Fine structure of oxygen absorption bands in Si at low temperature

1992 ◽  
Vol 72 (11) ◽  
pp. 5393-5396 ◽  
Author(s):  
K. Ryoo ◽  
H. R. Kim ◽  
J. S. Koh ◽  
G. Seo ◽  
J. H. Lee
Keyword(s):  
Fine Structure ◽  
Low Temperature ◽  
Oxygen Absorption ◽  
Absorption Bands

Investigation of the fine structure in overtone absorption bands of 12C2H4

1999 ◽  
Vol 97 (1) ◽  
pp. 265-277 ◽  
Author(s):  
M. BACH, R. GEORGES, M. HERMAN, A. PER
Keyword(s):  
Fine Structure ◽  
Absorption Bands

Absorption Bands and Luminescence of LiF Irradiated at Low Temperature

1950 ◽  
Vol 78 (3) ◽  
pp. 293-293 ◽  
Author(s):  
Peter Pringsheim ◽  
Philip Yuster
Keyword(s):  
Low Temperature ◽  
Absorption Bands

Intercomparison of Cloud Products based on S5P/TROPOMI Level 1b Data Version 1 and the updated Version 2

2021 ◽  
Author(s):  
Miriam Latsch ◽  
Andreas Richter ◽  
John P. Burrows ◽  
Thomas Wagner ◽  
Holger Sihler ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Recognition Algorithm ◽  
Cloud Fraction ◽  
Trace Gas ◽  
Oxygen Absorption ◽  
Data Sets ◽  
Absorption Bands ◽  
Data Set ◽  
Trace Species ◽  
Retrieval Scheme

<p>The first European Sentinel satellite for monitoring the composition of the Earth’s atmosphere, the Sentinel 5 Precursor (S5p), carries the TROPOspheric Monitoring Instrument (TROPOMI) to map trace species of the global atmosphere at high spatial resolution. Retrievals of tropospheric trace gas columns from satellite measurements are strongly influenced by clouds. Thus, cloud retrieval algorithms were developed and implemented in the trace gas processing chain to consider this impact.</p><p>In this study, different cloud products available for NO<sub>2</sub> retrievals based on the TROPOMI level 1b data version 1 and an updated TROPOMI level 1b test data set of version 2 (Diagnostic Data Set 2B, DDS2B) are analyzed. The data sets include a) the TROPOMI level 2 OCRA/ROCINN (Optical Cloud Recognition Algorithm/Retrieval of Cloud Information using Neural Networks) cloud products CRB (cloud as reflecting boundaries) and CAL (clouds as layers), b) the FRESCO (Fast Retrieval Scheme for Clouds from Oxygen absorption bands) cloud product,  c) the cloud fraction from the NO<sub>2</sub> fitting window, d) the VIIRS (Visible Infrared Imaging Radiometer Suite) cloud product, and e) the MICRU (Mainz Iterative Cloud Retrieval Utilities) cloud fraction. The cloud products are compared with regard to cloud fraction, cloud height, cloud albedo/optical thickness, flagging and quality indicators in all 4 seasons. In particular, the differences of the cloud products under difficult situations such as snow or ice cover and sun glint are investigated.</p><p>We present results of a statistical analysis on a limited data set comparing cloud products from the current and the upcoming lv2 data versions and their approaches. The aim of this study is to better understand TROPOMI cloud products and their quantitative impacts on trace gas retrievals.</p>

Low-temperature NO oxidation using lattice oxygen in Fe-site substituted SrFeO3−δ

2020 ◽  
Vol 22 (42) ◽  
pp. 24181-24190
Author(s):  
Kazuki Tamai ◽  
Saburo Hosokawa ◽  
Kazuo Kato ◽  
Hiroyuki Asakura ◽  
Kentaro Teramura ◽  
...  
Keyword(s):  
Fine Structure ◽  
Low Temperature ◽  
Lattice Oxygen ◽  
No Oxidation ◽  
Oxygen Release ◽  
X Ray ◽  
Absorption Fine ◽  
Perovskite Catalysts ◽  
X Ray Absorption

The dynamics of lattice oxygen release from perovskite catalysts during NO oxidation was investigated by dispersive X-ray absorption fine structure.

Validation of Sentinel-5p TROPOMI cloud data with ground-based Cloudnet and other satellite data products

2021 ◽  
Author(s):  
Steven Compernolle ◽  
Athina Argyrouli ◽  
Ronny Lutz ◽  
Maarten Sneep ◽  
Jean-Christopher Lambert ◽  
...  
Keyword(s):  
Major Change ◽  
Recognition Algorithm ◽  
Atmospheric Composition ◽  
Trace Gas ◽  
Oxygen Absorption ◽  
Absorption Bands ◽  
Cloud Data ◽  
Cloud Height ◽  
Data Products ◽  
Retrieval Scheme

