scholarly journals Simulation of GOES-R ABI aerosol radiances using WRF-CMAQ: a case study approach

2013 ◽  
Vol 13 (7) ◽  
pp. 18713-18748
Author(s):  
S. A. Christopher
Keyword(s):  
Air Quality ◽  
Near Infrared ◽  
Sparse Matrix ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Eastern United States ◽  
Study Approach ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Primary Focus

Abstract. The primary focus of this paper is to simulate visible and near-infrared reflectances of the GOES-R Advanced Baseline Imager (ABI) for cases of high aerosol loading containing regional haze and smoke over the eastern United States. The simulations are performed using the Weather Research and Forecasting (WRF), Sparse Matrix Operator Kernel Emissions (SMOKE), and Community Multiscale Air Quality (CMAQ) models. Geostationary satellite-derived biomass burning emissions are also included as an input to CMAQ. Using the CMAQ aerosol concentrations and Mie calculations, radiance is computed from the discrete ordinate atmospheric radiative transfer model. We present detailed methods for deriving aerosol extinction from WRF and CMAQ outputs. Our results show that the model simulations create a realistic set of reflectance in various aerosol scenarios. The simulated reflectance provides distinct spectral features of aerosols which is then compared to data from the Moderate Resolution Imaging Spectroradiometer (MODIS). We also present a simple technique to synthesize green band reflectance (which will not be available on the ABI), using the model-simulated blue and red band reflectance. This study is an example of the use of air quality modeling in improving products and techniques for Earth observing missions.

scholarly journals Simulation of GOES-R ABI aerosol radiances using WRF-CMAQ: a case study approach

2014 ◽  
Vol 14 (7) ◽  
pp. 3183-3194 ◽  
Author(s):  
S. A. Christopher
Keyword(s):  
Air Quality ◽  
Near Infrared ◽  
Sparse Matrix ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Eastern United States ◽  
Study Approach ◽  
Moderate Resolution ◽  
Regional Haze ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. In anticipation of the upcoming GOES-R launch we simulate visible and near-infrared reflectances of the Advanced Baseline Imager (ABI) for cases of high aerosol loading containing regional haze and smoke over the eastern United States. The simulations are performed using the Weather Research and Forecasting (WRF), Sparse Matrix Operator Kernel Emissions (SMOKE), and Community Multiscale Air Quality (CMAQ) models. Geostationary, satellite-derived, biomass-burning emissions are also included as an input to CMAQ. Using the CMAQ aerosol concentrations and Mie calculations, radiance is computed from the discrete ordinate atmospheric radiative transfer model. We present detailed methods for deriving aerosol extinction from WRF and CMAQ outputs. Our results show that the model simulations create a realistic set of reflectances in various aerosol scenarios. The simulated reflectances provide distinct spectral features of aerosols which are then compared to data from the Moderate Resolution Imaging Spectroradiometer (MODIS). We also present a simple technique to synthesize green band reflectance (which will not be available on the ABI), using the model-simulated blue and red band reflectance. This study is an example of the use of air quality modeling in improving products and techniques for Earth-observing missions.

scholarly journals Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: Retrieval algorithm and measurements during DISCOVER-AQ Texas 2013

2016 ◽  
Vol 9 (6) ◽  
pp. 2647-2668 ◽  
Author(s):  
Caroline R. Nowlan ◽  
Xiong Liu ◽  
James W. Leitch ◽  
Kelly Chance ◽  
Gonzalo González Abad ◽  
...  
Keyword(s):  
Air Quality ◽  
Near Infrared ◽  
Infrared Light ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Test Bed ◽  
Mixing Ratios ◽  
Sensor Optimization

Abstract. The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m  ×  250 m spatial resolution with a fitting precision of 2.2 × 1015 moleculescm−2. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements and r = 0.74 overall), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.85). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.81, slope = 0.91). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.

scholarly journals Comparison of PARASOL Observations with Polarized Reflectances Simulated Using Different Ice Habit Mixtures

2013 ◽  
Vol 52 (1) ◽  
pp. 186-196 ◽  
Author(s):  
Benjamin H. Cole ◽  
Ping Yang ◽  
Bryan A. Baum ◽  
Jerome Riedi ◽  
Laurent C.-Labonnote ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Ice Crystal ◽  
Ice Clouds ◽  
Atmospheric Sciences ◽  
Reflection Data ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Polarized Reflectance

AbstractInsufficient knowledge of the habit distribution and the degree of surface roughness of ice crystals within ice clouds is a source of uncertainty in the forward light scattering and radiative transfer simulations of ice clouds used in downstream applications. The Moderate Resolution Imaging Spectroradiometer (MODIS) collection-5 ice microphysical model presumes a mixture of various ice crystal shapes with smooth facets, except for the compact aggregate of columns for which a severely rough condition is assumed. When compared with Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) polarized reflection data, simulations of polarized reflectance using smooth particles show a poor fit to the measurements, whereas very rough-faceted particles provide an improved fit to the polarized reflectance. In this study a new microphysical model based on a mixture of nine different ice crystal habits with severely roughened facets is developed. Simulated polarized reflectance using the new ice habit distribution is calculated using a vector adding–doubling radiative transfer model, and the simulations closely agree with the polarized reflectance observed by PARASOL. The new general habit mixture is also tested using a spherical albedo differences analysis, and surface roughening is found to improve the consistency of multiangular observations. These results are consistent with previous studies that have used polarized reflection data. It is suggested that an ice model incorporating an ensemble of different habits with severely roughened surfaces would potentially be an adequate choice for global ice cloud retrievals.

