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The long-term relationship between temperature and hydroclimate remains uncertain due to the short length of instrumental measurements and inconsistent results from climate model simulations. This lack of understanding is particularly critical with regard to projected drought and flood risks. Here we assess warm-season co-variability patterns between temperature and hydroclimate over Europe back to 850 CE using instrumental measurements, tree-ring based reconstructions, and climate model simulations. We find that the temperature–hydroclimate relationship in both the instrumental and reconstructed data turns more positive at lower frequencies, but less so in model simulations, with a dipole emerging between positive (warm and wet) and negative (warm and dry) associations in northern and southern Europe, respectively. Compared to instrumental data, models reveal a more negative co-variability across all timescales, while reconstructions exhibit a more positive co-variability. Despite the observed differences in the temperature–hydroclimate co-variability patterns in instrumental, reconstructed and model simulated data, we find that all data types share relatively similar phase-relationships between temperature and hydroclimate, indicating the common influence of external forcing. The co-variability between temperature and soil moisture in the model simulations is overestimated, implying a possible overestimation of temperature-driven future drought risks.
Fredrik Charpentier Ljungqvist; Andrea Seim; Paul J. Krusic; Jesús Fidel González-Rouco; Johannes Peter Werner; Edward R Cook; Eduardo Zorita; Jürg Luterbacher; Elena Xoplaki; Georgia Destouni; Elena Garcia-Bustamante; Camilo Andrés Melo Aguilar; Kristina Seftigen; Jianglin Wang; Mary H. Gagen; Jan Esper; Olga Solomina; Dominik Fleitmann; Ulf Büntgen; Juerg Luterbacher. European warm-season temperature and hydroclimate since 850 CE. Environmental Research Letters 2019, 14, 084015 .
AMA StyleFredrik Charpentier Ljungqvist, Andrea Seim, Paul J. Krusic, Jesús Fidel González-Rouco, Johannes Peter Werner, Edward R Cook, Eduardo Zorita, Jürg Luterbacher, Elena Xoplaki, Georgia Destouni, Elena Garcia-Bustamante, Camilo Andrés Melo Aguilar, Kristina Seftigen, Jianglin Wang, Mary H. Gagen, Jan Esper, Olga Solomina, Dominik Fleitmann, Ulf Büntgen, Juerg Luterbacher. European warm-season temperature and hydroclimate since 850 CE. Environmental Research Letters. 2019; 14 (8):084015.
Chicago/Turabian StyleFredrik Charpentier Ljungqvist; Andrea Seim; Paul J. Krusic; Jesús Fidel González-Rouco; Johannes Peter Werner; Edward R Cook; Eduardo Zorita; Jürg Luterbacher; Elena Xoplaki; Georgia Destouni; Elena Garcia-Bustamante; Camilo Andrés Melo Aguilar; Kristina Seftigen; Jianglin Wang; Mary H. Gagen; Jan Esper; Olga Solomina; Dominik Fleitmann; Ulf Büntgen; Juerg Luterbacher. 2019. "European warm-season temperature and hydroclimate since 850 CE." Environmental Research Letters 14, no. 8: 084015.
The skill of the state-of-the-art climate field reconstruction technique BARCAST (Bayesian Algorithm for Reconstructing Climate Anomalies in Space and Time) to reconstruct temperature with pronounced long-range memory (LRM) characteristics is tested. A novel technique for generating fields of target data has been developed and is used to provide ensembles of LRM stochastic processes with a prescribed spatial covariance structure. Based on different parameter setups, hypothesis testing in the spectral domain is used to investigate if the field and spatial mean reconstructions are consistent with either the fractional Gaussian noise (fGn) process null hypothesis used for generating the target data, or the autoregressive model of order 1 (AR(1)) process null hypothesis which is the assumed temporal evolution model for the reconstruction technique. The study reveals that the resulting field and spatial mean reconstructions are consistent with the fGn process hypothesis for some of the tested parameter configurations, while others are in better agreement with the AR(1) model. There are local differences in reconstruction skill and reconstructed scaling characteristics between individual grid cells, and the agreement with the fGn model is generally better for the spatial mean reconstruction than at individual locations. Our results demonstrate that the use of target data with a different spatiotemporal covariance structure than the BARCAST model assumption can lead to a potentially biased climate field reconstruction (CFR) and associated confidence intervals.
Tine Nilsen; Johannes P. Werner; Dmitry V. Divine; Martin Rypdal. Assessing the performance of the BARCAST climate field reconstruction technique for a climate with long-range memory. Climate of the Past 2018, 14, 947 -967.
AMA StyleTine Nilsen, Johannes P. Werner, Dmitry V. Divine, Martin Rypdal. Assessing the performance of the BARCAST climate field reconstruction technique for a climate with long-range memory. Climate of the Past. 2018; 14 (6):947-967.
Chicago/Turabian StyleTine Nilsen; Johannes P. Werner; Dmitry V. Divine; Martin Rypdal. 2018. "Assessing the performance of the BARCAST climate field reconstruction technique for a climate with long-range memory." Climate of the Past 14, no. 6: 947-967.
