Floods are one of the main natural disasters that affect environment and ecosystems, and an increasing number of evidences highlights how climate change and urbanization are contributing to exacerbate the risk related to their occurrences. A parallel and coupled investigation of meteo-hydrological causes and of impacts on societies is therefore of primary importance for allowing a reliable analysis of flood events and improving current emergency management techniques. Within this framework, flood modelling assumes a key role in developing an accurate knowledge of rain-related impacts, especially in the urban fabric. Recent advances in flood modelling have enabled hyper-resolution street-level studies, offering significant potential for flood reconstruction, nowcasting, and forecasting. However, the calibration of flood models faces challenges due, among others, to limited availability of flood-related measurement, particularly in ungauged basins or during extreme events. While low-complexity and low-resolution inundation models may suffice to be calibrated on estimated flow discharges, space-time variability of rainfall patterns and hydrodynamic information, namely flood depths and flow velocities, become crucial for accurate simulations in urban areas. To address this issue, there is a growing need for accurate information, prompting research into alternative documentary sources concerning the impact of past floods and solutions for dataset merging. Moving from a consolidated catalogue of historical damaging hydrogeological events (ASICal), this work explores the potential of a composite meteorological and impact-based data collection for pilot case studies in Calabria region (southern Italy). Information gathered from different data sources and characterized by different levels of detail, from pixel (radar/satellite) scale up to the street level, have been systematically retrieved and organized. In our study we review and highlight (i) the abilities of weather radar in characterizing rainfall dynamics in time and space, and (ii) how photos and video posted on social media represent valuable sources for quantitative information offering insights up to the house number level, despite the limitation of the need for a visual inspection and interpretation of their contents. Results are supportive of the opportunities arising from the proposed approach in the collection of impact data from multiple sources and different levels of detail, which represents a key task for the improvement of the emergent flood related studies based on high-resolution hydrodynamics and hydrological approaches to rainfall classification and modelling.

How to cite: Lombardo, M., Totaro, V., Chiaravalloti, F., and Petrucci, O.: A systematic approach for flood-impact data retrieval in urban floods modelling, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-571, https://doi.org/10.5194/ems2024-571, 2024.

The reconstruction of floods in Poland in the last millennium (11^th–20^th centuries) was evaluated based on more than 1,300 weather notes and sources describing floods. After assessing the quality of each source, the most reliable sources were used for the investigation of flood occurrences. The most commonly used methods for the classification of flood intensity in Europe (Barriendos and Coeur 2004; Brázdil et al. 2006) have been used. The genesis of floods was estimated based on the method presented by Lambor (1954). The results demonstrated that more than 1,600 floods occurred in Poland in the last millennium. The highest number of floods occurred in the 18^th (356) and 16^th (345) centuries, while the lowest occurred in the 19^th (187) and 11^th–15^th (210) centuries. Assessment of flood trend analysis based on the Mann–Kendall test showed that from 1301 to 2000 there was an increasing trend in the frequency of floods. Analysing the spatial diversity of floods in Poland in the study period indicated that the highest number of floods occurred in the Oder River basin. Also, the number of floods in the Silesia and Baltic Coast regions was significantly more than in the other four analysed regions. The estimation of the intensity of floods demonstrated that most of the floods belong to the “above-average, or supra-regional flood” and the “extraordinary” categories according to Brázdil et al. (2006) and Barriendos and Coeur (2004) classifications, respectively. The evaluation of the main genesis of floods indicated that rain and its sub-types (torrential, frontal, long-lasting, territorially widespread) were the main cause of floods in Poland in the 11^th–20^th centuries. Studying floods in Poland before the 21^st century will improve our understanding of historical hydrology in Europe.

The work was supported by the National Science Centre, Poland, project No. 2020/37/B/ST10/00710.
References:
Barriendos, M., Coeur, D, 2004: Flood data reconstruction in historical times from non-instrumental sources in Spain and France. Systematic, Palaeoflood and Historical Data for the Improvement of Flood Risk Estimation. Methodological Guidelines, edited by: Benito, G. and Thorndycraft, VR, Centro de Ciencias Medioambientales, Madrid, Spain, pp. 29–42.
Brázdil, R., Kundzewicz, Z. W., & Benito, G., 2006: Historical hydrology for studying flood risk in Europe. Hydrological sciences journal, 51(5), 739–764. https://doi.org/10.1623/hysj.51.5.739.
Lambor, J., 1954: Klasyfikacja typów powodzi i ich przewidywanie. Gospodarka Wodna, 4, 129–131

How to cite: Ghazi, B., Przybylak, R., Oliński, P., and Pospieszyńska, A.: Reconstruction of floods in Poland in the last 1000 years, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-53, https://doi.org/10.5194/ems2024-53, 2024.

