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This study proposes dynamical downscaling simulations-high resolution of 12 km- by Weather Research and Forecasting (WRF) model, over the Arabian Peninsula. The downscaling of the Community Climate System Model (CCSM), to simulate (2000–2010), and future (2050–2060) time periods. The Arabian Peninsula is experiencing extreme weather events characterized by large precipitation and above average summer maximum temperatures, which are strong indicators of the climate change impact in the region. The CCSM-WRF model values were evaluated against values obtained by the Center for Climate Integrity (CCI) on a monthly basis, and during extreme weather events 10 years’ period (2000-2010). The CCSM-WRF results at 12 km are comparable with published outcomes of high-resolution regional climate models, and shows better performance especially during the extreme events over the region (flash floods and heat waves). The future projection of the model shows that the maximum summer average values of temperature, soil temperature, and soil moisture, will increase in the next 30 to 40 years.

Remote sensing has been a key resource for developing extensive and detailed datasets for studying and constraining aerosol-cloud-climate interactions. However, aerosol-cloud collocation challenges, algorithm limitations, as well as difficulties in unraveling dynamic from aerosol-related effects on cloud microphysics, have long challenged precise retrievals of cloud droplet number concentrations. By combining a series of remote sensing techniques and in situ measurements at ground level, we developed a semi-automated approach that can address several retrieval issues for a robust estimation of cloud droplet number for non-precipitating Planetary Boundary Layer (PBL) clouds. The approach is based on satellite retrievals of the PBL cloud droplet number (Ndsat) using the geostationary meteorological satellite data of the Optimal Cloud Analysis (OCA) product, which is obtained by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The parameters of the retrieval are optimized through closure with droplet number obtained from a combination of ground-based remote sensing data and in situ observations at ground level. More specifically, the remote sensing data are used to retrieve cloud-scale vertical velocity, and the in situ aerosol measurements at ground level were used constrain as input to a state-of-the-art droplet activation parameterization to predict the respective Cloud Condensation Nuclei (CCN) spectra, cloud maximum supersaturation and droplet number concentration (Nd), accounting for the effects of vertical velocity distribution and lateral entrainment. Closure studies between collocated Nd and Ndsat are then used to evaluate exising droplet spectral width parameters used for the retrieval of droplet number, and determine the optimal values for retrieval. This methodology, used to study aerosol-cloud interactions for non-precipitating clouds formed over the Athens Metropolitan Area (AMA), Greece from March to May 2020, shows that droplet closure can be achieved to within 30%, comparable to the level of closure obtained in many in situ studies. Given this, the ease of applying this approach with satellite data obtained from SEVIRI with high temporal (15 min) and spatial resolution (3.6 km × 4.6 km), opens the possibility of continuous and reliable Ndsat, giving rise to high value datasets for aerosol-cloud-climate interaction studies.

In this study we estimate the particle extinction profiles at Finokalia, Crete, using only the information provided by the elastic and polarization channels of a PollyXT lidar system. Most of the time Finokalia site is affected by only two aerosol types, i.e. marine and dust particles. These two aerosol types, having different optical properties, permit the separation of aerosol mixture. The proposed method uses the particle backscatter profiles at 532 nm and the vertically resolved particle linear depolarization ratio measurements at the same wavelength. The particle linear depolarization ratio and the lidar ratio values of pure aerosol types are taken from literature. The total extinction profile is then estimated and compared well with Raman retrievals. Any difference between the proposed methodology and Raman extinction profiles indicates that the non-dust component could be probably attributed to polluted marine or polluted continental aerosols. Comparison with sun-photometric aerosol optical depth observations is performed as well during daytime with reasonable differences between the two instruments. Differences in the total aerosol optical depth is attributed to the limited ability of the lidar to correctly represent the aerosol optical properties in the near range due to overlap problem.

Particle depolarization ratio retrieved from lidar measurements are commonly used for aerosol typing studies, microphysical inversion, or mass concentration retrievals. The particle depolarization ratio is one of the primary parameters that can differentiate several major aerosol components, but only if the measurements are accurate enough. The uncertainties related to the retrieval of particle depolarization ratios are the main factor in determining the accuracy of the derived parameters in such studies. This paper presents different depolarization calibration procedures used to improve the quality of the depolarization data. The results illustrate a significant improvement of the depolarization lidar products for all the selected lidar stations that had implemented depolarization calibration procedures. The calibrated volume and particle depolarization profiles at 532 nm show values that fall within a range of values that are generally accepted in the literature.