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Through trilateral cooperation between Indonesia, the Netherlands, and Japan, we have been working on data rescue of rainfall observation records from the Dutch East Indies in the second half of the 19th and first half of the 20th centuries. Digitized daily rainfall data from the beginning of the 20th century revealed clear seasonal changes between rainy seasons and dry seasons at six sites near the equator as well as large differences in annual rainfall and year-by-year changes among the sites. These indicate that the rainfall was influenced by geographical conditions such as the northwest monsoon, the southeast monsoon, and the surrounding seas.

Long-term instrumental meteorological series are crucial for the understanding of interannual-to-decadal variations in climate. Analyzed together with model simulations and climate proxies they may provide new insight into underlying climate mechanisms, such as long-lasting droughts, changes in atmospheric circulation, or effects of volcanic eruptions, and may serve as a basis for the generation of more comprehensive data products in reconstruction or data assimilation approaches. Long-term instrumental meteorological series also serve as a reference against which human induced climate change can be compared. For instance, Hawkins et al. (2017) suggested using the period 1720–1800 as a preindustrial reference, but only few records from this period are currently available. We define a record as a meteorological time series with one variable at one location. There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate dataset for the preindustrial period so far.

The recent transition of US presidential administrations has raised awareness and concern regarding the continuity of access to federal research data.  These data are part of the vital public record of federally-funded research, and their continued availability is critically important to scientific integrity and advancement, governmental accountability, and informed public policy.  The data.gov portal was created in 2009 as a central repository of government research data, and currently hosts over 135,000 datasets.  This information is, according to the 2013 federal open data policy, “a valuable national resource and a strategic asset to the Federal Government, its partners, and the public.”  As such, it is imperative that these data are subject to effective long-term stewardship.  Best practice within the preservation community calls for redundancy, at both a technical and organizational level, as a primary strategy for higher preservation assurance.  Consequently, California Digital Library (CDL) and Code for Science & Society (CSS) collaborated with the data.gov development team on datamirror.org, a full dynamic mirror of data.gov.  datamirror.org holds descriptive metadata and links to the dataset copies of record on federal agency websites, as well as alternative links to local datamirror-managed replicas (41 TB), and soon, to other known copies that may emerge through the efforts of the national data rescue movement, in which CDL and CSS are active participants.  While instigated by recent political events, the stewardship provided by datamirror.org is merely an expression of prudent research data management that is clearly called for to ensure permanent access to the nation’s rich digital patrimony.

For years scientists in fields from climate change to biodiversity to hydrology have used older data to address contemporary issues. Since the 1960s researchers, recognizing the value of this data, have expressed concern about its management and potential for loss. No widespread solutions have emerged to address the myriad issues around its storage, access, and findability. This paper summarizes observations and concerns of researchers in various disciplines who have articulated problems associated with analog data and highlights examples of projects that have used historical data. The authors also examined selected papers to discover how researchers located historical data and how they used it. While many researchers are not producing huge amounts of analog data today, there are still large volumes of it that are at risk. To address this concern, the authors recommend the development of best practices for managing historic data. This will take communication across disciplines and the involvement of researchers, departments, institutions, and associations in the process.

A 250‐year (1766–2016) archive of reconstructed river flows is presented for 51 catchments across Ireland. By leveraging meteorological data rescue efforts with gridded precipitation and temperature reconstructions, we develop monthly river flow reconstructions using the GR2M hydrological model and an Artificial Neural Network. Uncertainties in reconstructed flows associated with hydrological model structure and parameters are quantified. Reconstructions are evaluated by comparison with those derived from quality assured long‐term precipitation series for the period 1850–2000. Assessment of the reconstruction performance across all 51 catchments using metrics of MAE (9.3 mm/month; 13.3%), RMSE (12.6 mm/month; 18.0%) and mean bias (−1.16 mm/month; −1.7%), indicates good skill. Notable years with highest/lowest annual mean flows across all catchments were 1877/1855. Winter 2015/16 had the highest seasonal mean flows and summer 1826 the lowest, whereas autumn 1933 had notable low flows across most catchments. The reconstructed database will enable assessment of catchment specific responses to varying climatic conditions and extremes on annual, seasonal and monthly timescales., Long‐term river flow records are fundamental for understanding the risk posed by drought and high flow events. Whilst in many locations long‐term flow records are lacking, precipitation data rescue efforts have made extended climatic data readily available and when employed in tandem with hydrological models such data can be used to generate historic flows. Here, we use such an approach to generate a 250 year (1766–2016) monthly flow reconstruction archive for 51 catchments in Ireland.

