scholarly journals A radiation closure study of Arctic stratus cloud microphysical properties using the collocated satellite-surface data and Fu-Liou radiative transfer model

2016 ◽  
Vol 121 (17) ◽  
pp. 10,175-10,198 ◽  
Author(s):  
Xiquan Dong ◽  
Baike Xi ◽  
Shaoyue Qiu ◽  
Patrick Minnis ◽  
Sunny Sun-Mack ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Stratus Cloud ◽  
Microphysical Properties ◽  
Surface Data

scholarly journals Consistency of dimensional distributions and refractive indices of desert dust measured over Lampedusa with IASI radiances

2016 ◽  
Author(s):  
Giuliano Liuzzi ◽  
Guido Masiello ◽  
Carmine Serio ◽  
Daniela Meloni ◽  
Claudia Di Biagio ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Short Wave ◽  
Radiative Transfer Model ◽  
Refractive Indices ◽  
Transfer Model ◽  
Spectral Interval ◽  
Desert Dust ◽  
Microphysical Properties ◽  
Southern Mediterranean ◽  
The One

Abstract. In the context of the ChArMEx campaign, we present here some results concerning the quantitative comparison between simulated and observed radiances during a dust event occurred between June and July 2013 in the southern Mediterranean basin, involving the airmass above Lampedusa island. In particular, comparisons have been performed between radiances as observed by the Infrared Atmospheric Sounder Interferometer (IASI) and those simulated using the σ-IASI-as radiative transfer model, which takes into account aerosol extinction effect through a set of fast parameterizations. Simulations have been carried on with different sets of input complex refractive indices, which take into account the parent soils of the aerosols, and using the high-quality characterization of desert dust aerosol microphysical properties, achieved through direct measurements in the ChArMEx experiment; on the one hand, this comparison has offered the possibility to test the feasibility of the radiative transfer model. On the other hand, this work goes through a direct validation of different refractive indices sets for desert dust in the thermal infrared. Results show a good consistency between calculations and observations, especially in the spectral interval 800–1000 cm−1; moreover, the comparison between calculations and observations suggests that further efforts are needed to better characterize desert dust optical properties in the short wave (above 2000 cm−1). In any case, we show that it is necessary to properly tune the refractive indices according to the geographical origin of the observed aerosol.

scholarly journals Numerical Experiments of an Advanced Radiative Transfer Model in the U.S. Navy Operational Global Atmospheric Prediction System

2012 ◽  
Vol 51 (3) ◽  
pp. 554-570 ◽  
Author(s):  
Ming Liu ◽  
Young-Joon Kim ◽  
Qingyun Zhao
Keyword(s):  
Radiative Transfer ◽  
Effective Radius ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Forecast Errors ◽  
Prediction System ◽  
Surface Data ◽  
Ice Water ◽  
The Impact ◽  
Mean Square Errors

AbstractA high-order accurate radiative transfer (RT) model developed by Fu and Liou has been implemented into the Navy Operational Global Atmospheric Prediction System (NOGAPS) to improve the energy budget and forecast skill. The Fu–Liou RT model is a four-stream algorithm (with a two-stream option) integrating over 6 shortwave bands and 12 longwave bands. The experimental 10-day forecasts and analyses from data assimilation cycles are compared with the operational output, which uses a two-stream RT model of three shortwave and five longwave bands, for both winter and summer periods. The verifications against observations of radiosonde and surface data show that the new RT model increases temperature accuracy in both forecasts and analyses by reducing mean bias and root-mean-square errors globally. In addition, the forecast errors also grow more slowly in time than those of the operational NOGAPS because of accumulated effects of more accurate cloud–radiation interactions. The impact of parameterized cloud effective radius in estimating liquid and ice water optical properties is also investigated through a sensitivity test by comparing with the cases using constant cloud effective radius to examine the temperature changes in response to cloud scattering and absorption. The parameterization approach is demonstrated to outperform that of constant radius by showing smaller errors and better matches to observations. This suggests the superiority of the new RT model relative to its operational counterpart, which does not use cloud effective radius. An effort has also been made to improve the computational efficiency of the new RT model for operational applications.

scholarly journals Airborne validation of radiative transfer modelling of ice clouds at millimetre and sub-millimetre wavelengths

2018 ◽  
Author(s):  
Stuart Fox ◽  
Jana Mendrok ◽  
Patrick Eriksson ◽  
Robin Ekelund ◽  
Sebastian J. O'Shea ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Cloud Microphysics ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Atmospheric Measurements ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Research Aircraft ◽  
Cloud Ice ◽  
Ice Water

