Performance of the line-by-line radiative transfer model (LBLRTM) for temperature and species retrievals: IASI case studies from JAIVEx

Abstract. Presented here are comparisons between the Infrared Atmospheric Sounding instrument (IASI) and the "Line-By-Line Radiative Transfer Model" (LBLRTM). Spectral residuals from radiance closure studies during the IASI JAIVEx validation campaign provide insight into a number of spectroscopy issues relevant to remote sounding of temperature, water vapor and trace gases from IASI. In order to perform quality IASI trace gas retrievals, the temperature and water vapor fields must be retrieved as accurately as possible. In general, the residuals in the CO2 ν2 region are of the order of the IASI instrument noise. However, outstanding issues with the CO2 spectral regions remain. There is a large residual ~−1.7 K in the 667 cm−1 Q-branch, and residuals in the CO2 ν2 and N2O/CO2 ν3 spectral regions that sample the troposphere are inconsistent, with the N2O/CO2 ν3 region being too negative (warmer) by ~0.7 K. Residuals on this lower wavenumber side of the CO2 ν3 band will be improved by line parameter updates, while future efforts to reduce the residuals reaching ~−0.5 K on the higher wavenumber side of the CO2 ν3 band will focus on addressing limitations in the modeling of the CO2 line shape (line coupling and duration of collision) effects. Brightness temperature residuals from the radiance closure studies in the ν2 water vapor band have standard deviations of ~0.2–0.3 K with some large peak residuals reaching ±0.5–1.0 K. These are larger than the instrument noise indicating that systematic errors still remain. New H2O line intensities and positions have a significant impact on the retrieved water vapor, particularly in the upper troposphere where the water vapor retrievals are 10% drier when using line intensities compared with HITRAN 2004. In addition to O3, CH4, and CO, of the IASI instrument combined with an accurate forward model allows for the detection of minor species with weak atmospheric signatures in the nadir radiances, such as HNO3 and OCS.

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Performance of the line-by-line radiative transfer model (LBLRTM) for temperature and species retrievals: IASI case studies from JAIVEx

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-9-9313-2009 ◽

2009 ◽

Vol 9 (2) ◽

pp. 9313-9366 ◽

Cited By ~ 6

Author(s):

M. W. Shephard ◽

S. A. Clough ◽

V. H. Payne ◽

W. L. Smith ◽

S. Kireev ◽

...

Keyword(s):

Water Vapor ◽

Radiative Transfer ◽

Radiative Transfer Model ◽

Transfer Model ◽

Radiometric Calibration ◽

Line Intensities ◽

Remote Sounding ◽

Instrument Noise ◽

Large Peak ◽

Line Coupling

Abstract. Presented here are comparisons between the Infrared Atmospheric Sounding instrument (IASI) and the "Line-By- Line Radiative Transfer Model" (LBLRTM). Spectral residuals from radiance closure studies during the IASI JAIVEx validation campaign provide insight into a number of spectroscopy issues relevant to remote sounding of temperature, water vapor and trace gases from IASI. In order to perform quality IASI trace gas retrievals the temperature and water vapor fields must be retrieved as accurately as possible. In general, the residuals in the CO2 ν2 region are of the order of the IASI instrument noise. However, outstanding issues in the CO2 spectral regions remain. There is a large residual ~−1.5 K in the 667 cm−1 Q-branch, and residuals in the CO2 ν2 and N2O/CO2 ν3 spectral regions that sample the troposphere are inconsistent, with the N2O/CO2 ν3 region being too negative (warmer) by ~0.6 K. Residuals on this lower wavenumber side of the CO2 ν3 band will be improved by line parameter updates, while future efforts to reduce the residuals reaching ~−0.5 K on the higher wavenumber side of the CO2 ν3 band will focus on addressing limitations in the modeling of the CO2 line shape (line coupling and duration of collision) effects. Brightness temperature residuals from the radiance closure studies in the ν2 water vapor band have standard deviations of ~0.2–0.3 K with some large peak residuals reaching ±0.5–1.0 K. These are larger than the instrument noise indicating that systematic errors still remain. New H2O line intensities and positions from Coudert have a significant impact on the retrieved water vapor, particularly in the upper troposphere where the water vapor retrievals are 10% drier when using line intensities from Coudert compared with HITRAN2004. In addition to O3, CH4, and CO, the high radiometric calibration of the IASI instrument combined with an accurate forward model allows for the detection of minor species with weak atmospheric signatures in the nadir radiances, such as HNO3 and OCS.