Keywords: Paleoclimate proxy, Stable Isotope, Artificial Intelligence, Lake, Speleothem

Oxygen isotope ratios are the most used geochemical proxy data in paleoclimatic and paleohydrological  reconstructions, currently measured in a variety of continental carbonates, including shells, sediments and speleothems. δ¹⁸O of carbonates that form in conditions of (or close to) isotopic equilibrium does not only depend on local temperature (that controls isotopic fractionation) but also on the isotopic composition of the water from which they precipitate, which in most cases is in turn determined or controlled by the δ¹⁸O of rainfall.  For this reason, understanding patterns of temporal and spatial changes in rainfall δ¹⁸O is essential for the calibration of proxies based in carbonate δ¹⁸O. Intensive monitoring programs are currently being performed in target natural systems such as lakes and karst caves. These programs however yield local isotopic records of limited duration, hampering their regional utility.      

In this work, we present a Machine Learning based approach that takes into consideration not only the dependence of rainfall δ¹⁸O to latitude and altitude, but also to the main factors affecting winter precipitation variability within the Iberian Peninsula (IP), such as the North Atlantic Oscillation and the Western Mediterranean Oscillation. This approach is based in the available isotopic data of precipitation (IAEA Global Network of Isotopes in Precipitation – GNIP) and local series.

Our model provides predicted values of δ¹⁸O with improved accuracy and uncertainty relative to current approaches. By capturing the variability of δ¹⁸O associated with diverse atmospheric conditions, it will also contribute to refine the interpretation paleoclimatic reconstructions in this region.

Contribution to PID2021-122854OB-I00 and research group 910198 of the UCM.

How to cite: Stachnik, A., Morellón, M., and Martín-Chivelet, J.: Patterns of precipitation δ18O through the Iberian Peninsula: Machine Learning dynamic modeling for climate proxy calibration, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1086, https://doi.org/10.5194/ems2024-1086, 2024.

The European drought of 1921 is assessed in terms of its impacts on society and in terms of its physical characteristics. The development of impacts of the drought are categorized by a systematic survey of newspaper reports from five European newspapers covering the area from England to the Czech Republic and other parts of Europe. This is coupled to a reconstruction of daily temperature and precipitation based on meteorological measurements to quantify the drought severity and extent, and reanalysis data are used to identify its drivers. This analysis shows that the first impacts of the drought started to appear in early spring and lingered on until well into autumn and winter, affecting water supply and agriculture and livestock farming. The dominant impact in western Europe is on agriculture and livestock farming while in central Europe the effects of wildfires were reported on most often. The peak in the number of reports is in late summer. Preceding the first impacts was the dry autumn of 1920 and winter 1920–1921. The area hardest hit by the drought in the following spring and summer was the triangle between Brussels, Paris and Lyon, but a vast stretch of the continent, from Ireland to the Ukraine, was affected. The reported impacts on water supply and water-borne transport in that region were matched by an analysis of the hydrological situation over the Seine catchment. On average, the 1921 summer was not particularly hot, but the heatwave which was observed at the end of July saw temperatures matching those of the heatwaves in modern summers. Similar to modern droughts, an anticyclone was present roughly over the British Isles, maintaining sunny and dry weather in Europe and steering away cyclones to the north. Its persistence makes it exceptional in comparison to modern droughts.

The 1921 drought stands out as the most severe and most widespread drought in Europe since the start of the 20th century. The precipitation deficit in all seasons was large, but in none of the seasons in 1920 and 1921 was the precipitation deficit the largest on record. The severity of the 1921 drought relates to the conservative nature of drought which amplifies the lack of precipitation in autumn and winter into the following spring and summer.

