This session invites abstracts on the identification and rescue of historical weather observations from previously unexplored locations and periods. For example, former European territories and administrative regions, and historical weather records from newly independent countries in Asia and Africa. Contributions may focus on new data sources, innovative methods of data extraction, or applications of rescued data. We particularly welcome work using automated AI/ML workflows, citizen science approaches, best practices and studies applying historical data to understand climate extremes, floods, and other risks. This session will further the work on climate adaptation by taking extreme historical climate events into account.
Historical meteorological observations are crucial for better assessing past climate variability and trends in the frequency, intensity, duration, and distribution of extreme weather events, and for placing the current climate change into historical context. Specifically, long-term high-resolution data at daily and hourly scales are essential for a more accurate assessment of past and rare extreme weather events. Historical meteorological observations are crucial for generating climate products, such as reanalysis and gridded datasets.
Ireland has a great heritage of historical instrumental meteorological observations (Mateus, 2021). This presentation will primarily focus on four historical meteorological collections from Ireland, which have been rescued from the original paper sources and digitally preserved, including examples of data application for climate research:
1) Meteorological observations from over 40 locations in Ireland registered from 1783 to 1854 and preserved in the archives of the Royal Irish Academy. The meteorological records include observations of air temperature, maximum and minimum air temperatures, dry and wet bulb temperatures, sea temperature, rainfall, pressure, wind direction and force, cloud cover, cloud form, tension of vapour and weather remarks.
2) Meteorological observations from over 70 locations in Ireland registered from 1808 to 1939, which were published in newspapers. The majority of the original manuscripts are not traceable; hence, the importance of rescuing these meteorological observations from newspapers. Observed climate variables include maximum and minimum air temperatures, dry and wet bulb temperatures, rainfall, pressure, wind direction and speed, maximum air temperature in the sun, humidity, cloud cover, and qualitative remarks on the state of the weather.
3) Meteorological observations from Dunsink Observatory from 1818 to 1850.
4) A network of meteorological observations from multiple sites in Ulster (1796 – 1919), which includes the long-term series registered at the Linen Hall (1796 – 1895) and Queen’s College Belfast (1850-1919).
Many well-known historical extreme weather events in Ireland, such as extreme air temperatures and storms, are documented in historical instrumental and documentary meteorological records.
The metadata and data from these meteorological collections have been rescued and will be made available as open access in forthcoming peer-reviewed publications and digital datasets.
References
Mateus, C., 2021. Searching for historical meteorological observations on the Island of Ireland. Weather, 76(5), pp.160-165.
How to cite: Mateus, C.: Data rescue of historical meteorological observations from the Island of Ireland (1783 – 1939), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10795, https://doi.org/10.5194/egusphere-egu26-10795, 2026.
This study reconstructs the 18th century climate in the former Principality of Transylvania using direct historical sources (chronicles, administrative documents, travel accounts, etc.). The investigation focuses on identifying temperature and precipitation anomalies, as well as extreme climatic events that caused major disruptions in agriculture, public health and the socio-economic structure of local communities. Documented climatic events (abnormally cold winters, excessive precipitation, floods, droughts and associated food crises) were systematically coded and compared with the proxy data to validate the reconstruction. The convergence between documentary evidence and indirect records confirms the presence of a colder and wetter climate than the current one, characteristic of the persistent influence of the Little Ice Age in Europe. The extreme phenomena were reflected in frozen rivers, prolonged cold springs, rainy summers, frequent floods, locust invasions, poor harvests and different epidemics. In the absence of systematic historical-climatic studies for the formal Romanian Principalities, the results highlight the decisive role of climatic factors in shaping pre-modern social vulnerability.
How to cite: Caciora, T. I., Gaceu, O. R., Baias, Ș., Dudaș, M., Stupariu, M., Chioran, G., and Georgiță, M.: Climate extremes and human response in the former Romanian Principalities during the 18th century. A historical–climatological perspective, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-55, https://doi.org/10.5194/egusphere-egu26-55, 2026.
ROPEWALK, funded by the AP Møller Mærsk Fund, is a joint initiative of the Danish National Archive and the Danish Meteorological Institute, which aims at digitizing and transcribing all weather observations in Danish ship journals and logbooks stored in the Danish National Archive, consisting of more than 750 shelf metres beginning as early as the 1680s. With the exception of the Napoleonic wars, the data is complete.