Abstract. The next generation of European polar orbiting weather satellites will carry a novel instrument, the Ice Cloud Imager (ICI), which uses passive observations between 183 and 664 GHz to make daily global observations of cloud ice. Successful use of these observations requires accurate modelling of cloud ice scattering, and this study uses airborne observations from two flights of the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 research aircraft to validate radiative transfer simulations of cirrus clouds at frequencies between 325 and 664 GHz using the Atmospheric Radiative Transfer Simulator (ARTS) and a state-of-the-art database of cloud ice optical properties. Particular care is taken to ensure that the inputs to the radiative transfer model are representative of the true atmospheric state by combining both remote-sensing and in-situ observations of the same clouds to create realistic vertical profiles of cloud properties that are consistent with both observed particle size distributions and bulk ice mass. The simulations are compared to measurements from the International Submillimetre Airborne Radiometer (ISMAR), which is an airborne demonstrator for ICI. It is shown that whilst they are generally able to reproduce the observed cloud signals, for a given ice water path (IWP) there is considerable sensitivity to the cloud microphysics including the distribution of ice mass within the cloud and the ice particle habit. Accurate retrievals from ICI will therefore require realistic representations of cloud microphysical properties.

scholarly journals A radiative transfer module for calculating photolysis rates and solar heating in climate models: Solar-J v7.5

2017 ◽  
Vol 10 (7) ◽  
pp. 2525-2545 ◽  
Author(s):  
Juno Hsu ◽  
Michael J. Prather ◽  
Philip Cameron-Smith ◽  
Alex Veidenbaum ◽  
Alex Nicolau
Keyword(s):  
Radiative Transfer ◽  
General Circulation ◽  
Solar Spectrum ◽  
Solar Heating ◽  
Gas Absorption ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Cirrus Cloud ◽  
Stratus Cloud ◽  
Photolysis Rates

Abstract. Solar-J is a comprehensive radiative transfer model for the solar spectrum that addresses the needs of both solar heating and photochemistry in Earth system models. Solar-J is a spectral extension of Cloud-J, a standard in many chemical models that calculates photolysis rates in the 0.18–0.8 µm region. The Cloud-J core consists of an eight-stream scattering, plane-parallel radiative transfer solver with corrections for sphericity. Cloud-J uses cloud quadrature to accurately average over correlated cloud layers. It uses the scattering phase function of aerosols and clouds expanded to eighth order and thus avoids isotropic-equivalent approximations prevalent in most solar heating codes. The spectral extension from 0.8 to 12 µm enables calculation of both scattered and absorbed sunlight and thus aerosol direct radiative effects and heating rates throughout the Earth's atmosphere.The Solar-J extension adopts the correlated-k gas absorption bins, primarily water vapor, from the shortwave Rapid Radiative Transfer Model for general circulation model (GCM) applications (RRTMG-SW). Solar-J successfully matches RRTMG-SW's tropospheric heating profile in a clear-sky, aerosol-free, tropical atmosphere. We compare both codes in cloudy atmospheres with a liquid-water stratus cloud and an ice-crystal cirrus cloud. For the stratus cloud, both models use the same physical properties, and we find a systematic low bias of about 3 % in planetary albedo across all solar zenith angles caused by RRTMG-SW's two-stream scattering. Discrepancies with the cirrus cloud using any of RRTMG-SW's three different parameterizations are as large as about 20–40 % depending on the solar zenith angles and occur throughout the atmosphere.Effectively, Solar-J has combined the best components of RRTMG-SW and Cloud-J to build a high-fidelity module for the scattering and absorption of sunlight in the Earth's atmosphere, for which the three major components – wavelength integration, scattering, and averaging over cloud fields – all have comparably small errors. More accurate solutions with Solar-J come with increased computational costs, about 5 times that of RRTMG-SW for a single atmosphere. There are options for reduced costs or computational acceleration that would bring costs down while maintaining improved fidelity and balanced errors.

scholarly journals Airborne validation of radiative transfer modelling of ice clouds at millimetre and sub-millimetre wavelengths

2019 ◽  
Vol 12 (3) ◽  
pp. 1599-1617 ◽  
Author(s):  
Stuart Fox ◽  
Jana Mendrok ◽  
Patrick Eriksson ◽  
Robin Ekelund ◽  
Sebastian J. O'Shea ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Cloud Microphysics ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Atmospheric Measurements ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Research Aircraft ◽  
Cloud Ice ◽  
Ice Water

Abstract. The next generation of European polar orbiting weather satellites will carry a novel instrument, the Ice Cloud Imager (ICI), which uses passive observations between 183 and 664 GHz to make daily global observations of cloud ice. Successful use of these observations requires accurate modelling of cloud ice scattering, and this study uses airborne observations from two flights of the Facility for Airborne Atmospheric Measurements (FAAM) BAe 146 research aircraft to validate radiative transfer simulations of cirrus clouds at frequencies between 325 and 664 GHz using the Atmospheric Radiative Transfer Simulator (ARTS) and a state-of-the-art database of cloud ice optical properties. Particular care is taken to ensure that the inputs to the radiative transfer model are representative of the true atmospheric state by combining both remote-sensing and in situ observations of the same clouds to create realistic vertical profiles of cloud properties that are consistent with both observed particle size distributions and bulk ice mass. The simulations are compared to measurements from the International Submillimetre Airborne Radiometer (ISMAR), which is an airborne demonstrator for ICI. It is shown that whilst they are generally able to reproduce the observed cloud signals, for a given ice water path (IWP) there is considerable sensitivity to the cloud microphysics, including the distribution of ice mass within the cloud and the ice particle habit. Accurate retrievals from ICI will therefore require realistic representations of cloud microphysical properties.

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>

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.

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