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- ItemThe first pan-Alpine surface-gravity database, a modern compilation that crosses frontiers(Katlenburg-Lindau : Copernics Publications, 2021) Zahorec, Pavol; Papčo, Juraj; Pašteka, Roman; Bielik, Miroslav; Bonvalot, Sylvain; Braitenberg, Carla; Ebbing, Jörg; Gabriel, Gerald; Gosar, Andrej; Grand, Adam; Götze, Hans-Jürgen; Hetényi, György; Holzrichter, Nils; Kissling, Edi; Marti, Urs; Meurers, Bruno; Mrlina, Jan; Nogová, Ema; Pastorutti, Alberto; Salaun, Corinne; Scarponi, Matteo; Sebera, Josef; Seoane, Lucia; Skiba, Peter; Szűcs, Eszter; Varga, MatejThe AlpArray Gravity Research Group (AAGRG), as part of the European AlpArray program, focuses on the compilation of a homogeneous surface-based gravity data set across the Alpine area. In 2017 10 European countries in the Alpine realm agreed to contribute with gravity data for a new compilation of the Alpine gravity field in an area spanning from 2 to 23∘ E and from 41 to 51∘ N. This compilation relies on existing national gravity databases and, for the Ligurian and the Adriatic seas, on shipborne data of the Service Hydrographique et Océanographique de la Marine and of the Bureau Gravimétrique International. Furthermore, for the Ivrea zone in the Western Alps, recently acquired data were added to the database. This first pan-Alpine gravity data map is homogeneous regarding input data sets, applied methods and all corrections, as well as reference frames. Here, the AAGRG presents the data set of the recalculated gravity fields on a 4 km × 4 km grid for public release and a 2 km × 2 km grid for special request. The final products also include calculated values for mass and bathymetry corrections of the measured gravity at each grid point, as well as height. This allows users to use later customized densities for their own calculations of mass corrections. Correction densities used are 2670 kg m−3 for landmasses, 1030 kg m−3 for water masses above the ellipsoid and −1640 kg m−3 for those below the ellipsoid and 1000 kg m−3 for lake water masses. The correction radius was set to the Hayford zone O2 (167 km). The new Bouguer anomaly is station completed (CBA) and compiled according to the most modern criteria and reference frames (both positioning and gravity), including atmospheric corrections. Special emphasis was put on the gravity effect of the numerous lakes in the study area, which can have an effect of up to 5 mGal for gravity stations located at shorelines with steep slopes, e.g., for the rather deep reservoirs in the Alps. The results of an error statistic based on cross validations and/or “interpolation residuals” are provided for the entire database. As an example, the interpolation residuals of the Austrian data set range between about −8 and +8 mGal and the cross-validation residuals between −14 and +10 mGal; standard deviations are well below 1 mGal. The accuracy of the newly compiled gravity database is close to ±5 mGal for most areas. A first interpretation of the new map shows that the resolution of the gravity anomalies is suited for applications ranging from intra-crustal- to crustal-scale modeling to interdisciplinary studies on the regional and continental scales, as well as applications as joint inversion with other data sets. The data are published with the DOI https://doi.org/10.5880/fidgeo.2020.045 (Zahorec et al., 2021) via GFZ Data Services.
- ItemWFDE5: Bias-adjusted ERA5 reanalysis data for impact studies(Katlenburg-Lindau : Copernics Publications, 2020) Cucchi, Marco; Weedon, Graham P.; Amici, Alessandro; Bellouin, Nicolas; Lange, Stefan; Müller Schmied, Hannes; Hersbach, Hans; Buontempo, CarloThe WFDE5 dataset has been generated using the WATCH Forcing Data (WFD) methodology applied to surface meteorological variables from the ERA5 reanalysis. The WFDEI dataset had previously been generated by applying the WFD methodology to ERA-Interim. The WFDE5 is provided at 0.5 spatial resolution but has higher temporal resolution (hourly) compared to WFDEI (3-hourly). It also has higher spatial variability since it was generated by aggregation of the higher-resolution ERA5 rather than by interpolation of the lower-resolution ERA-Interim data. Evaluation against meteorological observations at 13 globally distributed FLUXNET2015 sites shows that, on average, WFDE5 has lower mean absolute error and higher correlation than WFDEI for all variables. Bias-adjusted monthly precipitation totals of WFDE5 result in more plausible global hydrological water balance components when analysed in an uncalibrated hydrological model (WaterGAP) than with the use of raw ERA5 data for model forcing. The dataset, which can be downloaded from https://doi.org/10.24381/cds.20d54e34 (C3S, 2020b), is distributed by the Copernicus Climate Change Service (C3S) through its Climate Data Store (CDS, C3S, 2020a) and currently spans from the start of January 1979 to the end of 2018. The dataset has been produced using a number of CDS Toolbox applications, whose source code is available with the data - allowing users to regenerate part of the dataset or apply the same approach to other data. Future updates are expected spanning from 1950 to the most recent year. A sample of the complete dataset, which covers the whole of the year 2016, is accessible without registration to the CDS at https://doi.org/10.21957/935p-cj60 (Cucchi et al., 2020). © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.