scholarly journals Volcanic Ash Retrieval Using a New Geostationary Satellite

2015 ◽  
Vol XL-7/W4 ◽  
pp. 67-74
Author(s):  
K. H. Lee ◽  
K. T. Lee
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Volcanic Ash ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
New Era ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Aerosol Remote Sensing ◽  
Moderate Resolution Imaging Spectroradiometer

The paper presents currently developing method of volcanic ash detection and retrieval for the Geostationary Korea Multi-Purpose Satellite (GK-2A). With the launch of GK-2A, aerosol remote sensing including dust, smoke, will begin a new era of geostationary remote sensing. The Advanced Meteorological Imager (AMI) onboard GK-2A will offer capabilities for volcanic ash remote sensing similar to those currently provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. Based on the physical principles for the current polar and geostationary imagers are modified in the algorithm. Volcanic ash is estimated in detection processing from visible and infrared channel radiances, and the comparison of satellite-observed radiances with those calculated from radiative transfer model. The retrievals are performed operationally every 15 min for volcanic ash for pixel sizes of 2 km. The algorithm currently under development uses a multichannel approach to estimate the effective radius, aerosol optical depth (AOD) simultaneously, both over water and land. The algorithm has been tested with proxy data generated from existing satellite observations and forward radiative transfer simulations. Operational assessment of the algorithm will be made after the launch of GK-2A scheduled in 2018.

scholarly journals Assessment of the calibration performance of satellite visible channels using cloud targets: application to Meteosat-8/9 and MTSAT-1R

2010 ◽  
Vol 10 (5) ◽  
pp. 12629-12664 ◽  
Author(s):  
S.-H. Ham ◽  
B. J. Sohn
Keyword(s):  
Three Dimensional ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Perfect Agreement ◽  
Convective Clouds ◽  
Calibration Methods ◽  
Matching Technique ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. To examine the calibration performance of the Meteosat-8/9 Spinning Enhanced Visible Infra-Red Imager (SEVIRI) 0.640-μm and the Multi-functional Transport Satellite (MTSAT)-1R 0.724-μm channels, three calibration methods were employed. First, a ray-matching technique was used to compare Meteosat-8/9 and MTSAT-1R visible channel reflectances with the well-calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) 0.646-μm channel reflectances. Spectral differences of the response function between the two channels of interest were taken into account for the comparison. Second, collocated MODIS cloud products were used as inputs to a radiative transfer model to calculate Meteosat-8/9 and MTSAT-1R visible channel reflectances. In the simulation, the three-dimensional radiative effect of clouds was taken into account and was subtracted from the simulated reflectance to remove the simulation bias caused by the plane-parallel assumption. Third, an independent method used the typical optical properties of deep convective clouds (DCCs) to simulate reflectances of selected DCC targets. Although the three methods were not in perfect agreement, the results suggest that calibration accuracies were within 5–10% for the Meteosat-8 0.640-μm channel, 4–9% for the Meteosat-9 0.640-μm channel, and up to 20% for the MTSAT-1R 0.724-μm channel. The results further suggest that the solar channel calibration scheme combining the three methods in this paper can be used as a tool to monitor the calibration performance of visible sensors that are particularly not equipped with an onboard calibration system.

Distribution and Radiative Forcing of Tropical Thin Cirrus Clouds

2009 ◽  
Vol 66 (12) ◽  
pp. 3721-3731 ◽  
Author(s):  
Joonsuk Lee ◽  
Ping Yang ◽  
Andrew E. Dessler ◽  
Bo-Cai Gao ◽  
Steven Platnick
Keyword(s):  
Radiative Forcing ◽  
Cirrus Clouds ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Atmospheric Infrared Sounder ◽  
Ice Cloud ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Autumn And Winter ◽  
Cloud Mask

Abstract To understand the radiative impact of tropical thin cirrus clouds, the frequency of occurrence and optical depths of these clouds have been derived. “Thin” cirrus clouds are defined here as being those that are not detected by the operational Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask, corresponding to an optical depth value of approximately 0.3 or smaller, but that are detectable in terms of the cirrus reflectance product based on the MODIS 1.375-μm channel. With such a definition, thin cirrus clouds were present in more than 40% of the pixels flagged as “clear sky” by the operational MODIS cloud mask algorithm. It is shown that these thin cirrus clouds are frequently observed in deep convective regions in the western Pacific. Thin cirrus optical depths were derived from the cirrus reflectance product. Regions of significant cloud fraction and large optical depths were observed in the Northern Hemisphere during the boreal spring and summer and moved southward during the boreal autumn and winter. The radiative effects of tropical thin cirrus clouds were studied on the basis of the retrieved cirrus optical depths, the atmospheric profiles derived from the Atmospheric Infrared Sounder (AIRS) observations, and a radiative transfer model in conjunction with a parameterization of ice cloud spectral optical properties. To understand how these clouds regulate the radiation field in the atmosphere, the instantaneous net fluxes at the top of the atmosphere (TOA) and at the surface were calculated. The present study shows positive and negative net forcings at the TOA and at the surface, respectively. The positive (negative) net forcing at the TOA (surface) is due to the dominance of longwave (shortwave) forcing. Both the TOA and surface forcings are in a range of 0–20 W m−2, depending on the optical depths of thin cirrus clouds.

