scholarly journals Deriving column-integrated thermospheric temperature with the N<sub>2</sub> Lyman–Birge–Hopfield (2,0) band

2021 ◽  
Vol 14 (11) ◽  
pp. 6917-6928
Author(s):  
Clayton Cantrall ◽  
Tomoko Matsuo
Keyword(s):  
Rotational Temperature ◽  
Mass Density ◽  
Radiative Transfer Model ◽  
Band Model ◽  
Transfer Model ◽  
Emission Data ◽  
Channel Ratio ◽  
Ratio Approach ◽  
Spectral Channels ◽  
Level 2

Abstract. This paper presents a new technique to derive thermospheric temperature from space-based disk observations of far ultraviolet airglow. The technique, guided by findings from principal component analysis of synthetic daytime Lyman–Birge–Hopfield (LBH) disk emissions, uses a ratio of the emissions in two spectral channels that together span the LBH (2,0) band to determine the change in band shape with respect to a change in the rotational temperature of N2. The two-channel-ratio approach limits representativeness and measurement error by only requiring measurement of the relative magnitudes between two spectral channels and not radiometrically calibrated intensities, simplifying the forward model from a full radiative transfer model to a vibrational–rotational band model. It is shown that the derived temperature should be interpreted as a column-integrated property as opposed to a temperature at a specified altitude without utilization of a priori information of the thermospheric temperature profile. The two-channel-ratio approach is demonstrated using NASA GOLD Level 1C disk emission data for the period of 2–8 November 2018 during which a moderate geomagnetic storm has occurred. Due to the lack of independent thermospheric temperature observations, the efficacy of the approach is validated through comparisons of the column-integrated temperature derived from GOLD Level 1C data with the GOLD Level 2 temperature product as well as temperatures from first principle and empirical models. The storm-time thermospheric response manifested in the column-integrated temperature is also shown to corroborate well with hemispherically integrated Joule heating rates, ESA SWARM mass density at 460 km, and GOLD Level 2 column O/N2 ratio.

scholarly journals Deriving column-integrated thermospheric temperature with the N<sub>2</sub> Lyman–Birge–Hopfield (2,0) band

2021 ◽  
Author(s):  
Clayton Cantrall ◽  
Tomoko Matsuo
Keyword(s):  
Rotational Temperature ◽  
Mass Density ◽  
Principal Component ◽  
Instrumental Performance ◽  
Heating Rates ◽  
Band Shape ◽  
Emission Data ◽  
Channel Ratio ◽  
Ratio Approach ◽  
Level 2

Abstract. This paper presents a new technique to derive thermospheric temperature from space-based disk observations of far ultraviolet airglow. The technique, guided by findings from principal component analysis of synthetic daytime LBH disk emissions, uses a ratio of the emissions in two spectral channels that together span the Lyman–Birge–Hopfield (LBH) (2,0) band to determine the change in band shape with respect to a change in the rotational temperature of N2. The benefits of the two-channel ratio approach include an elimination of representativeness error as absolute LBH intensities are not required in the derivation procedure and a reduced impact of systematic measurement error caused by variations in the instrumental performance across the LBH band system as a fully resolved system is also not required. It is shown that the derived temperature should, in general, be interpreted as a column-integrated property as opposed to a temperature at a specified altitude without utilization of a priori information of the thermospheric temperature profile. The two-channel ratio approach is demonstrated using NASA GOLD Level 1C disk emission data for the period of 2–8 November 2018 during which a small geomagnetic storm has occurred. Due to the lack of independent thermospheric temperature observations, the efficacy of the approach is validated through comparisons of the column-integrated temperature derived from GOLD Level 1C data with version 2 of the GOLD Level 2 temperature product as well as temperatures from first principle and empirical models. The storm-time thermospheric response manifested in the column-integrated temperature is also shown to corroborate well with hemispherically integrated Joule heating rates, ESA SWARM mass density at 460 km, and GOLD Level 2 column O / N2 ratio.

