Daily spectral effects on concentrating PV solar cells as affected by realistic aerosol optical depth and other atmospheric conditions

This paper presents the software package REFLECT for the retrieval of ground reflectance from high and very-high resolution multispectral satellite images. The computation of atmospheric parameters is based on the 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) routines. Aerosol optical properties are calculated using the OPAC (Optical Properties of Aerosols and Clouds) model, while aerosol optical depth is estimated using the dark target method. A new approach is proposed for adjacency effect correction. Topographic effects were also taken into account, and a new model was developed for forest canopies. Validation has shown that ground reflectance estimation with REFLECT is performed with an accuracy of approximately ±0.01 in reflectance units (for the visible, near-infrared, and mid-infrared spectral bands), even for surfaces with varying topography. The validation of the software was performed through many tests. These tests involve the correction of the effects that are associated with sensor calibration, irradiance, and viewing conditions, atmospheric conditions (aerosol optical depth AOD and water vapour), adjacency, and topographic conditions.

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Atmospheric effect on the ground-based measurements of broadband surface albedo

Atmospheric Measurement Techniques ◽

10.5194/amt-5-2675-2012 ◽

2012 ◽

Vol 5 (11) ◽

pp. 2675-2688 ◽

Cited By ~ 12

Author(s):

T. Manninen ◽

A. Riihelä ◽

G. de Leeuw

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Surface Albedo ◽

Test Site ◽

Empirical Method ◽

Atmospheric Conditions ◽

Atmospheric Effect ◽

Clear Sky ◽

Using Data ◽

Sky Conditions

Abstract. Ground-based pyranometer measurements of the (clear-sky) broadband surface albedo are affected by the atmospheric conditions (mainly by aerosol particles, water vapour and ozone). A new semi-empirical method for estimating the magnitude of the effect of atmospheric conditions on surface albedo measurements in clear-sky conditions is presented. Global and reflected radiation and/or aerosol optical depth (AOD) at two wavelengths are needed to apply the method. Depending on the aerosol optical depth and the solar zenith angle values, the effect can be as large as 20%. For the cases we tested using data from the Cabauw atmospheric test site in the Netherlands, the atmosphere caused typically up to 5% overestimation of surface albedo with respect to corresponding black-sky surface albedo values.

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The regional distribution characteristics of aerosol optical depth over the Tibetan Plateau

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-15-15683-2015 ◽

2015 ◽

Vol 15 (11) ◽

pp. 15683-15710 ◽

Cited By ~ 3

Author(s):

C. Xu ◽

Y. M. Ma ◽

C. You ◽

Z. K. Zhu

Keyword(s):

Tibetan Plateau ◽

Aerosol Optical Depth ◽

Optical Depth ◽

Qaidam Basin ◽

Regional Distribution ◽

Atmospheric Environment ◽

Main Body ◽

The Tibetan Plateau ◽

Atmospheric Conditions ◽

Natural Boundary

Abstract. The Tibetan Plateau (TP) is representative of typical clean atmospheric conditions. Aerosol optical depth (AOD) retrieved by Multi-angle Imaging SpectroRadiometer (MISR) is higher over Qaidam Basin than the rest of the TP all the year. Different monthly variation patterns of AOD are observed over the southern and northern TP, whereby the aerosol load is usually higher in the northern TP than in the southern part. The aerosol load over the northern part increases from April to June, peaking in May. The maximum concentration of aerosols over the southern TP occurs in July. Aerosols appear to be more easily transported over the main body of the TP across the northeastern edge rather than the southern edge. This is may be because the altitude is much lower at the northeastern edge than that of the Himalayas located along the southern edge of the TP. Three-dimensional distributions of dust, polluted dust, polluted continental and smoke are also investigated based on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data. Dust is found to be the most prominent aerosol type on the TP, and other types of aerosols affect the atmospheric environment slightly. A natural boundary seems to extend to an altitude of 6–8 km a.s.l., which may act as a dividing line of higher dust occurrence in the northern TP and lower dust occurrence in the southern TP, especially in spring and summer. This boundary appears around 33–35° N in the middle of the plateau, and it is possibly associated with the high altitude terrain in the same geographic location. Comparisons of CALIPSO and MISR data show that this natural boundary extending to upper troposphere is consistent with the spatial pattern of aerosol loading. The whole TP blocks the atmospheric aerosols transported from surrounding regions, and the extreme high mountains on the TP also cause an obstruction to the transport of aerosols. The aerosol distribution patterns are primarily driven by atmospheric circulation. Northerly winds prevail above the TP in spring, which also facilitates the transport of aerosols from the Tarim Basin and Qaidam Basin to the main body of the TP. Nevertheless, aerosols above the TP can originate from both the northern and southern sides of the TP during summer.

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Tracking Smoke from a Prescribed Fire and its Impacts on Local Air Quality using Temporally Resolved GOES-16 ABI Aerosol Optical Depth (AOD)

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-20-0162.1 ◽

2021 ◽

Author(s):

Amy K. Huff ◽

Shobha Kondragunta ◽

Hai Zhang ◽

Istvan Laszlo ◽

Mi Zhou ◽

...

