Mean radiation fluxes in the near-IR spectral range: Algorithms for calculation
Autor: | T.B. Zhuravleva, V.E. Zuev, G.A. Titov |
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Rok vydání: | 1997 |
Předmět: |
Physics
Atmospheric Science Spectral flux Ecology Computation Monte Carlo method Paleontology Soil Science Forestry Aquatic Science Oceanography Geophysics Atmosphere of Earth Orders of magnitude (time) Space and Planetary Science Geochemistry and Petrology Earth and Planetary Sciences (miscellaneous) Range (statistics) Shortwave radiation Spectral resolution Algorithm Earth-Surface Processes Water Science and Technology |
Zdroj: | Journal of Geophysical Research: Atmospheres. 102:1819-1832 |
ISSN: | 0148-0227 |
DOI: | 10.1029/96jd02218 |
Popis: | Algorithms are presented to compute the mean fluxes of shortwave radiation, modulated by statistically homogeneous broken clouds, in the near-IR spectral range (0.7–3.2 μm). One method of the mean spectral flux computation consists of dividing the spectral interval in question into Nint subintervals according to the spectral resolution specified. The mean spectral fluxes are then calculated with the Monte Carlo method by assuming constant cloud optical characteristics within each subinterval. This last method (algorithm 1) accurately accounts for the spectral behavior of optical characteristics of clouds and atmospheric gases and can therefore be regarded as a reference. The mean spectral flux computations of high spectral resolution (say, Δν = 10–20 cm−1 ) may require several hundreds of spectral intervals. Therefore the method of dependent tests (algorithm 2) is proposed, which effectively uses notable features of the spectral dependence of cloud optical parameters, thus allowing significant simplifications and extra savings of computer time. Comparison of results from algorithms 1 and 2 shows that the mean radiant fluxes agree to within the relative computation error (3%). This indicates that algorithm 2 is reasonably accurate; in addition, its efficiency is several orders of magnitude better than that of the reference algorithm 1. |
Databáze: | OpenAIRE |
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