Use of hyperspectral infrared radiances to infer atmospheric trace gases

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Hyperspectral infrared instruments operating in nadir (AIRS, IASI, TANSO-FTS, CrIS, IASI-NG) or limb (MIPAS, ACE-FTS) viewing modes provide high-resolution atmospheric spectra from which it is possible to retrieve information on many geophysical variables during both day and night. In particular, such instruments allow the simultaneous measurements of a series of atmospheric trace gases (e.g., H2O, CO2, O3, N2O, CO, CH4, CFCs, SO2, NO3, etc.) that can be divided into greenhouse gases and chemical reactive gases. Retrieving gas concentration from infrared observations relies on forward radiative transfer computation, using spectroscopic knowledge on atmospheric species, and inverse approaches, which are based on minimization schemes optimized for the instrument and the targeted species. The accuracy and vertical information achievable for a given species depends on the strength of its spectral signature and on the spectral and radiometric characteristics of the instrument. Probing the atmospheric boundary layer also requires high thermal contrast between the ground and the first atmospheric layers. Confined for many years to the study of meteorological variables, instruments operating in the thermal infrared are now a central part of atmospheric composition and climate studies.

Original languageEnglish
Title of host publicationComprehensive Remote Sensing
PublisherElsevier
Pages345-387
Number of pages43
Volume1-9
ISBN (Electronic)9780128032206
ISBN (Print)9780128032213
DOIs
Publication statusPublished - 1 Jan 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Atmospheric sounding
  • Gas retrieval
  • Greenhouse gases
  • Hyperspectral infrared observations
  • Line parameters and shapes
  • Nadir and limb viewing infrared spectrometers
  • Neural network
  • Physical retrieval
  • Radiative transfer model
  • Reactive gases
  • Trace gases
  • Vertical sensitivity of infrared observations

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