The Earth’s Clear-Sky Radiation Budget and Water Vapor Absorption in the Far Infrared

• Published in: Journal of climate Vol. 10; no. 7; pp. 1601 - 1614
• Main Authors: Sinha, Ashok, Harries, John E.
• Format: Journal Article
• Language: English
• Published: Boston, MA American Meteorological Society 01-07-1997
• Subjects: Atmospherics; Cooling; Earth, ocean, space; Exact sciences and technology; External geophysics; Far infrared radiation; Humidity; Meteorology; Rotation; Temperature dependence; Troposphere; Vapors; Water in the atmosphere (humidity, clouds, evaporation, precipitation); Water temperature; Water vapor; Water; Long wave; Clear sky; Simulation; Seasonal variation; Radiation balance; Vapors; Infrared absorption; Atmospheric radiation; Geographical variation
• ISSN: 0894-8755; 1520-0442
• DOI: 10.1175/1520-0442(1997)010<1601:TESCSR>2.0.CO;2

Detailed observational data are used to simulate the sensitivity of clear-sky outgoing longwave radiation (OLR) to water vapor perturbations in order to investigate the effect of uncertainties in water vapor measurements and spectroscopic parameters. Seasonal, geographical, and spectral variations in the clear-sky OLR, and of zonal mean clear-sky atmospheric cooling rate profiles are calculated for this purpose. Outside of deep convective regions, when only water vapor is varied, it is found that the 20–30-μm waveband of the far infrared (FIR) is the most substantial influence on the clear-sky OLR change. By contrast, the largest contribution to the clearsky OLR variation in deep convective areas is from the continuum. Similarly, seasonal clear-sky infrared cooling rates are largely determined by contributions from the FIR and continuum, with a systematic variation in these contributions with latitude and altitude. The results presented reinforce the conclusions of recent studies that the lack of validation of FIR model line parameters under atmospheric conditions may have serious implications for the accuracy of simulations of clear-sky OLR variability. FIR parameterizations in climate models should be therefore validated by observational programs.