In the summer of 2021, the head of the Department of Entomology and Plant Pathology contacted the Research Data Management Librarian seeking advice on what to do with the paper records, including original data, of two professors emeriti. In cooperation with the Agriculture Librarian, the Special Collections Librarian, and the Library Archivist, the collection was assessed and the files physically transported to the library. The data can be safely preserved in their original form within Special Collections. However, the department head and librarians all agreed that digitization, which would make the data more accessible and permit machine-readability, is the ideal solution. The Agriculture Librarian and the Research Data Management Librarian will select a subset of the paper records to scope out the time, effort, and level of expertise needed to digitize the data, translate it into machine-readable formats, and add appropriate metadata. Important questions about the process include determining the amount and type of training needed for different stages of the workflow, whether there are any steps where efficiency could be improved through automated processes, and how it can be scaled up to allow for processing the entire collection. The department head requested that we share recommendations for best practices and procedures with him as he works to develop a data archiving policy for the department. Recognizing that more faculty will retire and leave cabinets full of paper data, the librarians are eager to experiment with methods that could make this data FAIR before the problem becomes unmanageable and irreplaceable work is lost.

The highest currently recognised air temperature (33.3 °C) ever recorded in the Republic of Ireland was logged at Kilkenny Castle in 1887. The original observational record however no longer exists. Given that Ireland is now the only country in Europe to have a national heat record set in the 19th century, a reassessment of the verity of this record is both timely and valuable. The present analysis undertakes a fundamental reassessment of the plausibility of the 1887 temperature record using methods similar to those used to assess various weather extremes under WMO auspices over recent years. Specifically, we undertake an inter-station reassessment using sparse available records and make recourse to the new and improved 20CRv3 sparse-input reanalysis product. Neither surrounding available stations nor the reanalysis offer substantive support for the Kilkenny record of 33.3 °C being correct. Moreover, recent data rescue efforts have uncovered several earlier extreme values, one of which exceeds the Kilkenny value (33.5 °C on 16th July 1876 recorded at the Phoenix Park). However, the sparsity of early observational networks, a distinct lack of synoptic support from 20CRv3 for many of the extreme heat values, and the fact that these measurements were obtained using non-standard exposures leads us to conclude that there is grossly insufficient evidence to support any of these 19th Century extremes as robust national heat record candidates. Data from the early 20th Century onwards benefits from a denser network of stations undertaking measurements in a more standardised manner, many under the direct auspices of Met Éireann and its predecessors, adhering to WMO guidance and protocols. This enables more robust cross-checking of records. We argue that the Met Éireann recognised 20th Century heat record from Boora in 1976 verifies as the most plausible robust national temperature record based upon the synoptic situation and comparisons with nearby neighbouring stations. This measurement of 32.5 °C thus likely constitutes the highest reliably recorded temperature measurement in the Republic of Ireland. Ultimately, the formal decision on any reassessment and reassignment of the national record rests with the national meteorological service, Met Éireann.

Beginning in 1964, an academic lineage of Robert DuBois and his students, Daniel Wolfman and Jeffrey Eighmy, developed dedicated United States-based archaeomagnetic research programs. Collectively,...

Historical weather observations on the daily scale are vital for the improvement of reanalysis products and the analysis of long‐term variability of extreme events. While daily datasets extend for several centuries in parts of the Northern Hemisphere, the majority of historical data for the Southern Hemisphere are monthly averages or totals. In this paper, we describe a newly recovered dataset of ten daily meteorological variables for 1877 to 1922 from Eversleigh, a property in the New England region of New South Wales in Australia. Here, we present the full process of data rescue, from digitization to quality control and an assessment of homogeneity. We show that the majority of variables were recorded to a high standard and that the data are of general use for climate analysis. Forty years of daily temperature, cloud cover, wind, and pressure observations are now available for the New England Plateau, offering data that are more complete than any other records for the region in the Australian Bureau of Meteorology dataset. The Eversleigh dataset now provides an opportunity to gain more insight into the 19th century weather and climate of eastern Australia during a time of large interannual climate variability before the dominant impact of an anthropogenic warming signal.

