On the ability of RegCM4 regional climate model to simulate surface solar radiation patterns over Europe: an assessment using satellite-based observations

Abstract

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 (2000–2009) 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.

The MSG-SEVIRI-based cloud property data record CLAAS-2

“…The first edition of this data record (CLAAS-1) is described in Stengel et al (2014). This dataset has been used to study the diurnal cycle of clouds (e.g., Martins et al, 2016;Pfeifroth et al, 2016) and for model evaluation (e.g., Brisson et al, 2016;Alexandri et al, 2015). Recently a second reprocessed edition was released (CLAAS-2, Finkensieper et al, 2016) based on updated retrieval algorithms and incorporating measurements from MSG-1, 2 and 3 satellites every 15 min, thus extending the time period covered (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) and increasing the temporal resolution.…”

Simulation of Optical Properties and Direct and Indirect Radiative Effects of Smoke Aerosols Over Marine Stratocumulus Clouds During Summer 2008 in California With the Regional Climate Model RegCM

“…In a second step, CDNC is used to calculate the cloud droplet effective radius (CER) through the following relation: where L is the cloud water content, ρ w is the density of water, and k is the cube of the ratio of the mean volume radius and the effective radius of the cloud droplet spectrum, which is assumed to be equal to 0.67 over continent and 0.80 over ocean (Martin et al, ). In the current version and in the absence of anthropogenic sulfate particles, CER is fixed to the value of 10 μm over oceans, typical of clouds determined by a background cloud condensation nuclei (CCN) population (Briegleb, ), while over land it is given as a function of temperature (Alexandri et al, ). The radiative properties of liquid clouds, in the shortwave spectral region, are given by the following parameterizations (Briegleb, ): where λ denotes the spectral interval and CWP the cloud water path.…”

A Lookup-Table-Based Approach to Estimating Surface Solar Irradiance from Geostationary and Polar-Orbiting Satellite Data

“…SSI estimation under cloudy skies is much more complex compared to clear-sky models. The performance of physical SSI models under cloudy skies is largely dominated by cloud macrophysical and microphysical properties, such as cloud fractional cover (CFC), cloud optical thickness (COT), and cloud effective particle radius (ER) with high variability in space and time [30,31]. The Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites provides detailed and consistent atmospheric, terrestrial, and oceanic products, and studies have been developed for SSI mapping from pairs of MODIS products [2,32].…”