Josep Batlló, Hisashi Hayakawa, Victoria Slonosky, Richard I. Crouthamel
{"title":"Preface to the special issue on “Old records for new knowledge”","authors":"Josep Batlló, Hisashi Hayakawa, Victoria Slonosky, Richard I. Crouthamel","doi":"10.1002/gdj3.243","DOIUrl":"10.1002/gdj3.243","url":null,"abstract":"<p>Studying a changing world requires observations going back in time to extend and contextualize our latest scientific knowledge. Old legacy data exist in non-digital formats. Thus, techniques and methodologies for the preservation, dissemination, interpretation, homogenization, calibration, and use of such legacy data and their associated metadata, as well as for their present scientific use are important topics for advancing our understanding of the changing Earth and of past extreme events. The articles presented in this special issue review different issues involved in these diverse topics, including the importance of preserving old data and metadata, the actors involved in the task, the problems in converting them to digital files and databases, as well as to point some hints for the future.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"357-364"},"PeriodicalIF":3.3,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.243","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139979328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"CAMELS-SE: Long-term hydroclimatic observations (1961–2020) across 50 catchments in Sweden as a resource for modelling, education, and collaboration","authors":"Claudia Teutschbein","doi":"10.1002/gdj3.239","DOIUrl":"10.1002/gdj3.239","url":null,"abstract":"<p>This paper introduces a community-accessible dataset comprising daily hydroclimatic variables (precipitation, temperature, and streamflow) observed in 50 catchments in Sweden (median size of 1019 km<sup>2</sup>). The dataset covers a 60-year period (1961–2020) and includes information on geographical location, landcover, soil classes, hydrologic signatures, and regulation for each catchment. Data were collected from various sources, such as the Swedish Meteorological and Hydrological Institute, the Swedish Geological Survey, and several Copernicus products provided by the European Environment Agency. The compiled, spatially-matched, and processed data are publicly available online through the Swedish National Data Service (https://snd.se/en), contributing a new region to the collection of existing CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) datasets. The CAMELS-SE dataset spans a wide range of hydroclimatic, topographic, and environmental catchment properties, making it a valuable resource for researchers and practitioners to study hydrological processes, climate dynamics, environmental impacts, and sustainable water management strategies in Nordic regions.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"655-668"},"PeriodicalIF":3.3,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.239","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139758205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multitemporal landslide inventory and susceptibility map for the Arun River Basin, Nepal","authors":"Pukar Amatya, Robert Emberson, Dalia Kirschbaum","doi":"10.1002/gdj3.240","DOIUrl":"10.1002/gdj3.240","url":null,"abstract":"<p>The transboundary Arun River Basin (ARB) spreads across Nepal and Tibet. Nearly 95% of the basin lies in Tibet through which the Pumqu River flows, forming the Arun River once it enters Nepal. The ARB has five large hydropower projects undergoing construction or planned for the future. Rainfall and earthquake-induced landslides, landslide-dammed lakes and landslide-induced glacial lake outburst floods pose major risks to smooth operation of these projects. To safeguard upcoming hydropower projects, areas susceptible to landslides in the ARB must be identified. We used high-resolution satellite imagery and open-source tools to generate a multitemporal landslide inventory for the basin. The rigorously quality-controlled inventory represents a yearly record of landslides from 2011 to 2020. A data-driven approach was used to map areas susceptible to landslides within the ARB. The multitemporal landslide inventory combined with other readily available Earth observation-based variables was used to create a landslide susceptibility map. The susceptibility analysis provides a valuable initial estimate of where landslides are likely to initiate. These landslide products could form the basis of more comprehensive local studies to inform hydropower project development.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"669-679"},"PeriodicalIF":3.3,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.240","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139758296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kenneth Kin Cheung Chow, Housseyni Sankaré, Emilia P. Diaconescu, Trevor Q. Murdock, Alex J. Cannon
{"title":"Bias-adjusted and downscaled humidex projections for heat preparedness and adaptation in Canada","authors":"Kenneth Kin Cheung Chow, Housseyni Sankaré, Emilia P. Diaconescu, Trevor Q. Murdock, Alex J. Cannon","doi":"10.1002/gdj3.241","DOIUrl":"10.1002/gdj3.241","url":null,"abstract":"<p>To help with preparedness efforts of Canadian public health and safety systems for adaptation to climate change, the humidity index (humidex) and three threshold-based humidex indices (annual number of days with humidex greater than 30, 35 and 40) were computed for a multi-model ensemble of climate change projections, over Canada. The ensemble consists of one run from each 19 Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models and offers historical simulations starting in 1950 and future projections out to 2100 following Shared Socioeconomic Pathways (SSPs): SSP1-2.6, SSP2-4.5 and SSP5-8.5. Each ensemble member was bias-adjusted and statistically downscaled using the Multivariate bias correction—N-dimensional probability density function transform (MBCn) with hourly data from ERA5-Land as the target dataset and following a method proposed by Diaconescu et al. (2023; <i>International Journal of Climatology</i>, 43, 837) to calculate humidex from daily climate model outputs. This paper details the steps for data production including evaluation of the target historical gridded data and selection of downscaling method and presents some of the resulting humidex projections at the end of the century.