The archive keeps ship journals over large parts of the Northern Atlantic, with two regions of particular interest, Greenland and the Øresund:
The Greenlandic Trade Company had a monopoly for commerce with the colony of Greenland for nearly 200 years. The company conducted these "Greenland Voyages" to western Greenland several times per year, starting as early as 1721 and through the 1930s. Weather observations from these voyages often include detailed sea ice observations.
Every ship passing the sound or belts in Denmark had to pay for passage between 1426 and 1857. To ensure payment, Danish war ships were placed at strategic locations in Øresund and Great Belt. Weather observations on board of these ships (some as often as every half hour) go back to the end of the Little Ice Age.
Up to roughly 1750, the data consists of diary-like daily notes in free text. However, starting already in the 1710s, observations are recorded as numbers in preprinted tables. We have scanned and transcribed this latter dataset, which took 13 person-years, resulting in 2.1 million images covering more than 2.5 TB of data. We then constructed a data model, trained a machine learning algorithm and conducted metadata enhancement and quality control, the latter both in an automatised way and (in a subproject by means of an app we constructed) with the help of pupils in the final grades of Danish primary schools. Free text data will be considered later.
We are now able to present first results. When the project is finished, all transcribed data will be made publicly available for future research or reanalysis projects.
How to cite: Stendel, M., Kronegh, A. J., Skov, E. H., Møller, T., and Andersen, M.: Three centuries of weather observations on board of Danish ships: First results from ROPEWALK (Rescuing Old data with People's Efforts: Weather and climate Archives from LogbooK records), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1690, https://doi.org/10.5194/egusphere-egu26-1690, 2026.
Australian studies of daily rainfall extremes are often confined to the 20th century due to data limitations prior to 1900, leaving gaps in our understanding of earlier climate variability. The aim of this study was to capture the spatio-temporal evolution of widespread extreme rainfall event and understanding how many minimum numbers of station observation we need to do so, during the 19th Century. Here we focus on the region west of the Great Dividing Range in New South Wales, where we have a number of long weather records collected by early settlers. This region encompasses vital catchments that supply fresh water to millions, sustaining agriculture and is home to over 70% of Australia’s threatened species.
We use digitised instrumental records from the Bureau of Meteorology dating back to 1858 to identify widespread extreme rainfall events. The main challenge faced during the study was the quality and sparsity of data across the study region. Adaptive kernel density estimation was applied to convert individual rainfall data points into density plots. Trajectories for widespread extreme rainfall event was extracted. Dynamic time warping technique was used to determine the minimum numbers of station observation.
In this presentation, I will provide more detail of this new methodology, including the novel approach we took to factor in the impact of changing station network density.
How to cite: Kulkarni, R., Ashcroft, L., and Verdon-Kidd, D.: Forgotten storms of the past: extreme rainfall events in New South Wales during the 19th century, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4579, https://doi.org/10.5194/egusphere-egu26-4579, 2026.
Millions of historic handwritten weather observations remain locked in paper records, leaving this valuable information inaccessible for analysis and at risk of permanent loss. Manual transcription of these records is highly accurate but time-consuming and costly, making this a task where AI could play a pivotal role. Traditional optical character recognition (OCR) methods struggle with the irregularities of historical handwriting and tabular layouts. This study proposes a novel automated digitization pipeline that leverages multimodal large language models (MLLMs) alongside table structure recognition (TSR) and OCR techniques to transcribe handwritten climate records efficiently and accurately.
First, we compare two MLLMs, and find that by guiding the MLLM with structured prompts and validating outputs based on physical relationships between meteorological variables, we achieve transcription precisions of up to 97%. This rivals human accuracy, though at the cost of a lower inclusion rate due to strict filtering. Second, we link MLLM outputs to detected table structures to generate training data for fine-tuning a pretrained OCR model. Fine-tuning significantly enhances transcription quality, improving from 19% to 81% on unseen data. Challenges remain due to the complexities of TSR in historical documents, reducing the quality of our training data. Despite these limitations, our research establishes a viable framework for scaling data rescue efforts, bringing us one step closer to unlocking centuries of climate data for scientific analysis.
How to cite: van der Schee, M., Whan, K., Peeters, T., Shapovalova, Y., van Ekris, J., Garcia Marti, I., Bergman, B., and Zaanen, K.: Using Multimodal LLMs for Digitising Handwritten Climate Records, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2509, https://doi.org/10.5194/egusphere-egu26-2509, 2026.