In this article, the first spatially resolved and millennium-length summer (June–August) temperature reconstruction over the Arctic and sub-Arctic domain (north of 60° N) is presented. It is based on a set of 44 annually dated temperature-sensitive proxy archives of various types from the revised PAGES2k database supplemented with six new recently updated proxy records. As a major advance, an extension of the Bayesian BARCAST climate field (CF) reconstruction technique provides a means to treat climate archives with dating uncertainties. This results not only in a more precise reconstruction but additionally enables joint probabilistic constraints to be imposed on the chronologies of the used archives. The new seasonal CF reconstruction for the Arctic region can be shown to be skilful for the majority of the terrestrial nodes. The decrease in the proxy data density back in time, however, limits the analyses in the spatial domain to the period after 750 CE, while the spatially averaged reconstruction covers the entire time interval of 1–2002 CE.The centennial to millennial evolution of the reconstructed temperature is in good agreement with a general pattern that was inferred in recent studies for the Arctic and its subregions. In particular, the reconstruction shows a pronounced Medieval Climate Anomaly (MCA; here ca. 920–1060 CE), which was characterised by a sequence of extremely warm decades over the whole domain. The medieval warming was followed by a gradual cooling into the Little Ice Age (LIA), with 1766–1865 CE as the longest centennial-scale cold period, culminating around 1811–1820 CE for most of the target region.In total over 600 independent realisations of the temperature CF were generated. As showcased for local and regional trends and temperature anomalies, operating in a probabilistic framework directly results in comprehensive uncertainty estimates, even for complex analyses. For the presented multi-scale trend analysis, for example, the spread in different paths across the reconstruction ensemble prevents a robust analysis of features at timescales shorter than ca. 30 years. For the spatial reconstruction, the benefit of using the spatially resolved reconstruction ensemble is demonstrated by focusing on the regional expression of the recent warming and the MCA. While our analysis shows that the peak MCA summer temperatures were as high as in the late 20th and early 21st centuries, the spatial coherence of extreme years over the last decades of the reconstruction (1980s onwards) seems unprecedented at least back until 750 CE. However, statistical testing could not provide conclusive support of the contemporary warming to exceed the peak of the MCA in terms of the pan-Arctic mean summer temperatures: the reconstruction cannot be extended reliably past 2002 CE due to lack of proxy data and thus the most recent warming is not captured.
Johannes P. Werner; Dmitry V. Divine; Fredrik Charpentier Ljungqvist; Tine Nilsen; Pierre Francus. Spatio-temporal variability of Arctic summer temperatures over the past 2 millennia. Climate of the Past 2018, 14, 527 -557.
AMA StyleJohannes P. Werner, Dmitry V. Divine, Fredrik Charpentier Ljungqvist, Tine Nilsen, Pierre Francus. Spatio-temporal variability of Arctic summer temperatures over the past 2 millennia. Climate of the Past. 2018; 14 (4):527-557.
Chicago/Turabian StyleJohannes P. Werner; Dmitry V. Divine; Fredrik Charpentier Ljungqvist; Tine Nilsen; Pierre Francus. 2018. "Spatio-temporal variability of Arctic summer temperatures over the past 2 millennia." Climate of the Past 14, no. 4: 527-557.
Reanalysis data show an increasing trend in Arctic precipitation over the 20th century, but changes are not homogenous across seasons or space. The observed hydroclimate changes are expected to continue and possibly accelerate in the coming century, not only affecting pan-Arctic natural ecosystems and human activities, but also lower latitudes through the atmospheric and ocean circulations. However, a lack of spatiotemporal observational data makes reliable quantification of Arctic hydroclimate change difficult, especially in a long-term context. To understand Arctic hydroclimate and its variability prior to the instrumental record, climate proxy records are needed. The purpose of this review is to summarise the current understanding of Arctic hydroclimate during the past 2000 years. First, the paper reviews the main natural archives and proxies used to infer past hydroclimate variations in this remote region and outlines the difficulty of disentangling the moisture from the temperature signal in these records. Second, a comparison of two sets of hydroclimate records covering the Common Era from two data-rich regions, North America and Fennoscandia, reveals inter- and intra-regional differences. Third, building on earlier work, this paper shows the potential for providing a high-resolution hydroclimate reconstruction for the Arctic and a comparison with last-millennium simulations from fully coupled climate models. In general, hydroclimate proxies and simulations indicate that the Medieval Climate Anomaly tends to have been wetter than the Little Ice Age (LIA), but there are large regional differences. However, the regional coverage of the proxy data is inadequate, with distinct data gaps in most of Eurasia and parts of North America, making robust assessments for the whole Arctic impossible at present. To fully assess pan-Arctic hydroclimate variability for the last 2 millennia, additional proxy records are required.
Hans W. Linderholm; Marie Nicolle; Pierre Francus; Konrad Gajewski; Samuli Helama; Atte Korhola; Olga Solomina; Zicheng Yu; Peng Zhang; William J. D'Andrea; Maxime Debret; Dmitry V. Divine; Björn E. Gunnarson; Neil J. Loader; Nicolas Massei; Kristina Seftigen; Elizabeth K. Thomas; Johannes Werner; Sofia Andersson; Annika Berntsson; Tomi P. Luoto; Liisa Nevalainen; Saija Saarni; Minna Väliranta. Arctic hydroclimate variability during the last 2000 years: current understanding and research challenges. Climate of the Past 2018, 14, 473 -514.