How to cite: van der Schrier, G., Allan, R., Ossó, A., Sousa, P., Van de Vyver, H., Van Schaeybroeck, B., Coscarelli, R., Pasqua, A., Petrucci, O., Curley, M., Mietus, M., Filipiak, J., Štěpánek, P., Zahradníček, P., Brázdil, R., Řezníčková, L., van den Besselaar, E., Trigo, R., and Aguilar, E.: The 1921 European drought: impacts, reconstruction and drivers, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-983, https://doi.org/10.5194/ems2024-983, 2024.

Evidences from climate reconstructions and model simulations show that climate experienced important changes during the Last Millennium (LM). These changes can be associated with external forcing factors, such as cycles of solar activity, changes in the concentration of greenhouse gases in the atmosphere, volcanic eruptions, changes in orbital parameters, or changes in the land use and land cover, or with a redistribution of energy as part of climate internal variability. Both external forcing and internal variability contributed to alter temperatures, ice extent and atmospheric dynamics, with impacts on the hydroclimate in different parts of the world. The LM was characterised by a period of higher radiative forcing during the Medieval Climate Anomaly (MCA; ca. 950-1250), a period of lower radiative forcing during the Little Ice Age (LIA; ca. 1450-1850), and a rapid increase of the radiative forcing during the industrial era.

This work analyses simulations of the LM from the Paleoclimate Modelling Intercomparison Project (PMIP3 and PMIP4); grids of reconstructed data based on tree rings from the Drought Atlases of Europe (OWDA), North America (NADA) and Asia (MADA); data assimilation-based products like the Paleo Hydrodynamics Data Assimilation product (PHYDA) and the Last Millennium Reanalysis (LMR); as well as individual reconstructions based on tree rings, marine and lake sediments, speleothems, ice cores and documentary information, with the main objective of analysing the hydroclimate variability from interannual to multicentennial timescales from a global perspective, how these changes impacted tropical and extratropical regions, their relation to changes in temperatures and atmospheric dynamics, and the impact of external forcing and internal variability on their occurrence.

These analyses show coordinated changes in the hydroclimate of separate regions, both in extratropical and in tropical areas. These changes can be linked in extratropical areas to alterations of extratropical modes like the North Atlantic Oscillation (NAO), the Northern Annular Mode (NAM) and the Southern Annular Mode (SAM) and in tropical areas to alterations of the Intertropical Convergence Zone (ITCZ).

How to cite: Roldán-Gómez, P. J., González-Rouco, J. F., Smerdon, J., and García-Pereira, F.: Impacts of external forcing and internal variability on the evolution of hydroclimate during the last millennium, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-90, https://doi.org/10.5194/ems2024-90, 2024.

Extreme air temperatures in Toruń were analysed for the period 1871–2020. The air temperature data were collected from data of the Prussian, German and Polish (Archives of the Institute of Meteorology and Water Management − National Research Institute) networks. Possible deficiencies in the monthly average data were supplemented by the method of constancy of differences based on data from the station in Bydgoszcz (correlation of air temperature data from Bydgoszcz and Toruń reaches 0.99 and is statistically significant). The data was then homogenised using AnClim software (Štěpánek, 2008). Based on quantile thermal classification criteria (Czernecki & Miętus, 2011), months, seasons and years were determined to be: extremely warm (>95.00 percentile), anomalously warm (90.01–95.00), very warm (80.01–90.00), warm (70.01–80.00), slightly warm (60.01–70.00), normal (40.01–60.00), slightly cool (30.01–40.00), cool (20.01–30.00), very cool (10.01–20.00), anomalously cold (5.00–10.00), extremely cold (<5). Temperature values for individual intervals were determined for each month, season and year separately.

In the period 1871–2020, the average annual air temperature in Toruń was 7.8 °C. In the annual cycle, the air temperature values were highest in July (18.3 °C) and lowest in January (˗2.4 °C). In the analysed period, the average annual air temperature shows a statistically significant trend of +0.1 °C per decade. For more detailed analyses, the research period was divided into fifty-year sub-periods. For the subperiod 1871–1920, there were no years classified as very, anomalously or extremely warm. The period 1921–70 was characterised by almost 50% frequency of years below the 40.00 percentile (<7.56 °C). In the last fifty years of the study period (1971–2020), there were no extremely cold years, while years classified as warm (all classes above the 60.00 percentile; >8.10 °C) have an almost 60% frequency.