Long-term instrumental climate records are essential for understanding past climate variability and extremes. Monthly-scale datasets for the 18th and 19th centuries are relatively well-established, but high-resolution (daily and sub-daily) observations remain fragmented and difficult to access. This limitation restricts the analysis of historical weather extremes and dynamical processes necessary for climate adaptation.
We present HIST-DAILY, a new dataset of daily and sub-daily instrumental and non-instrumental weather observations from Europe prior to 1900. HIST-DAILY assembles rescued observations from a wide range of historical sources, including national meteorological services, scientific societies, observatories, and archival publications, alongside newly digitized material from the PALAEO-RA project.
The dataset focuses on near-surface air temperature and atmospheric pressure, with supplemental data of wind direction and precipitation. To facilitate integration into global data rescue workflows, all records are provided in the Station Exchange Format (SEF). This ensures consistent metadata and full traceability. Our standardized pre-processing includes calendar harmonization, unit conversion, and rigorous quality control. Ultimately, HIST-DAILY provides high-resolution empirical evidence needed to better understand past climate dynamics and improve the accuracy of historical weather reconstructions.
How to cite: Corbella, C. and Brönnimann, S.: HIST-DAILY: A dataset of daily and sub-daily European weather observations before 1900 , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7221, https://doi.org/10.5194/egusphere-egu26-7221, 2026.
Over the last decades, increasing attention has been directed toward the investigation of historical snowfall variability on a global scale, with a particular focus on mountainous regions. Snow represents a fundamental element of the hydrological cycle and plays a key role in the Earth’s energy balance by regulating surface albedo. Moreover, it exerts a strong influence on mountain ecosystems and on biogeochemical processes. In the context of ongoing climate change, which is increasingly threatening the cryosphere and high-altitude environments, the reconstruction and analysis of long-term historical snowfall records are essential to evaluate past variability and identify prevailing trends.
However, for several reasons, many mountain areas remain under-researched. In the Mediterranean, an example in this sense is represented by the Apennine region (Italy). A considerable lack, in fact, exists in the knowledge of the past snowfall variability for this area, although it has a good heritage of past in situ observations.
In this context, the present work seeks to partially bridge this gap by rescuing historical snowfall measurements collected in the Apennines. More specifically, the recovered dataset consists of monthly observations of the three snow-related variables, i.e. snow cover duration, number of days with snowfall and total height of new snow, collected at 395 stations located between 288 and 2165 m a.s.l. The data, originally available as scanned images in portable document format, have been digitized following the World Meteorological Organization standard practices. After a cross-check, the digitized data went through three different quality control tests: the gross error test, which verifies whether the data are within acceptable range limits; the consistency test, which involves an inter-variable check; and the tolerance test, which is focused on outlier detection. In addition, the available time series were subjected to homogenization tests using the Climatool toolbox.
The result of this process is a new historical dataset that includes digitized and quality-controlled snow-related observations collected from 1951 to 2001 in the Apennines. These data are critical to enhancing and complementing previously rescued historical datasets in the mountain regions and constitutes an added value for research focused on the comprehension of climate dynamics in mountainous areas, as well as on future changes in snow precipitation in the Mediterranean region.
How to cite: Capozzi, V., D'Esposito, L., Fucci, A., Lino, S., Serrapica, F., Gulisano, F., Fusco, G., and Budillon, G.: Rescue of historical snowfall data collected in the Italian Apennines, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22590, https://doi.org/10.5194/egusphere-egu26-22590, 2026.
Maritime weather data from historical ship logbooks are used to assess 19th century surface wind and precipitation conditions across the world oceans. Housed across several New England archives (e.g., Providence Public Library, New Bedford Whaling Museum, Nantucket Historical Association, and Martha’s Vineyard Museum), logbooks of U.S. whaling voyages contain systematic weather observations (e.g., wind strength/direction, sea state, precipitation) at (sub-)daily temporal resolution. As part of the eWHALES (extracting Weather data: Historical Analysis of Logbooks from Early Ships) project, qualitative wind descriptions by the whalers from >200 ship logbooks are quantified to generate a dataset with >80,000 daily records of wind strength and direction en route and covering key whaling grounds in the Atlantic, Pacific, Indian, and Southern Ocean during the period 1820-1900 CE.