AMA StyleHans W. Linderholm, Marie Nicolle, Pierre Francus, Konrad Gajewski, Samuli Helama, Atte Korhola, Olga Solomina, Zicheng Yu, Peng Zhang, William J. D'Andrea, Maxime Debret, Dmitry V. Divine, Björn E. Gunnarson, Neil J. Loader, Nicolas Massei, Kristina Seftigen, Elizabeth K. Thomas, Johannes Werner, Sofia Andersson, Annika Berntsson, Tomi P. Luoto, Liisa Nevalainen, Saija Saarni, Minna Väliranta. Arctic hydroclimate variability during the last 2000 years: current understanding and research challenges. Climate of the Past. 2018; 14 (4):473-514.
Chicago/Turabian StyleHans W. Linderholm; Marie Nicolle; Pierre Francus; Konrad Gajewski; Samuli Helama; Atte Korhola; Olga Solomina; Zicheng Yu; Peng Zhang; William J. D'Andrea; Maxime Debret; Dmitry V. Divine; Björn E. Gunnarson; Neil J. Loader; Nicolas Massei; Kristina Seftigen; Elizabeth K. Thomas; Johannes Werner; Sofia Andersson; Annika Berntsson; Tomi P. Luoto; Liisa Nevalainen; Saija Saarni; Minna Väliranta. 2018. "Arctic hydroclimate variability during the last 2000 years: current understanding and research challenges." Climate of the Past 14, no. 4: 473-514.
The Bayesian hierarchical model BARCAST (Bayesian Algorithm for Reconstructing Climate Anomalies in Space and Time) climate field reconstruction (CFR) technique, and idealized input data are used in the pseudoproxy experiments of this study. Ensembles of targets are generated from fields of long-range memory stochastic processes using a novel approach. The range of experiment setups include input data with different levels of persistence and levels of proxy noise, but without any form of external forcing. The input data are thereby a simplistic alternative to standard target data extracted from general circulation model (GCM) simulations. Ensemble-based temperature reconstructions are generated, representing the European landmass for a millennial time period. Hypothesis testing in the spectral domain is then used to investigate if the field and spatial mean reconstructions are consistent with either the fractional Gaussian noise (fGn) null hypothesis used for generating the target data, or the autoregressive model of order one (AR(1)) null hypothesis which is the assumed temperature model for this reconstruction technique. The study reveals that the resulting field and spatial mean reconstructions are consistent with the fGn hypothesis for most of the parameter configurations. There are local differences in reconstructed scaling characteristics between individual grid cells, and a generally better agreement with the fGn model for the spatial mean reconstruction than at individual locations. The discrepancy from an fGn is most evident for the high-frequency part of the reconstructed signal, while the long-range memory is better preserved at frequencies corresponding to decadal time scales and longer. Selected experiment setups were found to give reconstructions consistent with the AR(1) model. Reconstruction skill is measured on an ensemble member basis using selected validation metrics. Despite the mismatch between the BARCAST temporal covariance model and the model of the target, the ensemble mean was in general found to be consistent with the target data, while the estimated confidence intervals are more affected by this discrepancy. Our results show that the use of target data with a different spatiotemporal covariance structure than the BARCAST model assumption can lead to a potentially biased CFR reconstruction and associated confidence intervals, because of the wrong model assumptions.
Tine Nilsen; Johannes P. Werner; Dmitry V. Divine. How wrong are climate field reconstruction techniques in reconstructing a climate with long-range memory? 2018, 2018, 1 -39.
AMA StyleTine Nilsen, Johannes P. Werner, Dmitry V. Divine. How wrong are climate field reconstruction techniques in reconstructing a climate with long-range memory? . 2018; 2018 ():1-39.
Chicago/Turabian StyleTine Nilsen; Johannes P. Werner; Dmitry V. Divine. 2018. "How wrong are climate field reconstruction techniques in reconstructing a climate with long-range memory?" 2018, no. : 1-39.
Willem G.M. van der Bilt; William J. D'Andrea; Jostein Bakke; Nicholas L. Balascio; Johannes P. Werner; Marthe Gjerde; Raymond S. Bradley. Alkenone-based reconstructions reveal four-phase Holocene temperature evolution for High Arctic Svalbard. Quaternary Science Reviews 2018, 183, 204 -213.
AMA StyleWillem G.M. van der Bilt, William J. D'Andrea, Jostein Bakke, Nicholas L. Balascio, Johannes P. Werner, Marthe Gjerde, Raymond S. Bradley. Alkenone-based reconstructions reveal four-phase Holocene temperature evolution for High Arctic Svalbard. Quaternary Science Reviews. 2018; 183 ():204-213.
Chicago/Turabian StyleWillem G.M. van der Bilt; William J. D'Andrea; Jostein Bakke; Nicholas L. Balascio; Johannes P. Werner; Marthe Gjerde; Raymond S. Bradley. 2018. "Alkenone-based reconstructions reveal four-phase Holocene temperature evolution for High Arctic Svalbard." Quaternary Science Reviews 183, no. : 204-213.
