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

Shephard, Mark W.; Clough, S. A.; Payne, Vivienne H.; Smith, William L.; Kireev, Stanislav; Cady‐Pereira, Karen

doi:10.5194/acp-9-7397-2009

Cited by 79 publications

(46 citation statements)

References 52 publications

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“…Notice that peak OCS sensitivity with IASI is consistently around 500 hPa for all atmospheres and both surface temperature contrast scenarios. This is consistent with the OCS analyses published in Shephard et al (2009) and Kuai et al (2014). However, when the surface ground temperature is significantly warmer than the surface air temperature (positive thermal contrast), then the lowermost tropospheric OCS becomes up to 3 or 4 times more detectable.…”

Section: Spectral Range Consideredsupporting

confidence: 80%

Fast retrievals of tropospheric carbonyl sulfide with IASI

Vincent

Dudhia

2017

Atmos. Chem. Phys.

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Abstract. Iterative retrievals of trace gases, such as carbonyl sulfide (OCS), from satellites can be exceedingly slow. The algorithm may even fail to keep pace with data acquisition such that analysis is limited to local events of special interest and short time spans. With this in mind, a linear retrieval scheme was developed to estimate total column amounts of OCS at a rate roughly 10 4 times faster than a typical iterative retrieval. This scheme incorporates two concepts not utilized in previously published linear estimates. First, all physical parameters affecting the signal are included in the state vector and accounted for jointly, rather than treated as effective noise. Second, the initialization point is determined from an ensemble of atmospheres based on comparing the model spectra to the observations, thus improving the linearity of the problem. All of the 2014 data from the Infrared Atmospheric Sounding Interferometer (IASI), instruments A and B, were analysed and showed spatial features of OCS total columns, including depletions over tropical rainforests, seasonal enhancements over the oceans, and distinct OCS features over land. Error due to assuming linearity was found to be on the order of 11 % globally for OCS. However, systematic errors from effects such as varying surface emissivity and extinction due to aerosols have yet to be robustly characterized. Comparisons to surface volume mixing ratio in situ samples taken by NOAA show seasonal correlations greater than 0.7 for five out of seven sites across the globe. Furthermore, this linear scheme was applied to OCS, but may also be used as a rapid estimator of any detectable trace gas using IASI or similar nadir-viewing instruments.

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Section: Spectral Range Consideredsupporting

confidence: 80%

Fast retrievals of tropospheric carbonyl sulfide with IASI

Vincent

Dudhia

2017

Atmos. Chem. Phys.

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“…In this study we use the NH 3 retrieval as described by . The retrieval is based on an optimal estimation approach (Rodgers, 2000) that minimizes the differences between CrIS spectral radiances and simulated forward model radiances computed from the Optimal Spectral Sampling method (OSS) OSS-CrIS (Moncet et al, 2008), which is built from the well-validated Line-By-Line Radiative Transfer Model (LBLRTM) (Clough et al, 2005;Shephard et al, 2009;Alvarado et al, 2013) and uses the HITRAN database (Rothman et al, 2013) for its spectral lines. The fast computational speed of OSS facilitates the operational production of CrIS-retrieved (level 2) products using an optimal estimation retrieval approach (Moncet et al, 2005).…”

Section: The Cris Fast Physical Retrievalmentioning

confidence: 99%

Validation of the CrIS fast physical NH<sub>3</sub> retrieval with ground-based FTIR

et al. 2017

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Abstract. Presented here is the validation of the CrIS (Cross-track Infrared Sounder) fast physical NH 3 retrieval (CFPR) column and profile measurements using groundbased Fourier transform infrared (FTIR) observations. We use the total columns and profiles from seven FTIR sites in the Network for the Detection of Atmospheric Composition Change (NDACC) to validate the satellite data products. The overall FTIR and CrIS total columns have a positive correlation of r = 0.77 (N = 218) with very little bias (a slope of 1.02). Binning the comparisons by total column amounts, for concentrations larger than 1.0 × 10 16 molecules cm −2 , i.e. ranging from moderate to polluted conditions, the relative difference is on average ∼ 0-5 % with a standard deviation of 25-50 %, which is comparable to the estimated retrieval uncertainties in both CrIS and the FTIR. For the smallest total column range (< 1.0x × 10 16 molecules cm −2 ) where there are a large number of observations at or near the CrIS noise level (detection limit) the absolute differences between CrIS and the FTIR total columns show a slight positive column bias. The CrIS and FTIR profile comparison differences are mostly within the range of the single-level retrieved profile values from estimated retrieval uncertainties, showing average differences in the range of ∼ 20 to 40 %. The CrIS retrievals typically show good vertical sensitivity down into the boundary layer which typically peaks at ∼ 850 hPa (∼ 1.5 km). At this level the median absolute difference is 0.87 (std = ±0.08) ppb, corresponding to a median relative difference of 39 % (std = ±2 %). Most of the absolute andPublished by Copernicus Publications on behalf of the European Geosciences Union. 2646 E. Dammers et al.: Validation of the CrIS fast physical NH 3 retrieval with ground-based FTIR relative profile comparison differences are in the range of the estimated retrieval uncertainties. At the surface, where CrIS typically has lower sensitivity, it tends to overestimate in low-concentration conditions and underestimate in higher atmospheric concentration conditions.