Following extensive quality control, we find overall good agreement in wind strength and direction for the whaling logbook wind records with reanalysis products for mean and seasonal climatologies around the world. For the North Atlantic with the densest coverage of whaling records, interannual variations in the basin-wide wind field associated with variations in the Azores High subtropical pressure system are also reflected in the whaling ship recordings. Predominant precipitation patterns around the world oceans can be captured and variations across a range of timescales are assessed.
Our results demonstrate that the historical records provide an important long-term context for changing maritime wind and rainfall patterns in remote ocean regions lacking observational records during the 19th century. Challenges and opportunities for data rescue and digitisation of maritime weather records in these under-utilised historical ship logbooks for climate purposes will be discussed.
How to cite: Ummenhofer, C., Wimberly, F., Sander, N., Giacoppo, T., Bice, C., Muench, B., and Walker, T.: A breeze from the past: Maritime wind and rainfall patterns from historical New England whaling ship voyages in the 19th century, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14709, https://doi.org/10.5194/egusphere-egu26-14709, 2026.
Early instrumental observations are fundamental to understanding historical climate variability, but long-term instrumental records remain scarce outside Europe and North America. This data gap limits our ability to assess climate change over decades globally and highlights the urgent need to rescue and harmonize historical observations from data-poor regions. The Global Early Instrumental Monthly Meteorological Multivariable Database (HCLIM) provides a unique resource for rescued early observations, but the systematic evaluation of automated homogenization methods for such data remains limited.
In this study, we assess the performance of two widely used automated homogenization techniques, CLIMATOL and BART (Bayesian Analysis of Records), applied to early instrumental temperature series from HCLIM. The performance of the methods is evaluated based on data storage in preprocessed datasets, breakpoint characteristics in homogenized series, and consistency with the 20CRv3 reanalysis. French and South Asian station networks are used as representative examples of dense and sparse networks, respectively.
Our results show minor structural differences in preprocessing across methods, with BART retaining fewer but longer and more consistent records (80%) compared to CLIMATOL (96%). BART detected approximately eight times more breakpoints than the other methods, indicating higher sensitivity to inhomogeneities. Strong regional and temporal variation in breakpoint detection was observed. Comparisons with 20CRv3 show that BART generally shows the lowest deviations and highest consistency, especially in dense station networks such as France. In contrast, CLIMATOL shows mixed performance depending on network density and local climate variability. Larger deviations are found in sparse regions such as Southeast Asia, highlighting the strong influence of station density on homogenization quality.
These findings demonstrate that automated homogenization methods differ significantly in data storage, breakpoint sensitivity, and reconstruction capability. Overall, BART shows the highest accuracy, while CLIMATOL shows balanced performance. This study contributes to best practices for applying automated homogenization to salvaged historical data and supports ongoing work to expand climate records in data-sparse regions, improve the basis for climate model validation, reanalyses, and assessment of historical climate extremes relevant to adaptation planning.
How to cite: Lundstad, E.: How Reliable Are Automated Homogenization Methods for Early Climate Records?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21478, https://doi.org/10.5194/egusphere-egu26-21478, 2026.
The National Meteorological Archive holds a significant collection of international climatological data from locations around the world. This takes the form of large bound volumes containing monthly sheets of hand written daily weather observations, the earliest of which dates from 1846. Data is present from locations around the globe including Africa, the Middle East, Europe, Antarctica, Oceania, the Caribbean, Malaysia and the Far East, the Americas
These volumes hold a vast quantity of early and hugely valuable weather observations for areas of the globe which are often data sparse in climate modelling. The National Meteorological Archive has worked with colleagues across the Met Office and across wider UK Government to implement the large scale scanning of all international climate returns held in the archive.
This paper will discuss the role of archives in unlocking access to critical historical climate data and, using the International Climate Returns as a case study, will demonstrate the key logistical and strategic planning required for a successful short duration high intensity archival imaging project. It will also cover the potential additional activities which can be associated with such a project and the potential value to which such data may be put once fully recovered via AI or human led keying techniques.
How to cite: Ross, C.: Unlocking the gold mine - making international climate data from the National Meteorological Archive available for climate science, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3028, https://doi.org/10.5194/egusphere-egu26-3028, 2026.