To put recent climate change in perspective, it is necessary to extend the instrumental climate records with proxy data from paleoclimate archives. Arctic climate variability for the last 2 millennia has been investigated using statistical and signal analyses from three regionally averaged records from the North Atlantic, Siberia and Alaska based on many types of proxy data archived in the Arctic 2k database v1.1.1. In the North Atlantic and Alaska, the major climatic trend is characterized by long-term cooling interrupted by recent warming that started at the beginning of the 19th century. This cooling is visible in the Siberian region at two sites, warming at the others. The cooling of the Little Ice Age (LIA) was identified from the individual series, but it is characterized by wide-range spatial and temporal expression of climate variability, in contrary to the Medieval Climate Anomaly. The LIA started at the earliest by around AD 1200 and ended at the latest in the middle of the 20th century. The widespread temporal coverage of the LIA did not show regional consistency or particular spatial distribution and did not show a relationship with archive or proxy type either. A focus on the last 2 centuries shows a recent warming characterized by a well-marked warming trend parallel with increasing greenhouse gas emissions. It also shows a multidecadal variability likely due to natural processes acting on the internal climate system on a regional scale. A ∼ 16–30-year cycle is found in Alaska and seems to be linked to the Pacific Decadal Oscillation, whereas ∼ 20–30- and ∼ 50–90-year periodicities characterize the North Atlantic climate variability, likely in relation with the Atlantic Multidecadal Oscillation. These regional features are probably linked to the sea ice cover fluctuations through ice–temperature positive feedback.
Marie Nicolle; Maxime Debret; Nicolas Massei; Christophe Colin; Anne Devernal; Dmitry Divine; Johannes P. Werner; Anne Hormes; Atte Korhola; Hans W. Linderholm. Climate variability in the subarctic area for the last 2 millennia. Climate of the Past 2018, 14, 101 -116.
AMA StyleMarie Nicolle, Maxime Debret, Nicolas Massei, Christophe Colin, Anne Devernal, Dmitry Divine, Johannes P. Werner, Anne Hormes, Atte Korhola, Hans W. Linderholm. Climate variability in the subarctic area for the last 2 millennia. Climate of the Past. 2018; 14 (1):101-116.
Chicago/Turabian StyleMarie Nicolle; Maxime Debret; Nicolas Massei; Christophe Colin; Anne Devernal; Dmitry Divine; Johannes P. Werner; Anne Hormes; Atte Korhola; Hans W. Linderholm. 2018. "Climate variability in the subarctic area for the last 2 millennia." Climate of the Past 14, no. 1: 101-116.
Obtaining reliable reconstructions of long-term atmospheric circulation changes in the North Atlantic region presents a persistent challenge to contemporary paleoclimate research, which has been addressed by a multitude of recent studies. In order to contribute a novel methodological aspect to this active field, we apply here evolving functional network analysis, a recently developed tool for studying temporal changes of the spatial co-variability structure of the Earth's climate system, to a set of Late Holocene paleoclimate proxy records covering the last two millennia. The emerging patterns obtained by our analysis are related to long-term changes in the dominant mode of atmospheric circulation in the region, the North Atlantic Oscillation (NAO). By comparing the time-dependent inter-regional linkage structures of the obtained functional paleoclimate network representations to a recent multi-centennial NAO reconstruction, we identify co-variability between southern Greenland, Svalbard, and Fennoscandia as being indicative of a positive NAO phase, while connections from Greenland and Fennoscandia to central Europe are more pronounced during negative NAO phases. By drawing upon this correspondence, we use some key parameters of the evolving network structure to obtain a qualitative reconstruction of the NAO long-term variability over the entire Common Era (last 2000 years) using a linear regression model trained upon the existing shorter reconstruction.
Jasper G. Franke; Johannes P. Werner; Reik V. Donner. Reconstructing Late Holocene North Atlantic atmospheric circulation changes using functional paleoclimate networks. Climate of the Past 2017, 13, 1593 -1608.
AMA StyleJasper G. Franke, Johannes P. Werner, Reik V. Donner. Reconstructing Late Holocene North Atlantic atmospheric circulation changes using functional paleoclimate networks. Climate of the Past. 2017; 13 (11):1593-1608.
Chicago/Turabian StyleJasper G. Franke; Johannes P. Werner; Reik V. Donner. 2017. "Reconstructing Late Holocene North Atlantic atmospheric circulation changes using functional paleoclimate networks." Climate of the Past 13, no. 11: 1593-1608.
Johannes Werner. Trend analysis over Greenland. 2017, 1 .
AMA StyleJohannes Werner. Trend analysis over Greenland. . 2017; ():1.
Chicago/Turabian StyleJohannes Werner. 2017. "Trend analysis over Greenland." , no. : 1.
Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850–2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.
