The radiative transfer model for the greenhouse effect

SeMA Journal ◽  
2021 ◽  
Author(s):  
Claude Bardos ◽  
Olivier Pironneau
Keyword(s):  
Radiative Transfer ◽  
Greenhouse Effect ◽  
Radiative Transfer Model ◽  
Transfer Model

scholarly journals Carbon dioxide retrieval of Argus 1000 space data by using GENSPECT line-by-line radiative transfer model

2019 ◽  
Vol 9 (3) ◽  
pp. 77
Author(s):  
R. K. Jagpal ◽  
R. Siddiqui ◽  
S. M. Abrarov ◽  
B. M. Quine
Keyword(s):  
Carbon Dioxide ◽  
Radiative Transfer ◽  
Greenhouse Effect ◽  
Near Infrared ◽  
Trace Gases ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Major Contributor ◽  
Sources And Sinks ◽  
Space Data

The micro-spectrometer Argus 1000 being in space continuously monitors the sources and sinks of the trace gases. It is commonly believed that among other gases CO_2 is the major contributor causing the greenhouse effect. Argus 1000 along its orbit gathers the valuable spectral data that can be analyzed and retrieved. In this paper we present the retrieval of CO_2 gas in the near infrared window 1580 to 1620 nm by using line-by-line code GENSPECT. The retrieved Argus 1000 space data taken over British Columbia on May 31, 2010 indicates an enhancement of CO_2 by about 30%.

scholarly journals THE SENSITIVITY OF THE GREENHOUSE EFFECT TO CHANGES IN THE CONCENTRATION OF GASES IN PLANETARY ATMOSPHERES

2013 ◽  
Vol 53 (A) ◽  
pp. 832-838
Author(s):  
Smadar Bressler ◽  
Giora Shaviv ◽  
Nir J. Shaviv
Keyword(s):  
Radiative Transfer ◽  
Surface Temperature ◽  
Greenhouse Effect ◽  
Central Star ◽  
Temperature Limit ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Long Wavelength ◽  
Earth Like Planets ◽  
The One

We present a radiative transfer model for Earth-Like-Planets (ELP). The model allows the assessment of the effect of a change in the concentration of an atmospheric component, especially a greenhouse gas (GHG), on the surface temperature of a planet. The model is based on the separation between the contribution of the short wavelength molecular absorption and the long wavelength one. A unique feature of the model is the condition of energy conservation at every point in the atmosphere. The radiative transfer equation is solved in the two stream approximation without assuming the existence of an LTE in any wavelength range. The model allows us to solve the Simpson paradox, whereby the greenhouse effect (GHE) has no temperature limit. On the contrary, we show that the temperature saturates, and its value depends primarily on the distance of the planet from the central star. We also show how the relative humidity affects the surface temperature of a planet and explain why the effect is smaller than the one derived when the above assumptions are neglected.

scholarly journals On the Climatic Impact of CO2Ice Particles in Atmospheres of Terrestrial Exoplanets

2012 ◽  
Vol 8 (S293) ◽  
pp. 303-308
Author(s):  
D. Kitzmann ◽  
A. B. C. Patzer ◽  
H. Rauer
Keyword(s):  
Radiative Transfer ◽  
Thermal Radiation ◽  
Greenhouse Effect ◽  
Outer Boundary ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Climatic Impact ◽  
Absorption Bands ◽  
Ice Particles ◽  
Stellar Radiation

AbstractClouds play a significant role for the energy budget in planetary atmospheres. They can scatter incident stellar radiation back to space, effectively cooling the surface of terrestrial planets. On the other hand, they may contribute to the atmospheric greenhouse effect by trapping outgoing thermal radiation. For exoplanets near the outer boundary of the habitable zone, condensation of CO2can occur due to the low atmospheric temperatures. These CO2ice clouds may play an important role for the surface temperature and, therefore, for the question of habitability of those planets. However, the optical properties of CO2ice crystals differ significantly from those of water droplets or water ice particles. Except for a small number of strong absorption bands, they are almost transparent with respect to absorption. Instead, they are highly effective scatterers at long and short wavelengths. Therefore, the climatic effect of a CO2ice cloud will depend on how much incident stellar radiation is scattered to space in comparison to the amount of thermal radiation scattered back towards the planetary surface. This contribution aims at the potential greenhouse effect of CO2ice particles. Their scattering and absorption properties are calculated for assumed particle size distributions with different effective radii and particle densities. An accurate radiative transfer model is used to determine the atmospheric radiation field affected by such CO2particles. These results are compared to less detailed radiative transfer schemes employed in previous studies.

Probing clouds in planets with a simple radiative transfer model: the Jupiter case

2012 ◽  
Vol 33 (6) ◽  
pp. 1611-1624 ◽  
Author(s):  
Iñigo Mendikoa ◽  
Santiago Pérez-Hoyos ◽  
Agustín Sánchez-Lavega
Keyword(s):  
Radiative Transfer ◽  
Radiative Transfer Model ◽  
Transfer Model

scholarly journals Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rehman S. Eon ◽  
Charles M. Bachmann
Keyword(s):  
Soil Moisture ◽  
Radiative Transfer ◽  
Moisture Content ◽  
Layer Thickness ◽  
Soil Moisture Content ◽  
Hyperspectral Imagery ◽  
Barrier Island ◽  
Water Layer ◽  
Radiative Transfer Model ◽  
Transfer Model