<p>Space-born atmospheric composition measurements, like those from Sentinel-5p TROPOMI, are strongly affected by the presence of clouds. Dedicated cloud data products, typically retrieved with the same sensor, are therefore an important tool for the provider of atmospheric trace gas retrievals. Cloud products are used for filtering and modification of the modelled radiative transfer.</p><p>In this work, we assess the quality of the cloud data derived from Copernicus Sentinel-5 Precursor TROPOMI radiance measurements. Three cloud products are considered: (i) L2_CLOUD OCRA/ROCINN CAL (Optical Cloud Recognition Algorithm/Retrieval of Cloud Information using Neural Networks; Clouds-As-Layers), (ii) L2_CLOUD OCRA/ROCINN CRB (same; Clouds-as Reflecting Boundaries), and (iii) the S5p support product FRESCO-S (Fast Retrieval Scheme for Clouds from Oxygen absorption bands for Sentinel). These cloud products are used in the retrieval of several S5p trace gas products (e.g., ozone columns and profile, total and tropospheric nitrogen dioxide, sulfur dioxide, formaldehyde). The quality assessment of these cloud products is carried out within the framework of ESA’s Sentinel-5p Mission Performance Centre (MPC) with support from AO validation projects focusing on the respective atmospheric gases.</p><p>Cloud height data from the three S5p cloud products is compared to radar/lidar based cloud profile information from the ground-based networks CLOUDNET and ARM. The cloud height from S5p CLOUD CRB and S5p FRESCO are on average 0.6 km below the cloud mid-height of CLOUDNET measurements, and the cloud top height from S5p CLOUD CAL is on average 1 km below CLOUDNET’s cloud top height. However, the comparison is different for low and high clouds, with S5p CLOUD CAL cloud top height being only 0.3 km below CLOUDNET’s for low clouds.  The radiometric cloud fraction and cloud (top) height are compared to those of other satellite cloud products like Aura OMI O<sub>2</sub>-O<sub>2</sub>. While the latitudinal variation is often similar, offsets are encountered.</p><p>Recently, major S5p cloud product upgrades were released for S5p OCRA/ROCINN (July 2020) and for S5p FRESCO (December 2020), leading to a decrease of the ROCINN CRB cloud height and an increase of the FRESCO cloud height on average. Moreover, a major change in the ROCINN surface albedo treatment leads to a clear improvement of the comparison with CLOUDNET at the complicated sea/land/ice/snow site Ny-Alesund.</p><div></div>

scholarly journals Atmospheric Correction for Tower-Based Solar-Induced Chlorophyll Fluorescence Observations at O2-A Band

2019 ◽  
Vol 11 (3) ◽  
pp. 355 ◽  
Author(s):  
Xinjie Liu ◽  
Jian Guo ◽  
Jiaochan Hu ◽  
Liangyun Liu
Keyword(s):  
Chlorophyll Fluorescence ◽  
Atmospheric Correction ◽  
Field Measurements ◽  
Correction Method ◽  
Oxygen Absorption ◽  
Atmospheric Transmission ◽  
Absorption Bands ◽  
Transfer Path ◽  
The Difference ◽  
Atmospheric Transmittance

Solar-induced chlorophyll fluorescence (SIF) has been proven to be an efficient indicator of vegetation photosynthesis. To investigate the relationship between SIF and Gross Primary Productivity (GPP), tower-based continuous spectral observations coordinated with eddy covariance (EC) measurements are needed. As the strong absorption effect at the O2-A absorption bands has an obvious influence on SIF retrieval based on the Fraunhofer Line Discrimination (FLD) principle, atmospheric correction is required even for tower-based SIF observations made with a sensor tens of meters above the canopy. In this study, an operational and simple solution for atmospheric correction of tower-based SIF observations at the O2-A band is proposed. The aerosol optical depth (AOD) and radiative transfer path length (RTPL) are found to be the dominant factors influencing the upward and downward transmittances at the oxygen absorption band. Look-up tables (LUTs) are established to estimate the atmosphere transmittance using AOD and RTPL based on the MODerate resolution atmospheric TRANsmission 5 (MODTRAN 5) model simulations, and the AOD is estimated using the ratio of the downwelling irradiance at 790 nm to that at 660 nm (E790/E660). The influences of the temperature and pressure on the atmospheric transmittance are also compensated for using a corrector factor of RTPL based on an empirical equation. A series of field measurements were carried out to evaluate the performance of the atmospheric correction method for tower-based SIF observations. The difference between the SIF retrieved from tower-based and from ground-based observations decreased obviously after the atmospheric correction. The results indicate that the atmospheric correction method based on a LUT is efficient and also necessary for more accurate tower-based SIF retrieval, especially at the O2-A band.

Fine structure of the bands in the low-temperature spectra of sodium uranyl acetate

1982 ◽  
Vol 37 (5) ◽  
pp. 1277-1281 ◽  
Author(s):  
V. N. Boikov ◽  
A. N. Krasovskii ◽  
D. S. Umreiko
Keyword(s):  
Fine Structure ◽  
Low Temperature ◽  
Uranyl Acetate ◽  
Temperature Spectra
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