Technical note Description of a computer code to simulate the satellite signal in the solar spectrum: the 5S code

1990 ◽  
Vol 11 (4) ◽  
pp. 659-668 ◽  
Author(s):  
D. TANRÉ ◽  
C. DEROO ◽  
P. DUHAUT ◽  
M. HERMAN ◽  
J. J. MORCRETTE ◽  
...  
Keyword(s):  
Solar Spectrum ◽  
Computer Code ◽  
Technical Note ◽  
Satellite Signal

scholarly journals Calibration of Satellite Low Radiance by AERONET-OC Products and 6SV Model

2021 ◽  
Vol 13 (4) ◽  
pp. 781
Author(s):  
Cristiana Bassani ◽  
Sindy Sterckx
Keyword(s):  
Optical Sensors ◽  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Water Quality Monitoring ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Blue Band ◽  
Satellite Signal ◽  
Almost All ◽  
User Friendly

For water quality monitoring using satellite data, it is often required to optimize the low radiance signal through the application of radiometric gains. This work describes a procedure for the retrieval of radiometric gains to be applied to OLI/L8 and MSI/S2A data over coastal waters. The gains are defined by the ratio of the top of atmosphere (TOA) reflectance simulated using the Second Simulation of a Satellite Signal in the Solar Spectrum—vector (6SV) radiative transfer model, REF, and the TOA reflectance acquired by the sensor, MEAS, over AERONET-OC stations. The REF is simulated considering quasi-synchronous atmospheric and aquatic AERONET-OC products and the image acquisition geometry. Both for OLI/L8 and MSI/S2A the measured TOA reflectance was higher than the modeled signal in almost all bands resulting in radiometric gains less than 1. The use of retrieved gains showed an improvement of reflectance remote sensing, Rrs, when with ACOLITE atmospheric correction software. When the gains are applied an accuracy improvement of the Rrs in the 400–700 nm domain was observed except for the first blue band of both sensors. Furthermore, the developed procedure is quick, user-friendly, and easily transferable to other optical sensors.

scholarly journals Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading

2021 ◽  
Vol 13 (8) ◽  
pp. 1544
Author(s):  
Tang-Huang Lin ◽  
Si-Chee Tsay ◽  
Wei-Hung Lien ◽  
Neng-Huei Lin ◽  
Ta-Chih Hsiao
Keyword(s):  
Optical Depth ◽  
Complex Refractive Index ◽  
Solar Spectrum ◽  
Collective Models ◽  
Anthropogenic Pollutants ◽  
Satellite Signal ◽  
Aerosol Compositions ◽  
Theoretical Simulations ◽  
Derivatives Of ◽  
Aerosol Index

Quantifying aerosol compositions (e.g., type, loading) from remotely sensed measurements by spaceborne, suborbital and ground-based platforms is a challenging task. In this study, the first and second-order spectral derivatives of aerosol optical depth (AOD) with respect to wavelength are explored to determine the partitions of the major components of aerosols based on the spectral dependence of their particle optical size and complex refractive index. With theoretical simulations from the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) model, AOD spectral derivatives are characterized for collective models of aerosol types, such as mineral dust (DS) particles, biomass-burning (BB) aerosols and anthropogenic pollutants (AP), as well as stretching out to the mixtures among them. Based on the intrinsic values from normalized spectral derivatives, referenced as the Normalized Derivative Aerosol Index (NDAI), a unique pattern is clearly exhibited for bounding the major aerosol components; in turn, fractions of the total AOD (fAOD) for major aerosol components can be extracted. The subtlety of this NDAI method is examined by using measurements of typical aerosol cases identified carefully by the ground-based Aerosol Robotic Network (AERONET) sun–sky spectroradiometer. The results may be highly practicable for quantifying fAOD among mixed-type aerosols by means of the normalized AOD spectral derivatives.

scholarly journals Technical Note: A novel parameterization of the transmissivity due to ozone absorption in the <i>k</i>-distribution method and correlated-<i>k</i> approximation of Kato et al. (1999) over the UV band

2015 ◽  
Vol 15 (13) ◽  
pp. 7449-7456 ◽  
Author(s):  
W. Wandji Nyamsi ◽  
A. Arola ◽  
P. Blanc ◽  
A. V. Lindfors ◽  
V. Cesnulyte ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Solar Spectrum ◽  
Ground Level ◽  
Technical Note ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Spectral Interval ◽  
Computationally Efficient ◽  
Ozone Absorption ◽  
Distribution Method

