In this paper, we performed an analysis of the 500 most relevant scientific articles published since 2018, concerning machine learning methods in the field of climate and numerical weather prediction using the Google Scholar search engine. The most common topics of interest in the abstracts were identified, and some of them examined in detail: in numerical weather prediction research—photovoltaic and wind energy, atmospheric physics and processes; in climate research—parametrizations, extreme events, and climate change. With the created database, it was also possible to extract the most commonly examined meteorological fields (wind, precipitation, temperature, pressure, and radiation), methods (Deep Learning, Random Forest, Artificial Neural Networks, Support Vector Machine, and XGBoost), and countries (China, USA, Australia, India, and Germany) in these topics. Performing critical reviews of the literature, authors are trying to predict the future research direction of these fields, with the main conclusion being that machine learning methods will be a key feature in future weather forecasting.

In 2015, large parts of Europe were characterized by extraordinary high summer temperatures, accompanied by very dry conditions, particularly in central‐eastern Europe. Several major heat episodes occurred from the end of June until mid‐September. We provide an ad‐hoc evaluation of the observed climatological extremes in a secular context, by using a set of long station time series in daily resolution. Our data set comprises 42 temperature and 43 precipitation records, predominantly starting already in the 19th century. To investigate local record values, the individual full record length is analysed for each station, while regionally averaged analyses are presented for the core study period of 1901–2015. The study area covers Europe's central latitudes (44° to 52°N), extending from England in the west up to the central Ukraine in the east.During summer 2015, various indices representing extremely high maximum and minimum temperatures (strongly) exceeded previous record high values, mainly in an area extending from eastern Germany to western Ukraine. Additionally, severely to extremely dry conditions with unusually frequent dry days were prevailing particularly in the (central‐) eastern part of the study area. Drought indices combining temperature and precipitation revealed drought conditions comparable or even worse than those of former extreme summers like 2003.

An observed increase in air temperature can lead to significant changes in the phenology of plants and, consequently, changes in agricultural production. The aim of the study was to evaluate the spatial differentiation of thermal resources in Poland and their variability during a period of changing thermal conditions in Europe. Since the variability of thermal conditions is of paramount importance for perennial crops, the study focused on apple, plum, and cherry orchard regions in Poland. The analysis was conducted for the period of 1951–2010 using air temperature daily data. Thermal resources have been defined using the growing degree days (GDD) index calculated independently for the whole year and during in frost-free season for three air temperature thresholds: 0, 5, and 10 °C, which determine the non-winter period, growing season, and the period of full plant growth, respectively. In addition, due to the high significance for perennials in particular, the incidence and intensity of frost during flowering were calculated. In this study, a detailed analysis of the spatial differentiation of thermal resources was first performed, followed by an evaluation of long-term variability and associated change patterns. The obtained results confirmed an increase in thermal resources in Poland as a consequence of the lengthening of the growing season. However, the frequency and intensity of spring frost, especially during flowering or even during ripening of plants, remain a threat to harvests in both the eastern and western parts of the country.

The eruption of Mount Tambora (Indonesia) in April 1815 is the largest documented volcanic eruption in history. It is associated with a large global cooling during the following year, felt particularly in parts of Europe and North America, where the year 1816 became known as the "year without a summer". This paper describes an effort made to collect surface meteorological observations from the early instrumental period, with a focus on the years of and immediately following the eruption (1815–1817). Although the collection aimed in particular at pressure observations, correspondent temperature observations were also recovered. Some of the series had already been described in the literature, but a large part of the data, recently digitised from original weather diaries and contemporary magazines and newspapers, is presented here for the first time. The collection puts together more than 50 sub-daily series from land observatories in Europe and North America and from ships in the tropics. The pressure observations have been corrected for temperature and gravity and reduced to mean sea level. Moreover, an additional statistical correction was applied to take into account common error sources in mercury barometers. To assess the reliability of the corrected data set, the variance in the pressure observations is compared with modern climatologies, and single observations are used for synoptic analyses of three case studies in Europe. All raw observations will be made available to the scientific community in the International Surface Pressure Databank.