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Abstract. The automatic and non-supervised detection of the planetary boundary layer height (z PBL ) by means of lidar measurements was widely investigated during the last several years. Despite considerable advances, the experimental detection still presents difficulties such as advected aerosol layers coupled to the planetary boundary layer (PBL) which usually produces an overestimation of the z PBL . To improve the detection of the z PBL in these complex atmospheric situations, we present a new algorithm, called POLARIS (PBL height estimation based on lidar depolarisation). PO-LARIS applies the wavelet covariance transform (WCT) to the range-corrected signal (RCS) and to the perpendicularto-parallel signal ratio (δ) profiles. Different candidates for z PBL are chosen and the selection is done based on the WCT applied to the RCS and δ. We use two ChArMEx (Chemistry-Aerosol Mediterranean Experiment) campaigns with lidar and microwave radiometer (MWR) measurements, conducted in 2012 and 2013, for the POLARIS' adjustment and validation. POLARIS improves the z PBL detection compared to previous methods based on lidar measurements, especially when an aerosol layer is coupled to the PBL. We also compare the z PBL provided by the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model with respect to the z PBL determined with POLARIS and the MWR under Saharan dust events. WRF underestimates the z PBL during daytime but agrees with the MWR during night-time. The z PBL provided by WRF shows a better temporal evolution compared to the MWR during daytime than during night-time.

Solar radiation plays a key role in the atmospheric system but its distribution throughout the atmosphere and at the surface is still very uncertain in atmospheric models, and further assessment is required. In this study, the shortwave downward total solar radiation flux (SWD) predicted by the Weather Research and Forecasting (WRF) Model at the surface is validated over Spain for a 10-yr period based on observations of a network of 52 radiometric stations. In addition to the traditional pointwise validation of modeled data, an original spatially continuous evaluation of the SWD bias is also conducted using a principal component analysis. Overall, WRF overestimates the mean observed SWD by 28.9 W m−2, while the bias of ERA-Interim, which provides initial and boundary conditions to WRF, is only 15.0 W m−2. An important part of the WRF SWD bias seems to be related to a very low cumulus cloud amount in the model and, possibly, a misrepresentation of the radiative impact of this type of cloud.

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