scholarly journals Radiative Forcing by Light-Absorbing Particles in Snow in Northeastern China Retrieved from Satellite Observations

2019 ◽  
Author(s):  
Wei Pu ◽  
Jiecan Cui ◽  
Tenglong Shi ◽  
Xuelei Zhang ◽  
Cenlin He ◽  
...  
Keyword(s):  
Wet Deposition ◽  
Radiative Forcing ◽  
Solar Zenith Angle ◽  
Atmospheric Correction ◽  
Northeastern China ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Spatial Variance ◽  
Snow Albedo

Abstract. Light-absorbing particles (LAPs) deposited on snow can decrease snow albedo and affect climate through the snow-albedo radiative forcing. In this study, we use MODIS observations combined with a snow albedo model (SNICAR) and a radiative transfer model (SBDART) to retrieve the radiative forcing by LAPs in snow (RFLapsMODIS) across Northeastern China (NEC) in January–February from 2003 to 2017. RFLapsMODIS presents distinct spatial variability, with the minimum (22.3 W m−2) in western NEC and the maximum (64.6 W m−2) near industrial areas in central NEC. The regional mean RFLapsMODIS is ~ 45.1 ± 6.8 W m−2 in NEC. The positive (negative) uncertainties of retrieved RFLapsMODIS due to atmospheric correction range from 14 % to 57 % (−14 % to −47 %) and the uncertainty value basically decreased with the increased RFLapsMODIS. We attribute the variations of radiative forcing based on remote sensing and find that the spatial variance of RFLapsMODIS in NEC is 74.6 % due to LAPs, while 21.2 % and 4.2 % due to snow grain size, and solar zenith angle. Furthermore, based on multiple linear regression, the BC dry and wet deposition and snowfall could totally explain 81 % of the spatial variance of LAP contents, which confirms the reasonability of the spatial patterns of retrieved RFLapsMODIS in NEC. We validate RFLapsMODIS using in situ radiative forcing estimates. We find that the biases in RFLapsMODIS are negatively correlated with LAP concentrations and range from ~ 5 % to ~ 350 % in NEC.

scholarly journals The remote sensing of radiative forcing by light-absorbing particles (LAPs) in seasonal snow over northeastern China

2019 ◽  
Vol 19 (15) ◽  
pp. 9949-9968 ◽  
Author(s):  
Wei Pu ◽  
Jiecan Cui ◽  
Tenglong Shi ◽  
Xuelei Zhang ◽  
Cenlin He ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Radiative Forcing ◽  
Atmospheric Correction ◽  
Northeastern China ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Spatial Variance ◽  
Snow Albedo ◽  
Sky Conditions

Abstract. Light-absorbing particles (LAPs) deposited on snow can decrease snow albedo and affect climate through snow-albedo radiative forcing. In this study, we use MODIS observations combined with a snow-albedo model (SNICAR – Snow, Ice, and Aerosol Radiative) and a radiative transfer model (SBDART – Santa Barbara DISORT Atmospheric Radiative Transfer) to retrieve the instantaneous spectrally integrated radiative forcing at the surface by LAPs in snow (RFMODISLAPs) under clear-sky conditions at the time of MODIS Aqua overpass across northeastern China (NEC) in January–February from 2003 to 2017. RFMODISLAPs presents distinct spatial variability, with the minimum (22.3 W m−2) in western NEC and the maximum (64.6 W m−2) near industrial areas in central NEC. The regional mean RFMODISLAPs is ∼45.1±6.8 W m−2 in NEC. The positive (negative) uncertainties of retrieved RFMODISLAPs due to atmospheric correction range from 14 % to 57 % (−14 % to −47 %), and the uncertainty value basically decreases with the increased RFMODISLAPs. We attribute the variations of radiative forcing based on remote sensing and find that the spatial variance of RFMODISLAPs in NEC is 74.6 % due to LAPs and 21.2 % and 4.2 % due to snow grain size and solar zenith angle. Furthermore, based on multiple linear regression, the BC dry and wet deposition and snowfall could explain 84 % of the spatial variance of LAP contents, which confirms the reasonability of the spatial patterns of retrieved RFMODISLAPs in NEC. We validate RFMODISLAPs using in situ radiative forcing estimates. We find that the biases in RFMODISLAPs are negatively correlated with LAP concentrations and range from ∼5 % to ∼350 % in NEC.

