Abstract This report contains terrestrial absolute gravity measurements performed near the village of Kulusuk in southeast Greenland. It represents an exceptionally long time series of nearly two decades. The measurements began in July 1996 until July 2015. The station is located a few meters beside a permanent GNSS station. The final gravity values (g‐values), more precisely the accelerations due to gravity, are listed along their associated uncertainties. A description of the station, a short explanation on the absolute gravimeter, and the data processing are presented.

Abstract This article presents a curated database of the sea‐level measurements acquired by the network of the five geodetic tide gauges managed over French Polynesia by the Geodesy Observatory of Tahiti from 13 June 2009 to 28 January 2021. A unique feature of this database, with respect to previous databases that host the same raw data, like the Intergovernmental Oceanographic Commission database (IOC, www.ioc‐sealevelmonitoring.org) and the database of ‘Réseaux de référence des observations marégraphiques’ (REFMAR, http://refmar.shom.fr) is that all the time‐tags of the raw measurements (1‐ or 2‐min sampling) have been validated and, if necessary, corrected with a precision of 2 min (time shifts of up to 1 hr can be present in the raw data). Possible outliers have also been flagged, but not removed. In addition, smoothed hourly data are also provided, along with tidal analysis results and estimations of the sea‐level trends for the five tide gauges, with respect to their local geodetic datum. The database, entitled ‘SEA LEVEL collected from TIDE STATIONS in South Pacific Ocean from 2009‐06‐13 to 2021‐01‐28’, can be accessed on the NOAA data servers as ‘NCEI Accession 0244182’ and contains two subsets: The first one is relative to the original sampling rate and the second one is relative to an hourly re‐sampling with harmonic tide models for each tide gauge station.

Abstract The international Atmospheric Circulation Reconstructions over the Earth (ACRE) initiative works to recover global climate history and build an accessible databank, with data from the past 250 years of terrestrial and marine surface. Argentina is part of that effort with ACRE Argentina recovering data from various sources that have been recorded throughout the country since the 19th century. In this paper, weather observations transcribed from the original records into digital form and taken every day during the years 1860–1879 at Bahía Blanca and from 1873–1886 at Corrientes are presented. The digitization was carried out through the project Meteorologum ad Extremum Terrae (MET) launched in the Zooniverse interface, which is currently working with near 900 citizen scientist volunteers per day. The present analysis corresponds to data retrieved from the collection ‘Anales de la Oficina Meteorológica Argentina’ and contains information on atmospheric pressure, air temperature, relative humidity, cloud cover, cloud types, wind direction, wind speed, rainfall and weather remarks. For the present analysis, only temperature and pressure values, measured in °C and mm of Hg, respectively, were considered, after a quality control of the digitization process was applied. Data values were tested and used to rebuild the time series of both places and correlation with SOI index and monthly pressure values for both places was tested using Spearman correlation. Results show that the influence of El Niño episode during 1877–1878 can be found in the pressure values at Corrientes.

Abstract The Geophysical and Astronomical Observatory of the University of Coimbra (OGAUC) was officially created in 2013 after merging of two historical institutions: the Astronomical Observatory and the Geophysical Institute. As a result of almost 200 years of observations and research in astronomy and geophysical sciences, the OGAUC possesses a unique and valuable collection of long‐term observational and instrumental records. These data have an indispensable value in current geophysical and climatic studies, being among the most complete and significant in Portugal and the world. The OGAUC's data collections are complemented by a vast technical‐scientific production such as reports, research memoranda, articles, books, and instruments. This archive is largely not inventoried and poorly studied (particularly concerning meteorological, geomagnetic, and seismological data). This paper highlights the importance of the OGAUC's extensive data collection and discusses the difficulties and barriers related to its inventorying, preservation, and dissemination to the scientific community, policymakers, stakeholders, and the general public.

Abstract Millions of sub‐daily sea‐level pressure observations taken between 1919 and 1960 over the British and Irish Isles were transcribed from paper records in the early 2000s but were not published and subsequently forgotten. A chance discussion led to the rediscovery of the transcribed data and 5.47 million observations from 160 locations are now made available, although the data have not been fully quality‐controlled. Much of the data are 3‐hourly, allowing for detailed examinations of synoptic weather variations for this region and time period, and will be invaluable for constraining future reanalyses. We illustrate the value of the data using a stormy period during October and November 1928 and discuss the remaining quality‐control issues.