AbstractThe advent of remote sensing from unmanned aerial systems (UAS) has opened the door to more affordable and effective methods of imaging and mapping of surface geophysical properties with many important applications in areas such as coastal zone management, ecology, agriculture, and defense. We describe a study to validate and improve soil moisture content retrieval and mapping from hyperspectral imagery collected by a UAS system. Our approach uses a recently developed model known as the multilayer radiative transfer model of soil reflectance (MARMIT). MARMIT partitions contributions due to water and the sediment surface into equivalent but separate layers and describes these layers using an equivalent slab model formalism. The model water layer thickness along with the fraction of wet surface become parameters that must be optimized in a calibration step, with extinction due to water absorption being applied in the model based on equivalent water layer thickness, while transmission and reflection coefficients follow the Fresnel formalism. In this work, we evaluate the model in both field settings, using UAS hyperspectral imagery, and laboratory settings, using hyperspectral spectra obtained with a goniometer. Sediment samples obtained from four different field sites representing disparate environmental settings comprised the laboratory analysis while field validation used hyperspectral UAS imagery and coordinated ground truth obtained on a barrier island shore during field campaigns in 2018 and 2019. Analysis of the most significant wavelengths for retrieval indicate a number of different wavelengths in the short-wave infra-red (SWIR) that provide accurate fits to measured soil moisture content in the laboratory with normalized root mean square error (NRMSE)< 0.145, while independent evaluation from sequestered test data from the hyperspectral UAS imagery obtained during the field campaign obtained an average NRMSE = 0.169 and median NRMSE = 0.152 in a bootstrap analysis.

scholarly journals Potential of Hyperspectral Thermal Infrared Spaceborne Measurements to Retrieve Ice Cloud Physical Properties: Case Study of IASI and IASI-NG

2020 ◽  
Vol 13 (1) ◽  
pp. 116
Author(s):  
Lucie Leonarski ◽  
Laurent C.-Labonnote ◽  
Mathieu Compiègne ◽  
Jérôme Vidot ◽  
Anthony J. Baran ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Signal To Noise Ratio ◽  
Thermal Infrared ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Water Path ◽  
Ice Cloud ◽  
Ice Water Path ◽  
Ice Water

The present study aims to quantify the potential of hyperspectral thermal infrared sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and the future IASI next generation (IASI-NG) for retrieving the ice cloud layer altitude and thickness together with the ice water path. We employed the radiative transfer model Radiative Transfer for TOVS (RTTOV) to simulate cloudy radiances using parameterized ice cloud optical properties. The radiances have been computed from an ice cloud profile database coming from global operational short-range forecasts at the European Center for Medium-range Weather Forecasts (ECMWF) which encloses the normal conditions, typical variability, and extremes of the atmospheric properties over one year (Eresmaa and McNally (2014)). We performed an information content analysis based on Shannon’s formalism to determine the amount and spectral distribution of the information about ice cloud properties. Based on this analysis, a retrieval algorithm has been developed and tested on the profile database. We considered the signal-to-noise ratio of each specific instrument and the non-retrieved atmospheric and surface parameter errors. This study brings evidence that the observing system provides information on the ice water path (IWP) as well as on the layer altitude and thickness with a convergence rate up to 95% and expected errors that decrease with cloud opacity until the signal saturation is reached (satisfying retrievals are achieved for clouds whose IWP is between about 1 and 300 g/m2).

scholarly journals Fast Hyper-Spectral Radiative Transfer Model Based on the Double Cluster Low-Streams Regression Method

2021 ◽  
Vol 13 (3) ◽  
pp. 434
Author(s):  
Ana del Águila ◽  
Dmitry S. Efremenko
Keyword(s):  
Radiative Transfer ◽  
Single Scattering ◽  
Atmospheric Composition ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Absorption Bands ◽  
Acceleration Techniques ◽  
Scattering Approximation ◽  
Fine Resolution ◽  
Single Scattering Approximation

Fast radiative transfer models (RTMs) are required to process a great amount of satellite-based atmospheric composition data. Specifically designed acceleration techniques can be incorporated in RTMs to simulate the reflected radiances with a fine spectral resolution, avoiding time-consuming computations on a fine resolution grid. In particular, in the cluster low-streams regression (CLSR) method, the computations on a fine resolution grid are performed by using the fast two-stream RTM, and then the spectra are corrected by using regression models between the two-stream and multi-stream RTMs. The performance enhancement due to such a scheme can be of about two orders of magnitude. In this paper, we consider a modification of the CLSR method (which is referred to as the double CLSR method), in which the single-scattering approximation is used for the computations on a fine resolution grid, while the two-stream spectra are computed by using the regression model between the two-stream RTM and the single-scattering approximation. Once the two-stream spectra are known, the CLSR method is applied the second time to restore the multi-stream spectra. Through a numerical analysis, it is shown that the double CLSR method yields an acceleration factor of about three orders of magnitude as compared to the reference multi-stream fine-resolution computations. The error of such an approach is below 0.05%. In addition, it is analysed how the CLSR method can be adopted for efficient computations for atmospheric scenarios containing aerosols. In particular, it is discussed how the precomputed data for clear sky conditions can be reused for computing the aerosol spectra in the framework of the CLSR method. The simulations are performed for the Hartley–Huggins, O2 A-, water vapour and CO2 weak absorption bands and five aerosol models from the optical properties of aerosols and clouds (OPAC) database.

scholarly journals Retrieval of betalain contents based on the coupling of radiative transfer model and SVM model

2021 ◽  
Vol 100 ◽  
pp. 102340
Author(s):  
Rukeya Sawut ◽  
Ying Li ◽  
Yu Liu ◽  
Nijat Kasim ◽  
Umut Hasan ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Svm Model
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