Geostationary atmospheric infrared sounder: trace gases sensitivity

Abstract. Principal component (PC) analysis has received considerable attention as a technique for the extraction of meteorological signals from hyperspectral infra-red sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and the Atmospheric Infrared Sounder (AIRS). In addition to achieving substantial bit-volume reductions for dissemination purposes, the technique can also be used to generate reconstructed radiances in which random instrument noise has been reduced. Studies on PC analysis of hyperspectral infrared sounder data have been undertaken in the context of numerical weather prediction, instrument monitoring and geophysical variable retrieval, as well as data compression. This study examines the potential of PC analysis for chemistry applications. A major concern in the use of PC analysis for chemistry is that the spectral features associated with trace gases may not be well represented in the reconstructed spectra, either due to deficiencies in the training set or due to the limited number of PC scores used in the radiance reconstruction. In this paper we show examples of reconstructed IASI radiances for several trace gases: ammonia, sulphur dioxide, methane and carbon monoxide. It is shown that care must be taken in the selection of spectra for the initial training set: an iterative technique, in which outlier spectra are added to a base training set, gives the best results. For the four trace gases examined, key features of the chemical signatures are retained in the reconstructed radiances, whilst achieving a substantial reduction in instrument noise. A new regional re-transmission service for IASI is scheduled to start in 2010, as part of the EUMETSAT Advanced Retransmission Service (EARS). For this EARS-IASI service it is intended to include PC scores as part of the data stream. The paper describes the generation of the reference eigenvectors for this new service.

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Potential for the use of reconstructed IASI radiances in the detection of atmospheric trace gases

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-3-501-2010 ◽

2010 ◽

Vol 3 (1) ◽

pp. 501-529

Author(s):

N. C. Atkinson ◽

F. I. Hilton ◽

S. M. Illingworth ◽

J. R. Eyre ◽

T. Hultberg

Keyword(s):

Weather Prediction ◽

Trace Gases ◽

Substantial Reduction ◽

Principal Component ◽

Training Set ◽

Atmospheric Infrared Sounder ◽

Chemical Signatures ◽

Atmospheric Sounding ◽

Instrument Noise ◽

Selection Of

Abstract. Principal component (PC) analysis has received considerable attention as a technique for the extraction of meteorological signals from hyperspectral infra-red sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and the Atmospheric Infrared Sounder (AIRS). In addition to achieving substantial bit-volume reductions for dissemination purposes, the technique can also be used to generate reconstructed radiances in which random instrument noise has been suppressed. To date, most studies have been in the context of Numerical Weather Prediction (NWP). This study examines the potential of PC analysis for chemistry applications. A major concern in the use of PC analysis for chemistry has been that the spectral features associated with trace gases may not be well represented in the reconstructed spectra, either due to deficiencies in the training set or due to the limited number of PC scores used in the radiance reconstruction. In this paper we show examples of reconstructed IASI radiances for several trace gases: ammonia, sulphur dioxide, methane and carbon monoxide. It is shown that care must be taken in the selection of spectra for the initial training set: an iterative technique, in which outlier spectra are added to a base training set, gives the best results. For the four trace gases examined, the chemical signatures are retained in the reconstructed radiances, whilst achieving a substantial reduction in instrument noise. A new regional re-transmission service for IASI is scheduled to start in 2010, as part of the EUMETSAT Advanced Retransmission Service (EARS). For this EARS-IASI service it is intended to include PC scores as part of the data stream. The paper describes the generation of the reference eigenvectors for this new service.

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A simple model for Junge’s relationship between concentration fluctuations and residence times for tropospheric trace gases

Tellus B ◽

10.3402/tellusb.v40i3.15909 ◽

1988 ◽

Vol 40 (3) ◽

pp. 229-232 ◽

Cited By ~ 9

Author(s):

W.G.N. Slinn

Keyword(s):

Simple Model ◽

Trace Gases ◽

Concentration Fluctuations ◽

Residence Times

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Effects of Solar Heating by Aerosols and Trace Gases on the Temperature Structure Constant

10.21236/ada237675 ◽

1990 ◽

Author(s):

J. R. Hummel ◽

E. P. Shettle

Keyword(s):

Trace Gases ◽

Structure Constant ◽

Solar Heating ◽

Temperature Structure

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A Proof-of-Concept Algorithm for the Retrieval of Total Column Amount of Trace Gases in a Multi-Dimensional Atmosphere

Remote Sensing ◽

10.3390/rs13020270 ◽

2021 ◽

Vol 13 (2) ◽

pp. 270

Author(s):

Adrian Doicu ◽

Dmitry S. Efremenko ◽

Thomas Trautmann

Keyword(s):

Trace Gases ◽

Three Dimensional ◽

Principal Component ◽

Radiative Transfer Model ◽

Computational Time ◽

Transfer Model ◽

Proof Of Concept ◽

Discrete Ordinate ◽

Distribution Method ◽

Total Column

An algorithm for the retrieval of total column amount of trace gases in a multi-dimensional atmosphere is designed. The algorithm uses (i) certain differential radiance models with internal and external closures as inversion models, (ii) the iteratively regularized Gauss–Newton method as a regularization tool, and (iii) the spherical harmonics discrete ordinate method (SHDOM) as linearized radiative transfer model. For efficiency reasons, SHDOM is equipped with a spectral acceleration approach that combines the correlated k-distribution method with the principal component analysis. The algorithm is used to retrieve the total column amount of nitrogen for two- and three-dimensional cloudy scenes. Although for three-dimensional geometries, the computational time is high, the main concepts of the algorithm are correct and the retrieval results are accurate.

