Journal
JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER
Volume 234, Issue -, Pages 55-63Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jqsrt.2019.04.031
Keywords
HITRAN database; Influence; Line by line; Climate model; Heating rate and flux; Remote sensing; Brightness temperature
Categories
Funding
- National Key R&D Program of China [2018YFC1507002]
- National Natural Science Foundation of China [41675003, 4165056]
- Alexander von Humboldt Foundation
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The high-resolution transmission (HITRAN) database has been updated recently. Therefore, it is useful to analyze the effect of the updated data on radiative transfer calculations. This study identifies the impact of database updates that could affect climate models and satellite remote sensing applications. The fluxes and cooling rates of the longwave region are calculated by the line-by-line radiative transfer model based on the HITRAN08, HITRAN12 and HITRAN16 molecule spectroscopic databases under four typical atmospheric profiles. We show that the differences in cooling rates are mainly caused by the changes in the line parameters of H2O and CO2. The maximum difference in the upward fluxes at the top of the atmosphere between HITRAN08 and HITRAN16 is 0.6587 W m(-2), whereas that between HITRAN12 and HITRAN16 is only 0.0406 W m(-2), which is much smaller than the maximum difference between HITRAN08 and HITRAN16. Similar trends are also observed in the downward fluxes at the surface and cooling rates. Overall these differences are all less than the typical errors of radiative transfer schemes. On the contrary, we show that there are differences between the simulated brightness temperatures for the channels of hyperspectral measurements, such as FY-3D Hyperspectral Infrared Atmospheric Sounder (HIRAS), which are at least comparable to the noise equivalent temperature difference (NETD) of the corresponding channels. Therefore, it is necessary to consider the effect of using different HITRAN molecular spectroscopic databases in hyperspectral satellite remote sensing applications. (C) 2019 Published by Elsevier Ltd.
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