Aerosol particles are major drivers of the Earth shortwave radiation budget, which they affect directly (through scattering and absorption) and indirectly (through modification of cloud scattering and precipitation properties), while they semi-directly influence atmospheric stability and convection, mainly through modification of solar radiation absorption by the atmosphere. Despite the important climatic role of aerosols, large uncertainties in their radiative effects remain due to limited knowledge of the aerosol spatio-temporal distribution and physico-chemical properties. The interaction of aerosols with radiation is strongly dependent on their optical properties, which in turn are controlled by the particles size distribution, shape, chemical composition, and mixing state. In order to accurately estimate the magnitude of the aerosol direct radiative effect (DRE), detailed knowledge of their optical properties, at high spatial and temporal resolution, is required.

The European continent is a region of particular interest for studying atmospheric aerosol effects because of the presence of numerous and varying sources of particulate matter such as industries, large urban centers and biomass burning, especially when combined with high levels of solar insolation during summer.

The aerosol DRE over Europe is examined using the FORTH deterministic spectral radiative transfer model (RTM) and aerosol data from chemical transport models. Chemically and size-resolved aerosol concentrations predicted by the transport models are combined with a Mie model to calculate key aerosol optical properties (i.e. vertically resolved aerosol optical depth, single scattering albedo, and asymmetry parameter) that are necessary to compute aerosol DRE. The Mie model takes into account concentrations of organics, black carbon, sulfate, nitrate, ammonium, chlorine, sodium, water, and crustal material, and calculates aerosol optical properties assuming that the aerosol particles of the same size are internally mixed.

The DRE is estimated at the Earth’s surface, within the atmospheric column and at the top of the atmosphere (TOA), at high spatial and temporal resolution (36 x 36 km grids, 27 vertical layers, hourly). Initial modelling results reveal that DREs exhibit significant spatio-temporal variability, due to the heterogeneity of source emissions rates, mostly with regard to wildfires, and the varying synoptic conditions. Emphasis is thus given to biomass burning aerosols, which are among the most significant radiative forcing agents.

Clouds are of high importance for the climate system but they still remain a principal uncertainty. Remote sensing techniques applied to satellite observations have assisted tremendously in the creation of long-term and homogeneous data records; however, satellite data sets need to be validated and compared with other data records, especially ground measurements.

The spatiotemporal distribution and variability of Total Cloud Cover (TCC) from the Satellite Application Facility on Climate Monitoring (CM SAF) Cloud, Albedo and Surface Radiation dataset from AVHRR data-edition 2 (CLARA-A2) and the International Satellite Cloud Climatology Project H-series (ISCCP-H) is analyzed over Europe. The CLARA-A2 data record has been created using measurements of the Advanced Very High Resolution Radiometer (AVHRR) instrument onboard the polar orbiting NOAA and the EUMETSAT MetOp satellites, whereas the ISCCP-H data were produced by a combination of measurements from geostationary meteorological satellites and the AVHRR instrument on the polar orbiting satellites.

An inter-comparison of the two data records is performed over their common period, 1984 to 2012. In addition, a comparison of the two satellite data records is made against TCC observations at 22 meteorological stations in Europe, from the European Climate Assessment & Dataset (ECA&D). The results indicate generally larger ISCCP-H TCC with respect to the corresponding CLARA-A2 data, in particular in the Mediterranean. Compared to ECA&D data, both satellite datasets reveal a reasonable performance, with overall mean TCC biases of 2.1% and 5.2% for CLARA-A2 and ISCCP-H, respectively. This, along with the higher correlation coefficients between CLARA-A2 and ECA&D TCC, indicates the better performance of CLARA-A2 TCC data.

Surface solar radiation (SSR) is a major component of the Earth’s radiation and energy budget, driving various physical, chemical and biological processes, and creating climatic conditions that are essential for life. Knowledge of SSR and understanding of its spatial and temporal variability are of great importance. However, the determination of SSR, especially at large spatial scales, and with high accuracy, is difficult, because of the scarcity of available surface measurements, especially in remote and inaccessible areas. Hence, alternative solutions are sought. One of the most attractive and efficient is the use of radiation transfer models (RTMs), which simulate the transfer of solar radiation within the Earth-Atmosphere system and estimate SSR under both clear and cloudy-sky conditions.

When combined with satellite input data, RTM SSR computations offer the advantage of extended/complete spatial coverage. The operation of RTMs depends on the availability of input data that describe realistically the conditions of surface and atmosphere, including gases, aerosols, and clouds. The quality of RTM input data determines the accuracy of the SSR fluxes, which need to be evaluated against reference fluxes.