- ItemMapping the yields of lignocellulosic bioenergy crops from observations at the global scale(Katlenburg-Lindau : Copernics Publications, 2020) Li, Wei; Ciais, Philippe; Stehfest, Elke; van Vuuren, Detlef; Popp, Alexander; Arneth, Almut; Di Fulvio, Fulvio; Doelma, Jonathan; Humpenöder, Florian; Harper, Anna B.; Park, Taejin; Makowski, David; Havlik, Petr; Obersteiner, Michael; Wang, Jingmeng; Krause, Andreas; Liu, WenfengMost scenarios from integrated assessment models (IAMs) that project greenhouse gas emissions include the use of bioenergy as a means to reduce CO2 emissions or even to achieve negative emissions (together with CCS carbon capture and storage). The potential amount of CO2 that can be removed from the atmosphere depends, among others, on the yields of bioenergy crops, the land available to grow these crops and the efficiency with which CO2 produced by combustion is captured. While bioenergy crop yields can be simulated by models, estimates of the spatial distribution of bioenergy yields under current technology based on a large number of observations are currently lacking. In this study, a random-forest (RF) algorithm is used to upscale a bioenergy yield dataset of 3963 observations covering Miscanthus, switchgrass, eucalypt, poplar and willow using climatic and soil conditions as explanatory variables. The results are global yield maps of five important lignocellulosic bioenergy crops under current technology, climate and atmospheric CO2 conditions at a 0:5 0:5 spatial resolution. We also provide a combined "best bioenergy crop" yield map by selecting one of the five crop types with the highest yield in each of the grid cells, eucalypt and Miscanthus in most cases. The global median yield of the best crop is 16.3 tDMha1 yr1 (DM dry matter). High yields mainly occur in the Amazon region and southeastern Asia. We further compare our empirically derived maps with yield maps used in three IAMs and find that the median yields in our maps are 50% higher than those in the IAM maps. Our estimates of gridded bioenergy crop yields can be used to provide bioenergy yields for IAMs, to evaluate land surface models or to identify the most suitable lands for future bioenergy crop plantations. The 0:5 0:5 global maps for yields of different bioenergy crops and the best crop and for the best crop composition generated from this study can be download from https://doi.org/10.5281/zenodo.3274254 (Li, 2019). © 2019 Cambridge University Press. All rights reserved.
- ItemThe PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests(Katlenburg-Lindau : Copernics Publications, 2020) Reyer, Christopher P.O.; Silveyra Gonzalez, Ramiro; Dolos, Klara; Hartig, Florian; Hauf, Ylva; Noack, Matthias; Lasch-Born, Petra; Rötzer, Thomas; Pretzsch, Hans; Meesenburg, Henning; Fleck, Stefan; Wagner, Markus; Bolte, Andreas; Sanders, Tanja G.M.; Kolari, Pasi; Mäkelä, Annikki; Vesala, Timo; Mammarella, Ivan; Pumpanen, Jukka; Collalti, Alessio; Trotta, Carlo; Matteucci, Giorgio; D'Andrea, Ettore; Foltýnová, Lenka; Krejza, Jan; Ibrom, Andreas; Pilegaard, Kim; Loustau, Denis; Bonnefond, Jean-Marc; Berbigier, Paul; Picart, Delphine; Lafont, Sébastien; Dietze, Michael; Cameron, David; Vieno, Massimo; Tian, Hanqin; Palacios-Orueta, Alicia; Cicuendez, Victor; Recuero, Laura; Wiese, Klaus; Büchner, Matthias; Lange, Stefan; Volkholz, Jan; Kim, Hyungjun; Horemans, Joanna A.; Bohn, Friedrich; Steinkamp, Jörg; Chikalanov, Alexander; Weedon, Graham P.; Sheffield, Justin; Babst, Flurin; Vega del Valle, Iliusi; Suckow, Felicitas; Martel, Simon; Mahnken, Mats; Gutsch, Martin; Frieler, KatjaProcess-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data on European forests to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand level, and remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a “SQLite” relational database or “ASCII” flat file version (at https://doi.org/10.5880/PIK.2020.006/; Reyer et al., 2020). The data policies of the individual contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R package (https://CRAN.R-project.org/package=ProfoundData; Silveyra Gonzalez et al., 2020), which provides basic functions to explore, plot and extract the data for model set-up, calibration and evaluation.