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Impact of 3D cloud structures on tropospheric NO2 column measurements from UV-VIS sounders

10.5194/egusphere-egu2020-17626 ◽

2020 ◽

Author(s):

Huan Yu ◽

Arve Kylling ◽

Claudia Emde ◽

Bernhard Mayer ◽

Kerstin Stebel ◽

...

Keyword(s):

Radiative Transfer ◽

Mitigation Strategies ◽

Trace Gas ◽

Radiative Transfer Model ◽

Transfer Model ◽

Vertical Column ◽

Ice Clouds ◽

Cloud Data ◽

One Step ◽

The Impact

Operational retrievals of tropospheric trace gases from space-borne spectrometers are made using 1D radiative transfer models. To minimize cloud effects generally only partially cloudy pixels are analysed using simplified cloud contamination treatments based on radiometric cloud fraction estimates and photon path length corrections based on oxygen collision pair (O2-O2) or O2A-absorption band measurements. In reality, however, the impact of clouds can be much more complex, involving scattering of clouds in neighbouring pixels and cloud shadow effects. Therefore, to go one step further, other correction methods may be envisaged that use sub-pixel cloud information from co-located imagers. Such methods require an understanding of the impact of clouds on the real 3D radiative transfer. We quantify this impact using the MYSTIC 3D radiative transfer model. The generation of realistic 3D input cloud fields, needed by MYSTIC (or any other 3D radiative transfer model), is non-trivial. We use cloud data generated by the ICOsahedral Non-hydrostatic (ICON) atmosphere model for a region including Germany, the Netherlands and parts of other surrounding countries. The model simulates realistic liquid and ice clouds with a horizontal spatial resolution of 156 m and it has been validated against ground-based and satellite-based observational data.As a trace gas example, we study NO2, a key tropospheric trace gas measured by the atmospheric Sentinels. The MYSTIC 3D model simulates visible spectra, which are ingested in standard DOAS retrieval algorithms to retrieve the NO2 column amount. Spectra are simulated for a number of realistic cloud scenarios, snow free surface albedos, and solar and satellite geometries typical of low-earth and geostationary orbits. The retrieved NO2 vertical column densities (VCD) are compared with the true values to identify conditions where 3D cloud effects lead to significant biases on the NO2 VCDs. A variety of possible mitigation strategies for such pixels are then explored.

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Greenhouse effects of aircraft emissions as calculated by a radiative transfer model

Annales Geophysicae ◽

10.1007/s00585-995-0413-4 ◽

1995 ◽

Vol 13 (4) ◽

pp. 413-418 ◽

Cited By ~ 29

Author(s):

J. P. F. Fortuin ◽

R. van Dorland ◽

W. M. F. Wauben ◽

H. Kelder

Keyword(s):

Water Vapor ◽

Radiative Transfer ◽

Indirect Effect ◽

Radiative Forcing ◽

Combustion Products ◽

Ozone Production ◽

Radiative Transfer Model ◽

Transfer Model ◽

Aircraft Emissions ◽

The North

Abstract. With a radiative transfer model, assessments are made of the radiative forcing in northern mid-latitudes due to aircraft emissions up to 1990. Considered are the direct climate effects from the major combustion products carbon dioxide, nitrogen dioxide, water vapor and sulphur dioxide, as well as the indirect effect of ozone production from NOx emissions. Our study indicates a local radiative forcing at the tropopause which should be negative in summer (–0.5 to 0.0 W/m2) and either negative or positive in winter (–0.3 to 0.2 W/m2). To these values the indirect effect of contrails has to be added, which for the North Atlantic Flight Corridor covers the range –0.2 to 0.3 W/m2 in summer and 0.0 to 0.3 W/m2 in winter. Apart from optically dense non-aged contrails during summer, negative forcings are due to solar screening by sulphate aerosols. The major positive contributions come from contrails, stratospheric water vapor in winter and ozone in summer. The direct effect of NO2 is negligible and the contribution of CO2 is relatively small.