Keyword(s):

Air Quality ◽

Aerosol Optical Depth ◽

Optical Depth ◽

Prescribed Fire ◽

Fine Particulate Matter ◽

Ambient Air ◽

Absolute Error ◽

Atmospheric Conditions ◽

Polar Orbiting Satellite ◽

Relative Change

AbstractAerosol optical depth (AOD) retrieved from the GOES-16 Advanced Baseline Imager (ABI) was used to track a smoke plume from a prescribed fire in northeastern Virginia on March 8, 2020. Weather and atmospheric conditions created a favorable environment to transport the plume through the Washington, DC and Baltimore, Maryland metro areas in the afternoon and concentrate smoke near the surface, degrading air quality for several hours. ABI AOD with 5-min temporal resolution and 2-km spatial resolution definitively identified the timing and geographic extent of the plume during daylight hours. Comparison to AERONET AOD indicates that ABI AOD captured the relative change in AOD due to passage of the smoke, with a mean absolute error of 0.047. Ground-based measurements of fine particulate matter (PM2.5) confirm deteriorations in air quality coincident with the progression of the smoke. Ceilometer aerosol backscatter profiles verify plume transport timing and indicate that smoke aerosols were well mixed in a shallow boundary layer. This event illustrates the advantages of using multiple datasets to analyze the impacts of aerosols on ambient air quality. Given the quickly evolving nature of the event over several hours, ABI AOD provided information for the public and decision-makers that was not available from any other source, including polar-orbiting satellite sensors. This study suggests that PM2.5 concentrations estimated from ABI AOD can be used to fill in the gaps in nationwide regulatory PM2.5 monitor networks and may be a valuable addition to EPA’s PM2.5 Nowcast of current air quality conditions.

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Statistical Cluster Analysis of Global Aerosol Optical Depth for Simplified Atmospheric Modeling

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-21-0150.1 ◽

2021 ◽

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Atmospheric Aerosols ◽

Clustering Algorithm ◽

Atmospheric Modeling ◽

Lookup Table ◽

Anthropogenic Sources ◽

Upper And Lower Bounds ◽

Atmospheric Conditions ◽

Land Type

Abstract Atmospheric aerosols originating from natural and anthropogenic sources have important implications for modeling atmospheric phenomena, but aerosol conditions can change significantly and rapidly because of their dependence on local geography and atmospheric conditions. In this work, we applied a computational k-means clustering algorithm to a global set of data obtained from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) to yield a set of 25 clusters that discriminate based on land type, elevation, and atmospheric conditions to predict statistical aerosol optical depth (AOD) information. We considered different subsets of MERRA-2 data, consisting of all the data averaged over a single year (2016) as well as data averaged by meteorological season over a span of five years (2012–2016), arriving at five separate sets of 25 clusters. We make the clustered AOD information available with decision trees, qualitative cluster descriptions, and color-coded cluster maps to assist in identifying which cluster to use in retrieving AOD information. The results of this analysis have applications in atmospheric modeling where knowledge of approximate or typical aerosol conditions are needed in lookup table form without requiring access to large atmospheric databases or computationally intensive aerosol models; such applications could include quick-turn or large volume analyses of atmospheric conditions required to inform decision-making impacting national security, such as in modeling remote sensing and estimating upper and lower bounds for visible and infrared photon transport.

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Evidence of systematic errors in SCIAMACHY-observed CO<sub>2</sub> due to aerosols

Atmospheric Chemistry and Physics ◽

10.5194/acp-5-3003-2005 ◽

2005 ◽

Vol 5 (11) ◽

pp. 3003-3013 ◽

Cited By ~ 120

Author(s):

S. Houweling ◽

W. Hartmann ◽

I. Aben ◽

H. Schrijver ◽

J. Skidmore ◽

...

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Correlation Coefficients ◽

Real Data ◽

Radiative Transfer Model ◽

Transfer Model ◽

Atmospheric Conditions ◽

Large Variability ◽

Model Calculations ◽

The Impact

Abstract. SCIAMACHY CO2 measurements show a large variability in total column CO2 over the Sahara desert of up to 10%, which is not anticipated from in situ measurements and cannot be explained by results of atmospheric models. Comparisons with colocated aerosol measurements by TOMS and MISR over the Sahara indicate that the seasonal variation of SCIAMACHY-observed CO2 strongly resembles seasonal variations of windblown dust. Correlation coefficients of monthly datasets of colocated MISR aerosol optical depth and SCIAMACHY CO2 vary between 0.6 and 0.8, indicating that about half of the CO2 variance is explained by aerosol optical depth. Radiative transfer model calculations confirm the role of dust and can explain the size of the errors. Sensitivity tests suggest that the remaining variance may largely be explained by variations in the vertical distribution of dust. Further calculations for a few typical aerosol classes and a broad range of atmospheric conditions show that the impact of aerosols on SCIAMACHY retrieved CO2 is by far the largest over the Sahara, but may also reach significant levels elsewhere. Over the continents, aerosols lead mostly to overestimated CO2 columns with the exception of biomass burning plumes and dark coniferous forests. Inverse modelling calculations confirm that aerosol correction of SCIAMACHY CO2 measurements is needed to derive meaningful source and sink estimates. Methods for correcting aerosol-induced errors exist, but so far mainly on the basis of theoretical considerations. As demonstrated by this study, SCIAMACHY may contribute to a verification of such methods using real data.