The research was funded by the National Science Centre, Poland; Project No. 2020/37/B/ST10/00710.

References:

Czernecki B., Miętus M., 2011. Porównanie stosowanych klasyfikacji termicznych na przykładzie wybranych regionów Polski [Comparison of thermal classification for selected regions of Poland]. Przegląd Geofizyczny, z. 3–4, 201–227.

Štěpánek, P., 2008. AnClim - software for time series analysis: Dept. of Geography, Fac. of Natural Sciences, MU, Brno. 1.47 MB. http://www.climahom.eu/AnClim.html.

How to cite: Pospieszynska, A. and Przybylak, R.: Extreme air temperature in Toruń (Poland), 1871–2020, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-336, https://doi.org/10.5194/ems2024-336, 2024.

For Switzerland, high-resolution gridded data of daily mean temperature and daily precipitation sums have recently been developed based on a large amount of early instrumental data for a period from 1763 to 1960. These temperature and precipitation fields were reconstructed with the analogue resampling method and subsequently improved using data assimilation for the temperature fields and bias correction for the precipitation fields. This new data set together with present-day meteorological fields since 1961 allows us to study a wide range of historical extreme weather events in Switzerland and their impacts on past societies. However, to study the impact of historical weather events in more detail, other variables are often needed, such as sunshine duration, wind speed, and humidity, but also minimum and maximum temperature.

Here, we present the daily gridded Swiss reconstruction of daily temperature and precipitation, as well as the extension of the Swiss reconstruction to more variables, focusing mainly on sunshine duration, relative humidity, and wind speed. These additional reconstructions are based as well on the analogue resampling method, however, with a partly different reference period for the analogue pool compared to the temperature and precipitation reconstructions, and with a different data source for the resampled field. The extended Swiss gridded reconstructions make it possible to perform impact studies of historical weather and climate events, for example through agricultural modelling and calculating impact-based indices.

Furthermore, we explore the potential of the extended reconstructions by evaluating historical and contemporary wildfire events in Switzerland. Wildfires are analysed using commonly used fire weather indices, such as the Canadian Fire Weather Index. We compare these indices with historical documents reporting on the fire events in Switzerland and, where possible, with the synoptic conditions over Switzerland and Europe leading up to the event.

How to cite: Noemi, I. and Stefan, B.: A gridded data set to study historical climate impacts in Switzerland since 1763, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-891, https://doi.org/10.5194/ems2024-891, 2024.

Homogenization in climate research means the removal of non-climatic changes. This presentation describes the homogenization of the early instrumental dataset (HCLIM; https://doi.pangaea.de/10.1594/PANGAEA.940724) of monthly mean temperature time series. New homogenization algorithm validation methodology is assessed here on early instrumental data, and its use to assess the skill of three different algorithms, when applied to early instrumental data.This study addresses the challenge of homogenizing early instrumental meteorological observations spanning 365 years to accurately reconstruct historical climate change. Manual homogenization methods are time-consuming and prone to errors, necessitating an exploration of automated alternatives. We assess three current automatic homogenization algorithms—CLIMATOL, PHA, and BART—utilizing the global early instrumental dataset HCLIM, covering discontinuous monthly temperature records from 1658 to 2021, with record lengths varying from 15 to 260 years. Our analysis reveals significant differences in break frequency among algorithms, with BART detecting eight times more breaks than CLIMATOL and PHA. The ratio of homogeneous series also varies notably: PHA at 85%, CLIMATOL at 70%, and BART at 31%. Additionally, we evaluate algorithm performance by comparing detected records with collocated reference records from the 20CRv3 reanalysis product. Moreover, we identify certain data points unsuitable for homogenization due to missing neighbouring stations or apparent outliers, while highlighting their potential for identifying extreme climatic events. This research underscores the importance of rigorous assessment and validation of automated homogenization methods in historical meteorological records analysis. Furthermore, we find that both homogenization and the use of 20CRv3 are indispensable for refining results. By comparing the homogenized datasets with a reanalysis dataset, the results reveal that some data points necessitate homogenization, while others do not require this correction based on the reanalysis alone. Furthermore, the study demonstrates that utilizing three homogenization tools in conjunction with the reanalysis dataset yields optimal results for the early instrumental dataset Hclim.