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“…TES is a high-resolution (0.06 cm −1 ) Fourier transform spectrometer onboard NASA's Aura satellite, in a sun-synchronous orbit with measurements at 01:30 and 13:30 LT. The spectrometer measures infrared radiation, and NH 3 concentrations are retrieved using optimal estimation methods Rodgers, 2000) with the Line-By-Line Radiative Tansfer Model (LBLRTM) and the fast forward model (OSS-TES) Moncet et al, 2008;Shephard et al, 2009). The ammonia data used in this study are from the TES Lite data product, Version 5 (http://avdc.gsfc.nasa.gov/index.…”

Section: Satellite Measurements Of Ammoniamentioning

confidence: 99%

Simulation of nitrate, sulfate, and ammonium aerosols over the United States

et al. 2012

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Abstract. Atmospheric concentrations of inorganic gases and aerosols (nitrate, sulfate, and ammonium) are simulated for 2009 over the United States using the chemical transport model GEOS-Chem. Predicted aerosol concentrations are compared with surface-level measurement data from the Interagency Monitoring of Protected Visual Environments (IMPROVE), the Clean Air Status and Trends Network (CASTNET), and the California Air Resources Board (CARB). Sulfate predictions nationwide are in reasonably good agreement with observations, while nitrate and ammonium are over-predicted in the East and Midwest, but underpredicted in California, where observed concentrations are the highest in the country. Over-prediction of nitrate in the East and Midwest is consistent with results of recent studies, which suggest that nighttime nitric acid formation by heterogeneous hydrolysis of N 2 O 5 is over-predicted based on current values of the N 2 O 5 uptake coefficient, γ , onto aerosols. After reducing the value of γ by a factor of 10, predicted nitrate levels in the US Midwest and East still remain higher than those measured, and over-prediction of nitrate in this region remains unexplained. Comparison of model predictions with satellite measurements of ammonia from the Tropospheric Emissions Spectrometer (TES) indicates that ammonia emissions in GEOS-Chem are underestimated in California and that the nationwide seasonality applied to ammonia emissions in GEOS-Chem does not represent California very well, particularly underestimating winter emissions. An ammonia sensitivity study indicates that GEOS-Chem simulation of nitrate is ammonia-limited in southern California and much of the state, suggesting that an underestimate of ammonia emissions is likely the main cause for the underprediction of nitrate aerosol in many areas of California. An approximate doubling of ammonia emissions is needed to reproduce observed nitrate concentrations in southern California and in other ammonia sensitive areas of California. However, even a tenfold increase in ammonia emissions yields predicted nitrate concentrations that are still biased low in the central valley of California. The under-prediction of nitrate aerosol in the central valley of California may arise in part from an under-prediction of both ammonia and nitric acid in this region. Since nitrate aerosols are particularly sensitive to mixed layer depths, owing to the gas-particle equilibrium, the nitrate under-prediction could also arise in part from a potential regional overestimate of GEOS-5 mixed layer depths in the central valley due to unresolved topography in this region.

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

Cited by 79 publications

References 52 publications

Fast retrievals of tropospheric carbonyl sulfide with IASI

Fast retrievals of tropospheric carbonyl sulfide with IASI

Validation of the CrIS fast physical NH<sub>3</sub> retrieval with ground-based FTIR

Simulation of nitrate, sulfate, and ammonium aerosols over the United States

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

Cited by 79 publications

References 52 publications

Fast retrievals of tropospheric carbonyl sulfide with IASI

Fast retrievals of tropospheric carbonyl sulfide with IASI

Validation of the CrIS fast physical NH&lt;sub&gt;3&lt;/sub&gt; retrieval with ground-based FTIR

Simulation of nitrate, sulfate, and ammonium aerosols over the United States

Contact Info

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Validation of the CrIS fast physical NH<sub>3</sub> retrieval with ground-based FTIR