Projects

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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Precise monitoring of ionospheric conditions to establish accuracies of GNSS measurements mainly during the periods with the MSTID and ionospheric scintillation occurrence. Development of actual MSTID effects mitigation algorithms for implementation into the GNSS receiver firmware to lower positioning errors.
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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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The increasing concentration of greenhouse gases affects the troposphere but even more the higher levels of the atmosphere, where it induces cooling. The first scenario of long-term trends in the upper atmosphere (mesosophere-thermosphere-ionosphere) was created by an international team in 2006 (Laštovička et al., 2006, Science). It has been improved but still it is not connected with trends in the stratosphere. Until recently the trends in the stratosphere and upper atmosphere were studied separately. The trends are affected also by other drivers, not only by greenhouse gases (mainly CO2), which change in time. The project is therefore focused on various aspects of trends in the stratosphere to improve possibilities of their comparison and joining with trends in the upper atmosphere, then on removing new problems in studying ionospheric trends, on specification of temporally varying roles of various non-CO2 trend drives, and on the main aim of the project, creation of the first joint scenario of long-term trends in the stratosphere-mesosphere-thermosphere-ionosphere system.
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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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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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Monitoring space weather events is crucial. The EU-funded SafeSpace project aims to advance space weather nowcasting and forecasting capabilities, contributing significantly to the safety of space assets through the transition of powerful tools from research to operations. This will be achieved through the synergy of five well-established space weather models. SafeSpace hopes to improve radiation belt, culminating in a prototype early warning system for detrimental space weather events, integrating information all the way from the Sun to the inner magnetosphere. Working, also, with a major European space company, SafeSpace, hopes to define indicators of particle radiation of use to space industry and spacecraft operators.
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A geomagnetic storm is a major disturbance of Earth\'s magnetosphere. It occurs when there is a very efficient exchange of energy from the solar wind into the space environment surrounding Earth. Predicting these storms is vital. This is the objective of the EU-funded PAGER project, which has assembled a team of leading academic and industry experts in space weather research, space physics, empirical data modelling and space environment effects on spacecraft from Europe and the United States. The project will provide a 1-2 day probabilistic forecast of ring current and radiation belt environments. This will allow satellite operators to respond to predictions that present a threat. The most advanced codes will be used, adapted to perform ensemble simulations and uncertainty quantifications.  
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