PAGES2k Consortium; Julien Emile-Geay; Nicholas P. McKay; Darrell S. Kaufman; Lucien von Gunten; Jianghao Wang; Kevin Anchukaitis; Nerilie Abram; Jason Addison; Mark A.J. Curran; Michael Evans; Benjamin Henley; Zhixin Hao; Belen Martrat; Helen McGregor; Raphael Neukom; Gregory T. Pederson; Barbara Stenni; Kaustubh Thirumalai; Johannes Werner; Chenxi Xu; Dmitry V. Divine; Bronwyn C. Dixon; Joelle Gergis; Ignacio Mundo; Takeshi Nakatsuka; Steven Phipps; Cody C. Routson; Eric J. Steig; Jessica Tierney; Jonathan Tyler; Kathryn J. Allen; Nancy Bertler; Jesper Björklund; Brian M. Chase; Min-Te Chen; Ed Cook; Rixt De Jong; Kristine L. DeLong; Daniel A. Dixon; Alexey A. Ekaykin; Vasile Ersek; Helena Filipsson; Pierre Francus; Mandy B. Freund; Massimo Frezzotti; Narayan P. Gaire; Konrad Gajewski; Quansheng Ge; Hugues Goosse; Anastasia Gornostaeva; Martin Grosjean; Kazuho Horiuchi; Anne Hormes; Katrine Husum; Elisabeth Isaksson; Selvaraj Kandasamy; Kenji Kawamura; K. Halimeda Kilbourne; Nalan Koç; Guillaume Leduc; Hans Linderholm; Andrew M. Lorrey; Vladimir Mikhalenko; P. Graham Mortyn; Hideaki Motoyama; Andrew D. Moy; Robert Mulvaney; Philipp Munz; David Nash; Hans Oerter; Thomas Opel; Anais J. Orsi; Dmitriy V. Ovchinnikov; Trevor Porter; Heidi A. Roop; Casey Saenger; Masaki Sano; David Sauchyn; Krystyna M. Saunders; Marit-Solveig Seidenkrantz; Mirko Severi; Xuemei Shao; Marie-Alexandrine Sicre; Michael Sigl; Kate Sinclair; Scott St. George; Jeannine-Marie St. Jacques; Meloth Thamban; Udya Kuwar Thapa; Elizabeth R. Thomas; Chris Turney; Ryu Uemura; Andre E. Viau; Diana O. Vladimirova; Eugene R. Wahl; James W.C. White; Zicheng Yu; Jens Zinke. A global multiproxy database for temperature reconstructions of the Common Era. Scientific Data 2017, 4, 170088 -170088.
AMA StylePAGES2k Consortium, Julien Emile-Geay, Nicholas P. McKay, Darrell S. Kaufman, Lucien von Gunten, Jianghao Wang, Kevin Anchukaitis, Nerilie Abram, Jason Addison, Mark A.J. Curran, Michael Evans, Benjamin Henley, Zhixin Hao, Belen Martrat, Helen McGregor, Raphael Neukom, Gregory T. Pederson, Barbara Stenni, Kaustubh Thirumalai, Johannes Werner, Chenxi Xu, Dmitry V. Divine, Bronwyn C. Dixon, Joelle Gergis, Ignacio Mundo, Takeshi Nakatsuka, Steven Phipps, Cody C. Routson, Eric J. Steig, Jessica Tierney, Jonathan Tyler, Kathryn J. Allen, Nancy Bertler, Jesper Björklund, Brian M. Chase, Min-Te Chen, Ed Cook, Rixt De Jong, Kristine L. DeLong, Daniel A. Dixon, Alexey A. Ekaykin, Vasile Ersek, Helena Filipsson, Pierre Francus, Mandy B. Freund, Massimo Frezzotti, Narayan P. Gaire, Konrad Gajewski, Quansheng Ge, Hugues Goosse, Anastasia Gornostaeva, Martin Grosjean, Kazuho Horiuchi, Anne Hormes, Katrine Husum, Elisabeth Isaksson, Selvaraj Kandasamy, Kenji Kawamura, K. Halimeda Kilbourne, Nalan Koç, Guillaume Leduc, Hans Linderholm, Andrew M. Lorrey, Vladimir Mikhalenko, P. Graham Mortyn, Hideaki Motoyama, Andrew D. Moy, Robert Mulvaney, Philipp Munz, David Nash, Hans Oerter, Thomas Opel, Anais J. Orsi, Dmitriy V. Ovchinnikov, Trevor Porter, Heidi A. Roop, Casey Saenger, Masaki Sano, David Sauchyn, Krystyna M. Saunders, Marit-Solveig Seidenkrantz, Mirko Severi, Xuemei Shao, Marie-Alexandrine Sicre, Michael Sigl, Kate Sinclair, Scott St. George, Jeannine-Marie St. Jacques, Meloth Thamban, Udya Kuwar Thapa, Elizabeth R. Thomas, Chris Turney, Ryu Uemura, Andre E. Viau, Diana O. Vladimirova, Eugene R. Wahl, James W.C. White, Zicheng Yu, Jens Zinke. A global multiproxy database for temperature reconstructions of the Common Era. Scientific Data. 2017; 4 (1):170088-170088.