scholarly journals Impact of Aerosol and Cloud on the Solar Energy Potential over the Central Gangetic Himalayan Region

2021 ◽  
Vol 13 (16) ◽  
pp. 3248
Author(s):  
Umesh Chandra Dumka ◽  
Panagiotis G. Kosmopoulos ◽  
Shantikumar S. Ningombam ◽  
Akriti Masoom
Keyword(s):  
Solar Energy ◽  
Atmospheric Aerosols ◽  
Himalayan Region ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Energy Potential ◽  
Surface Solar Radiation ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact

We examine the impact of atmospheric aerosols and clouds on the surface solar radiation and solar energy at Nainital, a high-altitude remote location in the central Gangetic Himalayan region (CGHR). For this purpose, we exploited the synergy of remote-sensed data in terms of ground-based AERONET Sun Photometer and satellite observations from the MODerate Resolution Imaging Spectroradiometer (MODIS) and the Meteosat Second Generation (MSG), with radiative transfer model (RTM) simulations and 1 day forecasts from the Copernicus Atmosphere Monitoring Service (CAMS). Clouds and aerosols are one of the most common sources of solar irradiance attenuation and hence causing performance issues in the photovoltaic (PV) and concentrated solar power (CSP) plant installations. The outputs of RTM results presented with high accuracy under clear, cloudy sky and dust conditions for global horizontal (GHI) and beam horizontal irradiance (BHI). On an annual basis the total aerosol attenuation was found to be up to 105 kWh m−2 for the GHI and 266 kWh m−2 for BHI, respectively, while the cloud effect is much stronger with an attenuation of 245 and 271 kWh m−2 on GHI and BHI. The results of this study will support the Indian solar energy producers and electricity handling entities in order to quantify the energy and financial losses due to cloud and aerosol presence.

scholarly journals Correcting for trace gas absorption when retrieving aerosol optical depth from satellite observations of reflected shortwave radiation

2018 ◽  
Author(s):  
Falguni Patadia ◽  
Robert Levy ◽  
Shana Mattoo
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Infrared Imaging ◽  
Gas Absorption ◽  
Shortwave Radiation ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite-measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon Moderate Resolution Imaging Spectroradiometer (MODIS, onboard Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, onboard Suomi-NPP) sensors, use wavelength bands in “window” regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper we use High-resolution TRANsmission (HITRAN) database and Line-by-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are “similar”, they are different enough that applying MODIS specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases up to 0.07. As recent studies are attempting to create a long-term data record by joining multiple satellite datasets, including MODIS and VIIRS, the consistency of gas correction becomes even more crucial.

scholarly journals Correcting for trace gas absorption when retrieving aerosol optical depth from satellite observations of reflected shortwave radiation

2018 ◽  
Vol 11 (6) ◽  
pp. 3205-3219 ◽  
Author(s):  
Falguni Patadia ◽  
Robert C. Levy ◽  
Shana Mattoo
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Infrared Imaging ◽  
Gas Absorption ◽  
Shortwave Radiation ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Data Sets ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite-measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from the underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon the Moderate Resolution Imaging Spectroradiometer (MODIS, on board Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, on board Suomi-NPP) sensors, use wavelength bands in “window” regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper, we use the High-resolution TRANsmission (HITRAN) database and Line-By-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are “similar”, they are different enough that applying MODIS-specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases of up to 0.07. As recent studies have been attempting to create a long-term data record by joining multiple satellite data sets, including MODIS and VIIRS, the consistency of gas correction has become even more crucial.

scholarly journals Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: retrieval algorithm and measurements during DISCOVER-AQ Texas 2013

2015 ◽  
Vol 8 (12) ◽  
pp. 13099-13155 ◽  
Author(s):  
C. R. Nowlan ◽  
X. Liu ◽  
J. W. Leitch ◽  
K. Chance ◽  
G. González Abad ◽  
...  
Keyword(s):  
Air Quality ◽  
Near Infrared ◽  
Infrared Light ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Mixing Ratios ◽  
Sensor Optimization

Abstract. The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a testbed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas in September 2013. Measurements of backscattered solar radiation between 420–465 nm collected on four days during the campaign are used to determine slant column amounts of NO2 at 250 m × 250 m spatial resolution with a fitting precision of 2.2 × 1015 molecules cm−2. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.91 for the most polluted day). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.84, slope = 0.94). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.

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