On the 15th of October 2024, the meeting of the partners of the EuroCC2 Lithuania project took place at the Calvary Hotel in Vilnius. The progress of the EuroCC2 project was discussed, experiences were exchanged, current and planned project activities were presented by the participants from the Faculties of Physics and Mathematics and Informatics of Vilnius University, Kaunas University of Technology Artificial Intelligence Centre, VILNIUS TECH – Vilnius Gediminas Technical University and Lithuanian Hydrometeorological Service. The main focus of the meeting was on the organisation of practical trainings and there was a discussion on the best practices of the partners in this field.
The strengthening of the co-operation between the project partners was the main focus of the discussions. Ideas were also exchanged on how to innovate and promote digital literacy in HPC in Lithuania. Discussions were held on identified needs for using HPC infrastructure in science, public administration, business and industry.
At the end of the event, the next steps for the achievement of the project goals were decided. The aim of the project is to strengthen the competences in High Performance Computing (HPC), High Performance Data Processing (HPDA) and Artificial Intelligence (AI) in Lithuania and to promote their use in the research, public and business sectors, and to foster peer collaboration.
A delegation from the Lithuanian Hydrometeorological Service visited the Norwegian Meteorological Institute (MET Norway) as part of a project under the Nordic-Baltic Mobility Program for Public Administration. The visit aimed to strengthen international cooperation and facilitate the exchange of best practices between the two organisations.
During the visit, the delegation explored several key topics. One of the main areas of focus was the development of impact-based weather forecasting, aimed at improving the accuracy of warnings and raising public awareness of potential hazardous weather events.
Discussions also covered the potential for partnerships with other institutions to expand the meteorological observation network and ensure data quality, with particular attention given to integrating stations from third countries.
Another significant topic of discussion was the application of artificial intelligence and machine learning in meteorology. The delegation examined how these technologies could enhance the precision of hazardous weather predictions and improve data processing efficiency.
On October 10, the Lithuanian Hydrometeorological Service (LHMT) hosted a meeting with Jonathan How, Senior Meteorologist from the Bureau of Meteorology, Australia. During his visit, Jonathan shared valuable insights on Australia’s climate zones, the distribution of annual rainfall, and public communication strategies that help deliver meteorological information effectively to the public and decision-makers.
LHMT specialists also gave presentations, covering important topics such as forecasting, meteorological observations, and information dissemination. The discussions focused on the latest practices, challenges, and ways to improve the delivery of meteorological data to the public, ensuring more accurate forecasts.
Project Overview The management of ice jam flood risk in the Latvian and Lithuanian regions in the context of climate change (hereinafter referred to as ICEREG) is a cross-border project aimed at improving the management of ice jam flood risk in the border regions of Lithuania and Latvia. The main objective of the project is to develop comprehensive flood risk maps and improve the conceptual model of ice jam formation, taking into account the impact of climate change.
Ice jams pose a significant threat as they can cause large-scale flooding and inflict considerable damage on the environment and economy, particularly in border communities. Since the dynamics of ice jams have not been thoroughly studied to date, the ICEREG project seeks to analyze this phenomenon in greater detail, with special attention to the meteorological and hydrological conditions that lead to flood formation.
Research Overview and Results The project analyzed ice jam occurrences in rivers across northern Lithuania, focusing on 10 water measurement stations (WMS) located on the Bartuva, Venta, Mūša, Nemunėlis, Lėvuo, Tatula, Daugyvenė, and Svyla rivers. The analyzed period spanned from 1961 to 2023. During this time, a total of 237 ice jam events were recorded, with the highest number of events (50) at the Trečionys WMS and the lowest (1) at Žilpamūčiai WMS.
Impact and Damage of Ice Jams Ice jams are particularly dangerous due to their unpredictability and the rapid rise in water levels they can cause. They form when larger ice floes get stuck on obstacles in the river, creating a temporary dam, which can quickly lead to natural disasters. Water levels rise above the jam and drop below, posing a significant threat to residents, infrastructure, and the environment.
Key Events In the early 21st century, significant ice jam floods occurred in the Mūša and Lėvuo rivers. In 2010 and 2013, water levels in the Mūša River near Ustukiai exceeded critical levels by 90 cm and 125 cm, respectively. The April 2013 floods caused considerable damage in the Pasvalys district, where homes, gardens, and warehouses were flooded.
Similarly, in the Lėvuo River, significant water level increases due to ice jams occurred in 2010 and 2018, posing risks to nearby areas.
Conditions for Ice Jam Formation Ice jams typically form when there is a sudden thaw after ice cover has developed in rivers, especially with significant temperature fluctuations between day and night. On average, ice jams start on January 10th at the observed WMS, and the ice jam period lasts about 8 days. The earliest recorded ice jam start date was October 30th (Tatula – Trečionys WMS, 1979), and the latest was April 14th (Mūša – Ustukiai WMS, 2013).
Pilot River Sections for Modeling Two pilot river sections were selected for the project – Lėvuo (from Pamarliškiai to Skaistgiriai) and Mūša (from Gustoniai to Ustukiai). These sections were chosen due to their long observation periods and the significant impact ice jams are likely to have on the environment and residents. Based on historical data analysis, a conceptual model of ice jam formation and flooding is being developed, which will help assess changes in the primary parameters of ice jams based on climate change scenarios.
Conclusions and Next Steps The ICEREG project is an important step towards improving the management of ice jam flood risks. The development of flood maps and the conceptual model will not only enhance the resilience of regions to flooding but also help create more effective early warning systems. The results of the project will be used not only for scientific purposes but also for practical flood prevention measures.
In the next phase of the project, detailed climate change scenario assessments will be conducted to better understand future ice jam dynamics and ensure that regions are prepared to face the challenges posed by a changing climate.
This September was the warmest in the history of instrumental observations in Lithuania (i.e. the least since 1961, and in Vilnius since 1778)! The average monthly air temperature in Lithuania was 16.8 °C (or 4 degrees warmer than average). September of 2023 (16.5 °C) was in second place, while September 1975 (14.9 °C) was in third place.
Both last year and this year, September saw no shortage of new heat records. In 2023, there were six daily maximum temperature records for the whole month, and this year there were seven more. There were also a few more days when the new record was very close to being broken.
The meteorological summer of 2023 ended late, as late as 4-5 October. And this year it ended a little earlier, on 28-29 September (or 3.5 weeks later than average). As a reminder, the average end of meteorological summer (1991-2020) is 4 September.
The graph shows the average air temperature in Lithuania for the period 1991-2020, in September 2023 and 2024. Note that almost all days in September 2023 and 2024 were warmer than the long-term average. Average daily air temperatures were often even in line with values for midsummer.