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The Pure Rotational Line Emission of Ortho‐Water Vapor in Comets. I. Radiative Transfer Model

The Astrophysical Journal ◽

10.1086/424439 ◽

2004 ◽

Vol 615 (1) ◽

pp. 531-544 ◽

Cited By ~ 33

Author(s):

F. Bensch ◽

E. A. Bergin

Keyword(s):

Water Vapor ◽

Radiative Transfer ◽

Line Emission ◽

Radiative Transfer Model ◽

Rotational Line ◽

Transfer Model

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Performance of the Line-By-Line Radiative Transfer Model (LBLRTM) for temperature, water vapor, and trace gas retrievals: recent updates evaluated with IASI case studies

Atmospheric Chemistry and Physics ◽

10.5194/acp-13-6687-2013 ◽

2013 ◽

Vol 13 (14) ◽

pp. 6687-6711 ◽

Cited By ~ 51

Author(s):

M. J. Alvarado ◽

V. H. Payne ◽

E. J. Mlawer ◽

G. Uymin ◽

M. W. Shephard ◽

...

Keyword(s):

Water Vapor ◽

Radiative Transfer ◽

Fixed Ratio ◽

Satellite Observations ◽

Radiative Transfer Model ◽

Transfer Model ◽

Temperature Profiles ◽

A Posteriori ◽

The Impact ◽

Temperature Water

Abstract. Modern data assimilation algorithms depend on accurate infrared spectroscopy in order to make use of the information related to temperature, water vapor (H2O), and other trace gases provided by satellite observations. Reducing the uncertainties in our knowledge of spectroscopic line parameters and continuum absorption is thus important to improve the application of satellite data to weather forecasting. Here we present the results of a rigorous validation of spectroscopic updates to an advanced radiative transfer model, the Line-By-Line Radiative Transfer Model (LBLRTM), against a global dataset of 120 near-nadir, over-ocean, nighttime spectra from the Infrared Atmospheric Sounding Interferometer (IASI). We compare calculations from the latest version of LBLRTM (v12.1) to those from a previous version (v9.4+) to determine the impact of spectroscopic updates to the model on spectral residuals as well as retrieved temperature and H2O profiles. We show that the spectroscopy in the CO2 ν2 and ν3 bands is significantly improved in LBLRTM v12.1 relative to v9.4+, and that these spectroscopic updates lead to mean changes of ~0.5 K in the retrieved vertical temperature profiles between the surface and 10 hPa, with the sign of the change and the variability among cases depending on altitude. We also find that temperature retrievals using each of these two CO2 bands are remarkably consistent in LBLRTM v12.1, potentially allowing these bands to be used to retrieve atmospheric temperature simultaneously. The updated H2O spectroscopy in LBLRTM v12.1 substantially improves the a posteriori residuals in the P-branch of the H2O ν2 band, while the improvements in the R-branch are more modest. The H2O amounts retrieved with LBLRTM v12.1 are on average 14% lower between 100 and 200 hPa, 42% higher near 562 hPa, and 31% higher near the surface compared to the amounts retrieved with v9.4+ due to a combination of the different retrieved temperature profiles and the updated H2O spectroscopy. We also find that the use of a fixed ratio of HDO to H2O in LBLRTM may be responsible for a significant fraction of the remaining bias in the P-branch relative to the R-branch of the H2O ν2 band. There were no changes to O3 spectroscopy between the two model versions, and so both versions give positive a posteriori residuals of ~ 0.3 K in the R-branch of the O3 ν3 band. While the updates to the H2O self-continuum employed by LBLRTM v12.1 have clearly improved the match with observations near the CO2 ν3 band head, we find that these updates have significantly degraded the match with observations in the fundamental band of CO. Finally, significant systematic a posteriori residuals remain in the ν4 band of CH4, but the magnitude of the positive bias in the retrieved mixing ratios is reduced in LBLRTM v12.1, suggesting that the updated spectroscopy could improve retrievals of CH4 from satellite observations.