The detailed FORTH spectral radiation transfer model (Hatzianastassiou et al. 2005; Vardavas and Taylor 2011) is used along with MODIS satellite input data to estimate SSR on the Italian island of Lampedusa (35.5North, 12.6East), in the Mediterranean, over the period 2001-2015. The computations are made using daily instantaneous MODIS-Terra Level-2 data for aerosol, cloud and other atmospheric and surface properties, at 10 x 10 km and 5 x 5 km, as well as surface albedo data derived from 1-km MODIS MCD43B3 products.

The RTM SSR is compared to local SSR measurements taken by calibrated pyranometers installed at the ENEA Station for Climate Observations in Lampedusa. The comparisons are made separately under cloud-free and all-sky conditions, in order to assess the performance of the RTM and MODIS input data, in the presence or absence of clouds, which are the primary modulators of the SSR.

MODIS cloud data are derived by improved retrieval algorithms but there is still uncertainty associated with them. Thus, in an effort to assess their quality and the possible associated uncertainties of the computed SSR fluxes, cloud cover (CC) and cloud optical thickness (COT) data obtained by empirical algorithms, applied to local SSR measurements, are also introduced into the RTM.

Long-term global databases of aerosol optical properties are very useful for the quantification of the aerosol effects and allow the investigation of their interannual trends. Such data have been made available through Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). In MERRA-2, meteorological and aerosol observations are assimilated into a global assimilation system. MERRA-2 provide aerosol properties for five main aerosol types (desert dust, sea salt, sulfate, organic and black carbon particles), enabling the opportunity to separately investigate the spatio-temporal distribution and the radiative effects of aerosols of different type and origin.

MERRA-2 reanalysis data and the FORTH deterministic spectral radiation transfer model (RTM) (Hatzianastassiou et al. 2007) are used to investigate the spatio-temporal distribution of the Direct Radiative Effect (DRE) for each aerosol type, on a monthly, global scale, during the period 1980-2019, with emphasis on their vertical profiles. In order to be able to make such computations, both vertically and spectrally resolved aerosol optical properties (Aerosol Optical Depth or AOD, Single Scattering Albedo or SSA, and asymmetry parameter or g) are required. However, MERRA-2 does not provide directly such data. Thus, as a first step, we build a spectral 4-D database of MERRA-2 based aerosol optical properties. For this purpose, we use 3-hourly vertically resolved instantaneous aerosol mixing ratios and relative humidity data (both included in the MERRA-2 reanalysis and provided in 72 vertical atmospheric layers) and look-up tables providing the scattering and absorption efficiencies per aerosol type, size bin, relative humidity, and wavelength. Apart from aerosols, all remaining RTM input data (such as cloud optical properties and surface albedo) are also taken from MERRA-2.

We focus on the spatio-temporal distribution, the vertical profile and the spectral variation of the MERRA-2 based AOD, SSA and g, for desert dust, sea salt, sulfate, organic and black carbon particles, as well as for the total aerosol load. We also provide RTM results of DRE for the five main aerosol types.

Nikolaos Hatzianastassiou¹, Christos Matsoukas², Nikolaos Benas⁶, Paul Stackhouse Jr.⁷, Jan Fokke Meirink⁶, Alcide Giorgio di Sarra⁹, Arlindo M. Da Silva⁴, Antonis Gkikas³, Marios-Bruno Korras-Carraca^1,2, Stavros Dafis⁸, Maria Gavrouzou¹, Konstantinos Tsioumitas¹, Giandomenico Pace⁹, Daniela Meloni⁹, Ilias Vardavas⁵

Affiliations
¹ Laboratory of Meteorology, Department of Physics, University of Ioannina, Ioannina, Greece
² Department of Environment, University of the Aegean, Mytilene, Greece
³ Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing (IAASARS), National Observatory of Athens, Athens, Greece
⁴ NASA/GSFC, Greenbelt, MD, USA
⁵ Department of Physics, University of Crete, Heraklion, Crete, Greece
⁶ R & D Satellite Observations Department, Royal Netherlands Meteorological Institute (KNMI), The Netherlands
⁷ Science Directorate/Climate Science Branch, NASA Langley Research Center, Hampton, VA, USA
⁸ Institute for Environmental Research and Sustainable Development, National Observatory of Athens, Athens, Greece
⁹ ENEA, Laboratory for Observations and Analyses of Earth and Climate, Rome, Italy