Chicago/Turabian StylePAGES2k Consortium; Julien Emile-Geay; Nicholas P. McKay; Darrell S. Kaufman; Lucien von Gunten; Jianghao Wang; Kevin Anchukaitis; Nerilie Abram; Jason Addison; Mark A.J. Curran; Michael Evans; Benjamin Henley; Zhixin Hao; Belen Martrat; Helen McGregor; Raphael Neukom; Gregory T. Pederson; Barbara Stenni; Kaustubh Thirumalai; Johannes Werner; Chenxi Xu; Dmitry V. Divine; Bronwyn C. Dixon; Joelle Gergis; Ignacio Mundo; Takeshi Nakatsuka; Steven Phipps; Cody C. Routson; Eric J. Steig; Jessica Tierney; Jonathan Tyler; Kathryn J. Allen; Nancy Bertler; Jesper Björklund; Brian M. Chase; Min-Te Chen; Ed Cook; Rixt De Jong; Kristine L. DeLong; Daniel A. Dixon; Alexey A. Ekaykin; Vasile Ersek; Helena Filipsson; Pierre Francus; Mandy B. Freund; Massimo Frezzotti; Narayan P. Gaire; Konrad Gajewski; Quansheng Ge; Hugues Goosse; Anastasia Gornostaeva; Martin Grosjean; Kazuho Horiuchi; Anne Hormes; Katrine Husum; Elisabeth Isaksson; Selvaraj Kandasamy; Kenji Kawamura; K. Halimeda Kilbourne; Nalan Koç; Guillaume Leduc; Hans Linderholm; Andrew M. Lorrey; Vladimir Mikhalenko; P. Graham Mortyn; Hideaki Motoyama; Andrew D. Moy; Robert Mulvaney; Philipp Munz; David Nash; Hans Oerter; Thomas Opel; Anais J. Orsi; Dmitriy V. Ovchinnikov; Trevor Porter; Heidi A. Roop; Casey Saenger; Masaki Sano; David Sauchyn; Krystyna M. Saunders; Marit-Solveig Seidenkrantz; Mirko Severi; Xuemei Shao; Marie-Alexandrine Sicre; Michael Sigl; Kate Sinclair; Scott St. George; Jeannine-Marie St. Jacques; Meloth Thamban; Udya Kuwar Thapa; Elizabeth R. Thomas; Chris Turney; Ryu Uemura; Andre E. Viau; Diana O. Vladimirova; Eugene R. Wahl; James W.C. White; Zicheng Yu; Jens Zinke. 2017. "A global multiproxy database for temperature reconstructions of the Common Era." Scientific Data 4, no. 1: 170088-170088.
Johannes Werner. Reply to the review by N. McKay. 2017, 1 .
AMA StyleJohannes Werner. Reply to the review by N. McKay. . 2017; ():1.
Chicago/Turabian StyleJohannes Werner. 2017. "Reply to the review by N. McKay." , no. : 1.
Johannes Werner. Reply to the first reviewer. 2017, 1 .
AMA StyleJohannes Werner. Reply to the first reviewer. . 2017; ():1.
Chicago/Turabian StyleJohannes Werner. 2017. "Reply to the first reviewer." , no. : 1.
Johannes Werner. Reply to the Data Review Comment. 2017, 1 .
AMA StyleJohannes Werner. Reply to the Data Review Comment. . 2017; ():1.
Chicago/Turabian StyleJohannes Werner. 2017. "Reply to the Data Review Comment." , no. : 1.
J Esper; U Büntgen; S Denzer; Pj Krusic; J Luterbacher; R Schäfer; R Schreg; J Werner. Environmental drivers of historical grain price variations in Europe. Climate Research 2017, 72, 39 -52.
AMA StyleJ Esper, U Büntgen, S Denzer, Pj Krusic, J Luterbacher, R Schäfer, R Schreg, J Werner. Environmental drivers of historical grain price variations in Europe. Climate Research. 2017; 72 (1):39-52.
Chicago/Turabian StyleJ Esper; U Büntgen; S Denzer; Pj Krusic; J Luterbacher; R Schäfer; R Schreg; J Werner. 2017. "Environmental drivers of historical grain price variations in Europe." Climate Research 72, no. 1: 39-52.
To put in perspective the recent climate change, it is necessary to extend the instrumental climate records with proxy data from palaeoclimate archives. Arctic climate variability for the last two millennia has been investigated using statistical and signal analyses from three regionally averaged records from the North Atlantic, Siberia and Alaska based on many sort of proxy data archived in the Arctic 2k database. In the North Atlantic and Alaska areas, the major climatic trend is characterized by long-term cooling interrupted by the recent warming that started at the beginning of the 19th century. This cooling trend is not clearly visible in the Siberian region. The Little Ice Age (LIA) was identified from the individual series and is characterized by an important spatial and temporal expression of climate variability. It started at the earliest by around 1200 AD and ended at the latest in the middle of the 20th century. The large spread temporal coverage of LIA did not show regional consistency or particular spatial distribution and did not show relationship with archive/proxy type either. A focus on the last two centuries shows a recent warming characterized by a well-marked warming trend paralleling with increasing greenhouse gas emissions. It also shows a multi-decadal variability likely due to natural processes acting on the internal climate system variability at regional scale. A 16–30 years cycle is found in Alaska and seems to be linked to the Pacific Decadal Oscillation (PDO) whereas ~ 20–30 and ~ 50–90 years periodicities characterize the North Atlantic climate regime, likely in relation with the Atlantic Multidecadal Oscillation (AMO). These regional features are apparently linked to the sea-ice cover fluctuations through ice-temperature positive feedback.
Marie Nicolle; Maxime Debret; Nicolas Massei; Christophe Colin; Anne Devernal; Dmitry Divine; Johannes P. Werner; Anne Hormes; Atte Korhola; Hans W. Linderholm. Climate variability in subarctic area for the last two millennia. 2017, 2017, 1 -24.
AMA StyleMarie Nicolle, Maxime Debret, Nicolas Massei, Christophe Colin, Anne Devernal, Dmitry Divine, Johannes P. Werner, Anne Hormes, Atte Korhola, Hans W. Linderholm. Climate variability in subarctic area for the last two millennia. . 2017; 2017 ():1-24.