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Recommendations for HCHO and SO2 Retrieval Settings from MAX-DOAS Observations under Different Meteorological Conditions

Remote Sensing ◽

10.3390/rs13122244 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2244

Author(s):

Zeeshan Javed ◽

Aimon Tanvir ◽

Muhammad Bilal ◽

Wenjing Su ◽

Congzi Xia ◽

...

Keyword(s):

Column Density ◽

Trace Gases ◽

Meteorological Conditions ◽

Optical Absorption Spectroscopy ◽

Chemical Production ◽

Vertical Column ◽

Phase Oxidation ◽

Fog Days ◽

Rms Errors ◽

Optimal Settings

Recently, the occurrence of fog and haze over China has increased. The retrieval of trace gases from the multi-axis differential optical absorption spectroscopy (MAX-DOAS) is challenging under these conditions. In this study, various reported retrieval settings for formaldehyde (HCHO) and sulfur dioxide (SO2) are compared to evaluate the performance of these settings under different meteorological conditions (clear day, haze, and fog). The dataset from 1st December 2019 to 31st March 2020 over Nanjing, China, is used in this study. The results indicated that for HCHO, the optimal settings were in the 324.5–359 nm wavelength window with a polynomial order of five. At these settings, the fitting and root mean squared (RMS) errors for column density were considerably improved for haze and fog conditions, and the differential slant column densities (DSCDs) showed more accurate values compared to the DSCDs between 336.5 and 359 nm. For SO2, the optimal settings for retrieval were found to be at 307–328 nm with a polynomial order of five. Here, root mean square (RMS) and fitting errors were significantly lower under all conditions. The observed HCHO and SO2 vertical column densities were significantly lower on fog days compared to clear days, reflecting a decreased chemical production of HCHO and aqueous phase oxidation of SO2 in fog droplets.

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DETERMINATION OF PHASE TRANSFER PARAMETERS OF THE ATMOSPHERIC TRACE GASES NITRIC ACID, OZONE, AND DINITROGENPENTOXIDE AT LIQUID SURFACES

Journal of Aerosol Science ◽

10.1016/s0021-8502(21)00144-0 ◽

2001 ◽

Vol 32 ◽

pp. 301-302

Author(s):

M. SCHÜTZE ◽

T. BERNDT ◽

H. HERRMANN

Keyword(s):

Nitric Acid ◽

Phase Transfer ◽

Trace Gases ◽

Atmospheric Trace Gases ◽

Transfer Parameters ◽

Liquid Surfaces

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Total Ozone Columns from the Environmental Trace Gases Monitoring Instrument (EMI) Using the DOAS Method

Remote Sensing ◽

10.3390/rs13112098 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2098

Author(s):

Yuanyuan Qian ◽

Yuhan Luo ◽

Fuqi Si ◽

Haijin Zhou ◽

Taiping Yang ◽

...

Keyword(s):

Optical Absorption ◽

Absorption Spectroscopy ◽

Total Ozone ◽

Scattered Light ◽

Trace Gases ◽

Rapid Change ◽

Differential Optical Absorption Spectroscopy ◽

Optical Absorption Spectroscopy ◽

Monitoring Instrument ◽

Monthly Average

Global measurements of total ozone are necessary to evaluate ozone hole recovery above Antarctica. The Environmental Trace Gases Monitoring Instrument (EMI) onboard GaoFen 5, launched in May 2018, was developed to measure and monitor the global total ozone column (TOC) and distributions of other trace gases. In this study, some of the first global TOC results of the EMI using the differential optical absorption spectroscopy (DOAS) method and validation with ground-based TOC measurements and data derived from Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) observations are presented. Results show that monthly average EMI TOC data had a similar spatial distribution and a high correlation coefficient (R ≥ 0.99) with both OMI and TROPOMI TOC. Comparisons with ground-based measurements from the World Ozone and Ultraviolet Radiation Data Centre also revealed strong correlations (R > 0.9). Continuous zenith sky measurements from zenith scattered light differential optical absorption spectroscopy instruments in Antarctica were also used for validation (R = 0.9). The EMI-derived observations were able to account for the rapid change in TOC associated with the sudden stratospheric warming event in October 2019; monthly average TOC in October 2019 was 45% higher compared to October 2018. These results indicate that EMI TOC derived using the DOAS method is reliable and has the potential to be used for global TOC monitoring.

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