Abstract. The k-distribution method and the correlated-k approximation of Kato et al. (1999) is a computationally efficient approach originally designed for calculations of the broadband solar radiation at ground level by dividing the solar spectrum in 32 specific spectral bands from 240 to 4606 nm. Compared to a spectrally resolved computation, its performance in the UV band appears to be inaccurate, especially in the spectral intervals #3 [283, 307] nm and #4 [307, 328] nm because of inaccuracy in modeling the transmissivity due to ozone absorption. Numerical simulations presented in this paper indicate that a single effective ozone cross section is insufficient to accurately represent the transmissivity over each spectral interval. A novel parameterization of the transmissivity using more quadrature points yields maximum errors of respectively 0.0006 and 0.0143 for intervals #3 and #4. How to practically implement this new parameterization in a radiative transfer model is discussed for the case of libRadtran (library for radiative transfer). The new parameterization considerably improves the accuracy of the retrieval of irradiances in UV bands.

scholarly journals MODEL KOREKSI ATMOSFER CITRA LANDSAT-7 (ATMOSPHERIC CORRECTION MODELS OF LANDSAT-7 IMAGERY)

2018 ◽  
Vol 14 (2) ◽  
Author(s):  
Fadila Muchsin ◽  
Liana Fibriawati ◽  
Kuncoro Adhi Pradhono
Keyword(s):  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Processing System ◽  
Line Of Sight ◽  
Adaptive Processing ◽  
Spectral Pattern ◽  
Ecosystem Disturbance ◽  
Corrected Image ◽  
Landsat 7 ◽  
Satellite Signal

Three methods of atmospheric correction, Second Simulation of the Satellite Signal in the Solar Spectrum (6S), Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) and the model Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), have been applied to the level 1T Landsat-7 image Jakarta area. The atmospheric corrected image is then compared with the TOA reflectance image. The results show that there is an improvement of the spectral pattern on the TOA reflectance image by the decrease of the reflectance value of each object by (1 - 11) % after the atmospheric correction of all models for visible bands (blue, green and red). In the NIR and SWIR bands there is an increase in the spectral value of about 1% to the TOA reflectance on all objects except wetland for the LEDAPS model. The percentage of the increase and the decrease in spectral values of 6S and FLAASH models have the same tendency. Analyzes were also performed on the NDVI values of each model, where NDVI values were relatively higher after atmospheric correction. The NDVI value of rice crop on FLAASH model is the same as 6S model that is equal to 0.95 and for wetland, it has the same value between FLAASH model and LEDAPS which is 0.23. NDVI value of entire scene for FLAASH model = 0.63, LEDAPS model = 0.56 and 6S model = 0.66. Before the atmospheric correction, the TOA is 0.45. Abstrak Tiga metode koreksi atmosfer diantaranya  Second Simulation of the Satellite Signal in the Solar Spectrum (6S), Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) dan model Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) telah diterapkan pada citra Landsat-7 level 1T wilayah Jakarta. Citra yang telah terkoreksi atmosfer dibandingkan dengan citra reflektan TOA. Hasilnya menunjukkan bahwa terdapat perbaikan pola spektral pada citra reflektan TOA dengan adanya penurunan nilai reflektan setiap obyek sebesar (1 – 11) % setelah dilakukan koreksi atmosfer pada semua model untuk kanal-kanal visible (blue, green dan red). Pada kanal NIR dan SWIR terjadi kenaikan nilai spektral yaitu sekitar 1% terhadap reflektan TOA pada semua objek terkecuali objek lahan basah untuk model LEDAPS. Persentase kenaikan dan penurunan nilai spektral model 6S dan FLAASH memiliki kecenderungan yang sama. Analisis juga dilakukan terhadap nilai NDVI masing-masing model, dimana nilai NDVI relatif lebih tinggi setelah koreksi atmosfer. Nilai NDVI tanaman padi pada model FLAASH sama dengan model 6S yaitu sebesar 0.95 dan untuk lahan basah memiliki nilai yang sama antara model FLAASH dan LEDAPS yaitu 0.23. Nilai NDVI seluruh scene untuk model FLAASH = 0.63, model LEDAPS = 0.56 dan model 6S = 0.66. Sebelum koreksi atmosfer (TOA) adalah 0.45. 

scholarly journals Technical Note: A novel parameterization of the transmissivity due to ozone absorption in the <i>k</i>-distribution method and correlated-<i>k</i> approximation of Kato et al. (1999) over the UV band