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Method for Water Vapor Profile Retievals by Means of Minimizing Difference Between Estimated and Actual Brightness Temperatures Derived from AIRS data and Radiative Transfer Model

International Journal of Advanced Computer Science and Applications ◽

10.14569/ijacsa.2012.031223 ◽

2012 ◽

Vol 3 (12) ◽

Author(s):

Kohei Arai

Keyword(s):

Water Vapor ◽

Radiative Transfer ◽

Radiative Transfer Model ◽

Transfer Model ◽

Brightness Temperatures

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Improving Satellite-Derived Sea Surface Temperature Accuracies Using Water Vapor Profile Data

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2010jtecha1502.1 ◽

2011 ◽

Vol 28 (1) ◽

pp. 85-93 ◽

Cited By ~ 7

Author(s):

Ian J. Barton

Keyword(s):

Water Vapor ◽

Radiative Transfer ◽

Surface Temperature ◽

Sea Surface Temperature ◽

Satellite Data ◽

Sea Surface ◽

Radiative Transfer Model ◽

Clear Correlation ◽

Transfer Model ◽

The Difference

Abstract Analyses based on atmospheric infrared radiative transfer simulations and collocated ship and satellite data are used to investigate whether knowledge of vertical atmospheric water vapor distributions can improve the accuracy of sea surface temperature (SST) estimates from satellite data. Initially, a simulated set of satellite brightness temperatures generated by a radiative transfer model with a large maritime radiosonde database was obtained. Simple linear SST algorithms are derived from this dataset, and these are then reapplied to the data to give simulated SST estimates and errors. The concept of water vapor weights is introduced in which a weight is a measure of the layer contribution to the difference between the surface temperature and that measured by the satellite. The weight of each atmospheric layer is defined as the layer water vapor amount multiplied by the difference between the SST and the midlayer temperature. Satellite-derived SST errors are then plotted against the difference in the sum of weights above an altitude of 2.5 km and that below. For the simple two-channel (with typical wavelengths of 11 and 12 μm) analysis, a clear correlation between the weights differences and the SST errors is found. A second group of analyses using ship-released radiosondes and satellite data also show a correlation between the SST errors and the weights differences. The analyses suggest that, for an SST derived using a simple two-channel algorithm, the accuracy may be improved if account is taken of the vertical distribution of water vapor above the ocean surface. For SST estimates derived using algorithms that include data from a 3.7-μm channel, there is no such correlation found.

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Impact of 3D cloud structures on tropospheric NO2 column measurements from UV-VIS sounders

10.5194/egusphere-egu21-7523 ◽

2021 ◽

Author(s):

Huan Yu ◽

Arve Kylling ◽

Claudia Emde ◽

Bernhard Mayer ◽

Michel Van Roozendael ◽

...

Keyword(s):

Radiative Transfer ◽

Synthetic Data ◽

Sensitivity Study ◽

Trace Gas ◽

Radiative Transfer Model ◽

Retrieval Algorithm ◽

Transfer Model ◽

Boundary Layer Clouds ◽

Cloud Parameters ◽

The Impact

Operational retrievals of tropospheric trace gases from space-borne spectrometers are made using 1D radiative transfer models. To minimize cloud effects generally only partially cloudy pixels are analysed using simplified cloud contamination treatments based on radiometric cloud fraction estimates and photon path length corrections based on oxygen collision pair (O2-O2) or O2A-absorption band measurements. In reality, however, the impact of clouds can be much more complex, involving unresolved sub-pixel clouds, scattering of clouds in neighbouring pixels, and cloud shadow effects, such that 3D radiation scattering from unresolved boundary layer clouds may give significant biases in the trace gas retrievals. In order to quantify this impact, we use the MYSTIC 3D radiative transfer model to generate synthetic data. The realistic 3D cloud fields, needed for MYSTIC input, are generated by the ICOsahedral Non-hydrostatic (ICON) atmosphere model for a region including Germany, the Netherlands and parts of other surrounding countries. The retrieval algorithm is applied to the synthetic data and comparison to the known input trace gas concentrations yields the retrieval error due to 3D cloud effects.&#160; In this study, we study NO2, which is a key tropospheric trace gas measured by TROPOMI and the future atmospheric Sentinels (S4 and S5). The work starts with a sensitivity study for the simulations with a simple 2D box cloud. The influence of cloud parameters (e.g., cloud top height, cloud optical thickness), observation geometry, and spatial resolution are studied, and the most significant dependences of retrieval biases are identified and investigated. Several approaches to correct the NO2 retrieval in the cloud shadow are explored and ultimately applied to both synthetic data with realistic 3D clouds and real observations.

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