Chicago/Turabian StyleMarie Nicolle; Maxime Debret; Nicolas Massei; Christophe Colin; Anne Devernal; Dmitry Divine; Johannes P. Werner; Anne Hormes; Atte Korhola; Hans W. Linderholm. 2017. "Climate variability in subarctic area for the last two millennia." 2017, no. : 1-24.
Marie Nicolle; Maxime Debret; Nicolas Massei; Christophe Colin; Anne Devernal; Dmitry Divine; Johannes P. Werner; Anne Hormes; Atte Korhola; Hans W. Linderholm. Supplementary material to "Climate variability in subarctic area for the last two millennia". 2017, 1 .
AMA StyleMarie Nicolle, Maxime Debret, Nicolas Massei, Christophe Colin, Anne Devernal, Dmitry Divine, Johannes P. Werner, Anne Hormes, Atte Korhola, Hans W. Linderholm. Supplementary material to "Climate variability in subarctic area for the last two millennia". . 2017; ():1.
Chicago/Turabian StyleMarie Nicolle; Maxime Debret; Nicolas Massei; Christophe Colin; Anne Devernal; Dmitry Divine; Johannes P. Werner; Anne Hormes; Atte Korhola; Hans W. Linderholm. 2017. "Supplementary material to "Climate variability in subarctic area for the last two millennia"." , no. : 1.
In this article, the first spatially resolved millennium-long summer (June–August) temperature reconstruction over the Arctic and Subarctic domain (north of 60° N) is presented. It is based on a set of 54 annually dated temperature sensitive proxy archives of various types, mainly from the updated and revised PAGES2k database supplemented with 6 new recently published proxy records. As a major novelty, an extension of the Bayesian BARCAST climate field (CF) reconstruction technique provides a means to treat climate archives with dating uncertainties. In total 1400 realisations of the temperature CF were generated, enabling further analyses to be carried out in a probabilistic framework. The new seasonal CF reconstruction for the Arctic region can be shown to be skilful for the majority of the terrestrial nodes. The decrease in the proxy data density back in time however limits the analyses in the spatial domain to the period after 750 CE, while the spatially averaged reconstruction covers the entire time interval of 1–2002 CE. The analysis of basic features of the reconstructed seasonal CF focuses on the regional expression of past major climate anomalies in order to uncover the potential of the new product for studying Common Era temperature variability in the region. The long-term, centennial to millennial, evolution of the reconstructed temperature is in good agreement with a general pattern that was inferred in recent studies for the Arctic and its sub-regions. On the pan-Arctic scale the reconstruction shows a cooling trend which is, however, statistically insignificant and the estimated magnitude of the millennial scale cooling is three times smaller than inferred in the previous studies. The trend is spatially heterogeneous and for some regions such as Greenland the reconstruction demonstrates a tendency to the warming instead. The reconstruction shows a pronounced Medieval Climate Anomaly (MCA, here, ca. ~ 960–1060 CE), which was characterised by a sequence of extremely warm decades over the whole domain. The medieval warming was followed by a gradual cooling into the Little Ice Age (LIA), with 1580–1680 CE as the longest centennial-scale cold period, culminating around 1812–1822 CE for most of the target region. At the same time there is evidence for a drastic reduction in sea-ice on the Greenland shelf, which is reflected by rather high summer temperatures over Greenland and Baffin Island during that decade. During the MCA, the contrast between reconstructed summer temperatures over mid- and high-latitudes in Europe and the European/North Atlantic sector of the Arctic shows a very dynamic expression of the Arctic amplification, with leads and lags between continental and more marine and extreme latitude settings. While our analysis shows that the peak MCA summer temperatures were as high as in the late 20th and early 21st century, the spatial coherence of extreme years over the last decades seems unprecedented at least back until 750 CE. However, statistical testing could not provide conclusive support of the contemporary warming to supersede the peak of the MCA in terms of the pan-Arctic mean summer temperatures.
Johannes P. Werner; Dmitry V. Divine; Fredrik Charpentier Ljungqvist; Tine Nilsen; Pierre Francus. Spatio-temporal variability of Arctic summer temperatures over the past two millennia: an overview of the last major climate anomalies. 2017, 1 -43.
AMA StyleJohannes P. Werner, Dmitry V. Divine, Fredrik Charpentier Ljungqvist, Tine Nilsen, Pierre Francus. Spatio-temporal variability of Arctic summer temperatures over the past two millennia: an overview of the last major climate anomalies. . 2017; ():1-43.
Chicago/Turabian StyleJohannes P. Werner; Dmitry V. Divine; Fredrik Charpentier Ljungqvist; Tine Nilsen; Pierre Francus. 2017. "Spatio-temporal variability of Arctic summer temperatures over the past two millennia: an overview of the last major climate anomalies." , no. : 1-43.