Historical data provides observational information crucial to our understanding of the evolution of geophysical processes. However, there is a gap between predigital age observations, which are typically handwritten, and data that is discoverable and analysable. The data rescue protocols here address this gap, covering the information lifecycle from handwritten register pages to transcription‐ready content, describing the historical data, the database design for the data rescue, and the development of an application design to transcribe the meteorological information directly from an image file to the database. The preparatory steps necessary to organize, curate, image, and structure the meteorological information, prior to transcribing the historical data, are outlined here in an integrated methodology. The initial organization, the development of an image file nomenclature to link the rescued data to the original source, and the description of a metadata schema to optimize the transcription application are all vital to the process of ensuring traceability and transparency in the data rescue process. Taken together, these steps describe best practices guidelines for similar projects. Although we designed the methodology and application to be used in any data rescue context, our particular concern was to accommodate the needs of citizen scientists. We thus focused on making our application easily maintained, flexible, direct to database, clear, and simple to use. Open Practices This article has earned an Open Data badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. The data is available at https://citsci.geog.mcgill.ca. Learn more about the Open Practices badges from the Center for Open Science: https://osf.io/tvyxz/wiki.

Historical ship logbooks provide vital historic meteorological observations in the Southern Ocean, one of the largest climate‐data deficient regions on the Earth. Christian Salvesen Whaling Company logbooks from whaling ships operating in the Southern Ocean, starting from the 1930s through the 1950s, are examined. Meteorological information contained in these logbooks has been extracted to produce a historical climate dataset. We discuss various instructions recommended by the British Admiralty to observe and record weather conditions on‐board whaling ships. Statistical tests were used to flag erroneous values and corrections were made using neighbouring values. Meteorological parameters such as air pressure, air and sea temperature and wind force on the Beaufort scale were standardized, converting imperial to metric units. The data were structured according to the internationally accepted International Maritime Meteorological Archive format, which includes the most commonly reported meteorological variables, including the time, location and ship‐related meta‐data. Hence, a readily accessible, error‐corrected and standardized historical climate dataset of the Weddell Sea sector of the Southern Ocean is presented. Open Practices This article has earned an Open Data badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. The data is available at https://doi.org/10.17863/CAM.31530. Learn more about the Open Practices badges from the Center for Open Science: https://osf.io/tvyxz/wiki.

Climatological data exists in historical documents, such as observatory registers, newspapers, ships’ logs and private diaries. Using present-day technologies, such as open source repositories and ...

International audience; In coastal areas, the characterization of sea-level rise and variations of sea level due to extreme weather events (e.g. storm surges) remains a strong societal concern. The analysis of long historical water level records proved to be an ideal way to provide. relevant arguments regarding the observed long-term sea-level evolution. In France, many systematic sea level observations performed by mechanical tide gauge were. carried out since the mid-1800s. Despite this rich history, long water-level data sets digitally available are still scarce: historical water level measurements need to be digitized.In this context, an extensive work in sea level data rescuing is undertaken at SHOM. This time-demanding effort aims at recovering the French scientifi c and cultural heritage on sea level observations and providing researcher community with new datasets to analyze. This initiative responds to the recommendations of the Global Sea Level Observing System program (GLOSS) on the recovery of forgotten sea level measurements.More than 60,000 documents have been identifi ed and accurately inventoried at SHOM and about 50% have already been scanned, but thousands of documents still remain to carefully inventory and scan. These measurements mainly concern French ports (~300 sites) and also overseas sites (~240 sites). Time series duration span time periods ranging from few days to several decades. Longest time series can be directly use to assess long term sea level evolution (SONEL) and shorter dataset could be used to quantify historical storm surges, allowing the improvement of estimation and prediction of extreme coastal water levels (French Working Group ‘Historical Storms and Floodings’).; Dans les zones côtières, la caractérisation de l'élévation du niveau de la mer et des variations du niveau de la mer dues à des événements météorologiques extrêmes (par exemple, les ondes de tempête) reste une forte préoccupation sociétale. L'analyse de longs enregistrements historiques du niveau de l'eau s'est avérée être un moyen idéal pour fournir. des arguments pertinents concernant l'évolution du niveau de la mer observée à long terme. En France, de nombreuses observations systématiques du niveau de la mer effectuées par des marégraphes mécaniques ont été réalisées depuis le milieu des années 1800. Malgré cette riche histoire, les longues séries de données sur le niveau de la mer disponibles sous forme numérique sont encore rares : les mesures historiques du niveau de la mer doivent être numérisées.Dans ce contexte, un travail important de sauvetage des données de niveau de la mer est entrepris au SHOM. Cet effort exigeant en temps vise à récupérer le patrimoine scientifique et culturel français sur les observations du niveau de la mer et à fournir à la communauté des chercheurs de nouveaux ensembles de données à analyser. Cette initiative répond aux recommandations du programme GLOSS (Global Sea Level Observing System) sur la récupération des mesures oubliées du niveau de la mer.Plus de 60 000 documents ont été identifiés et inventoriés avec précision au SHOM et environ 50% ont déjà été scannés, mais il reste encore des milliers de documents à inventorier soigneusement et à scanner. Ces mesures concernent principalement les ports français (~300 sites) et également des sites d'outre-mer (~240 sites). La durée des séries temporelles s'étend sur des périodes allant de quelques jours à plusieurs décennies. Les séries temporelles les plus longues peuvent être utilisées directement pour évaluer l'évolution du niveau de la mer à long terme (SONEL) et les séries temporelles plus courtes peuvent être utilisées pour quantifier les ondes de tempête historiques, permettant ainsi d'améliorer l'estimation et la prédiction des niveaux d'eau côtiers extrêmes (Groupe de travail français 'Tempêtes et inondations historiques').