- ItemPRIMAP-crf: UNFCCC CRF data in IPCC 2006 categories(Katlenburg-Lindau : Copernics Publications, 2018) Jeffery, M. Louise; Gütschow, Johannes; Gieseke, Robert; Gebel, RonjaAll Annex I Parties to the United Nations Framework Convention on Climate Change (UNFCCC) are required to report domestic emissions on an annual basis in a “Common Reporting Format” (CRF). In 2015, the CRF data reporting was updated to follow the more recent 2006 guidelines from the IPCC and the structure of the reporting tables was modified accordingly. However, the hierarchical categorisation of data in the IPCC 2006 guidelines is not readily extracted from the reporting tables. In this paper, we present the PRIMAP-crf data as a re-constructed hierarchical dataset according to the IPCC 2006 guidelines. Furthermore, the data are organised in a series of tables containing all available countries and years for each individual gas and category reported. It is therefore readily usable for climate policy assessment, such as the quantification of emissions reduction targets. In addition to single gases, the Kyoto basket of greenhouse gases (CO2, N2O, CH4, HFCs, PFCs, SF6, and NF3) is provided according to multiple global warming potentials. The dataset was produced using the PRIMAP emissions module. Key processing steps include extracting data from submitted CRF Excel spreadsheets, mapping CRF categories to IPCC 2006 categories, constructing missing categories from available data, and aggregating single gases to gas baskets. Finally, we describe key aspects of the data with relevance for climate policy: the contribution of NF3 to national totals, changes in data reported over subsequent years, and issues or difficulties encountered when processing currently available data. The processed data are available under an Open Data CC BY 4.0 license, and are available at https://doi.org/10.5880/pik.2018.001.
- ItemEUREC4A(Katlenburg-Lindau : Copernics Publications, 2021) Stevens, Bjorn; Bony, Sandrine; Farrell, David; Ament, Felix; Blyth, Alan; Fairall, Christopher; Karstensen, Johannes; Quinn, Patricia K.; Speich, Sabrina; Acquistapace, Claudia; Aemisegger, Franziska; Crewell, Susanne; Cronin, Timothy; Cui, Zhiqiang; Cuypers, Yannis; Daley, Alton; Damerell, Gillian M.; Dauhut, Thibaut; Deneke, Hartwig; Desbios, Jean-Philippe; Dörner, Steffen; Albright, Anna Lea; Donner, Sebastian; Douet, Vincent; Drushka, Kyla; Dütsch, Marina; Ehrlich, André; Emanuel, Kerry; Emmanouilidis, Alexandros; Etienne, Jean-Claude; Etienne-Leblanc, Sheryl; Faure, Ghislain; Bellenger, Hugo; Feingold, Graham; Ferrero, Luca; Fix, Andreas; Flamant, Cyrille; Flatau, Piotr Jacek; Foltz, Gregory R.; Forster, Linda; Furtuna, Iulian; Gadian, Alan; Galewsky, Joseph; Bodenschatz, Eberhard; Gallagher, Martin; Gallimore, Peter; Gaston, Cassandra; Gentemann, Chelle; Geyskens, Nicolas; Giez, Andreas; Gollop, John; Gouirand, Isabelle; Gourbeyre, Christophe; de Graaf, Dörte; Caesar, Kathy-Ann; de Groot, Geiske E.; Grosz, Robert; Güttler, Johannes; Gutleben, Manuel; Hall, Kashawn; Harris, George; Helfer, Kevin C.; Henze, Dean; Herbert, Calvert; Holanda, Bruna; Chewitt-Lucas, Rebecca; Ibanez-Landeta, Antonio; Intrieri, Janet; Iyer, Suneil; Julien, Fabrice; Kalesse, Heike; Kazil, Jan; Kellman, Alexander; Kidane, Abiel T.; Kirchner, Ulrike; Klingebiel, Marcus; de