We investigated the liquid water path and global solar irradiance at ground (Q) according to the ICON model, CLOUDNET measurements in Lindenberg, Munich, Jülich, and BSRN observations in Lindenberg. The liquid water path is underestimated, while global irradiance is overestimated. The lower liquid water path is due to liquid water content underestimation practically in all atmosphere layers and lower frequency of liquid clouds occurrence compare to observations. The latter is partly associated with a reduced model’ sensitivity to the cloud condensation nuclei (CCN). An increase in CCN from 250 cm-3 (typical background value for the region of interest) to 1700 cm-3 (characteristic of polluted continental clouds) leads to an increase in grid-scale liquid water path by 40% and a decrease in Q under overcast conditions by 12%. However, we also showed that liquid water path is not a key factor of Q overestimation. The main factor is an inaccurate description of the cloud spatial structure, where the correct prediction of the direct to global irradiance ratio as a spatial characteristic of clouds plays the most important role compared to standard cloud fraction.

Quality control (QC) may be a lengthy and tedious process. As a result, most data users use data from meteorological services without performing data quality checks. The South African Weather Service (SAWS) re-established the national solar radiometric network comprising of 13 new stations within the six climatic zones of the country. This study reports on the performance results of the Baseline Surface Radiation Network (BSRN) QC procedures applied to the solar radiation data within the SAWS radiometric network. The overall percentage performance of the SAWS solar radiation network based on BSRN QC methodology is 97.79%, 93.64%, 91.6% and 92.23% for Long Wave Downward Irradiance (LWD), Global Horizontal Irradiance (GHI), Diffuse Horizontal Irradiance (DHI) and Direct Normal Irradiance (DNI) respectively with operational problems largely dominating the percentage of bad data. The overall average performance of the Surface Solar Radiation Dataset – Heliosat (SARAH) data records for the GHI estimation for all the stations showed a Mean Bias Deviation (MBD) of -8.28 Wm^-2, a Mean Absolute Deviation (MAD) of 9.06 Wm^-2 and the Root Mean Square Deviation (RMSD) of 11.02 Wm^-2. The correlation (quantified by R²) between ground-based and SARAH-derived GHI time series was ~ 0.98. The established network has the potential of providing high quality minute solar radiation data sets (GHI, DHI, DNI and LWD) and auxiliary hourly meteorological parameters vital for scientific and practical applications in renewable energy technologies in South Africa.

The study conducts a comparative analysis of solar radiation estimation methods, assessing the efficacy of the Heliosat-2 algorithm against ground measurements across seven distinct countries: Netherlands, Spain, Japan, Namibia, South Africa, Saudi Arabia, and India. To achieve this, it utilizes two distinct satellite data sources—Himawari-8 for Japan and Metosat Second Generation-MSG for the rest of the countries—spanning the years Jan 2022 to April 2024. A robust methodology for determining albedo parameters specific to Heliosat-2 was developed. During cloudy days, the estimates provided by Heliosat-2 generally exceeded the ground measurements in all the countries. Conversely, on clear days, there was a tendency for underestimation, as indicated by the median value of the mean bias (MB) across most of the countries. The Heliosat-2 model slightly underestimates daily radiation values, with a median MB ranging from −27.5 to +10.2 W.m⁻². Notably, the median root mean squared error (RMSE) on clear days is significantly lower, with values ranging from 24.8 to 108.7 W.m⁻², compared to cloudy days where RMSE values lie between 75.3 and 180.2 W.m⁻². In terms of R² values, both satellites show a strong correlation between the estimated and actual values, with a median value consistently above 0.86 on a monthly scale and over 92% of daily data points falling within ±2 standard deviation.

Radiative budget is one of the key factors influencing climate change. The aim of this study is to analyze radiative regime in Moscow using the MSU-RAD(BSRN) instrumentation complex and to estimate radiative effects of the main atmospheric factors during the 2021-2023 period. Due to variations in aerosol content, the loss of global shortwave irradiance (Q) varies from 37 to 186 W/m2 (or about 18-22%) at different solar elevations with a significant decrease in direct irradiance and increase in diffuse irradiance due to multiple scattering. In winter, we observed the increase in Q of about 45 W/m2 (or 9%) at h=30° due to high surface albedo, smaller aerosol and water vapor content. At the same time, net shortwave irradiance (Bsh) demonstrates a significant decrease due to prevailing effects of snow albedo. A nonlinear dependence of Q and Bsh cloud transmittance on relative sunshine duration (Sd) is observed. Mean changes in Q against the 1955-2020 period are characterized by negative anomalies (-22%) in winter and positive anomalies in summer (+3%) due to the changes in cloudiness, reflected in Sd variations. This is in line with global tendencies in long-term changes of shortwave irradiance in moderate climate in Europe during the last years.