We report the recovery and processing methodology of the first ever multi-year lidar dataset of the stratospheric aerosol layer. A Q-switched Ruby lidar measured 66 vertical profiles of 694nm attenuated backscatter at Lexington, Massachusetts between January 1964 and August 1965, with an additional 9 profile measurements conducted from College, Alaska during July and August 1964.We describe the processing of the recovered lidar backscattering ratio profiles to produce mid-visible (532nm) stratospheric aerosol extinction profiles (sAEP532) and stratospheric aerosol optical depth (sAOD532) measurements.Stratospheric soundings of temperature, and pressure generate an accurate local molecular backscattering profile, with nearby ozone soundings determining the ozone absorption, those profiles then used to correct for two-way ozone transmittance. Two-way aerosol transmittance corrections were also applied based on nearby observations of total aerosol optical depth (across the troposphere and stratosphere) from sun photometer measurements.We show the two-way transmittance correction has substantial effects on the retrieved sAEP532 and sAOD532, calculated without the corrections resulting in substantially lower values of both variables, as it was not applied in the original processing producing the lidar scattering ratio profiles we rescued. The combined transmittance corrections causes the aerosol extinction to increase by 67 % for Lexington and 27 % for Fairbanks, for sAOD532 the increases 66 % and 26 % respectively. Comparing the magnitudes of the aerosol extinction and sAOD with the few contemporary available measurements reported show a better agreement in the case of the two way transmittance corrected values.The sAEP and sAOD timeseries at Lexington show a surprisingly large degree of variability, three periods where the stratospheric aerosol layer had suddenly elevated optical thickness, the highest sAOD532 of 0.07 measured at the end of March 1965. The two other periods of enhanced sAOD532 are both two-month periods where the lidars show more than 1 night where retrieved sAOD532 exceeded 0.05: in January and February 1964 and November and December 1964.Interactive stratospheric aerosol model simulations of the 1963 Agung cloud illustrate that although substantial variation in mid-latitude sAOD532 is expected from the seasonal cycle in the Brewer-Dobson circulation, the Agung cloud dispersion will have caused much slower increase than the more episodic variations observed, with also different timing, elevated optical thickness from Agung occurring in winter and spring.The abruptness and timing of the steadily increasing sAOD from January to July 1965 suggests this variation was from a different source than Agung, possibly from one or both of the two VEI3 eruptions that occurred in 1964/65: Trident, Alaska and Vestmannaeyjar, Heimey, south of Iceland.A detailed error analysis of the uncertainties in each of the variables involved in the processing chain was conducted, relative errors of 54 % for Fairbanks and 44 % Lexington for the uncorrected sAEP532, corrected sAEP532 of 61 % and 64 % respectively.The analysis of the uncertainties identified variables that, with additional data recovery and reprocessing could reduce these relative error levels. Data described in this work are available at https://doi.pangaea.de/10.1594/PANGAEA.922105 (Dataset in Review) (Antuña-Marrero et al., 2020).

