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| Titel |
Uncertainties of parameterized surface downward clear-sky shortwave and all-sky longwave radiation. |
| VerfasserIn |
S. Gubler, S. Gruber, R. S. Purves |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 12, no. 11 ; Nr. 12, no. 11 (2012-06-08), S.5077-5098 |
| Datensatznummer |
250011229
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| Publikation (Nr.) |
 copernicus.org/acp-12-5077-2012.pdf |
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| Zusammenfassung |
As many environmental models rely on simulating the energy balance at the
Earth's surface based on parameterized radiative fluxes, knowledge of the
inherent model uncertainties is important. In this study we evaluate one
parameterization of clear-sky direct, diffuse and global shortwave downward
radiation (SDR) and diverse parameterizations of clear-sky and all-sky
longwave downward radiation (LDR). In a first step, SDR is estimated based on
measured input variables and estimated atmospheric parameters for hourly time
steps during the years 1996 to 2008. Model behaviour is validated using the
high quality measurements of six Alpine Surface Radiation Budget (ASRB)
stations in Switzerland covering different elevations, and measurements of
the Swiss Alpine Climate Radiation Monitoring network (SACRaM) in Payerne. In
a next step, twelve clear-sky LDR parameterizations are calibrated using the
ASRB measurements. One of the best performing parameterizations is elected to
estimate all-sky LDR, where cloud transmissivity is estimated using measured
and modeled global SDR during daytime. In a last step, the performance of
several interpolation methods is evaluated to determine the cloud
transmissivity in the night.
We show that clear-sky direct, diffuse and global SDR is adequately
represented by the model when using measurements of the atmospheric
parameters precipitable water and aerosol content at Payerne. If the
atmospheric parameters are estimated and used as a fix value, the relative
mean bias deviance (MBD) and the relative root mean squared deviance (RMSD)
of the clear-sky global SDR scatter between between −2 and 5%, and 7 and
13% within the six locations. The small errors in clear-sky global SDR can
be attributed to compensating effects of modeled direct and diffuse SDR since
an overestimation of aerosol content in the atmosphere results in
underestimating the direct, but overestimating the diffuse SDR. Calibration
of LDR parameterizations to local conditions reduces MBD and RMSD strongly
compared to using the published values of the parameters, resulting in
relative MBD and RMSD of less than 5% respectively 10% for the best
parameterizations. The best results to estimate cloud transmissivity during
nighttime were obtained by linearly interpolating the average of the cloud
transmissivity of the four hours of the preceeding afternoon and the
following morning.
Model uncertainty can be caused by different errors such as code
implementation, errors in input data and in estimated parameters, etc. The
influence of the latter (errors in input data and model parameter
uncertainty) on model outputs is determined using Monte Carlo. Model
uncertainty is provided as the relative standard deviation
σrel of the simulated frequency distributions of the model
outputs. An optimistic estimate of the relative uncertainty
σrel resulted in 10% for the clear-sky direct, 30%
for diffuse, 3% for global SDR, and 3% for the fitted all-sky LDR. |
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