in CÆLIS

2020 ◽  
Vol 9 (2) ◽  
pp. 417-433 ◽  
Author(s):  
Ramiro González ◽  
Carlos Toledano ◽  
Roberto Román ◽  
David Fuertes ◽  
Alberto Berjón ◽  
...  
Keyword(s):  
Quality Control ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Processing System ◽  
Software Tool ◽  
Mean Differences ◽  
The University ◽  
Phase Angles ◽  
Climate Studies ◽  
Cloud Screening

Abstract. The University of Valladolid (UVa, Spain) has managed a calibration center of the AErosol RObotic NETwork (AERONET) since 2006. The CÆLIS software tool, developed by UVa, was created to manage the data generated by AERONET photometers for calibration, quality control and data processing purposes. This paper exploits the potential of this tool in order to obtain products like the aerosol optical depth (AOD) and Ångström exponent (AE), which are of high interest for atmospheric and climate studies, as well as to enhance the quality control of the instruments and data managed by CÆLIS. The AOD and cloud screening algorithms implemented in CÆLIS, both based on AERONET version 3, are described in detail. The obtained products are compared with the AERONET database. In general, the differences in daytime AOD between CÆLIS and AERONET are far below the expected uncertainty of the instrument, ranging in mean differences between -1.3×10-4 at 870 nm and 6.2×10-4 at 380 nm. The standard deviations of the differences range from 2.8×10-4 at 675 nm to 8.1×10-4 at 340 nm. The AOD and AE at nighttime calculated by CÆLIS from Moon observations are also presented, showing good continuity between day and nighttime for different locations, aerosol loads and Moon phase angles. Regarding cloud screening, around 99.9 % of the observations classified as cloud-free by CÆLIS are also assumed cloud-free by AERONET; this percentage is similar for the cases considered cloud-contaminated by both databases. The obtained results point out the capability of CÆLIS as a processing system. The AOD algorithm provides the opportunity to use this tool with other instrument types and to retrieve other aerosol products in the future.

scholarly journals Aerosol optical depth retrievals at the Izaña Atmospheric Observatory from 1941 to 2013 by using artificial neural networks

2015 ◽  
Vol 8 (9) ◽  
pp. 9075-9103 ◽  
Author(s):  
R. D. García ◽  
O. E. García ◽  
E. Cuevas ◽  
V. E. Cachorro ◽  
A. Barreto ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Artificial Neural Networks ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Mineral Dust ◽  
Dust Particles ◽  
Filter Radiometer ◽  
Artificial Neural

Abstract. This paper presents the reconstruction of the 73 year time series of the aerosol optical depth (AOD) at 500 nm at the subtropical high-mountain Izaña Atmospheric Observatory (IZO) located in Tenerife (Canary Islands, Spain). For this purpose, we have combined AOD estimates from artificial neural networks (ANNs) from 1941 to 2001 and AOD measurements directly obtained with a Precision Filter Radiometer (PFR) between 2003 and 2013. The analysis is limited to summer months (July–August–September), when the largest aerosol load is observed at IZO (Saharan mineral dust particles). The ANN AOD time series has been comprehensively validated against coincident AOD measurements performed with a solar spectrometer Mark-I (1984–2009) and AERONET (AErosol RObotic NETwork) CIMEL photometers (2004–2009) at IZO, obtaining a rather good agreement on a daily basis: Pearson coefficient, R, of 0.97 between AERONET and ANN AOD, and 0.93 between Mark-I and ANN AOD estimates. In addition, we have analyzed the long-term consistency between ANN AOD time series and long-term meteorological records identifying Saharan mineral dust events at IZO (synoptical observations and local wind records). Both analyses provide consistent results, with correlations larger than 85 %. Therefore, we can conclude the reconstructed AOD time series captures well the AOD variations and dust-laden Saharan air mass outbreaks at short-term and long-term time scales and, thus, it is suitable to be used in climate analysis.

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