How to cite: Lundstad, E.: Towards automated and global homogenization procedures for early instrumental temperature data., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-346, https://doi.org/10.5194/ems2024-346, 2024.

The Mediterranean basin, home to over 510 million people and characterized by unique geography, a rich cultural landscape, and economies heavily dependent on tourism, has emerged as the critical focal point for climate change impacts.^. In fact, it experienced an unprecedented heatwave in the warm season of 2022. With a temperature anomaly of +3.6°C, it was the most severe event recorded in the last millennium. In this study, we analyzed the 2022 extreme warm season by placing it within three distinct frameworks: instrumental data, millennial-length historical context, and future climate projections. Our analysis reveals that climate change has significantly increased the frequency of such extreme events, historically occurring once in 10,000 years, to now potentially as often as every 7 to 75 years depending on future climate scenarios.

We also compared projections from EURO-CORDEX models, which are recognized for their superior spatial resolution and enhanced ability to accurately represent regional climate dynamics and trends, againts CMIP6 outputs. A key finding is the significant discrepancy in return period projections under the SSP2-4.5 scenario: CMIP6 models forecast these extreme events to recur once every 7 years, whereas EURO-CORDEX predicts a frequency of once every 75 years. While the performance of CMIP6 models is broadly comparable to that of CMIP5 models (employed in EURO-CORDEX), indicating modest enhancements in modeling capabilities for extreme events, it is notable that the CMIP6 ensemble predicts more pronounced warming in the Mediterranean compared to the CMIP5 ensemble.

The rapid emergence and severity of these events underscore the urgent need for effective adaptation strategies and a reevaluation of projections to better prepare Western Mediterranean countries for future climate risks. This study aims to deepen understanding of these dynamics, offering insights that could help guide regional response efforts and support the development of policies to enhance climate resilience, emphasizing the critical role of refined, high-resolution models like EURO-CORDEX in capturing and responding to these trends.

How to cite: Tejedor, E., Benito, G., Serrano-Notivoli, R., González-Rouco, F., Esper, J., and Buntgen, U.: Anticipating the Future: The 2022 Heatwave as a Harbinger of Climate Extremes in the Mediterranean Region., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1013, https://doi.org/10.5194/ems2024-1013, 2024.

Ireland has a rich heritage of long-term air temperature observations. The analysis of long-term historical instrumental records is essential to assessing extreme air temperature indices and examining modern climate warming within a historical context. This presentation highlights the methodologies for data rescue, quality control, homogenisation, and assessment of trends in extreme air temperature indices back to the 19^th century.

This research assessed the frequency, duration, intensity and geographical distribution of the daily extreme air temperature indices recommended by the ETCCDI (Expert Team on Climate Change Detection and Indices) based on long-term rescued, quality-controlled and homogenised maximum and minimum air temperature series across Ireland.

Significant increasing trends were assessed in the seasonal and annual maximum and minimum air temperature series. Additionally, significant increasing trends were assessed in the warm nights (+7.5 nights), warm days (+6.8 days), warm spell duration index (+3.9 days), growing season length (+22 days), coldest night (+2.7 °C) and coldest day (+1.5 °C) in the period 1885–2018 in Ireland. Significant decreasing trends were identified in the frost days (−13.7 days), cold days (−9.3 days), cold nights (−7 nights), cold spell duration index (−6.9 days) and diurnal air temperature range (−0.1 °C) in the same period in Ireland.

References

Mateus, C., Potito, A. and Curley, M., 2020. Reconstruction of a long‐term historical daily maximum and minimum air temperature network dataset for Ireland (1831‐1968). Geoscience Data Journal, 7(2), pp.102-115.

Mateus, C., 2021. Searching for historical meteorological observations on the Island of Ireland. Weather, 76(5), pp.160-165.

Mateus, C., Potito, A. and Curley, M., 2021. Engaging secondary school students in climate data rescue through service‐learning partnerships. Weather, 76(4), pp.113-118.

Mateus, C. and Potito, A., 2021. Development of a quality-controlled and homogenised long-term daily maximum and minimum air temperature network dataset for Ireland. Climate, 9(11), p.158.

Mateus, C. and Potito, A., 2022. Long-term trends in daily extreme air temperature indices in Ireland from 1885 to 2018. Weather and Climate Extremes, 36, p.100464.