Improvements to the Simplified Level 2 Prototype Processor for Retrieving Canopy Biophysical Variables from Sentinel 2 Multispectral Instrument Data

2021 ◽  
Author(s):  
Richard Fernandes ◽  
Fred Baret ◽  
Luke Brown ◽  
Francis Canisius ◽  
Jadu Dash ◽  
...  
Keyword(s):  
North America ◽  
Google Earth ◽  
Model Complexity ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Wide Field ◽  
Area Index ◽  
Product Generation ◽  
Level 2 ◽  
Sentinel 2

&lt;p&gt;The Sentinel 2 (S2) constellation mission was designed to facilitate the systematic mapping canopy biophysical variables at medium resolution on a global basis and in a free and open manner.&amp;#160; The mission concept requires the development of downstream services to map variables such as the fraction of absorbed photosynthetically active radiation (fAPAR), fraction of canopy cover (fCOVER) and leaf area index (LAI) using Level 2A surface reflectance inputs from the S2 ground segment.&amp;#160; Currently, free and open products generation can be performed using the Simplified Level 2 Prototype Processor (SL2P) applied on a product granule basis.&amp;#160; Considering that the processor is a prototype this study addresses three questions: 1) Can the SL2P algorithm, or subsequent versions, be engineered to facilitate systematic product generation over large extents in a free and open manner? 2) What is the uncertainty of SL2P products over North America during the growing season? 3) Can the uncertainty be reduced by changing the calibration database used within SL2P?&amp;#160;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;br&gt;&lt;br&gt;&lt;/p&gt;&lt;p&gt;To facilitate validation and product generation, SL2P was ported to a Google Earth Engine application (the Landscape Evolution and Forecasting Toolbox).&amp;#160; This now allows mapping of up to one million square kilometers in near real time using either the original SL2P algorithm or updated versions.&amp;#160; SL2P uncertainty was quantified over North America using direct comparison to 20 in-situ sites within the National Environmental Observing Network in the continental United States of America and within a Canada wide field campaign over forests and shrublands conducted by Canada Centre for Remote Sensing. SL2P outputs were also compared to MODIS and Copernicus Global Land Service products over the Belmanip II regional sites and 30 additional forested regions in North America.&amp;#160; Results from NEON validation indicate SL2P is generally within uncertainty requirements except for forests; where it underestimates fAPAR, fCOVER and LAI.&amp;#160; Results for other sites will also be presented.&amp;#160; To address the forest bias, SL2P was recalibrated using simulations from the FLIGHT 3D radiative transfer model representative of North American forests.&amp;#160; The uncertainty of the recalibrated SL2P algorithm will be compared to baseline SL2P estimates to determine if increased model complexity is warranted.&lt;/p&gt;

scholarly journals Snow Surface Albedo Sensitivity to Black Carbon: Radiative Transfer Modelling

Atmosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1077
Author(s):  
Nicholas D. Beres ◽  
Magín Lapuerta ◽  
Francisco Cereceda-Balic ◽  
Hans Moosmüller
Keyword(s):  
Radiative Transfer ◽  
Black Carbon ◽  
Surface Albedo ◽  
Mass Density ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Snow Surface ◽  
Snow Albedo ◽  
Carbon Mass ◽  
The Relationship

The broadband surface albedo of snow can greatly be reduced by the deposition of light-absorbing impurities, such as black carbon on or near its surface. Such a reduction increases the absorption of solar radiation and may initiate or accelerate snowmelt and snow albedo feedback. Coincident measurements of both black carbon concentration and broadband snow albedo may be difficult to obtain in field studies; however, using the relationship developed in this simple model sensitivity study, black carbon mass densities deposited can be estimated from changes in measured broadband snow albedo, and vice versa. Here, the relationship between the areal mass density of black carbon found near the snow surface to the amount of albedo reduction was investigated using the popular snow radiative transfer model Snow, Ice, and Aerosol Radiation (SNICAR). We found this relationship to be linear for realistic amounts of black carbon mass concentrations, such as those found in snow at remote locations. We applied this relationship to measurements of broadband albedo in the Chilean Andes to estimate how vehicular emissions contributed to black carbon (BC) deposition that was previously unquantified.

scholarly journals SSolar-GOA v1.0: a simple, fast, and accurate Spectral SOLAR radiative transfer model for clear skies

2021 ◽  
Author(s):  
Victoria Eugenia Cachorro ◽  
Juan Carlos Antuña-Sánchez ◽  
Ángel Máximo de Frutos
Keyword(s):  
Radiative Transfer ◽  
Ground Level ◽  
Environmental Research ◽  
Radiative Transfer Model ◽  
Homogeneous Layer ◽  
Band Model ◽  
Transfer Model ◽  
Atmospheric Conditions ◽  
Irradiance Data ◽  
Relative Differences