Boer, Gijs; Körner, Mareike; Kremper, Leslie Ann; Kretzschmar, Jan; Krüger, Ovid; Kumala, Wojciech; Kurz, Armin; L'Hégaret, Pierre; Labaste, Matthieu; Lachlan-Cope, Tom; Laing, Arlene; Delanoë, Julien; Landschützer, Peter; Lang, Theresa; Lange, Diego; Lange, Ingo; Laplace, Clément; Lavik, Gauke; Laxenaire, Rémi; Le Bihan, Caroline; Leandro, Mason; Lefevre, Nathalie; Denby, Leif; Lena, Marius; Lenschow, Donald; Li, Qiang; Lloyd, Gary; Los, Sebastian; Losi, Niccolò; Lovell, Oscar; Luneau, Christopher; Makuch, Przemyslaw; Malinowski, Szymon; Ewald, Florian; Manta, Gaston; Marinou, Eleni; Marsden, Nicholas; Masson, Sebastien; Maury, Nicolas; Mayer, Bernhard; Mayers-Als, Margarette; Mazel, Christophe; McGeary, Wayne; McWilliams, James C.; Fildier, Benjamin; Mech, Mario; Mehlmann, Melina; Meroni, Agostino Niyonkuru; Mieslinger, Theresa; Minikin, Andreas; Minnett, Peter; Möller, Gregor; Morfa Avalos, Yanmichel; Muller, Caroline; Musat, Ionela; Forde, Marvin; Napoli, Anna; Neuberger, Almuth; Noisel, Christophe; Noone, David; Nordsiek, Freja; Nowak, Jakub L.; Oswald, Lothar; Parker, Douglas J.; Peck, Carolyn; Person, Renaud; George, Geet; Philippi, Miriam; Plueddemann, Albert; Pöhlker, Christopher; Pörtge, Veronika; Pöschl, Ulrich; Pologne, Lawrence; Posyniak, Michał; Prange, Marc; Quiñones Meléndez, Estefanía; Radtke, Jule; Gross, Silke; Ramage, Karim; Reimann, Jens; Renault, Lionel; Reus, Klaus; Reyes, Ashford; Ribbe, Joachim; Ringel, Maximilian; Ritschel, Markus; Rocha, Cesar B.; Rochetin, Nicolas; Hagen, Martin; Röttenbacher, Johannes; Rollo, Callum; Royer, Haley; Sadoulet, Pauline; Saffin, Leo; Sandiford, Sanola; Sandu, Irina; Schäfer, Michael; Schemann, Vera; Schirmacher, Imke; Hausold, Andrea; Schlenczek, Oliver; Schmidt, Jerome; Schröder, Marcel; Schwarzenboeck, Alfons; Sealy, Andrea; Senff, Christoph J.; Serikov, Ilya; Shohan, Samkeyat; Siddle, Elizabeth; Smirnov, Alexander; Heywood, Karen J.; Späth, Florian; Spooner, Branden; Stolla, M. Katharina; Szkółka, Wojciech; de Szoeke, Simon P.; Tarot, Stéphane; Tetoni, Eleni; Thompson, Elizabeth; Thomson, Jim; Tomassini, Lorenzo; Hirsch, Lutz; Totems, Julien; Ubele, Alma Anna; Villiger, Leonie; von Arx, Jan; Wagner, Thomas; Walther, Andi; Webber, Ben; Wendisch, Manfred; Whitehall, Shanice; Wiltshire, Anton; Jacob, Marek; Wing, Allison A.; Wirth, Martin; Wiskandt, Jonathan; Wolf, Kevin; Worbes, Ludwig; Wright, Ethan; Wulfmeyer, Volker; Young, Shanea; Zhang, Chidong; Zhang, Dongxiao; Jansen, Friedhelm; Ziemen, Florian; Zinner, Tobias; Zöger, Martin; Kinne, Stefan; Klocke, Daniel; Kölling, Tobias; Konow, Heike; Lothon, Marie; Mohr, Wiebke; Naumann, Ann Kristin; Nuijens, Louise; Olivier, Léa; Pincus, Robert; Pöhlker, Mira; Reverdin, Gilles; Roberts, Gregory; Schnitt, Sabrina; Schulz, Hauke; Siebesma, A. Pier; Stephan, Claudia Christine; Sullivan, Peter; Touzé-Peiffer, Ludovic; Vial, Jessica; Vogel, Raphaela; Zuidema, Paquita; Alexander, Nicola; Alves, Lyndon; Arixi, Sophian; Asmath, Hamish; Bagheri, Gholamhossein; Baier, Katharina; Bailey, Adriana; Baranowski, Dariusz; Baron, Alexandre; Barrau, Sébastien; Barrett, Paul A.; Batier, Frédéric; Behrendt, Andreas; Bendinger, Arne; Beucher, Florent; Bigorre, Sebastien; Blades, Edmund; Blossey, Peter; Bock, Olivier; Böing, Steven; Bosser, Pierre; Bourras, Denis; Bouruet-Aubertot, Pascale; Bower, Keith; Branellec, Pierre; Branger, Hubert; Brennek, Michal; Brewer, Alan; Brilouet, Pierre-Etienne; Brügmann, Björn; Buehler, Stefan