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Abstract:
In this work, we assess the ability of RegCM4 regional climate model to
simulate surface solar radiation (SSR) patterns over Europe. A decadal
RegCM4 run (20002009) was implemented and evaluated against
satellite-based observations from the Satellite Application Facility on
Climate Monitoring (CM SAF), showing that the model simulates adequately
the SSR patterns over the region. The SSR bias between RegCM4 and CM SAF
is + 1.5% for MFG (Meteosat First Generation) and + 3.3% for MSG
(Meteosat Second Generation) observations. The relative contribution of
parameters that determine the transmission of solar radiation within the
atmosphere to the deviation appearing between RegCM4 and CM SAF SSR is
also examined. Cloud macrophysical and microphysical properties such as
cloud fractional cover (CFC), cloud optical thickness (COT) and cloud
effective radius (Re) from RegCM4 are evaluated against data from CM
SAF. Generally, RegCM4 underestimates CFC by 24.3% and Re for liquid/ice
clouds by 36.1 %/28.3% and overestimates COT by 4.3 %. The same
procedure is repeated for aerosol optical properties such as aerosol
optical depth (AOD), asymmetry factor (ASY) and single-scattering albedo
(SSA), as well as other parameters, including surface broadband albedo
(ALB) and water vapor amount (WV), using data from MACv1 aerosol
climatology, from CERES satellite sensors and from ERA-Interim
reanalysis. It is shown here that the good agreement between RegCM4 and
satellite-based SSR observations can be partially attributed to
counteracting effects among the above mentioned parameters. The
potential contribution of each parameter to the RegCM4-CM SAF SSR
deviations is estimated with the combined use of the aforementioned data
and a radiative transfer model (SBDART). CFC, COT and AOD are the major
determinants of these deviations on a monthly basis; however, the other
parameters also play an important role for specific regions and seasons.
Overall, for the European domain, CFC, COT and AOD are the most
important factors, since their underestimations and overestimations by
RegCM4 cause an annual RegCM4-CM SAF SSR absolute deviation of 8.4, 3.8
and 4.5 %, respectively.