Radiative forcing over the Arctic of aerosols from the August 2017 Canadian and Greenlandic wildfires

2021 ◽  
Author(s):  
Filippo Calì Quaglia ◽  
Daniela Meloni ◽  
Alcide Giorgio di Sarra ◽  
Tatiana Di Iorio ◽  
Virginia Ciardini ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Radiative Forcing ◽  
Solar Zenith Angle ◽  
Surface Albedo ◽  
High Arctic ◽  
The Arctic ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Radiative Effect

<p>Extended and intense wildfires occurred in Northern Canada and, unexpectedly, on the Greenlandic West coast during summer 2017. The thick smoke plume emitted into the atmosphere was transported to the high Arctic, producing one of the largest impacts ever observed in the region. Evidence of Canadian and Greenlandic wildfires was recorded at the Thule High Arctic Atmospheric Observatory (THAAO, 76.5°N, 68.8°W, www.thuleatmos-it.it) by a suite of instruments managed by ENEA, INGV, Univ. of Florence, and NCAR. Ground-based observations of the radiation budget have allowed quantification of the surface radiative forcing at THAAO. </p><p>Excess biomass burning chemical tracers such as CO, HCN, H2CO, C2H6, and NH3 were  measured in the air column above Thule starting from August 19 until August 23. The aerosol optical depth (AOD) reached a peak value of about 0.9 on August 21, while an enhancement of wildfire compounds was  detected in PM10. The measured shortwave radiative forcing was -36.7 W/m2 at 78° solar zenith angle (SZA) for AOD=0.626.</p><p>MODTRAN6.0 radiative transfer model (Berk et al., 2014) was used to estimate the aerosol radiative effect and the heating rate profiles at 78° SZA. Measured temperature profiles, integrated water vapour, surface albedo, spectral AOD and aerosol extinction profiles from CALIOP onboard CALIPSO were used as model input. The peak  aerosol heating rate (+0.5 K/day) was  reached within the aerosol layer between 8 and 12 km, while the maximum radiative effect (-45.4 W/m2) is found at 3 km, below the largest aerosol layer.</p><p>The regional impact of the event that occurred on August 21 was investigated using a combination of atmospheric radiative transfer modelling with measurements of AOD and ground surface albedo from MODIS. The aerosol properties used in the radiative transfer model were constrained by in situ measurements from THAAO. Albedo data over the ocean have been obtained from Jin et al. (2004). Backward trajectories produced through HYSPLIT simulations (Stein et al., 2015) were also employed to trace biomass burning plumes.</p><p>The radiative forcing efficiency (RFE) over land and ocean was derived, finding values spanning from -3 W/m2 to -132 W/m2, depending on surface albedo and solar zenith angle. The fire plume covered a vast portion of the Arctic, with large values of the daily shortwave RF (< -50 W/m2) lasting for a few days. This large amount of aerosol is expected to influence cloud properties in the Arctic, producing significant indirect radiative effects.</p>

scholarly journals A Parametric Radiative Forcing Model for Contrail Cirrus

2012 ◽  
Vol 51 (7) ◽  
pp. 1391-1406 ◽  
Author(s):  
U. Schumann ◽  
B. Mayer ◽  
K. Graf ◽  
H. Mannstein
Keyword(s):  
Analytical Model ◽  
Optical Depth ◽  
Zenith Angle ◽  
Radiative Forcing ◽  
Solar Zenith Angle ◽  
Life Cycles ◽  
Radiative Transfer Model ◽  
Model Parameters ◽  
Transfer Model ◽  
Wide Range

AbstractA new parameterized analytical model is presented to compute the instantaneous radiative forcing (RF) at the top of the atmosphere (TOA) produced by an additional thin contrail cirrus layer (called “contrail” below). The model calculates the RF using as input the outgoing longwave radiation and reflected solar radiation values at TOA for a contrail-free atmosphere, so that the model is applicable for both cloud-free and cloudy ambient atmospheres. Additional input includes the contrail temperature, contrail optical depth (at 550 nm), effective particle radius, particle habit, solar zenith angle, and the optical depth of cirrus above the contrail layer. The model parameters (5 for longwave and 10 for shortwave) are determined from least squares fits to calculations from the “libRadtran” radiative transfer model over a wide range of atmospheric and surface conditions. The correlation coefficient between model and calculations is larger than 98%. The analytical model is compared with published results, including a 1-yr simulation of global RF, and is found to agree well with previous studies. The fast analytical model is part of a larger modeling system to simulate contrail life cycles (“CoCiP”) and can allow for the rapid simulation of contrail cirrus RF over a wide range of meteorological conditions and for a given size-dependent habit mixture. Ambient clouds are shown to have large local impact on the net RF of contrails. Net RF of contrails may both increase and decrease and even change sign in the presence of higher-level cirrus, depending on solar zenith angle.