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Comparison of AOD, AAOD and column single scattering albedo from AERONET retrievals and in situ profiling measurements

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-6041-2017 ◽

2017 ◽

Vol 17 (9) ◽

pp. 6041-6072 ◽

Cited By ~ 25

Author(s):

Elisabeth Andrews ◽

John A. Ogren ◽

Stefan Kinne ◽

Bjorn Samset

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Single Scattering ◽

Systematic Difference ◽

In Situ Measurements ◽

Single Scattering Albedo ◽

Atmospheric Conditions ◽

Aerosol Absorption ◽

Study Sites

Abstract. Here we present new results comparing aerosol optical depth (AOD), aerosol absorption optical depth (AAOD) and column single scattering albedo (SSA) obtained from in situ vertical profile measurements with AERONET ground-based remote sensing from two rural, continental sites in the US. The profiles are closely matched in time (within ±3 h) and space (within 15 km) with the AERONET retrievals. We have used Level 1.5 inversion retrievals when there was a valid Level 2 almucantar retrieval in order to be able to compare AAOD and column SSA below AERONET's recommended loading constraint (AOD > 0.4 at 440 nm). While there is reasonable agreement for the AOD comparisons, the direct comparisons of in situ-derived to AERONET-retrieved AAOD (or SSA) reveal that AERONET retrievals yield higher aerosol absorption than obtained from the in situ profiles for the low aerosol optical depth conditions prevalent at the two study sites. However, it should be noted that the majority of SSA comparisons for AOD440 > 0.2 are, nonetheless, within the reported SSA uncertainty bounds. The observation that, relative to in situ measurements, AERONET inversions exhibit increased absorption potential at low AOD values is generally consistent with other published AERONET–in situ comparisons across a range of locations, atmospheric conditions and AOD values. This systematic difference in the comparisons suggests a bias in one or both of the methods, but we cannot assess whether the AERONET retrievals are biased towards high absorption or the in situ measurements are biased low. Based on the discrepancy between the AERONET and in situ values, we conclude that scaling modeled black carbon concentrations upwards to match AERONET retrievals of AAOD should be approached with caution as it may lead to aerosol absorption overestimates in regions of low AOD. Both AERONET retrievals and in situ measurements suggest there is a systematic relationship between SSA and aerosol amount (AOD or aerosol light scattering) – specifically that SSA decreases at lower aerosol loading. This implies that the fairly common assumption that AERONET SSA values retrieved at high-AOD conditions can be used to obtain AAOD at low-AOD conditions may not be valid.

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Evidence of systematic errors in SCIAMACHY-observed CO<sub>2</sub> due to aerosols

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-5-3313-2005 ◽

2005 ◽

Vol 5 (3) ◽

pp. 3313-3340 ◽

Cited By ~ 5

Author(s):

S. Houweling ◽

W. Hartmann ◽

I. Aben ◽

H. Schrijver ◽

J. Skidmore ◽

...

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Inverse Modelling ◽

Radiative Transfer Model ◽

Transfer Model ◽

Atmospheric Conditions ◽

Large Variability ◽

Model Calculations ◽

Continental Scale ◽

The Impact

Abstract. SCIAMACHY CO2 measurements show a large variability in total column CO2 over the Sahara desert of up to 10% that is not anticipated from in situ measurements and cannot be explained by results of atmospheric models. Comparisons with colocated aerosol measurements by TOMS and MISR over the Sahara indicate that the seasonal variation of SCIAMACHY-observed CO2 strongly resembles seasonal variations of windblown dust. Correlation coefficients of monthly datasets of colocated MISR aerosol optical depth and SCIAMACHY CO2 vary between 0.6 and 0.8, indicating that about half of the CO2 variance is explained by aerosol optical depth. Radiative transfer model calculations confirm the role of dust and can explain the size of the errors. Sensitivity tests suggest that the remaining variance may largely be explained by variations in the vertical distribution of dust. Further calculations for a few typical aerosol classes and a broad range of atmospheric conditions show that the impact of aerosols on SCIAMACHY retrieved CO2 is by far the largest over the Sahara, but may also reach significant levels elsewhere. Inverse modelling calculations indicate that continental scale source and sink estimation on the basis of SCIAMACHY CO2 data without aerosol correction leads to significant errors. To improve terrestrial CO2 flux estimates by inverse modelling using SCIAMACHY measurements at 1.6μm, aerosol correction will be needed. Methods for correcting aerosol-induced errors exist, but so far mainly on the basis of theoretical considerations. As demonstrated by this study, SCIAMACHY may contribute to a verification of such methods using real data.

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