Trabajo presentado en EGU General Assembly, celebrada en modalidad virtual del 19 al 30 de abril de 2021., Here we present the progress of the first work package (WP1) of the project “Assessing centennial wind speed variability from a historical weather data rescue project in Sweden” (WINDGUST), funded by FORMAS – A Swedish Research Council for Sustainable Development (ref. 2019-00509); previously introduced in EGU2019-17792-1 and EGU2020-3491. In a global climate change, one of the major uncertainties on the causes driving the climate variability of winds (i.e., the “stilling” phenomenon and the recent “recovery” since the 2010s) is mainly due to short availability (i.e., since the 1960s) and low quality of observed wind records as stated by the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). The WINDGUST is a joint initiative between the Swedish Meteorological and Hydrological Institute (SMHI) and the University of Gothenburg aimed at filling the key gap of short availability and low quality of wind datasets, and improve the limited knowledge on the causes driving wind speed variability in a changing climate across Sweden. During 2020, we worked in WP1 to rescue historical wind speed series available in the old weather archives at SMHI for the 1920s-1930s. In the process we followed the “Guidelines on Best Practices for Climate Data Rescue” of the World Meteorological Organization. Our protocol consisted on: (i) designing a template for digitization; (ii) digitizing papers by an imaging process based on scanning and photographs; and (iii) typing numbers of wind speed data into the template. We will report the advances and current status, challenges and experiences learned during the development of WP1. Until new year 2020/2021 eight out of thirteen selected stations spanning over the years 1925 to 1948 have been scanned and digitized by three staff members of SMHI during 1,660 manhours.

Long-term glacier monitoring in Switzerland has resulted in some of the longest and most complete data series globally. Point mass balance observations, starting in the 19th century, are the backbone of the monitoring as they represent the raw and original data demonstrating the response of surface accumulation and melt to changes in climate forcing. Some of these time series on Swiss glaciers provide over 100 years of continuous measurements.In the past, the variety of sources of historic measurements has only been partially investigated and never been completely and systematically processed and documented. Therefore, a new format for a point mass balance database was developed that allows full traceability of all measurements back to their original source as well as indicators for the quality of the data and corresponding measuring uncertainties. All previously included data sources were transferred into the new data base format and the original sources were re-assessed to validate or correct the entries and identify metadata. Furthermore, newly investigated measurements were added to the data base. The sources of data include an extremely diverse field from over 140 years of measurements such as published reports or studies, unpublished documents from field projects, field notes, digital sources as well as metaknowledge of the observers. Currently, data series with complete metadata for about 60 individual glaciers are available, corresponding to almost 60.000 point observations, one third of which are newly added.In addition to extending the data base, this project also allowed us to systematically and homogenously fill in missing information such as estimates of the surface elevation of the measurement points and snow/firn density. In the past, these density values often had to be assumed without actual measurements but those assumptions could vary up to 20% within different projects and assumptions were rarely flagged as such. The newly added metadata now allows performing an analysis of all actually measured density values and a homogenous interpolation of missing values across all times series based on known values. Furthermore, a system to estimate uncertainties of the mass balance measurements based on the metadata was developed as the accuracy of measurements between different measuring techniques and projects with very differing scientific objectives over a time frame of 140 years can vary significantly and therefore needs to be assessed. This quality-checked and complete data base now permits the re-analysis of consistent time series of glacier-wide mass balance allowing further interpretation of the climate change impacts on Swiss glaciers.

Widespread investments in facilitating reuse and reproducibility of scientific research have spurred an increasing recognition of the potential value of data biding in unpublished records and legacy research materials, such as scientists’ papers, historical publications, and working files. Recovering usable scientific data from legacy collections constitutes one kind of data rescue: the usually urgent application of selected data curation processes to data at imminent risk of loss. Given growing interest in data-intensive research, and a concomitant movement toward computationally amenable collections in memory institutions, scientific data repositories and collecting institutions would benefit from systematic approaches to assessing and processing legacy collections with the specific goal of retrieving reusable or historically valuable scientific data. This paper suggests a preliminary framework for assessing legacy collections of research materials for the purpose of data rescue. Developed through three case studies of agricultural research collections held by the United States Department of Agriculture’s National Agricultural Library, this framework aims to guide data rescue initiatives in agricultural research centers, and to provide conceptual framing for emerging conversations around data rescue across disciplines.