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>

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 Level 2 processing for the imaging Fourier transform spectrometer GLORIA: derivation and validation of temperature and trace gas volume mixing ratios from calibrated dynamics mode spectra

2015 ◽  
Vol 8 (6) ◽  
pp. 2473-2489 ◽  
Author(s):  
J. Ungermann ◽  
J. Blank ◽  
M. Dick ◽  
A. Ebersoldt ◽  
F. Friedl-Vallon ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Horizontal Resolution ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Ionization Mass ◽  
Fourier Transform Spectrometer ◽  
Upper Troposphere ◽  
Mixing Ratios

Abstract. The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is an airborne infrared limb imager combining a two-dimensional infrared detector with a Fourier transform spectrometer. It was operated aboard the new German Gulfstream G550 High Altitude LOng Range (HALO) research aircraft during the Transport And Composition in the upper Troposphere/lowermost Stratosphere (TACTS) and Earth System Model Validation (ESMVAL) campaigns in summer 2012. This paper describes the retrieval of temperature and trace gas (H2O, O3, HNO3) volume mixing ratios from GLORIA dynamics mode spectra that are spectrally sampled every 0.625 cm−1. A total of 26 integrated spectral windows are employed in a joint fit to retrieve seven targets using consecutively a fast and an accurate tabulated radiative transfer model. Typical diagnostic quantities are provided including effects of uncertainties in the calibration and horizontal resolution along the line of sight. Simultaneous in situ observations by the Basic Halo Measurement and Sensor System (BAHAMAS), the Fast In-situ Stratospheric Hygrometer (FISH), an ozone detector named Fairo, and the Atmospheric chemical Ionization Mass Spectrometer (AIMS) allow a validation of retrieved values for three flights in the upper troposphere/lowermost stratosphere region spanning polar and sub-tropical latitudes. A high correlation is achieved between the remote sensing and the in situ trace gas data, and discrepancies can to a large extent be attributed to differences in the probed air masses caused by different sampling characteristics of the instruments. This 1-D processing of GLORIA dynamics mode spectra provides the basis for future tomographic inversions from circular and linear flight paths to better understand selected dynamical processes of the upper troposphere and lowermost stratosphere.

scholarly journals SEVIRI Hyper-Fast Forward Model with Application to Emissivity Retrieval

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1532 ◽  
Author(s):  
Guido Masiello ◽  
Carmine Serio ◽  
Sara Venafra ◽  
Laurent Poutier ◽  
Frank-M. Göttsche
Keyword(s):  
Radiative Transfer ◽  
Real Time ◽  
Forward Model ◽  
Radiative Transfer Model ◽  
Computational Time ◽  
Transfer Model ◽  
Real Time Processing ◽  
In Situ Observations ◽  
Infrared Radiances

Timely processing of observations from multi-spectral imagers, such as SEVIRI (Spinning Enhanced Visible and Infrared Imager), largely depends on fast radiative transfer calculations. This paper mostly concerns the development and implementation of a new forward model for SEVIRI to be applied to real time processing of infrared radiances. The new radiative transfer model improves computational time by a factor of ≈7 compared to the previous versions and makes it possible to process SEVIRI data at nearly real time. The new forward model has been applied for the retrieval of surface parameters. Although the scheme can be applied for the simultaneous retrieval of temperature and emissivity, the paper mostly focuses on emissivity. The inverse scheme relies on a Kalman filter approach, which allows us to exploit a sequential processing of SEVIRI observations. Based on the new forward model, the paper also presents a validation retrieval performed with in situ observations acquired during a field experiment carried out in 2017 at Gobabeb (Namib desert) validation station. Furthermore, a comparison with IASI (Infrared Atmospheric Sounder Interferometer) emissivity retrievals has been performed as well. It has been found that the retrieved emissivities are in good agreement with each other and with in situ observations, i.e., average differences are generally well below 0.01.

