VLIDORT: A linearized pseudo-spherical vector discrete ordinate radiative transfer code for forward model and retrieval studies in multilayer multiple scattering media

Spurr, Robert

doi:10.1016/j.jqsrt.2006.05.005

Cited by 408 publications

(317 citation statements)

References 49 publications

Supporting

Mentioning

311

Contrasting

Unclassified

Order By: Relevance

“…It is a two-step process: We first perform radiative transfer model (RTM) simulations of TEMPO radiance spectra and weighting functions (or Jacobians) using the VLIDORT radiative transfer model [98] and then conduct calculations of retrieval errors for various trace gases using the optimal estimation approach.…”

Section: Tempo Retrieval Sensitivity Studymentioning

confidence: 99%

Tropospheric emissions: Monitoring of pollution (TEMPO)

Zoogman

Liu

Suleiman

et al. 2017

Journal of Quantitative Spectroscopy and Radiative Transfer

283

144

View full text Add to dashboard Cite

show abstract

Section: Tempo Retrieval Sensitivity Studymentioning

confidence: 99%

Tropospheric emissions: Monitoring of pollution (TEMPO)

Zoogman

Liu

Suleiman

et al. 2017

Journal of Quantitative Spectroscopy and Radiative Transfer

283

144

View full text Add to dashboard Cite

show abstract

“…The AMFs in previous sections were derived by convolving the monthly mean water vapor profiles used in the GEOS-Chem model (2 • × 2.5 • ) with the scattering weights interpolated from a look-up table (Wang et al, 2014). The look-up table was constructed using the radiative transfer model VLIDORT (Spurr, 2006). The scattering weights in the look-up table depend on surface pressure, surface albedo, solar zenith angle (SZA), view zenith angle (VZA), relative azimuth angle (RAA), ozone column amount, cloud fraction, cloud pressure, and wavelength.…”

Section: Amf Updatementioning

confidence: 99%

Validation and update of OMI Total Column Water Vapor product

Wang¹,

Abad²,

Liu³

et al. 2016

Atmos. Chem. Phys.

View full text Add to dashboard Cite

Abstract. The collection 3 Ozone Monitoring Instrument (OMI) Total Column Water Vapor (TCWV) data generated by the Smithsonian Astrophysical Observatory's (SAO) algorithm version 1.0 and archived at the Aura Validation Data Center (AVDC) are compared with NCAR's ground-based GPS data, AERONET's sun-photometer data, and Remote Sensing System's (RSS) SSMIS data. Results show that the OMI data track the seasonal and interannual variability of TCWV for a wide range of climate regimes. During the period from 2005 to 2009, the mean OMI−GPS over land is −0.3 mm and the mean OMI−AERONET over land is 0 mm. For July 2005, the mean OMI−SSMIS over the ocean is −4.3 mm. The better agreement over land than over the ocean is corroborated by the smaller fitting residuals over land and suggests that liquid water is a key factor for the fitting quality over the ocean in the version 1.0 retrieval algorithm. We find that the influence of liquid water is reduced using a shorter optimized retrieval window of 427.7-465 nm. As a result, the TCWV retrieved with the new algorithm increases significantly over the ocean and only slightly over land. We have also made several updates to the air mass factor (AMF) calculation. The updated version 2.1 retrieval algorithm improves the land/ocean consistency and the overall quality of the OMI TCWV data set. The version 2.1 OMI data largely eliminate the low bias of the version 1.0 OMI data over the ocean and are 1.5 mm higher than RSS's "clear" sky SSMIS data in July 2005. Over the ocean, the mean of version 2.1 OMI−GlobVapour is 1 mm for July 2005 and 0 mm for January 2005. Over land, the version 2.1 OMI data are about 1 mm higher than GlobVapour when TCWV < 15 mm and about 1 mm lower when TCWV > 15 mm.

show abstract

“…Aerosol properties are retrieved for cloud-free and snow-free pixels by finding the best match between observed and precalculated TOA reflectances stored as a function of solar/viewing geometries, AOD, aerosol optical models (SSA for land, and SSA and find-mode AOD fraction for ocean), and surface conditions (surface reflectance for land and wind speed for ocean). The lookup tables (LUTs) for land and ocean were calculated using the Dave radiative transfer code [Dave, 1972] and the VLIDORT code (linearized pseudo-spherical vector discrete ordinate radiative transfer model) [Spurr, 2006], respectively.…”

Section: Viirs Deep Blue Aerosol Productsmentioning

confidence: 99%

Retrieving the height of smoke and dust aerosols by synergistic use of VIIRS, OMPS, and CALIOP observations

et al. 2015

View full text Add to dashboard Cite

This study extends the application of the previously developed Aerosol Single-scattering albedo and layer Height Estimation (ASHE) algorithm, which was originally applied to smoke aerosols only, to both smoke and dust aerosols by including nonspherical dust properties in the retrieval process. The main purpose of the algorithm is to derive aerosol height information over wide areas using aerosol products from multiple satellite sensors simultaneously: aerosol optical depth (AOD) and Ångström exponent from the Visible Infrared Imaging Radiometer Suite (VIIRS), UV aerosol index from the Ozone Mapping and Profiler Suite (OMPS), and total backscatter coefficient profile from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The case studies suggest that the ASHE algorithm performs well for both smoke and dust aerosols, showing root-mean-square error of the retrieved aerosol height as compared to CALIOP observations from 0.58 to 1.31 km and mean bias from À0.70 to 1.13 km. In addition, the algorithm shows the ability to retrieve single-scattering albedo to within 0.03 of Aerosol Robotic Network inversion data for moderate to thick aerosol loadings (AOD of~1.0). For typical single-layered aerosol cases, the estimated uncertainty in the retrieved height ranges from 1.20 to 1.80 km over land and from 1.15 to 1.58 km over ocean when favorable conditions are met. Larger errors are observed for multilayered aerosol events, due to the limited sensitivities of the passive sensors to such cases.

show abstract

VLIDORT: A linearized pseudo-spherical vector discrete ordinate radiative transfer code for forward model and retrieval studies in multilayer multiple scattering media

Cited by 408 publications

References 49 publications

Tropospheric emissions: Monitoring of pollution (TEMPO)

Tropospheric emissions: Monitoring of pollution (TEMPO)

Validation and update of OMI Total Column Water Vapor product

Retrieving the height of smoke and dust aerosols by synergistic use of VIIRS, OMPS, and CALIOP observations

Contact Info

Product

Resources

About