The growing evidence of an anthropogenically induced climatic change and the need to compare present day climate with that of past centuries, has boosted the search of early meteorological data from all kind of historical archives. The objective of this work is to present new data from Nigeria corresponding to the 1820s decade. This period coincides with the last years of the so-called ‘Dalton Minimum’, a period of minimum solar activity and intense volcanic eruptions. Data sources are the books describing the expeditions by Hugh Clapperton from 1822 to 1827 into the interior of Africa. Instrumental measurements of temperature and pressure, and qualitative descriptions of the “state of weather” (wind, rain, fog, thunderstorms, cloudiness) in some localities of the country were recorded. These observations are compared with modern instrumental records. Results show an interesting overview on climate conditions in this Sahelian area during the beginning of the 19th century.
How to cite: Rodrigo, F. S.: Meteorological observations in the expeditions by H. Clapperton into the interior of Africa, 1822-1827., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1669, https://doi.org/10.5194/egusphere-egu26-1669, 2026.
An effective educational tool to understand the Earth’s climate system, its causes, and the consequences of climate change can be the recovery and digitization of historical meteorological data. In this context, high schools and universities play a key role in climate education by engaging both students and teachers.
In 2023, the project “Let’s Not waste Time: Adopt a Historical Series of Meteorological Data of Rome” was launched within the PCTO programs promoted by Sapienza University of Rome. The activity involves digitising one year of data from the Meteorological Register of the historic Collegio Romano Observatory (founded in 1787) and comparing temperature data with measurements taken 100 years later.
The project aims to: (i) engage students in rediscovering historically and scientifically valuable meteorological data preserved on paper records, and (ii) contribute to the recovery and digitization of historical data, raising awareness of the importance of long-term observations for studying climate trends. So far, about 80 high school students from two schools in Rome and its province have participated. This contribution presents the project structure, results from the first two years, and an evaluation of its educational impact.
How to cite: Francesca, F., Di Bernardino, A., Erriu, M., Falasca, S., Boccacci, G., Iafrate, L., and Siani, A. M.: Exploring the role of Italian transversal skills and orientation programmes for high school students as Tools for Climate Education through Data Rescue Initiatives, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7905, https://doi.org/10.5194/egusphere-egu26-7905, 2026.
Long-term weather records are often preserved in archives still in paper format. These data come from different sources and represent a crucial starting point for understanding past climate, a reference for validating climate models and an essential input for reanalysis products. This issue affects both data-rich regions and data-sparse areas. Over recent decades, numerous climate data rescue initiatives have been launched worldwide. These projects aim to safeguard historical observations by scanning, transcribing and analyzing them, making the data accessible to the scientific community. One of these initiatives is presented in this study, ReData (Recovery of Data), launched in 2017 by the MeteoNetwork Association in collaboration with the University of Milan. The project aims to scan and digitize daily weather bulletins available from 1879 to 1940, covering Italy as well as some former colonies and surrounding territories, originally issued by the Italian Royal Central Meteorological Office. The scanning phase has been finished, producing a collection of 99,518 pages (about 200 GB) which is now freely available (https://doi.org/10.13130/RD_UNIMI/R1GVKF). Digitization is currently ongoing through the Zooniverse platform (https://www.zooniverse.org/projects/meteonetwork/redata) where volunteers from around the world can contribute by transcribing 12 meteorological parameters for a station of their choice. The transcription of one station day takes about one minute. Since the project launch on Zooniverse in December 2024, more than 10 years of data have been digitized for 37 stations, with an average of about 5000 classification per week and a stable number of 50 to 100 active weekly participants. To facilitate quality control, each measurement was initially transcribed by three different volunteers. Given the high quality of the transcriptions (around 99% of the data show agreement between two out of three independent digitisations), it was later decided to reduce the number of redundant digitisations from three to two, thereby shortening the overall transcription time. Overall, the project provides valuable input for reanalysis models and contributes to a better understanding of historical climate variability over the Italian peninsula, offering substantial scientific and cultural value.
How to cite: Manara, V., Ceppi, A., Brugnara, Y., Buccheri, G., Caruso, G., Cerri, L., Di Giovanni, M., Giazzi, M., Luperi, L. L., Ronca, L., Sogno, E., and Maugeri, M.: The ReData Project: Scanning and Digitization of Historical Daily Weather Bulletins through Citizen Scientists, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10352, https://doi.org/10.5194/egusphere-egu26-10352, 2026.
