The paper aims to analyse the relationship between the amount of global solar radiation (GSR) reaching the Earth’s surface in Poland and the dir…The paper aims to analyse the relationship between the amount of global solar radiation (GSR) reaching the Earth’s surface in Poland and the direction of air mass advection, using 72-h backward trajectories (1986–2015). The study determined average daily sums of GSR related to groups of trajectories with certain similarities in shape. It was found that the average daily sums of GSR during air mass inflow from all the directions (clusters) identified were significantly different from the average daily sum in the multi-year period. A significant increase in the amount of GSR over Poland is accompanied by air mass inflow from the north and east. The frequency of these advection directions is 27% of all days. The western directions of advection prompt different GSR sums: from slightly increased during advection from the north-west, to significantly decreased during advection from the west (from the central and western part of the North Atlantic). Special attention was given to days with extremely large (above the 0.95 percentile) and with the largest (above the 0.99 percentile) GSR sums. These are prompted by two main types of synoptic conditions: the Azores High ridge covering Central and Southern Europe; and the high-pressure areas which appear in Northern and Central Europe.more
Convective clouds play an important role in the local energy budget by directly interacting with solar and terrestrial radiation. However, radiation p…Convective clouds play an important role in the local energy budget by directly interacting with solar and terrestrial radiation. However, radiation parameterization schemes of atmospheric models generally consider clouds produced from microphysics schemes or some other grid saturation criteria. Deep convective parameterization schemes tend to rain out the convective cloud before the radiation scheme perceives its water load. This may be a source of the positive bias of the incoming solar radiation at the surface. The objective of this work is to include the effects of deep convective clouds in the radiation scheme of the regional Eta model and to evaluate the impacts on the net radiative energy and other meteorological variables. The radiation scheme is the Rapid Radiative Transfer Model. The work is developed in four stages. The positive bias in the incoming solar radiation was diagnosed in the first stage. In the second stage, the parameters of the convective parameterization scheme were modified to increase convective precipitation. In the third stage, the parameters of the microphysics scheme were modified to increase explicit clouds. In the fourth and last stage, in addition to the previous modifications, the condensates from the convective parameterization were input into the radiation scheme. The runs were performed for a period of one summer rainy month with intense convective activity over South America. Including deep convective cloud condensates into the radiation scheme improved the cloud cover, the diurnal cycle of the surface net radiation, and the 2-m temperature. However, the reduction of the net radiation at the surface caused the reduction of the available energy for convective instability and, consequently, the precipitation reduction. The results show the importance of including cumulus cloud water load in the radiative scheme for bias reduction in the radiative energy components.more
The SM2RAIN (soil moisture to rain) model has been widely used for rainfall estimation worldwide. However, due to the lack of sufficient ground observ…The SM2RAIN (soil moisture to rain) model has been widely used for rainfall estimation worldwide. However, due to the lack of sufficient ground observation, the SM2RAIN model driven by different passive microwave soil moisture products over the Tibetan Plateau has not been fully validated. In this article, four widely used satellite microwave soil moisture products (including SMAP, ASCAT, SMOS, and AMSR2) were used as input data for rainfall estimation. Rainfall data from eight ground observation stations during 2016–2018 were used to evaluate the overall performance of the SM2RAIN algorithm under various soil moisture products at different time aggregation scales. In addition, different satellite soil moisture products were merged to evaluate whether the combined soil moisture products could improve the performance of the SM2RAIN model. Finally, the rainfall estimates with different soil moisture data were further evaluated and compared with two benchmark rainfall products (IMERG and ERA5). Results indicate that: 1) Overall, SM2RAIN-SMAP has the highest rainfall estimation accuracy, but with the time aggregation scale up to 30 days, the mean R of the four rainfall estimates could reach above 0.8 and the mean value of Kling–Gupta efficiency could reach above 0.8. 2) Combined satellite soil moisture products can significantly improve the rainfall estimates. The SM2RAIN model performed the best when SMAP and ASCAT soil moisture products were combined. 3) Using the SMAP product or combined soil moisture products yielded more accurate rainfall estimates than the two benchmark rainfall products (IMERG and ERA5).more
The key factor that affects the inflow of radiant energy to the Earth's surface is the circulation of the atmosphere (caused by uneven distribution of…The key factor that affects the inflow of radiant energy to the Earth's surface is the circulation of the atmosphere (caused by uneven distribution of air pressure on the globe) and the related changes in the amount of aerosols and cloudiness. This paper identified the areas in the Euro-Atlantic region where the air pressure change had a significant impact on global solar radiation (GSR) changes over Poland, during the period 1986–2015. In general, growing GSR sums over Poland are to some extent related to the positive phase of the NAO (simultaneous pressure growth in the area of the Azores High and the pressure decrease in the area of the Icelandic Low). Correlation coefficient between the NAO index and GSR over Poland equals 0.18 (statistically significant at α = 0.05). In turn, in summer and autumn the pressure growth in southern Scandinavia results in a significant increase in the amount of GSR over Poland. Days with extremely large GSR sums (above the 95th percentile) are also prompted by the Azores High ridge which covers Central and Southern Europe, and by air mass inflow from the Atlantic.more
The estimation of downward long-wave radiation (DLR) at the surface is very important for the understanding of the Earth’s radiative budget with impli…The estimation of downward long-wave radiation (DLR) at the surface is very important for the understanding of the Earth’s radiative budget with implications in surface–atmosphere exchanges, climate variability, and global warming. Theoretical radiative transfer and observationally based studies identify the crucial role of clouds in modulating the temporal and spatial variability of DLR. In this study, a new machine learning algorithm that uses multivariate adaptive regression splines (MARS) and the combination of near-surface meteorological data with satellite cloud information is proposed. The new algorithm is compared with the current operational formulation used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Land Surface Analysis (LSA-SAF). Both algorithms use near-surface temperature and dewpoint temperature along with total column water vapor from the latest European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis ERA5 and satellite cloud information from the Meteosat Second Generation. The algorithms are trained and validated using both ECMWF-ERA5 and DLR acquired from 23 ground stations as part of the Baseline Surface Radiation Network (BSRN) and the Atmospheric Radiation Measurement (ARM) user facility. Results show that the MARS algorithm generally improves DLR estimation in comparison with other model estimates, particularly when trained with observations. When considering all the validation data, root mean square errors (RMSEs) of 18.76, 23.55, and 22.08 W·m−2 are obtained for MARS, operational LSA-SAF, and ERA5, respectively. The added value of using the satellite cloud information is accessed by comparing with estimates driven by ERA5 total cloud cover, showing an increase of 17% of the RMSE. The consistency of MARS estimate is also tested against an independent dataset of 52 ground stations (from FLUXNET2015), further supporting the good performance of the proposed model.more