How to cite: Mateus, C.: Long-term trends in extreme air temperature indices in Ireland, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-956, https://doi.org/10.5194/ems2024-956, 2024.

How do societies respond to varying climates? This query not only piques academic curiosity but also holds the key to how our society can adapt to the ongoing climate change. To shed light on this, we focus on the Tenpō Famine, a pivotal event in the 1830s that was one of the most severe famines due to poor harvests caused by an abnormal climate. By investigating such a significant occurrence, we aim to provide insights into vulnerable areas in the modern era. We chose the Tenpō Famine for the case study because it falls within a period for which analytical data are readily accessible (e.g., old diaries and price records). It occurred nationwide with regional differences, which makes it valuable for gaining a broad picture of the effects of climate variation. To understand the impact of climate change on societies in the past, it is necessary to consider social and economic information from such periods. This involves reconstructing spatial patterns of climate variation at a higher temporal resolution than provided by annual data. Japan has a wealth of historical diaries from 1821 to 1850.   Using these records, we developed a method to estimate solar radiation, enabling the successful reconstruction of historical solar radiation for all seasons at a higher temporal resolution than provided in annual data. Weather descriptions were categorised to estimate solar radiation, making possible analyses of climate variability and its effects at the monthly time scale. This represents a novel approach for analysing climate impacts on agriculture and the economy during this period. We then correlated the reconstructed solar radiation to rice prices, revealing a significant relationship between climatic anomalies and economic stability, particularly during the summer growing season. The results show that lower solar radiation, indicative of poor weather conditions, corresponded to higher rice prices, particularly during the summers of 1833 and 1836. The temporal resolution of economic data has also improved recently. Hence, this study contributes to understanding historical climatic impacts on society by providing an even more refined temporal resolution than was previously available. This underscores the need to integrate climate data into economic analyses to better understand the dynamics of societies facing environmental challenges. Our study is particularly relevant in the context of contemporary climate change and provides historical perspectives that can inform current policies and adaptation strategies.

How to cite: Ichino, M., Masuda, K., Mikami, T., and Takatsuki, Y.: Abnormal Climate and Market Economy: The Impact of Solar Radiation on Rice Prices during the 1830s Famine in Japan, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-376, https://doi.org/10.5194/ems2024-376, 2024.

Meteorological data recorded in logbooks form the sailing era has received increased attention in the last decades. The daily and even sub-daily data kept by seamen, allows extending back in time the time series of wind and other relevant variables along the historically busiest naval routes. Different projects have integrated these data in the ICOADS open database, and the availability of this massive data collection in its raw format has inspired the development of a new class of climatic indices based on the wind direction variability known as “directional indices”. They have the advantage that wind direction is the only variable needed, and little or no metadata are required to convert historical observations to current standards. This minimizes the possibility of appearance of data-induced inhomogeneities and non-climatic biases in the resulting series. On these bases, during the last decade, our team has worked in the development of a suite of instrumental circulation indices for remote areas and for periods of time significantly longer than those attained by any other methodology based uniquely on in-situ meteorological observations.

Directional indices have been applied to the construction of NAO-like records, to the evaluation of the intensity of several monsoons, to the examination of the variability of local wind systems and even to the analysis of the long-term variability of upwelling favorable winds for several Eastern Boundary Upwelling Systems. The common factor of all these investigations is the lack of stationarity in the relation of the structures analyzed and the classical modes of global climate variability such as El Niño / Southern Oscillation, the Atlantic Multidecadal Oscillation, both Annular Modes, etc. Our combined results provide direct instrumental evidence of the lack of stationarity between global variability modes and their associated local impacts at worldwide scale, challenging the implicit assumption of stationarity that underlies the use of proxies for climate reconstruction.

How to cite: Gallego, D., Alvarez-Castro, C., Barriopedro, D., García-Herrera, R., and Peña-Ortiz, C.: On the ubiquitous unstable relation among climate modes and their local effects, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-456, https://doi.org/10.5194/ems2024-456, 2024.