Italy has long played a pivotal role in the development of meteorology, from the invention of key instruments to the establishment of some of the earliest international observational networks. Over the past three centuries, this legacy has resulted in a vast and valuable archive of meteorological data preserved in Italian repositories. Although numerous initiatives have contributed to safeguarding parts of this heritage, a substantial fraction of the records remains available only in paper format. These collections are particularly vulnerable to physical deterioration, putting at risk data of considerable scientific value for meteorology, climate science, and climate change assessments.
This study presents a recent project developed by the Italian Association of Atmospheric Sciences and Meteorology (AISAM) within the framework of Climate Data Rescue (Cli-DaRe) initiatives. In particular, the Cli-DaRe@Images project, launched in 2024 and close to its end, integrates education and climate change awareness with the recovery of historical meteorological data. The project actively involves high school students in the Trentino region in the digitization of meteorological records preserved at the San Bernardino Library in Trento.
Following the photographic acquisition of the original documents, the data will be transcribed into digital spreadsheets, thereby recovering and making accessible a priceless scientific heritage. The project adopts a Citizen Science approach, moving beyond a traditional educational model, in which students are passive recipients of knowledge, toward one in which they become active contributors to scientific research. Through this process, participating students gain firsthand experience in the digital retrieval of historical meteorological data and manuscripts in addition to the subsequent processing.
How to cite: Tadiello, A., Carpentari, S., Ceppi, A., Manara, V., Maugeri, M., Beltrano, M. C., Brugnara, Y., Franceschini, I., Brunetti, M., Giovannini, L., Orlando, F., Pisani, S., and Zardi, D.: Cli-DaRe@Images: Citizen Science for Italian Climate Data Rescue with Images, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11001, https://doi.org/10.5194/egusphere-egu26-11001, 2026.
Snow depth is a key climate variable that plays an important role in the hydrological cycle, surface energy balance through albedo control and the functioning of mountain ecosystems. In Italy, snow monitoring was historically carried out by the Italian National Hydrological and Mareographic Service, which managed hydro-meteorological observations from 1917 to 2002 through 14 regional compartments defined according to the main river catchments, now transferred to regional authorities. Despite its potential scientific importance, the snow dataset is available primarily in paper-based hydrological yearbooks, remaining mostly unexploited. However, the scanned images of the original hydrological yearbooks are available via the ISPRA portal (http://www.bio.isprambiente.it/annalipdf/), thanks to a dedicated digitisation project carried out between December 2003 and September 2012.
Significant efforts have been made to digitize historical snow depth observations from the hydrological yearbooks, particularly for areas of the Apennine region. In parallel, for the Alps, additional programs have focused on the analysis and harmonisation of long-term snow depth records that were already available in digital form, taken from a variety of regional and local organizations throughout the Alpine area and surrounding countries. However, there are still significant temporal and spatial gaps, especially before 1970.
The objective of this study is to further close these gaps by recovering additional snow depth measurements from historical hydrological yearbooks for the Italian Alps that were not included in previous compilations, specifically from Parma,Venice and Genova sections. We are applying an optical character recognition (OCR) technique based on an algorithm designed to extract tabular snow data from scanned archival documents. This method will allow the digitization of previously unavailable observations, improving the data coverage both in time and space. The resulting dataset will be an important contribution to long-term snow variability research, climate change assessments, and hydrological applications in Alpine regions.
How to cite: Spezza, A., Almagioni, C. D., Arcuri, B., Brunetti, M., Ceppi, A., Diolaiuti, G. A., Fugazza, D., Manara, V., Maugeri, M., Nicoli, D., and Senese, A.: Retrieval of unexploited historical snow data from hydrological yearbooks in the Italian Alps, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11652, https://doi.org/10.5194/egusphere-egu26-11652, 2026.
This study presents a recent project in which the Italian national agency for meteorology and climatology (Italia Meteo) and the Italian Association of Atmospheric Sciences and Meteorology (AISAM) with the contribution of some research institutes and universities collaborate on climate data rescue activities.
This initiative builds upon the Dieci e Lode project (https://aisam.eu/10-e-lode-en/), carried out during 2023–2025, which aimed to rescue and scan meteorological data collected in former Italian colonies and territories. Among the unrecovered materials, a particularly significant subset includes data from regions administered by Italy at various times between the late 19th and early 20th centuries, including Eritrea, Somalia, Ethiopia, Libya, the Dodecanese Islands, Albania, Dalmatia, and Istria. The project involved an extensive search for meteorological records from these areas, covering the relevant historical periods.