Abstract. The aim of this work is to describe the features and to validate a simple, fast, accurate and physical-based spectral radiative transfer model in the solar wavelength range under clear skies. The model, named SSolar-GOA (the first “S” stands for “Spectral”), was developed to evaluate the instantaneous values of spectral solar irradiances at ground level. The model data output are well suited to work at a spectral resolution of 1–10 nm, are adapted to commercial spectroradiometers or filter radiometers, and are addressed to a wide community of users for many different applications (atmospheric and environmental research studies, remote sensing, solar energy, agronomy/forestry, ecology, etc.). The model requirements are designed based on the simplicity of the analytical expressions for the transmittance functions in order to be easily replicated and applied by users. Although spectral, the model runs quickly and has sufficient accuracy. The model assumes a single mixed molecule-aerosol scattering layer where the original Ambartsumian method of “adding layers" in a one-dimensional medium is applied, obtaining a parameterized expression for the total transmittance of scattering. Absorption by the different atmospheric gases follows “band model” parameterized expressions. Both processes are applied to a single atmospheric homogeneous layer as necessary approaches for developing a simple model under the consideration of non-interaction. Besides, the input parameters must be realistic and easily available since the spectral aerosol optical depth (AOD) is the main driver of the model. The validation of the SSolar-GOA model has been carried out through extensive comparison with simulated irradiance data from the LibRadtran package and with direct/global spectra measured by spectroradiometers. Thousands of spectra under clear skies have been compared for different atmospheric conditions and solar zenithal angles (SZA). From the results of the comparison with LibRadtran, the SSolar-GOA model shows a high performance for the entire solar spectral range for direct, global, and diffuse spectral components with relative differences of +1 %, +3 %, and 8 %, respectively, and our model always gives an underestimation. Compared with the measured irradiance data of the Licor1800 and ASD spectroradiometers, the relative differences of direct and global components are within the overall experimental error (about ±2–12 %) with underestimated or overestimated values. The diffuse component presents the highest degree of difference which can reach ±20–30 %. Obviously, the relative differences depend strongly on the spectral solar region analysed and the SZA. Model approach errors combined with calibration instrument errors may explain the observed differences.

scholarly journals A first comparison of TROPOMI aerosol layer height (ALH) to CALIOP data

2020 ◽  
Vol 13 (6) ◽  
pp. 3043-3059 ◽  
Author(s):  
Swadhin Nanda ◽  
Martin de Graaf ◽  
J. Pepijn Veefkind ◽  
Maarten Sneep ◽  
Mark ter Linden ◽  
...  
Keyword(s):  
Optimal Estimation ◽  
Satellite Observation ◽  
Radiative Transfer Model ◽  
Orthogonal Polarization ◽  
Ultraviolet Region ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Layer Height ◽  
Significant Difference ◽  
Level 2

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) level-2 aerosol layer height (ALH) product has now been released to the general public. This product is retrieved using TROPOMI's measurements of the oxygen A-band, radiative transfer model (RTM) calculations augmented by neural networks and an iterative optimal estimation technique. The TROPOMI ALH product will deliver ALH estimates over cloud-free scenes over the ocean and land that contain aerosols above a certain threshold of the measured UV aerosol index (UVAI) in the ultraviolet region. This paper provides background for the ALH product and explores its quality by comparing ALH estimates to similar quantities derived from spaceborne lidars observing the same scene. The spaceborne lidar chosen for this study is the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission, which flies in formation with NASA's A-train constellation since 2006 and is a proven source of data for studying ALHs. The influence of the surface and clouds is discussed, and the aspects of the TROPOMI ALH algorithm that will require future development efforts are highlighted. A case-by-case analysis of the data from the four selected cases (mostly around the Saharan region with approximately 800 co-located TROPOMI pixels and CALIOP profiles in June and December 2018) shows that ALHs retrieved from TROPOMI using the operational Sentinel-5 Precursor Level-2 ALH algorithm is lower than CALIOP aerosol extinction heights by approximately 0.5 km. Looking at data beyond these cases, it is clear that there is a significant difference when it comes to retrievals over land, where these differences can easily go over 1 km on average.

scholarly journals Radiometrically Consistent Climate Fingerprinting Using CrIS and AIRS Hyperspectral Observations

