scholarly journals Reducing cloud contamination in AOD measurements

2020 ◽  
Author(s):  
Verena Schenzinger ◽  
Axel Kreuter

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.

2021 ◽  
Vol 14 (4) ◽  
pp. 2787-2798
Author(s):  
Verena Schenzinger ◽  
Axel Kreuter

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.


2018 ◽  
Author(s):  
Emilio Cuevas ◽  
Pedro Miguel Romero-Campos ◽  
Natalia Kouremeti ◽  
Stelios Kazadzis ◽  
Rosa Delia García ◽  
...  

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


2016 ◽  
Vol 9 (1) ◽  
pp. 53-62 ◽  
Author(s):  
R. D. García ◽  
O. E. García ◽  
E. Cuevas ◽  
V. E. Cachorro ◽  
A. Barreto ◽  
...  

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.


2010 ◽  
Vol 10 (1) ◽  
pp. 977-1004
Author(s):  
C. Paton-Walsh ◽  
L. K. Emmons ◽  
S. R. Wilson

Abstract. In this paper we describe a new method for estimating trace gas emissions from large vegetation fires using measurements of aerosol optical depth from the MODIS instruments onboard NASA's Terra and Aqua satellites, combined with the atmospheric chemical transport model MOZART. The model allows for an estimate of double counting of enhanced levels of aerosol optical depth in consecutive satellite overpasses. Using this method we infer an estimated total emission of 10±3 Tg of carbon monoxide from the Canberra fires of 2003. Emissions estimates for several other trace gases are also given. An assessment of the uncertainties in the new method is made and we show that our estimate agrees (within expected uncertainties) with estimates made using current conventional methods of multiplying together factors for the area burned, fuel load, the combustion efficiency and the emission factor for carbon monoxide. The new method for estimating emissions from large vegetation fires described in this paper has some significant uncertainties, but these are mainly quantifiable and largely independent of the uncertainties inherent in conventional techniques. Thus we conclude that the new method is a useful additional tool for characterising emissions from vegetation fires.


1993 ◽  
Vol 17 ◽  
pp. 386-390 ◽  
Author(s):  
Sonia C. Gallegos ◽  
Jeffrey D. Hawkins ◽  
Chiu Fu Cheng

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).


2016 ◽  
Vol 9 (2) ◽  
pp. 455-467 ◽  
Author(s):  
D. Toledo ◽  
P. Rannou ◽  
J.-P. Pommereau ◽  
A. Sarkissian ◽  
T. Foujols

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.


2010 ◽  
Vol 10 (12) ◽  
pp. 5739-5748 ◽  
Author(s):  
C. Paton-Walsh ◽  
L. K. Emmons ◽  
S. R. Wilson

Abstract. In this paper we describe a new method for estimating trace gas emissions from large vegetation fires using satellite measurements of aerosol optical depth (AOD) at 550 nm, combined with an atmospheric chemical transport model. The method uses a threshold value to screen out normal levels of AOD that may be caused by raised dust, sea salt aerosols or diffuse smoke transported from distant fires. Using this method we infer an estimated total emission of 15±5 Tg of carbon monoxide, 0.05±0.02 Tg of hydrogen cyanide, 0.11±0.03 Tg of ammonia, 0.25±0.07 Tg of formaldehyde, 0.03±0.01 of acetylene, 0.10±0.03 Tg of ethylene, 0.03±0.01 Tg of ethane, 0.21±0.06 Tg of formic acid and 0.28±0.09 Tg of methanol released to the atmosphere from the Canberra fires of 2003. An assessment of the uncertainties in the new method is made and we show that our estimate agrees (within expected uncertainties) with estimates made using current conventional methods of multiplying together factors for the area burned, fuel load, the combustion efficiency and the emission factor for carbon monoxide. A simpler estimate derived directly from the satellite AOD measurements is also shown to be in agreement with conventional estimates, suggesting that the method may, under certain meteorological conditions, be applied without the complication of using a chemical transport model. The new method is suitable for estimating emissions from distinct large fire episodes and although it has some significant uncertainties, these are largely independent of the uncertainties inherent in conventional techniques. Thus we conclude that the new method is a useful additional tool for characterising emissions from vegetation fires.


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