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"680-698"},"PeriodicalIF":3.3,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.241","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139757982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Australian Ocean surface waves dataset from SAR","authors":"S. Khan, M. Hemer, E. Echevarria, E. King","doi":"10.1002/gdj3.238","DOIUrl":"10.1002/gdj3.238","url":null,"abstract":"<p>In this article, a regional ocean surface waves dataset from Sentinel-1 A and B Synthetic Aperture Radar (SAR) satellites has been described. The ocean wave data have been extracted from the Sentinel-1 level-2 OCN (ocean) product as provided by the European Space Agency and downloadable for this region from the Copernicus Australasia regional data hub. The source OCN data have been produced by evolving versions of Sentinel-1 Instrument Processing Facility (IPF). The structure of the source OCN NetCDF files changes over time and presents a challenge in performing long duration, time series analyses, including the examination of potential inconsistencies in OCN wave data, due to employment of different IPF versions over the duration of the satellite missions. Here, the input OCN wave data have been homogenized to a single, easily usable standard format after applying a quality assurance and control procedure that removes various inconsistencies in variables, coordinates, dimensions and land flag, and through the addition of new auxiliary variables. The new format has the desirable properties of being compact in size, consistent in structure, and scalable in temporal and spatial coverage. It is also convenient to use and offers opportunities to perform fast, multi-year regional processing and analysis for calibration and validation studies and scientific applications. No re-processing of Sentinel-1 level-1 data has been carried out in this work.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"638-654"},"PeriodicalIF":3.3,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.238","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139555863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Digitizing observations from the 1861–1875 Met Office Daily Weather Reports using citizen scientist volunteers","authors":"Philip M. Craig, Ed Hawkins","doi":"10.1002/gdj3.236","DOIUrl":"10.1002/gdj3.236","url":null,"abstract":"<p>We describe the transcription and quality control processes for rescuing around 570,000 sub-daily and daily weather observations which were recorded in the UK Met Office Daily Weather Reports during the 1861–1875 period. These data are from the start of coordinated weather observations and were collected with the aim of making the first-ever weather forecasts. The observations were rescued thanks to 3500 volunteers and include sub-daily sea-level pressure, dry and wet bulb temperatures, daily maximum and minimum temperatures, and daily rainfall amounts from 70 different locations across Western Europe, and one in Canada. We highlight how these observations will be used to fill gaps in existing pressure and temperature datasets and use two case studies to show how the pressure observations will likely better constrain the atmospheric circulation during two severe storms. We also compare a sub-sample of the newly rescued observations with data that were previously digitized for a small number of locations for the same dates, finding good agreement in general, although some discrepancies remain.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"608-622"},"PeriodicalIF":3.3,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.236","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139458806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. M. Barrios, A. Arboleda, E. Dutra, I. Trigo, F. Gellens-Meulenberghs
{"title":"Evapotranspiration and surface energy fluxes across Europe, Africa and Eastern South America throughout the operational life of the Meteosat second generation satellite","authors":"J. M. Barrios, A. Arboleda, E. Dutra, I. Trigo, F. Gellens-Meulenberghs","doi":"10.1002/gdj3.235","DOIUrl":"10.1002/gdj3.235","url":null,"abstract":"<p>The exchange of energy and water fluxes between the Earth's surface and the atmosphere is crucial to a series of processes that impact human life. Noteworthy examples are agriculture yields, water availability, intensity and extent of droughts and the ability of ecosystems to provide services to society. The relevance of these processes has motivated the Satellite Application Facility on Land Surface Analysis (LSA SAF) programme to set up an operational framework to estimate—among other variables—evapotranspiration (ET) and surface energy fluxes (SEF) on the basis of observations by the Meteosat Second Generation (MSG) satellite. The LSA SAF programme has recently launched the reprocessing of the ET and SEF datasets on the basis of the most recent version of the algorithm and homogenous forcing datasets. This article features the resulting ET/SEF dataset, a Data Record that encompasses the period from the start of the operational life of the MSG satellite (2004) till 2020 and covers the field of view of the MSG satellite (i.e. Europe, Africa and Eastern South America). Details on the algorithm and the datasets driving the ET/SEF estimates are also provided as well as a quality assessment.