Search

The onset of periods with very high or low air temperatures has aroused general interest for a long time, which is understandable since it has many dangerous effects directly affecting humans. Such perilous climatic phenomena include exceptionally cold and exceptionally warm months, which this study investigates for all Europe and for its five physico-geographic regions over the 190-year period of 1831-2020. Therefore, the research in this paper includes two periods characteristic of the history of climate - the late Little Ice Age (LIA) and present-day warming. The studies are based on average monthly air temperature values from 40 weather stations in Europe. In this paper, exceptionally cold months (ECMs) or exceptionally warm months (EWMs) are considered to have occurred when the average air temperature at a station differed from the respective long-term average by at least two standard deviations. The highlights of the study include the identification of a drop in the number of ECMs by 20 over the entire 190-year period, and a highly statistically significant increase in EWMs by 44 between 1980 and 2020. These changes proceeded with different intensities from one physico-geographic region of Europe to another.

Modelling rainfall extremes and dry periods over the Southeast Asia (SEA) region is challenging due to the characteristics of the region, which consists of the Maritime Continent and a mountainous region; it also experiences monsoonal conditions, as it is located between the Asian summer monsoon and the Australian summer monsoon. Representing rainfall extremes is important for flood and drought assessments in the region. This paper evaluates extreme rainfall climatic indices from regional climate models from CORDEX Southeast Asia and compares them with the results of high-resolution global climate models with a comparable spatial resolution from the HighResMIP experiment. Observations indicate a high intensity of rainfall over areas affected by tropical cyclones and long consecutive dry day periods over some areas in Indochina and the southern end of Indonesia. In the model simulations, we find that both coupled and sea surface temperature-forced HighResMIP model experiments are more similar to the observations than CORDEX model results. However, the models produce a poorer simulation of precipitation intensity-related indices due to model biases in the rainfall intensity. This bias is higher in CORDEX than in HighResMIP and is evident in both the low- and high-resolution HighResMIP model versions. The comparable performances of HighResSST (atmosphere-only runs) and Hist-1950 (coupled ocean–atmosphere runs) demonstrate the accuracy of the ocean model. Comparable performances were also found for the two different resolutions of HighResMIP, suggesting that there is no improvement in the performance of the high-resolution HighResMIP model compared to the low-resolution HighResMIP model. © 2022 The Authors. International Journal of Climatology published by John Wiley Sons Ltd on behalf of Royal Meteorological Society.

The tracking of thunderstorms provides critical information on their frequency and behaviour for early warning, prediction and preparedness. Thunderstorm tracking has previously been constrained by the boundaries of a particular country or has focused on a particular category such as severe thunderstorms and mesoscale convective systems. However, less severe thunderstorms also pose a risk to life and property and occur more frequently and thus warrant inclusion in investigations of thunderstorm behaviour. In this paper, we present a new thunderstorm event catalogue, including all detected thunderstorms with at least three lightning flashes, derived from a tracking methodology applied to Northwest Europe within the bounds of 48° to 65°N and 15°W to 10°E between 2008 and 2018. The catalogue is based on ATDnet lightning flash data which was clustered into thunderstorms using a spatio-temporal proximity assessment lightning clustering code written in the R coding language. The thunderstorm lightning clusters enabled the production of thunderstorm behaviour statistics such as speed, direction of movement, lightning flashes per minute and duration. This revealed that in winter, thunderstorms are shorter lived and move faster than in summer as well as more typically tracking from the west rather than from the south-west. Thunderstorm behaviour characteristics were attributed to weather pattern types for the first time, providing probabilistic data that can be attributed to synoptic conditions. This can improve preparedness and early warning. Such results demonstrate how this new thunderstorm event catalogue, which includes all types and severities of thunderstorms unconstrained by political boundaries, can provide additional important information to enhance understanding of thunderstorm behaviour in the region. Our lightning clustering method may be useful for similar studies in other locales.

There is growing interest in the international scientific community in characterizing climate variability in Antarctica because of the continent's fundamental role in regulating the world's climate. Researchers have intensively studied the Antarctic Peninsula since the warming that began in the mid-1950s. This was followed by a subsequent cooling period over the last decades. For this paper, using the available data, we analyzed the variability in surface air temperatures at five meteorological stations located on King George Island (KGI) (a subantarctic island that is part of the South Shetland Islands); we also investigated the relationships between the air temperatures and large-scale atmospheric patterns from 1968 to 2019. In this study we found that summer temperatures are above 0°C from December to March and close to melting temperatures (extreme values) in spring and autumn; consequently, a small increase in temperature can have a significant impact on the cryosphere. The statistical analysis of the mean temperatures confirmed a trend toward cooling during the summer and in the mean monthly maximum temperatures over the 1990s at most of the weather stations whose data we analyzed. Analyzing the teleconnection patterns showed that the Southern Annular Mode (SAM) had strong, direct, and positive correlations during the autumn and less strong connections in spring, winter, and on an annual scale. Furthermore, we observed a lesser influence of El Niño-Southern Oscillation (ENSO).