2020 ◽  
Vol 12 (8) ◽  
pp. 1291
Author(s):  
Wan Wu ◽  
Xu Liu ◽  
Qiguang Yang ◽  
Daniel K. Zhou ◽  
Allen M. Larar
Keyword(s):  
Water Vapor ◽  
Atmospheric Temperature ◽  
Satellite Observations ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Climate Data ◽  
Fingerprinting Method ◽  
Level 2

We introduce a novel spectral fingerprinting scheme that can be used to derive long-term atmospheric temperature and water vapor anomalies from hyperspectral infrared sounders such as Cross-track Infrared Sounder (CrIS) and Atmospheric Infrared Sounder (AIRS). It is a challenging task to derive climate trends from real satellite observations due to the difficulty of carrying out accurate cloudy radiance simulations and constructing radiometrically consistent radiative kernels. To address these issues, we use a principal component based radiative transfer model (PCRTM) to perform multiple scattering calculations of clouds and a PCRTM-based physical retrieval algorithm to derive radiometrically consistent radiative kernels from real satellite observations. The capability of including the cloud scattering calculations in the retrieval process allows the establishment of a rigorous radiometric fitting to satellite-observed radiances under all-sky conditions. The fingerprinting solution is directly obtained via an inverse relationship between the atmospheric anomalies and the corresponding spatiotemporally averaged radiance anomalies. Since there is no need to perform Level 2 retrievals on each individual satellite footprint for the fingerprinting approach, it is much more computationally efficient than the traditional way of producing climate data records from spatiotemporally averaged Level 2 products. We have applied the spectral fingerprinting method to six years of CrIS and 16 years of AIRS data to derive long-term anomaly time series for atmospheric temperature and water vapor profiles. The CrIS and AIRS temperature and water vapor anomalies derived from our spectral fingerprinting method have been validated using results from the PCRTM-based physical retrieval algorithm and the AIRS operational retrieval algorithm, respectively.

scholarly journals Retrieval of atmospheric profiles and cloud properties from IASI spectra using super-channels

2009 ◽  
Vol 9 (23) ◽  
pp. 9121-9142 ◽  
Author(s):  
X. Liu ◽  
D. K. Zhou ◽  
A. M. Larar ◽  
W. L. Smith ◽  
P. Schluessel ◽  
...  
Keyword(s):  
Surface Properties ◽  
Information Content ◽  
Weather Prediction ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Cloud Properties ◽  
South Central ◽  
Atmospheric Profiles ◽  
Spectral Channels

Abstract. The Infrared Atmospheric Sounding Interferometer (IASI) is an ultra-spectral satellite sensor with 8461 spectral channels. IASI spectra contain high information content on atmospheric, cloud, and surface properties. The instrument presents a challenge for using thousands of spectral channels in a physical retrieval system or in a Numerical Weather Prediction (NWP) data assimilation system. In this paper we describe a method of simultaneously retrieving atmospheric temperature, moisture, and cloud properties using all available IASI channels without sacrificing computational speed. The essence of the method is to convert the IASI channel radiance spectra into super-channels by an Empirical Orthogonal Function (EOF) transformation. Studies show that about 100 super-channels are adequate to capture the information content of the radiance spectra. A Principal Component-based Radiative Transfer Model (PCRTM) is used to calculate both the super-channel magnitudes and derivatives with respect to atmospheric profiles and other properties. A physical retrieval algorithm then performs an inversion of atmospheric, cloud, and surface properties in the super channel domain directly therefore both reducing the computational need and preserving the information content of the IASI measurements. While no large-scale validation has been performed on any retrieval methodology presented in this paper, comparisons of the retrieved atmospheric profiles, sea surface temperatures, and surface emissivities with co-located ground- and aircraft-based measurements over four days in Spring 2007 over the South-Central United States indicate excellent agreement.

scholarly journals Retrieval of atmospheric profiles and cloud properties from IASI spectra using super-channels

2009 ◽  
Vol 9 (2) ◽  
pp. 8683-8736 ◽  
Author(s):  
X. Liu ◽  
D. K. Zhou ◽  
A. M. Larar ◽  
W. L. Smith ◽  
P. Schluessel ◽  
...  
Keyword(s):  
Surface Properties ◽  
Information Content ◽  
Weather Prediction ◽  
Principal Component ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Cloud Properties ◽  
Atmospheric Profiles ◽  
Spectral Channels

