The daily (24 h) averages of the aerosol radiative forcing (ARF) at the surface and the top of the atmosphere (TOA) were calculated during desert dust events over Granada (southeastern Spain) from 2005 to 2010. A radiative transfer model (SBDART) was utilized to simulate the solar irradiance values (0.31–2.8 μm) at the surface and TOA, using as input aerosol properties retrieved from CIMEL sun photometer measurements via an inversion methodology that uses the sky radiance measurements in principal plane configuration and a spheroid particle shape approximation. This inversion methodology was checked by means of simulated data from aerosol models, and the derived aerosol properties were satisfactorily compared against well-known AERONET products. Good agreement was found over a common spectral interval (0.2–4.0 μm) between the simulated SBDART global irradiances at surface and those provided by AERONET. In addition, simulated SBDART solar global irradiances at the surface have been successfully validated against CM-11 pyranometer measurements. The comparison indicates that the radiative transfer model slightly overestimates (mean bias of 3%) the experimental solar global irradiance. These results show that the aerosol optical properties used to estimate ARF represent appropriately the aerosol properties observed during desert dust outbreak over the study area. The ARF mean monthly values computed during desert dust events ranged from −13 ± 8 W m⁻² to −34 ± 15 W m⁻² at surface, from −4 ± 3 W m⁻² to −13 ± 7 W m⁻² at TOA and from +6 ± 4 to +21 ± 12 W m⁻² in the atmosphere. We have checked if the differences found in aerosol optical properties among desert dust sectors translate to differences in ARF. The mean ARF at surface (TOA) were −20 ± 12 (−5 ± 5) W m⁻², −21 ± 9 (−7 ± 5) W m⁻² and −18 ± 9 (−6 ± 5) W m⁻² for sector A (northern Morocco; northwestern Algeria), sector B (western Sahara, northwestern Mauritania and southwestern Algeria), and sector C (eastern Algeria, Tunisia), respectively. The Kolmogorov-Smirnov statistical test revealed that daily {ARF} values at TOA for sector A were significantly different from the other two sectors, likely as a result of the lower values of single scattering albedo obtained for sector A. The mean values of aerosol radiative forcing efficiency at surface (TOA) were −74 ± 12 W m⁻² (−17 ± 7 W m⁻²) for sector A, −70 ± 14 W m⁻² (−20 ± 9 W m⁻²) for sector B, and −65 ± 16 W m⁻² (−22 ± 10 W m⁻²) for sector C, and thus comparable between the three sectors in all seasons.

This article focuses on the comparison of the total ozone column data from the Ozone Monitoring Instrument (OMI) flying aboard the NASA EOS‐Aura satellite platform with ground‐based measurement recorded by Brewer spectroradiometers located at five Spanish remote sensing ground stations between January 2005 and December 2007. The satellite data are derived from two algorithms: OMI Total Ozone Mapping Spectrometer (OMI‐TOMS) and OMI Differential Optical Absorption Spectroscopy (OMI‐DOAS). The largest relative differences between these OMI total ozone column estimates reach 5% with a significant seasonal dependence. The agreement between OMI ozone data and Brewer measurements is excellent. Total ozone columns from OMI‐TOMS are on average a mere 2.0% lower than Brewer data. For OMI‐DOAS data the bias is a mere 1.4%. However, the relative difference between OMI‐TOMS and Brewer measurements shows a notably lower seasonal dependence and variability than the differences between OMI‐DOAS and ground‐based data. For both OMI ozone data products these relative differences show significant dependence on the satellite ground pixel solar zenith angle for cloud‐free cases as well as for cloudy conditions. However, the OMI ozone data products are shown to reveal opposite behavior with respect to the two antagonistic sky conditions. No significant dependency of the ground‐based to satellite‐based differences with respect to the satellite cross‐track position is seen for either OMI retrieval algorithm.

The main goal of this study is to analyze the dependence of columnar aerosol optical and microphysical properties on source region and transport pathways during desert dust intrusions over Granada (Spain) from January 2005 to December 2010. Columnar aerosol properties have been derived from a non‐spherical inversion code using the solar extinction measurements and sky radiances in the principal plane. Two classification methods of the African air masses ending at the study location were used by means of the HYSPLIT back‐trajectories analysis. The first one, based on desert dust origin sources, discriminated the optical properties only for sector B (corresponding to western Sahara, northwest Mauritania and southwest Algeria). The particles present marked absorbing properties (low value of single scattering albedo at all wavelengths) during the desert dust events when the air masses were transported from sector A (north Morocco, northwest Algeria). This result may be related to the mixing of desert dust with anthropogenic pollutants from North African industrial areas in addition to the mixing with local anthropogenic aerosol and pollutants transported from European and Mediterranean areas. The second classification method was based on a statistics technique called cluster classification which allows grouping the air masses back trajectories with similar speed and direction of the trajectory. This method showed slight differences in the optical properties between the several transport pathways of air masses. High values of the aerosol optical depth and low mean values of the Angström parameter were associated with longer transport pathways over desert dust sources and slowly moving air masses. Both classification methods showed that the fine mode was mixed with coarse mode, being the fine mode fraction smaller than 55%.

After 30 years since the beginning of the Global Positioning System (GPS), or, more generally, Global Navigation Satellite System (GNSS) meteorology, this technique has proven to be a reliable method for retrieving atmospheric water vapor; it is low-cost, weather independent, with high temporal resolution and is highly accurate and precise. GNSS ground-based networks are becoming denser, and the first stations installed have now quite long time-series that allow the study of the temporal features of water vapor and its relevant role inside the climate system. In this review, the different GNSS methodologies to retrieve atmospheric water vapor content re-examined, such as tomography, conversion of GNSS tropospheric delay to water vapor estimates, analyses of errors, and combinations of GNSS with other sources to enhance water vapor information. Moreover, the use of these data in different kinds of studies is discussed. For instance, the GNSS technique is commonly used as a reference tool for validating other water vapor products (e.g., radiosounding, radiometers onboard satellite platforms or ground-based instruments). Additionally, GNSS retrievals are largely used in order to determine the high spatio-temporal variability and long-term trends of atmospheric water vapor or in models with the goal of determining its notable influence on the climate system (e.g., assimilation in numerical prediction, as input to radiative transfer models, study of circulation patterns, etc.).

This paper proposes a method to obtain spectral sky radiances, at three wavelengths (464, 534 and 626 nm), from hemispherical sky images. Images are registered with the All-Sky Imager installed at the Andalusian Center for Environmental Research (CEAMA) in Granada (Spain). The methodology followed in this work for the absolute calibration in radiance of this instrument is based on the comparison of its output measurements with modelled sky radiances derived from the LibRadtran/UVSPEC radiative transfer code under cloud-free conditions. Previously, in order to check the goodness of the simulated radiances, these are compared with experimental values recorded by a CIMEL sunphotometer. In general, modelled radiances are in agreement with experimental data, showing mean differences lower than 20% except for the pixels located next to the Sun position that show larger errors. The relationship between the output signal of the All-Sky Imager and the modelled sky radiances provides a calibration matrix for each image. The variability of the matrix coefficients is analyzed, showing no significant changes along a period of 5 months. Therefore, a unique calibration matrix per channel is obtained for all selected images (a total of 705 images per channel). Camera radiances are compared with CIMEL radiances, finding mean absolute differences between 2% and 15% except for pixels near to the Sun and high scattering angles. We apply these calibration matrices to three images in order to study the sky radiance distributions for three different sky conditions: cloudless, overcast and partially cloudy. Horizon brightening under cloudless conditions has been observed together with the enhancement effect of individual clouds on sky radiance.