2015 ◽  
Vol 15 (1) ◽  
pp. 1027-1040
Author(s):  
W. Wandji Nyamsi ◽  
A. Arola ◽  
P. Blanc ◽  
A. V. Lindfors ◽  
V. Cesnulyte ◽  
...  
Keyword(s):  
Solar Spectrum ◽  
Ground Level ◽  
Maximum Error ◽  
Technical Note ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Spectral Interval ◽  
Computationally Efficient ◽  
Ozone Absorption ◽  
Distribution Method

Abstract. The k-distribution method and the correlated-k approximation of Kato et al. (1999) is a computationally efficient approach originally designed for calculations of the broadband solar radiation at ground level by dividing the solar spectrum in 32 specific spectral bands from 240 to 4606 nm. Compared to a spectrally-resolved computation, its performance in the UV band appears to be inaccurate, especially in the spectral intervals #3 [283, 307] nm and #4 [307, 328] nm because of inaccuracy in modelling the transmissivity due to ozone absorption. Numerical simulations presented in this paper indicate that a single effective ozone cross section is insufficient to accurately represent the transmissivity over each spectral interval. A novel parameterization of the transmissivity using more quadrature points yields maximum error of respectively 0.0006 and 0.0041 for interval #3 and #4. How to practically implement this new parameterization in a radiative transfer model is discussed for the case of libRadtran.

scholarly journals Implementation of aerosol assimilation in Gridpoint Statistical Interpolation (v. 3.2) and WRF-Chem (v. 3.4.1)

2014 ◽  
Vol 7 (4) ◽  
pp. 1621-1627 ◽  
Author(s):  
M. Pagowski ◽  
Z. Liu ◽  
G. A. Grell ◽  
M. Hu ◽  
H.-C. Lin ◽  
...  
Keyword(s):  
Weather Forecasting ◽  
Meteorological Data ◽  
Computer Code ◽  
Technical Note ◽  
Background Error ◽  
Error Covariance ◽  
The Usa ◽  
Surface Measurements ◽  
Environmental Prediction ◽  
Statistical Interpolation

Abstract. Gridpoint Statistical Interpolation (GSI) is an assimilation tool that is used at the National Centers for Environmental Prediction (NCEP) in operational weather forecasting in the USA. In this article, we describe implementation of an extension to the GSI for assimilating surface measurements of PM2.5, PM10, and MODIS aerosol optical depth at 550 nm with WRF-Chem (Weather Research and Forecasting model coupled with Chemistry). We also present illustrative results. In the past, the aerosol assimilation system has been employed to issue daily PM2.5 forecasts at NOAA/ESRL (Earth System Research Laboratory) and, we believe, it is well tested and mature enough to be made available for wider use. We provide a package that, in addition to augmented GSI, consists of software for calculating background error covariance statistics and for converting in situ and satellite data to BUFR (Binary Universal Form for the Representation of meteorological data) format, and sample input files for an assimilation exercise. Thanks to flexibility in the GSI and coupled meteorology–chemistry of WRF-Chem, assimilating aerosol observations can be carried out simultaneously with meteorological data assimilation. Both GSI and WRF-Chem are well documented with user guides available online. This article is primarily intended to be a technical note on the implementation of the aerosol assimilation. Its purpose is also to provide guidance for prospective users of the computer code. Scientific aspects of aerosol assimilation are also briefly discussed.

Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: an overview

1997 ◽  
Vol 35 (3) ◽  
pp. 675-686 ◽  
Author(s):  
E.F. Vermote ◽  
D. Tanre ◽  
J.L. Deuze ◽  
M. Herman ◽  
J.-J. Morcette
Keyword(s):  
Solar Spectrum ◽  
Satellite Signal

scholarly journals Technical Note: Improved total atmospheric water vapour amount determination from near-infrared filter measurements with sun photometers

2007 ◽  
Vol 7 (17) ◽  
pp. 4613-4623 ◽  
Author(s):  
F. Mavromatakis ◽  
C. A. Gueymard ◽  
Y. Franghiadakis
Keyword(s):  
Radiative Transfer ◽  
Water Vapour ◽  
Near Infrared ◽  
Solar Spectrum ◽  
Theoretical Data ◽  
Precipitable Water ◽  
Technical Note ◽  
Residual Effects ◽  
Response Curves ◽  
Absolute Level