A.; Burke, Elmo; Burton, Ralph; Calmer, Radiance; Canonici, Jean-Christophe; Carton, Xavier; Cato Jr., Gregory; Charles, Jude Andre; Chazette, Patrick; Chen, Yanxu; Chilinski, Michal T.; Choularton, Thomas; Chuang, Patrick; Clarke, Shamal; Coe, Hugh; Cornet, Céline; Coutris, Pierre; Couvreux, FleurThe science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or the life cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso- (200 km) and larger (500 km) scales, roughly 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air–sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that EUREC4A explored – from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation – are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at https://doi.org/10.25326/165 (Stevens, 2021), and a film documenting the campaign is provided as a video supplement.
- ItemA comprehensive in situ and remote sensing data set from the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign(Katlenburg-Lindau : Copernics Publications, 2019) Ehrlich, André; Wendisch, Manfred; Lüpkes, Christof; Buschmann, Matthias; Bozem, Heiko; Chechin, Dmitri; Clemen, Hans-Christian; Dupuy, Régis; Eppers, Olliver; Hartmann, Jörg; Herber, Andreas; Jäkel, Evelyn; Järvinen, Emma; Jourdan, Olivier; Kästner, Udo; Kliesch, Leif-Leonard; Köllner, Franziska; Mech, Mario; Mertes, Stephan; Neuber, Roland; Ruiz-Donoso, Elena; Schnaiter, Martin; Schneide, Johannes; Stapf, Johannes; Zanatta, MarcoThe Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign was carried out north-west of Svalbard (Norway) between 23 May and 6 June 2017. The objective of ACLOUD was to study Arctic boundary layer and mid-level clouds and their role in Arctic amplification. Two research aircraft (Polar 5 and 6) jointly performed 22 research flights over the transition zone between open ocean and closed sea ice. Both aircraft were equipped with identical instrumentation for measurements of basic meteorological parameters, as well as for turbulent and radiative energy fluxes. In addition, on Polar 5 active and passive remote sensing instruments were installed, while Polar 6 operated in situ instruments to characterize cloud and aerosol particles as well as trace gases. A detailed overview of the specifications, data processing, and data quality is provided here. It is shown that the scientific analysis of the ACLOUD data benefits from the coordinated operation of both aircraft. By combining the cloud remote sensing techniques operated on Polar 5, the synergy of multi-instrument cloud retrieval is illustrated. The remote sensing methods were validated using truly collocated in situ and remote sensing observations. The data of identical instruments operated on both aircraft were merged to extend the spatial coverage of mean atmospheric quantities and turbulent and radiative flux measurement. Therefore, the data set of the ACLOUD campaign provides comprehensive in situ and remote sensing observations characterizing the cloudy Arctic atmosphere. All processed, calibrated, and validated data are published in the World Data Center PANGAEA as instrument-separated data subsets (Ehrlich et al., 2019b, https://doi.org/10.1594/PANGAEA.902603).
