Projects

Heat waves are considered as one of the largest hazards related to climate change. Initial studies using one-dimensional station data were gradually supplemented by papers employing more advanced two-dimensional products, i.e. station data interpolated into a regular grid. They allowed capturing spatial patterns of heat waves but lacked the ability to identify vertical air mass characteristics. Besides radiative heating of the surface during clear-sky conditions, heat wave characteristics are also determined by a horizontal advection and an adiabatic heating during air subsidence – the processes that require data from free atmosphere to be analysed. In order to advance in knowledge of heat waves’ mechanisms, we propose this project which aims to study atmospheric circulation and land–atmosphere coupling as a joint driver governing heat waves in three-dimensional space. The state-of-the-art ERA5 reanalysis and CORDEX regional climate models will be employed to achieve project aims defined below.
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Relationships between weather and human health are very complex. Many studies have shown a typical seasonal pattern of mortality, with its maximum in the cold period and minimum in summer. It remains unclear, however, to what extent seasonality of mortality can be explained by direct effects of winter weather and to what extent other factors are important, such as incidence of acute respiratory diseases (until recently, mainly seasonal influenza epidemics). This topic has become even more relevant in connection with the ongoing COVID-19 pandemic, which caused unprecedented excess mortality in 2020 and 2021. The aim of the project is to assess historical connections between weather variability, seasonal patterns of mortality, and the occurrence of acute respiratory infections in temperate climate conditions. Special emphasis will be given to how these patterns have been affected by the COVID-19 pandemic.
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Long-term changes (trends) in short-term (day-to-day to intraseasonal) variability of temperature and precipitation are examined in the Northern Extratropics, both in the observed data and in outputs of global and regional climate models. Various characteristics of variability, which provide complementary information, are analyzed (standard deviation, persistence, dayto- day variations, transition probabilities, lengths of dry and wet spells). Their climatologies and trends are compared between different dataset types (station, gridded, reanalysis) with the aim to identify biases specific to individual dataset types. We also focus on mechanisms governing the short-term variability, and the day-to-day temperature changes in particular, in which atmospheric fronts are likely to play a role. We validate the short-term variability in climate model outputs and evaluate its future projections by models. Finally, we attempt to find out whether the anthropogenic climate change is already manifested in the recently observed changes of variability
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Weather and climate extremes are associated with large impacts on society and environment, and frequency of some of these extremes has increased and/or is projected to increase in a future climate. It is important to better understand physical mechanisms leading to extremes, their mutual links, and how they are reproduced in climate models. The project deals with temperature and precipitation extremes in Europe, with focus on warm season. The main aims are to (i) examine the role of atmospheric circulation and land-atmosphere coupling in initiating development of temperature extremes and supporting their persistence in observed climate and ERA-5 reanalysis, including the study of links to extremes of precipition and other variables, (ii) analyze spatial patterns of differences between individual driving mechanisms (advective, radiative, and land-surface factors) in key regions of Europe, and (iii) evaluate ability of current high-resolution climate models to reproduce the driving mechanisms of extremes and their spatial patterns. This represents an important step towards better understanding credibility of climate model outputs, and for further model improvements.
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Many complex process-based models are available in Europe to project future climate impacts. Yet, the current climate impact research community is fragmented, modeling mostly individual systems. The integration of climate impacts across different natural and societal sectors is only slowly emerging. Likewise, attribution of impacts to climate and other factors is still a strongly under-researched field given that climate change is already strongly manifesting itself, an increasing number of court cases dealing with climate impacts is being negotiated and policy debates on loss and damage are intensifying. This lack of coordination amongst impact modelers and insufficient awareness about impact attribution methods hampers important scientific and political progress and more coordination and networking is urgently needed. Therefore, PROCLIAS aims to develop common protocols, harmonized datasets and a joint understanding of how to conduct cross-sectoral, multi-model climate impact studies at regional and global scales allowing for attribution of impacts of recent climatic changes and robust projections of future climate impacts. The Action will do so by focusing on key interactions of climate impacts across sectors, their accumulated effect, especially of extreme events, the attribution of impacts to climate change and the quantification of uncertainties. PROCLIAS will make use of all COST networking tools to train young researchers to conduct and analyse multi-model simulations in a cross-sectoral way, to support a common platform for collecting impact model simulations and methods for analyzing them and to disseminate the data, code and results to scientists as well as, in a more synthesized form, to stakeholders.
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