Abstract. In this work we explore the effect of the contribution of the solar spectrum to the recorded signal in wavelengths outside the typical 940-nm filter's bandwidth. We employ gaussian-shaped filters as well as actual filter transmission curves, mainly AERONET data, to study the implications imposed by the non-zero out-of-band contribution to the coefficients used to derive precipitable water from the measured water vapour band transmittance. Published parameterized transmittance functions are applied to the data to determine the filter coefficients. We also introduce an improved, three-parameter, fitting function that can describe the theoretical data accurately, with significantly less residual effects than with the existing functions. The moderate-resolution SMARTS radiative transfer code is used to predict the incident spectrum outside the filter bandpass for different atmospheres, solar geometries and aerosol optical depths. The high-resolution LBLRTM radiative transfer code is used to calculate the water vapour transmittance in the 940-nm band. The absolute level of the out-of-band transmittance has been chosen to range from 10−6 to 10−4, and typical response curves of commercially available silicon photodiodes are included into the calculations. It is shown that if the out-of-band transmittance effect is neglected, as is generally the case, then the derived columnar water vapour is mainly underestimated by a few percents. The actual error depends on the specific out-of-band transmittance, optical air mass of observation and water vapour amount. Further investigations will use experimental data from field campaigns to validate these findings.

scholarly journals Implementation of aerosol assimilation in Gridpoint Statistical Interpolation v. 3.2 and WRF-Chem v. 4.3.1

2014 ◽  
Vol 7 (2) ◽  
pp. 2483-2500 ◽  
Author(s):  
M. Pagowski ◽  
Z. Liu ◽  
G. A. Grell ◽  
M. Hu ◽  
H.-C. Lin ◽  
...  
Keyword(s):  
Weather Forecasting ◽  
Meteorological Data ◽  
Computer Code ◽  
Technical Note ◽  
Background Error ◽  
Error Covariance ◽  
Surface Measurements ◽  
On Line ◽  
Environmental Prediction ◽  
Statistical Interpolation

Abstract. Gridpoint Statistical Interpolation (GSI) is an assimilation tool that is used at the National Centers for Environmental Prediction in operational weather forecasting. In this article we describe implementation of an extension to the GSI for assimilating surface measurements of PM2.5, PM10, and MODIS Aerosol Optical Depth at 550 nm with WRF-Chem. We also present illustrations of the results. In the past the aerosol assimilation system has been employed to issue daily PM2.5 forecasts at NOAA/ESRL and, in our belief, is well tested and mature enough to make available for wider use. We provide a package that, in addition to augmented GSI, consists of software for calculating background error covariance statistics and for converting in-situ and satellite data to BUFR format, plus sample input files for an assimilation exercise. Thanks to flexibility in the GSI and coupled meteorology-chemistry of WRF-Chem, assimilating aerosol observations can be carried out simultaneously with meteorological data assimilation. Both GSI and WRF-Chem are well documented with user guides available on-line. This article is primarily intended as a technical note on the implementation of the aerosol assimilation. Its purpose is also to provide guidance for prospective users of the computer code. Limited space is devoted to scientific aspects of aerosol assimilation.

scholarly journals DEVELOPMENT OF SCHEME FOR THE ATMOSPHERIC CORRECTION OF LANDSAT-8 OLI DATA

2018 ◽  
Vol XLII-5 ◽  
pp. 671-674
Author(s):  
V. N. Pathak ◽  
M. R. Pandya ◽  
D. B. Shah ◽  
H. J. Trivedi
Keyword(s):  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Coefficient Of Determination ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Standard Data ◽  
Satellite Signal

<p><strong>Abstract.</strong> In the present study, a physics based method called Scheme for Atmospheric Correction of Landsat-8 (SACLS8) is developed for the Operational Land Imager (OLI) sensor of Landsat-8. The Second Simulation of the Satellite Signal in the Solar Spectrum Vector (6SV) radiative transfer model is used in the simulations to obtain the surface reflectance. The surface reflectance derived using the SACL8 scheme is validated with the <i>in-situ</i> measurements of surface reflectance carried out at the homogeneous desert site located in the Little Rann of Kutch, Gujarat, India. The results are also compared with Landsat-8 surface reflectance standard data product over the same site. The good agreement of results with high coefficient of determination (R<sup>2</sup><span class="thinspace"></span>><span class="thinspace"></span>0.94) and low root mean square error (of the order of 0.03) with <i>in-situ</i> measurement values as well as those obtained from the Landsat-8 surface reflectance data establishes a good performance of the SACLS8 scheme for the atmospheric correction of Landsat-8 dataset.</p>

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