In the paper, we focused on the possibility of reconstructing information about occurrence of strong and very strong, potentially high-impact, winds in the 18th century. The analysis was dedicated to the city of Gdansk, for which there are massive sources of various historical data - a long series of instrumental data and detailed weather notes. Among instrumental data, sub-daily weather data on wind force and sea level pressure from the period 1739-1772 were used; they were measured from two to four times a day, depending on the year, by Michael Christian Hanov, a pioneer of regular meteorological instrumental measurements in Gdansk. He has developed a special classification of wind force, dedicated to the city's conditions. One of our tasks was a translation of Hanov’s classes of wind force into Bft scale. Instrumental data were combined with a weather notes made by the same observer. We compared the above mentioned information with detailed weather chronicles published by Gottfried Reyger (Filipiak et al. 2018). The monthly number of strong winds classified according to Brazdil et al. 2004 as: fresh and strong breeze (5-7°Bft), gale (8-9°Bft) and storm (10°Bft) was reconstructed. The results of analyzes based on various data sources indicate the differentiated monthly number of strong winds, depending on the source used. The further actions towards the elimination of some inconsistencies were taken. The frequency of occurrence of strong winds in the 18th century in Gdansk was further compared with contemporary results taken at synoptic station Gdansk Northern Harbour from the period 1987–2012.

The work was done within a NCN project entitled The occurrence of extreme weather, climate and water events in Poland from the 11th to 18th centuries in the light of multiproxy data, supported by the National Science Centre, Poland, project No. 2020/37/B/ST10/00710.

References:

Brázdil R, Dobrovolný P., Štekl J., Kotyza O., Valášek H, Jež J., 2004, History of weather and climate in the Czech Lands VI: Strong winds, Masaryk University, Brno.

Filipiak J., Przybylak R., Oliński P., 2018. The longest one-man weather chronicle (1721–1786) by Gottfried Reyger for Gdańsk, Poland as a source for improved understanding of past climate variability. International Journal of Climatology, 39, 2, 828-842, doi: 10.1002/joc.5845.

How to cite: Filipiak, J., Przybylak, R., Pospieszyńska, A., Oliński, P., and Araźny, A.: Reconstruction of strong winds in Gdansk, Poland, in the 18th century, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-665, https://doi.org/10.5194/ems2024-665, 2024.

For the first time, a comprehensive database of strong winds related to the period prior to 1800 has been created for Poland by team of climatologists and historians based on all documentary evidence available for us. The work was done within a NCN project entitled The occurrence of extreme weather, climate and water events in Poland from the 11th to 18th centuries in the light of multiproxy data. The following documentary sources were used: handwritten and unpublished, published, and so-called “secondary” literature. The database contains detailed information about the occurrence of strong winds (the location/region, time, duration and indexation for intensity, extent and character of damage), as well as the exact textual content of the original weather note, the name of the source, and an evaluation of the source’s quality. Indexation of intensity, initially done by the author of a particular contribution (record), was then evaluated by the whole team preparing the database. Four categories of strong winds were delimited: 1 − fresh and strong breeze (Beaufort scale 5–7), 2 − gale (8–9), 3 − storm (10–12), and 4 − squall (i.e., gusty wind during a thunderstorm). Extent and character of damage was estimated based on the proposition given by Brázdil et al. (2004), slightly modified by us to include the Baltic Sea and its influence on coastal parts. In the database, ~1,200 thus-defined strong winds were identified. The first weather note reporting an occurrence of strong wind (gale) was found for the year 1283. In the paper, the preliminary results describing frequency of occurrence of strong winds in the area of Poland and in its different regions will be presented. In addition, results of the extent and character of damages will be shown. Some case studies of particularly strong winds (including identified tornadoes) will be analysed in detail. The frequency of occurrence of strong winds in the historical period (1201–1800) and some of its sub-periods will be compared with contemporary results taken from 12 meteorological stations (Świnoujście, Chojnice, Olsztyn, Suwałki, Poznań, Kalisz, Warszawa, Siedlce, Kraków, Tarnów, Wrocław and Opole) from the period 1991–2020.

The work was supported by the National Science Centre, Poland, project No. 2020/37/B/ST10/00710.

Reference:

Brázdil R, Dobrovolný P., Štekl J., Kotyza O., Valášek H, Jež J., 2004, History of weather and climate in the Czech Lands VI: Strong winds, Masaryk University, Brno.

How to cite: Przybylak, R., Araźny, A., Filipiak, J., Oliński, P., and Szwaba, A.: Strong winds in Poland from the 13th to 18th centuries, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-321, https://doi.org/10.5194/ems2024-321, 2024.