Abstract. The Infrared Atmospheric Sounding Interferometer (IASI) is an ultra-spectral satellite sensor with 8461 spectral channels. IASI spectra contain high information content on atmospheric, cloud, and surface properties. The instrument presents a challenge for using thousands of spectral channels in a physical retrieval system or in a Numerical Weather Prediction (NWP) data assimilation system. In this paper we describe a method of simultaneously retrieving atmospheric temperature, moisture, and cloud properties using all available IASI channels without sacrificing computational speed. The essence of the method is to convert the IASI channel radiance spectra into super-channels by an Empirical Orthogonal Function (EOF) transformation. Because the EOFs are orthogonal to each other, about 100 super-channels are adequate to capture the information content of the radiance spectra. A Principal Component-based Radiative Transfer Model (PCRTM) is used to calculate both the super-channel magnitudes and derivatives with respect to atmospheric profiles and other properties. A physical retrieval algorithm then performs an inversion of atmospheric, cloud, and surface properties in super channel domain directly therefore both reducing the computational need and preserving the information content of the IASI measurements.

scholarly journals Validating TROPOMI aerosol layer height retrievals with CALIOP data

2019 ◽  
Author(s):  
Swadhin Nanda ◽  
Martin de Graaf ◽  
J. Pepijn Veefkind ◽  
Maarten Sneep ◽  
Mark ter Linden ◽  
...  
Keyword(s):  
Optimal Estimation ◽  
Satellite Observations ◽  
Radiative Transfer Model ◽  
Ultraviolet Region ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Estimation Technique ◽  
Layer Height ◽  
Level 2 ◽  
Orthogonal Polarisation

Abstract. The Tropospheric Monitoring Instrument's (TROPOMI) level-2 aerosol layer height (ALH) product has now been released to the general public. This product is retrieved using TROPOMI's measurements of the oxygen A-band, radiative transfer model (RTM) calculations augmented by neural networks and an iterative optimal estimation technique. The TROPOMI ALH product will deliver aerosol layer height estimates over cloud-free scenes over the ocean and land that contain aerosols above a certain threshold of the measured UV absorbing index (UVAI) in the ultraviolet region. This paper provides background for the ALH product and explores its quality by comparing ALH estimates to similar quantities derived from spaceborne lidars observing the same scene. The spaceborne lidar chosen for this study is the Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP) on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, which flies in formation with NASA's A-train constellation since 2006 and is a proven source of data for studying aerosol layer heights. The influence of the surface and clouds are discussed and the aspects of the TROPOMI ALH algorithm that will require future development efforts are highlighted.

scholarly journals RADIATIVE TRANSFER MODEL SIMULATIONS TO DETERMINE THE NIGHT TIME FOG DETECTION THRESHOLD

2018 ◽  
Vol XLII-5 ◽  
pp. 511-517
Author(s):  
S. Gaurav ◽  
P. Jindal
Keyword(s):  
Radiative Transfer ◽  
Satellite Image ◽  
Detection Threshold ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Night Time ◽  
Northern India ◽  
Microphysical Properties ◽  
Spectral Channels ◽  
Fog Detection

<p><strong>Abstract.</strong> Every winter the Indo-Gangetic plains (IGP) of northern India are severely impacted both socially and economically by fog. For night time fog detection, visible imagery cannot be used. Also, as emissions from ground and fog is almost similar in thermal infrared (TIR, 10.8<span class="thinspace"></span>&amp;mu;m) channel, TIR channel cannot help in identifying fog. However, emission in middle infrared (MIR, 3.9<span class="thinspace"></span>&amp;mu;m) channel is less than emission in TIR channel over foggy area. Therefore, brightness temperature difference (BTD) between TIR and MIR is positive during night time over fog area. This BTD technique cannot be directly used during day time as MIR channel is contaminated by solar radiations. In the present work, a spectral sensitivity analysis study has been done for these two spectral channels using radiative transfer model (RTM) simulations to determine a threshold BTD for night time fog detection. SBDART (Santa Barbara DISORT Radiative Transfer) model was used for this study to simulate brightness temperatures (BT). The RTM simulations of BT of the two spectral channels was carried out for different fog microphysical characteristics like fog optical depth (FOD) and fog droplet size (Re). The fog episode of January 2018 over IGP was studied by applying threshold BTD obtained from simulation results for INSAT-3D data. A threshold BTD value ><span class="thinspace"></span>5<span class="thinspace"></span>K detected night time fog over IGP with good accuracy. The threshold BTD obtained from satellite image is compared with different cases established from simulation result which gave idea about microphysical properties of fog over IGP during winter seasons.</p>

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