Under the framework of Copernicus programme, this new mission aims to organize and initiate the digitization of these historical colonial datasets. The first step involves reviewing approximately 40,000 scans produced within the previous project and identifying which documents are most relevant for digitization and which should be prioritized. Subsequently, the digitization process is implemented, involving both manual data entry through citizen scientists and students, and the application of AI/ML-based OCR techniques. In addition to the recovery of specific data series, the project is important for establishing a permanent framework for data rescue activities to complete the digitization of the vast amount of data.
How to cite: Brunetti, M., Ceppi, A., Arcuri, B., Bellezza, E., Cacciamani, C., Kibu, G., Stefanini, F. M., Maugeri, M., Nicoli, D., Nieus, T., Pelosini, R., Pietrollini, G., Pisani, S., Zardi, D., and Manara, V.: Digitization of Historical Meteorological Data from Africa: Extending the Dieci e Lode Project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12088, https://doi.org/10.5194/egusphere-egu26-12088, 2026.
This study presents professional work carried out within the Climate Directorate of the LNMC outside regular working hours. Its primary objective is to initiate rescue of Libya’s climate data by scanning historical weather and climate records stored in the LNMC’s Climatic Archive, which operates under the mandate of the Climate Directorate.
A data heritage of enormous scientific value has been accumulated in Libya’s Climatic Archive since the early 20th century. Part of these data were observed during the Italian colonial period (1911–1943), when Libya was under Italian rule. However, a substantial portion of Libya’s historical climate data, dating back to the colonial era, remains scattered across several European archives (particularly in the UK and Germany) and still needs to be recovered.
The LNMC archive currently contains approximately 45,201 items, including registers, notebooks, and publications (updated as of May 2025). In addition, the archive continues to receive new registers each year, as Libyan meteorological stations, including automatic weather stations (AWSs), still record observations in logbooks.
To date, only about 6,600 registers (approximately 198,000 pages) have been imaged and stored in JPG and PDF formats. Moreover, LNMC has recently received scanned copies of registers and books produced during the Italian colonial period, from Italy. These meteorological observations still require digitization.
In parallel, LNMC conducts digitization activities during regular working hours; however, these efforts are limited to more recent observations, some of which date back to the early 1960s. Additionally, data from some online published studies have been recovered and digitized.
Given that historical data rescue is a key pillar for closing Libya’s early warning gap and for improving the understanding of historical climate variability and change, LNMC plans to accelerate its data rescue activities. This effort is expected to be supported by external donors who have committed to providing scanners and high-capacity server infrastructure.
How to cite: Ceppi, A., Ahmeed, H., Ali, A., Brunetti, M., El Hadi, R., Manara, V., Mansour, S., Maugeri, M., and Eddenjal, A.: Libya Climate Data Rescue Effort , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13069, https://doi.org/10.5194/egusphere-egu26-13069, 2026.
The aim of the Cli-DaRe (Citizen Science for Italian Climate Data Rescue) project is the recovery of historical Italian meteorological data still available only on paper or as scanned documents.
Through the sub-project Cli-DaRe@School, it has been possible, using a citizen-science based approach with the help of high school students and teachers, to digitize the data published in four monographs by the Italian Hydrographic Service: three of them collecting precipitation data for the period prior to 1950 and one with temperature data for the period 1926-1955.
The digitized data are subjected to a quality check to detect transcription errors and inconsistencies in the coordinates. This process is carried out using a hybrid approach, combining automated and manual procedures. This has made it possible to analyze and categorize frequent errors affecting both data and metadata. The methodology has been published in the Bulletin of the American Meteorological Society (https://doi.org/10.1175/BAMS-D-24-0078.1).
For the 1921-1950 precipitation data, the quality check has already been completed, and the records have been compared with those available in existing datasets. Among the 3,614 stations reported in the monograph, 1,907 were already available in digital form in other datasets and were checked for correctness, while the remaining 1,707 stations were digitized within the CliDaRe@School project. The entire dataset is now freely available (https://doi.org/10.5281/zenodo.15084062), and the results of this study have been published in the Bulletin of the Atmospheric Science and Technology (https://doi.org/10.1007/s42865-025-00111-3).