scholarly journals An Approach to Minimize Atmospheric Correction Error and Improve Physics-Based Satellite-Derived Bathymetry in a Coastal Environment

2020 ◽  
Vol 12 (17) ◽  
pp. 2752
Author(s):  
Christopher O. Ilori ◽  
Anders Knudby
Keyword(s):  
Remote Sensing ◽  
Environmental Factors ◽  
Complete Solution ◽  
Atmospheric Correction ◽  
Florida Keys ◽  
Radiative Transfer Model ◽  
Inversion Method ◽  
Transfer Model ◽  
Landsat 8 ◽  
Depth Range

Physics-based radiative transfer model (RTM) inversion methods have been developed and implemented for satellite-derived bathymetry (SDB); however, precise atmospheric correction (AC) is required for robust bathymetry retrieval. In a previous study, we revealed that biases from AC may be related to imaging and environmental factors that are not considered sufficiently in all AC algorithms. Thus, the main aim of this study is to demonstrate how AC biases related to environmental factors can be minimized to improve SDB results. To achieve this, we first tested a physics-based inversion method to estimate bathymetry for a nearshore area in the Florida Keys, USA. Using a freely available water-based AC algorithm (ACOLITE), we used Landsat 8 (L8) images to derive per-pixel remote sensing reflectances, from which bathymetry was subsequently estimated. Then, we quantified known biases in the AC using a linear regression that estimated bias as a function of imaging and environmental factors and applied a correction to produce a new set of remote sensing reflectances. This correction improved bathymetry estimates for eight of the nine scenes we tested, with the resulting changes in bathymetry RMSE ranging from +0.09 m (worse) to −0.48 m (better) for a 1 to 25 m depth range, and from +0.07 m (worse) to −0.46 m (better) for an approximately 1 to 16 m depth range. In addition, we showed that an ensemble approach based on multiple images, with acquisitions ranging from optimal to sub-optimal conditions, can be used to estimate bathymetry with a result that is similar to what can be obtained from the best individual scene. This approach can reduce time spent on the pre-screening and filtering of scenes. The correction method implemented in this study is not a complete solution to the challenge of AC for satellite-derived bathymetry, but it can eliminate the effects of biases inherent to individual AC algorithms and thus improve bathymetry retrieval. It may also be beneficial for use with other AC algorithms and for the estimation of seafloor habitat and water quality products, although further validation in different nearshore waters is required.

scholarly journals Contrasting the direct radiative effect and direct radiative forcing of aerosols

2014 ◽  
Vol 14 (11) ◽  
pp. 5513-5527 ◽  
Author(s):  
C. L. Heald ◽  
D. A. Ridley ◽  
J. H. Kroll ◽  
S. R. H. Barrett ◽  
K. E. Cady-Pereira ◽  
...  
Keyword(s):  
Energy Balance ◽  
Radiative Forcing ◽  
Transport Model ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Radiative Effect ◽  
Chemical Transport Model ◽  
Anthropogenic Aerosols ◽  
Anthropogenic Aerosol ◽  
Direct Radiative Forcing

Abstract. The direct radiative effect (DRE) of aerosols, which is the instantaneous radiative impact of all atmospheric particles on the Earth's energy balance, is sometimes confused with the direct radiative forcing (DRF), which is the change in DRE from pre-industrial to present-day (not including climate feedbacks). In this study we couple a global chemical transport model (GEOS-Chem) with a radiative transfer model (RRTMG) to contrast these concepts. We estimate a global mean all-sky aerosol DRF of −0.36 Wm−2 and a DRE of −1.83 Wm−2 for 2010. Therefore, natural sources of aerosol (here including fire) affect the global energy balance over four times more than do present-day anthropogenic aerosols. If global anthropogenic emissions of aerosols and their precursors continue to decline as projected in recent scenarios due to effective pollution emission controls, the DRF will shrink (−0.22 Wm−2 for 2100). Secondary metrics, like DRE, that quantify temporal changes in both natural and anthropogenic aerosol burdens are therefore needed to quantify the total effect of aerosols on climate.

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