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"589-607"},"PeriodicalIF":3.3,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.235","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139459000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"High-resolution dataset of nocturnal air temperatures in Bern, Switzerland (2007–2022)","authors":"Moritz Burger, Moritz Gubler, Stefan Brönnimann","doi":"10.1002/gdj3.237","DOIUrl":"10.1002/gdj3.237","url":null,"abstract":"<p>To prepare for a hotter future, information on intra-urban temperature distributions is crucial for cities worldwide. In recent years, different methods to compute high-resolution temperature datasets have been developed. Such datasets commonly originate from downscaling techniques, which are applied to enhance the spatial resolution of existing data. In this study, we present an approach based on a fine-scaled low-cost urban temperature measurement network and a formerly developed land use regression approach. The dataset covers mean nocturnal temperatures of 16 summers (2007–2022) of a medium-sized urban area with adapted land cover data for each year. It has a high spatial (50 m) and temporal (daily) resolution and performs well in validation (RMSEs of 0.70 and 0.69 K and mean biases of +0.41 and −0.19 K for two validation years). The dataset can be used to examine very detailed statistics in space and time, such as first heatwave per year, cumulative heat risks or inter-annual variability. Here, we evaluate the dataset with two application cases regarding urban planning and heat risk assessment, which are of high interest for both researchers and practitioners. Due to potential biases of the low-cost measurement devices during daytime, the dataset is currently limited to night-time temperatures. With minor adaptions, the presented approach is transferable to cities worldwide in order to set a basis for researchers, city administrations and private stakeholders to address their heat mitigation and adaptation strategies.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"623-637"},"PeriodicalIF":3.3,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.237","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139458895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zsolt Magyari-Sáska, Adina-Eliza Croitoru, Csaba Horváth, Ștefan Dombay
{"title":"ClimShift – A new toolbox for the detection of climate change","authors":"Zsolt Magyari-Sáska, Adina-Eliza Croitoru, Csaba Horváth, Ștefan Dombay","doi":"10.1002/gdj3.234","DOIUrl":"10.1002/gdj3.234","url":null,"abstract":"<p>Climate change no longer involves and affects just a few people or communities. However, most of them need climate change detection studies to adapt to the current and future climate conditions efficiently. The present research aimed to detect climate changes by considering the shift in climate conditions from one region to another over different periods based on a similarity index in the Carpathians basin using the new ClimShift toolbox, specially created for this purpose. Developed in R, based on the cosine similarity index and using a set of 32 climate indices (temperature and precipitation), ClimShift uses NC raster format (NetCDF files) as input data. The application is compatible with Microsoft and Unix/Linux environments. The toolbox allows the detection of forward and backward climate shifts. The results can be employed as a Climate Service and are extremely helpful for an efficient process of adaption to climate changes at a local/regional scale. A user-friendly interface and a tutorial on how to use the toolbox are also available. The toolbox was tested for four locations in the Carpathians Basin (Vienna, Bekes, Cluj-Napoca and Kosice) using 1961–1990 as a base period and 1991–2021 as an analysis period for the forward climate shift analysis. For Cluj-Napoca, the application was also tested for the backward climate shift, using 1991–2021 as the base period and 1961–1990 as the analysis period, identifying the region where present climate conditions were specific during the older period. The scientific results indicated a significant shift towards the east and northeast from the older period to the most recent one and a low percentage (6%–10%) in the overlapping area with highly similar conditions between the two periods.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"1058-1072"},"PeriodicalIF":3.3,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.234","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138951427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christian Schwatke, Denise Dettmering, Marcello Passaro, Michael Hart-Davis, Daniel Scherer, Felix L. Müller, Wolfgang Bosch, Florian Seitz
{"title":"OpenADB: DGFI-TUM's Open Altimeter Database","authors":"Christian Schwatke, Denise Dettmering, Marcello Passaro, Michael Hart-Davis, Daniel Scherer, Felix L. Müller, Wolfgang Bosch, Florian Seitz","doi":"10.1002/gdj3.233","DOIUrl":"10.1002/gdj3.233","url":null,"abstract":"<p>For more than three decades, satellite altimetry has provided valuable measurement data for the monitoring and analysis of ocean and inland water surfaces. Since 1992, there have always been at least two simultaneous missions providing continuous measurement data, starting with TOPEX/Poseidon and ERS-1 in the early 1990s and continuing with about 10 satellites active today, including ICESat-2, Sentinel-6A and SWOT. Most mission data are freely available, but in different formats, processing levels and with respect to different references (e.g. ellipsoid or time), making common multi-mission applications difficult. In addition, the derivation of ready-to-use and high-quality scientific products requires expertise that not every user is willing to acquire. Over the years, DGFI-TUM has developed and maintained an Open Altimeter Database (OpenADB) that allows consistent data management and combination. It consists of the internal Multi-Version Altimetry (MVA) data repository and the OpenADB web portal. OpenADB provides user-friendly access to derived along-track products, such as sea surface heights and ocean tides. It also provides general information about the satellite altimetry missions, their observing configurations and about the data provided in the database. All products are freely available on the OpenADB web portal (https://openadb.dgfi.tum.de) after registration.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"573-588"},"PeriodicalIF":3.3,"publicationDate":"2023-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.233","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138741304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}