The quality check for the precipitation data for the periods 1916-1920 and pre-1916 is nearly completed, making available respectively 1,526 and 2,193 records. At the same time, two additional processes are ongoing: one aimed at identifying correspondences with existing datasets, and another focused on merging together into single time series records from the three different periods and with the already available more recent data.
These activities will lead to the creation of long-term precipitation series spanning up to 120 years, providing a substantially improved basis for climate analyses over Italy. Such extended and quality-checked time series are expected to support future studies on long-term climate variability and change, as well as the development and validation of high-resolution historical climate reconstructions.
How to cite: Arcuri, B., Brunetti, M., Beltrano, M. C., Bertoldi, G., Brugnara, Y., Cat Berro, D., Ceppi, A., Crespi, A., Manara, V., Maugeri, M., Melada, J., Nicoli, D., Spezza, A., Stefanini, F. M., Sudati, F., and Zardi, D.: The Cli-DaRe project for the recovery of historical Italian meteorological data and construction of long-term precipitation series, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12213, https://doi.org/10.5194/egusphere-egu26-12213, 2026.
Met Éireann, the Irish Meteorological Service, has historical climate records spanning nearly 200 years, many of them hand-written in observer logs. A majority of Ireland’s historical climate extremes (e.g. monthly maximum/minimum temperatures, wind gusts, highest and lowest monthly rainfall) have occurred before the use of sophisticated electronic instrumentation. This inherently raises concerns over the validity of these records compared to today’s modern standards. As such, herein we use a novel standardised procedure for verifying the monthly minimum temperature extremes across Ireland. This approach includes archival research, data rescue, contemporaneous observational and synoptic reports, and a thorough statistical analysis, in order to validate (or negate) the historical records. Through this standardised approach we have verified the veracity of all of the monthly minimum temperature records, including the all-time low temperature record for Ireland of -19.1°C which occurred at Markree Castle in January 1881.
How to cite: Evans, C., O'Sullivan, J., and Curley, M.: The Reassessment of Monthly Minimum Temperature Extremes Across Ireland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3807, https://doi.org/10.5194/egusphere-egu26-3807, 2026.
Posters virtual: Fri, 8 May, 14:00–18:00 | vPoster spot 4
EGU26-3138 | Posters virtual | VPS7
Historical floods of the 19th century in the amazonFri, 08 May, 14:18–14:21 (CEST) vPoster spot 4
Instrumental long-term climate records are scarce worldwide, especially in tropical regions such as the Brazilian Amazon. The lack of systematic data prior to the 20th century limits understanding of long-term climate variability and extreme events. This study is situated within the field of Historical climatology. It aims to contribute to knowledge of climate extreme events that occurred during periods of limited climatological data through analysis, focusing on the flooding events of 1859/60 and 1892 in the Amazon River basin. The research aligns 19th-century historical documents, such as newspapers, periodicals, official correspondence, and travel logs, with climate information from dendrochronological studies to reconstruct the magnitude, duration, and impacts of these flood events. Methodologically, it is constructed through an interdisciplinary approach combining environmental history, historical climatology, and hydrology, using written records as climate proxies that provide crucial information on river levels, rainfall seasonality, and flood persistence. Analysis of tree-rings from the Amazonian trees known as “Cedro-Vermelho” (Cedrela Odorata) indicates that the floods of 1859/60 and 1892 were among, if not the, most severe flooding extremes of the 19th century on the Amazon River basin. Historical descriptions of damage to livestock, farming, agriculture, urban infrastructure, and the living conditions of the population, which mainly consisted of “ribeirinhos”, a traditional culture and way of life near the rivers, back this up. The results demonstrate that rescuing and systematizing historical climate information from a region with a traditional lack of instrumental records helps fill a gap in tropical data. Regions such as those analyzed in this study have often been overlooked in historical climate research. The potential of historical records combined with dendrochronological analysis has proven extremely promising. It allows not only cross-validation of information but also the recovery of climate data through a non-conventional method of analyzing climate before the 20th century, helping to build a more comprehensive understanding of past climate in the vast Amazonian territory.
How to cite: Sousa, K., Granato, D., Neto, A., and Nunes, E.: Historical floods of the 19th century in the amazon, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3138, https://doi.org/10.5194/egusphere-egu26-3138, 2026.