Recent years have seen early instrumental observations play an increasingly important role in climate research, allowing past daily-to-decadal climate variability and weather extremes to be explored in greater detail. The 18th century saw the formation of several short-lived meteorological networks of which the one organised by the Societas Meteorologica Palatina is arguably the most well-known. This network stood out as one of those few that efficiently managed to control its members, integrating, refining and publishing measurements taken from numerous stations around Europe and beyond. Although much has been written about the network in both history, science, and individual prominent series used for climatological studies, the actual measurements have not yet been digitised and published in extenso. This paper represents an important step towards filling this perceived gap in research. Here we provide an inventory listing the availability of observed variables for the 37 stations that belonged to the Society's network and discuss their historical context. Most of these observations have been digitised and a considerable fraction has been converted and formatted. In this paper we focus on the temperature and pressure measurements, which have been corrected and homogenised. We then demonstrate their potential for climate research by analysing two cases of extreme weather. The recovered series will have wide applications and could contribute to a better understanding of the mechanisms behind climatic variations and extremes, as well as the societal reactions to adverse weather. Even the shorter series could be ingested into reanalyses and improve the quality of large scale reconstructions.

Sea level in the South Atlantic Ocean has only been measured at a small number of tide-gauge locations, which causes considerable uncertainty in 20th-century sea-level trend estimates in this basin. To obtain a better-constrained sea-level trend in the South Atlantic Ocean, this study aims to answer two questions. The first question is: can we combine new observations, vertical land motion estimates, and information on spatial sampling biases to obtain a likely range of 20th-century sea-level rise in the South Atlantic? We combine existing observations with recovered observations from Dakar and a high-resolution sea-level reconstruction based on salt-marsh sediments from the Falkland Islands and find that the rate of sea-level rise in the South Atlantic has likely been between 1.1 and 2.2 mm year−1 (5%–95% confidence intervals), with a central estimate of 1.6 mm year−1. This rate is on the high side, but not statistically different compared to global-mean trends from recent reconstructions. The second question is: are there any physical processes that could explain a large deviation from the global-mean sea-level trend in the South Atlantic? Sterodynamic (changes in ocean dynamics and steric effects) and gravitation, rotation, and deformation effects related to ice mass loss and land water storage have probably led to a 20th-century sea-level trend in the South Atlantic above the global mean. Both observations and physical processes thus suggest that 20th-century sea-level rise in the South Atlantic has been about 0.3 mm year−1 above the rate of global-mean sea-level rise, although even with the additional observations, the uncertainties are still too large to distinguish a statistically significant difference., The idea for this study emerged from the project “Towards a Unified Sea-Level Record: Assessing the Performance of Global-Mean Sea-Level Reconstructions from Satellite Altimetry, Tide Gauges, Paleo-Proxies and Geophysical Models,” which was funded by the Internationalit Space Science Instute (ISSI), Bern Switzerland. Part of this work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. Radiocarbon dating for the Falkland Islands proxy sea-level record was supported by the Natural Environment Research Council Radiocarbon Facility through allocation 1885.0415 (to RG).

There is a growing interest for rescue and reuse of data from past studies (so-called legacy data). Data loss is alarming, especially where natural archives are under threat, such as peat deposits. Here we develop a workflow for reuse of legacy radiocarbon dates in peatland studies, including a rigorous quality assessment that can be tailored to specific research questions and study regions. A penalty score is assigned to each date based on criteria that consider taphonomic quality (i.e. sample provenance) and dating quality (i.e. sample material and method used). The weights of quality criteria may be adjusted based on the research focus, and resulting confidence levels may be used in further analyses to ensure robustness of conclusions. We apply the proposed approach to a case study of a (former) peat landscape in the northern Netherlands, aiming to reconstruct the timing of peat initiation spatially. Our search yielded 313 radiocarbon dates from the 1950s to 2019. Based on the quality assessment the dates—of highly diverse quality—were assigned to four confidence levels. Results indicate that peat initiation for the study area first peaked in the Late Glacial, dropped during the Boreal (10640 – 9220 cal y BP) and showed a second peak in the Subboreal (5660 – 2400 cal y BP). Further spatial analysis shows that for local valleys peat initiation occurred throughout the Holocene, with age-elevation plots indicating a prominent control by Holocene sea level rise. On plains and ridges peat initiation only occurred during the Subboreal, likely controlled by groundwater rise related to sea level rise. Our study highlights the potential of legacy data for palaeogeographic reconstructions, as it is cost-efficient and provides access to information no longer available in the field. However, data retrieval may be challenging and reuse of data requires that basic information on location, elevation, stratigraphy, sample and analysis details are documented irrespective of the original research aims.