Along with Arctic amplification, changes in Arctic hydroclimate have become increasingly apparent. Reanalysis data show increasing trends in Arctic temperature and precipitation over the 20th century, but changes are not homogenous across seasons or space. The observed hydroclimate changes are expected to continue, and possibly accelerate, in the coming century, not only affecting pan-Arctic natural ecosystems and human activities, but also lower latitudes through changes in atmospheric and oceanic circulation. However, a lack of spatiotemporal observational data makes reliable quantification of Arctic hydroclimate change difficult, especially in a long-term context. To understand hydroclimate variability and the mechanisms driving observed changes, beyond the instrumental record, climate proxies are needed. Here we bring together the current understanding of Arctic hydroclimate during the past 2000 years, as inferred from natural archives and proxies and palaeoclimate model simulations. Inadequate proxy data coverage is apparent, with distinct data gaps in most of Eurasia and parts of North America, which makes robust assessments for the whole Arctic currently impossible. Hydroclimate proxies and climate models indicate that the Medieval Climate Anomaly (MCA) was anomalously wet, while conditions were in general drier during the Little Ice Age (LIA), relative to the last 2000 years. However, it is clear that there are large regional differences, which are especially evident during the LIA. Due to the spatiotemporal differences in Arctic hydroclimate, we recommend detailed regional studies, e.g. including field reconstructions, to disentangle spatial patterns and potential forcing factors. At present, it is only possible to carry out regional syntheses for a few areas of the Arctic, e.g. Fennoscandia, Greenland and western North America. To fully assess pan-Arctic hydroclimate variability for the last two millennia additional proxy records are required.
Hans W. Linderholm; Marie Nicolle; Pierre Francus; Konrad Gajewski; Samuli Helama; Atte Korhola; Olga Solomina; Zicheng Yu; Peng Zhang; William J. D'andrea; Maxime Debret; Dmitry Divine; Björn E. Gunnarson; Neil J. Loader; Nicolas Massei; Kristina Seftifgen; Elizabeth K. Thomas; Johannes Werner. Arctic hydroclimate variability during the last 2000 years – current understanding and research challenges. 2017, 2017, 1 -87.
AMA StyleHans W. Linderholm, Marie Nicolle, Pierre Francus, Konrad Gajewski, Samuli Helama, Atte Korhola, Olga Solomina, Zicheng Yu, Peng Zhang, William J. D'andrea, Maxime Debret, Dmitry Divine, Björn E. Gunnarson, Neil J. Loader, Nicolas Massei, Kristina Seftifgen, Elizabeth K. Thomas, Johannes Werner. Arctic hydroclimate variability during the last 2000 years – current understanding and research challenges. . 2017; 2017 ():1-87.
Chicago/Turabian StyleHans W. Linderholm; Marie Nicolle; Pierre Francus; Konrad Gajewski; Samuli Helama; Atte Korhola; Olga Solomina; Zicheng Yu; Peng Zhang; William J. D'andrea; Maxime Debret; Dmitry Divine; Björn E. Gunnarson; Neil J. Loader; Nicolas Massei; Kristina Seftifgen; Elizabeth K. Thomas; Johannes Werner. 2017. "Arctic hydroclimate variability during the last 2000 years – current understanding and research challenges." 2017, no. : 1-87.
Hans W. Linderholm; Marie Nicolle; Pierre Francus; Konrad Gajewski; Samuli Helama; Atte Korhola; Olga Solomina; Zicheng Yu; Peng Zhang; William J. D'andrea; Maxime Debret; Dmitry Divine; Björn E. Gunnarson; Neil J. Loader; Nicolas Massei; Kristina Seftifgen; Elizabeth K. Thomas; Johannes Werner. Supplementary material to "Arctic hydroclimate variability during the last 2000 years – current understanding and research challenges". 2017, 1 .
AMA StyleHans W. Linderholm, Marie Nicolle, Pierre Francus, Konrad Gajewski, Samuli Helama, Atte Korhola, Olga Solomina, Zicheng Yu, Peng Zhang, William J. D'andrea, Maxime Debret, Dmitry Divine, Björn E. Gunnarson, Neil J. Loader, Nicolas Massei, Kristina Seftifgen, Elizabeth K. Thomas, Johannes Werner. Supplementary material to "Arctic hydroclimate variability during the last 2000 years – current understanding and research challenges". . 2017; ():1.
Chicago/Turabian StyleHans W. Linderholm; Marie Nicolle; Pierre Francus; Konrad Gajewski; Samuli Helama; Atte Korhola; Olga Solomina; Zicheng Yu; Peng Zhang; William J. D'andrea; Maxime Debret; Dmitry Divine; Björn E. Gunnarson; Neil J. Loader; Nicolas Massei; Kristina Seftifgen; Elizabeth K. Thomas; Johannes Werner. 2017. "Supplementary material to "Arctic hydroclimate variability during the last 2000 years – current understanding and research challenges"." , no. : 1.
Jasper G. Franke; Johannes P. Werner; Reik V. Donner. Supplementary material to "Reconstructing Late Holocene North Atlantic atmospheric circulation changes using functional paleoclimate networks". 2017, 1 .
AMA StyleJasper G. Franke, Johannes P. Werner, Reik V. Donner. Supplementary material to "Reconstructing Late Holocene North Atlantic atmospheric circulation changes using functional paleoclimate networks". . 2017; ():1.
Chicago/Turabian StyleJasper G. Franke; Johannes P. Werner; Reik V. Donner. 2017. "Supplementary material to "Reconstructing Late Holocene North Atlantic atmospheric circulation changes using functional paleoclimate networks"." , no. : 1.