Abstract Modern analysis of earthquakes depends on digital time series; however, only about 30% of the timespan of recorded seismicity is available in digital format. During the first half of the 20th century, most of the earthquake ground motions in Mexico were recorded by Wiechert mechanical instruments on smoked paper. In this work, we developed and use Tiitba, a new portable multiplatform graphical user interface (GUI) open‐source software coded on python, to vectorize and correct old analogue seismograms. Using this software, we vectorized the 11/1/1928 Parral (M6.3) earthquake seismograms to obtain the constant time‐interval digitized time series for each component and station of the seismogram. Then, we obtained its source focal mechanism using a genetic algorithm methodology. Also, with an auxiliary Tiitba module, we constructed a SEISAN S‐file to relocate the hypocentre of this earthquake. The obtained relocation is about 125 km south of a recently recorded seismic swarm that occurred in 2013, which has a similar focal mechanism to the one that we obtained in this work.

Abstract Historical materials contain descriptions of various events involved in natural processes and human societies (such as weather, earthquakes, volcanic eruptions, harvests, market prices, and famines). They have been used for studies in diverse fields, including natural sciences (such as seismology, climatology, and astronomy), social sciences, and humanities. Hence, researchers have made various efforts, such as identifying and obtaining the materials, reading handwritten characters and transcribing them into digital texts, standardizing formats, extracting descriptions of relevant phenomena, and constructing integrated datasets, to use documentary information. Because scientists, other than historians, find it quite challenging even to ascertain where to find appropriate research materials, the Rekiske Development Group has, therefore, developed a system called Rekiske to facilitate interdisciplinary sharing of information available from historical materials. Rekiske is designed for sharing bibliographic and scientific information of historical materials, along with researchers’ experience and knowledge, through interdisciplinary collaboration. Rekiske can assist researchers in identifying and obtaining useful historical materials for research purposes. It also facilitates collaboration among experts to share their expertise and knowledge of historical information, materials, and recent studies. Using Rekiske, we register various types of information on historical materials regarding weather or earthquakes considered in geoscience research to utilize researchers’ experiences and to produce new knowledge through interdisciplinary collaborations. The developed system is designed to be used as a metadata portal and pathfinder to promote and preserve historical data and facilitate an understanding of the spatiotemporal connection between nature and human society. We have applied Rekiske to historical climatic studies and discuss its usage, benefits, usability, and other remaining issues.

Abstract Magnetic observations at the Clementinum Observatory were started in July 1839 and data up to 1917 were published in yearbooks. In addition to regular daily observations with a typical 2‐hr time step, two categories of data with a higher cadence were provided in the first decade. The first category captures 73 magnetic storms with their magnitude being of at least a moderate level. The second category is the dense observations during the days that had been agreed for joint measurements by the observatories organized in the Göttingen Magnetic Union (GMU), these measurements being known as term‐day observations. Whereas four terms per year were set by GMU, many observatories agreed to carry out additional observations in the eight remaining months. The term‐day observations also continued being performed for several years after the end of the GMU activities in 1841. Data of 120 term days from January 1840 to December 1849 were published. The declination was observed using the magnetic compass principle, while a bifilar apparatus was used to measure the horizontal intensity. When converting the data to the physical units of the SI, we have achieved the consistency of these high cadence data with previously published regular hourly observations of the geomagnetic field. This requirement was also met by considering the temperature dependence of measurements by the bifilar apparatus in determining the absolute values of horizontal intensity. Revealing the historical observations of the geomagnetic field can serve as a valuable material for studying the space weather in the past and may also contribute to the refinement of global field modelling.

Abstract The Canadian Large Ensembles Adjusted Dataset version 1 (CanLEADv1) contains 50‐member ensembles of bias‐adjusted near‐surface global and regional climate model variables on a 0.5° grid over North America for historical and future scenarios (1950–2100). Canadian Earth System Model Large Ensembles (CanESM2 LE) and Canadian Regional Climate Model Large Ensemble (CanRCM4 LE) datasets are bias‐corrected using a multivariate quantile‐mapping algorithm for statistical consistency – in terms of marginal distributions and multivariate dependence structure – with two observationally constrained historical meteorological forcing datasets. For each observational dataset, bias‐adjusted variables are provided for two sets of 50‐member initial‐condition CanESM2 ensembles (historical plus RCP8.5 scenarios, 1950–2005 and 2006–2100, respectively; and historicalNAT scenario, 1950–2020, which excludes anthropogenic forcings), and one 50‐member CanRCM4 ensemble (historical plus RCP8.5). The archive includes daily minimum temperature, maximum temperature, precipitation, relative humidity, surface pressure, wind speed, incoming shortwave radiation and incoming longwave radiation. Intended uses include hydrological and land surface impact modelling, as well as related event attribution studies.