Statistics – Computation
Scientific paper
Sep 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009jgrd..11418107v&link_type=abstract
Journal of Geophysical Research, Volume 114, Issue D18, CiteID D18107
Statistics
Computation
1
Global Change: Atmosphere (0315, 0325), Atmospheric Composition And Structure: Radiation: Transmission And Scattering, Computational Geophysics: Model Verification And Validation
Scientific paper
Downward atmospheric longwave radiation (DLR) is an important component of the terrestrial energy budget, strongly related with the greenhouse effect and therefore remarkably affecting the climate. In this study, DLR at the surface has been calculated using a one-dimensional radiative transfer model, Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART). A sensitivity study has been performed in order to assess the influence of several variables on DLR levels for cloudless conditions. Among these variables, the atmospheric profiles of temperature and water content have been confirmed as the most important. Calculations have been compared with measurements made with pyrgeometers. The study has been applied to data from two European stations, Payerne (Switzerland) and Girona (Spain). For the Payerne case, for which radio soundings were available, calculations show differences with measurements in the range -2.7 ± 3.4 W m-2. For Girona, where no in situ radio soundings are available, soundings taken about 90 km away and atmospheric profiles from a gridded analysis (European Centre for Medium-Range Weather Forecasts (ECMWF)) were used along with the meteorological information at screen level. In the latter case, differences between modeling and measurements were about 0.3 ± 9.4 W m-2. From our results, it is found that radiative transfer modeling of DLR can produce results that agree with measurements reasonably well even if no in situ radio soundings are available; the use of profiles from the ECMWF analyses does not greatly increase the bias, while the dispersion of differences is only slightly larger than the uncertainty of the measurements. It has also been confirmed that radiative transfer modeling produces better results than previously published simple parameterizations based only on surface measurements.
Calbo Josep
Gonzalez Jose A.
Jimenez M. A.
Viúdez-Mora A.
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