- ItemSISALv2: A comprehensive speleothem isotope database with multiple age-depth models(Katlenburg-Lindau : Copernics Publications, 2020) Comas-Bru, Laia; Rehfeld, Kira; Roesch, Carla; Amirnezhad-Mozhdehi, Sahar; Harrison, Sandy P.; Atsawawaranunt, Kamolphat; Ahmad, Syed Masood; Brahim, Yassine Ait; Baker, Andy; Bosomworth, Matthew; Breitenbach, Sebastian F.M.; Burstyn, Yuval; Columbu, Andrea; Deininger, Michael; Demény, Attila; Dixon, Bronwyn; Fohlmeister, Jens; Hatvani, István Gábor; Hu, Jun; Kaushal, Nikita; Kern, Zoltán; Labuhn, Inga; Lechleitner, Franziska A.; Lorrey, Andrew; Martrat, Belen; Felipe Novello, Valdir; Oster, Jessica; Pérez-Mejías, Carlos; Scholz, Denis; Scroxton, Nick; Sinha, Nitesh; Ward, Brittany Marie; Warken, Sophie; Zhang, Haiwei; SISAL Working Group membersCharacterizing the temporal uncertainty in palaeoclimate records is crucial for analysing past climate change, correlating climate events between records, assessing climate periodicities, identifying potential triggers and evaluating climate model simulations. The first global compilation of speleothem isotope records by the SISAL (Speleothem Isotope Synthesis and Analysis) working group showed that age model uncertainties are not systematically reported in the published literature, and these are only available for a limited number of records (ca. 15 %, n = 107=691). To improve the usefulness of the SISAL database, we have (i) improved the database's spatiooral coverage and (ii) created new chronologies using seven different approaches for age depth modelling. We have applied these alternative chronologies to the records from the first version of the SISAL database (SISALv1) and to new records compiled since the release of SISALv1. This paper documents the necessary changes in the structure of the SISAL database to accommodate the inclusion of the new age models and their uncertainties as well as the expansion of the database to include new records and the qualitycontrol measures applied. This paper also documents the age depth model approaches used to calculate the new chronologies. The updated version of the SISAL database (SISALv2) contains isotopic data from 691 speleothem records from 294 cave sites and new age depth models, including age depth temporal uncertainties for 512 speleothems. SISALv2 is available at https://doi.org/10.17864/1947.256 (Comas-Bru et al., 2020a). © 2020 Author(s).
- ItemGenerating a rule-based global gridded tillage dataset(Katlenburg-Lindau : Copernics Publications, 2020) Porwollik, Vera; Rolinski, Susanne; Heinke, Jens; Müller, ChristophTillage is a central element in agricultural soil management and has direct and indirect effects on processes in the biosphere. Effects of agricultural soil management can be assessed by soil, crop, and ecosystem models, but global assessments are hampered by lack of information on the type of tillage and their spatial distribution. This study describes the generation of a classification of tillage practices and presents the spatially explicit mapping of these crop-specific tillage systems for around the year 2005. Tillage practices differ by the kind of equipment used, soil surface and depth affected, timing, and their purpose within the cropping systems. We classified the broad variety of globally relevant tillage practices into six categories: no-tillage in the context of Conservation Agriculture, traditional annual, traditional rotational, rotational, reduced, and conventional annual tillage. The identified tillage systems were allocated to gridded crop-specific cropland areas with a resolution of 5 arcmin. Allocation rules were based on literature findings and combine area information on crop type, water management regime, field size, water erosion, income, and aridity. We scaled reported national Conservation Agriculture areas down to grid cells via a probability-based approach for 54 countries. We provide area estimates of the six tillage systems aggregated to global and country scale. We found that 8.67Mkm2 of global cropland area was tilled intensively at least once a year, whereas the remaining 2.65Mkm2 was tilled less intensely. Further, we identified 4.67Mkm2 of cropland as an area where Conservation Agriculture could be expanded to under current conditions. The tillage classification enables the parameterization of different soil management practices in various kinds of model simulations. The crop-specific tillage dataset indicates the spatial distribution of soil management practices, which is a prerequisite to assess erosion, carbon sequestration potential, as well as water, and nutrient dynamics of cropland soils. The dynamic definition of the allocation rules and accounting for national statistics, such as the share of Conservation Agriculture per country, also allow for derivation of datasets for historical and future global soil management scenarios. The resulting tillage system dataset and source code are accessible via an open-data repository (DOIs: https://doi.org/10.5880/PIK.2019.009 and https://doi.org/10.5880/PIK.2019.010, Porwollik et al., 2019a, b). © Author(s) 2019.