Articles | Volume 17, issue 2
https://doi.org/10.5194/cp-17-721-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-17-721-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Technical note: Considerations on using uncertain proxies in the analogue method for spatiotemporal reconstructions of millennial-scale climate
Institute of Coastal Systems – Analysis and Modeling, Helmholtz Zentrum Geesthacht, 21502 Geesthacht, Germany
Eduardo Zorita
Institute of Coastal Systems – Analysis and Modeling, Helmholtz Zentrum Geesthacht, 21502 Geesthacht, Germany
Related authors
Nils Weitzel, Heather Andres, Jean-Philippe Baudouin, Marie-Luise Kapsch, Uwe Mikolajewicz, Lukas Jonkers, Oliver Bothe, Elisa Ziegler, Thomas Kleinen, André Paul, and Kira Rehfeld
Clim. Past, 20, 865–890, https://doi.org/10.5194/cp-20-865-2024, https://doi.org/10.5194/cp-20-865-2024, 2024
Short summary
Short summary
The ability of climate models to faithfully reproduce past warming episodes is a valuable test considering potentially large future warming. We develop a new method to compare simulations of the last deglaciation with temperature reconstructions. We find that reconstructions differ more between regions than simulations, potentially due to deficiencies in the simulation design, models, or reconstructions. Our work is a promising step towards benchmarking simulations of past climate transitions.
Lukas Jonkers, Oliver Bothe, and Michal Kucera
Clim. Past, 17, 2577–2581, https://doi.org/10.5194/cp-17-2577-2021, https://doi.org/10.5194/cp-17-2577-2021, 2021
Kai Bellinghausen, Birgit Hünicke, and Eduardo Zorita
EGUsphere, https://doi.org/10.5194/egusphere-2026-523, https://doi.org/10.5194/egusphere-2026-523, 2026
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
Storm extremes across Northern Hemisphere land areas have a structured synchronised pattern. Using ERA5 data (1940–2023) and a storm index based on local wind‑speed extremes, we find that northern regions above 50° N vary together, opposite to more southern areas. Links to SST, SKT and pressure fields point to climate modes like the NAO as possible drivers. ACE2 emulator experiments confirm that surface‑temperature patterns can drive jet‑stream shifts possibly altering the mode of storminess.
Kai Bellinghausen, Birgit Hünicke, and Eduardo Zorita
Nat. Hazards Earth Syst. Sci., 25, 1139–1162, https://doi.org/10.5194/nhess-25-1139-2025, https://doi.org/10.5194/nhess-25-1139-2025, 2025
Short summary
Short summary
We designed a tool to predict the storm surges at the Baltic Sea coast with satisfactory predictability (80 % correct predictions), using lead times of a few days. The proportion of false warnings is typically as low as 10 % to 20 %. We were able to identify the relevant predictor regions and their patterns – such as low-pressure systems and strong winds. Due to its short computing time, the method can be used as a pre-warning system to trigger the application of more sophisticated algorithms.
Nils Weitzel, Heather Andres, Jean-Philippe Baudouin, Marie-Luise Kapsch, Uwe Mikolajewicz, Lukas Jonkers, Oliver Bothe, Elisa Ziegler, Thomas Kleinen, André Paul, and Kira Rehfeld
Clim. Past, 20, 865–890, https://doi.org/10.5194/cp-20-865-2024, https://doi.org/10.5194/cp-20-865-2024, 2024
Short summary
Short summary
The ability of climate models to faithfully reproduce past warming episodes is a valuable test considering potentially large future warming. We develop a new method to compare simulations of the last deglaciation with temperature reconstructions. We find that reconstructions differ more between regions than simulations, potentially due to deficiencies in the simulation design, models, or reconstructions. Our work is a promising step towards benchmarking simulations of past climate transitions.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
Short summary
Short summary
Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Nele Tim, Birgit Hünicke, and Eduardo Zorita
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-147, https://doi.org/10.5194/nhess-2023-147, 2023
Manuscript not accepted for further review
Short summary
Short summary
Our study analyses extreme precipitation over southern Africa in regional high-resolution atmospheric simulations of the past and future. We investigated heavy precipitation over Southern Africa, coastal South Africa, Cape Town, and the KwaZulu-Natal province in eastern South Africa. Coastal precipitation extremes are projected to intensify, double in intensity in KwaZulu-Natal, and weaken in Cape Town. Extremes are not projected to occur more often in the 21st century than in the last decades.
Nele Tim, Eduardo Zorita, Birgit Hünicke, and Ioana Ivanciu
Weather Clim. Dynam., 4, 381–397, https://doi.org/10.5194/wcd-4-381-2023, https://doi.org/10.5194/wcd-4-381-2023, 2023
Short summary
Short summary
As stated by the IPCC, southern Africa is one of the two land regions that are projected to suffer from the strongest precipitation reductions in the future. Simulated drying in this region is linked to the adjacent oceans, and prevailing winds as warm and moist air masses are transported towards the continent. Precipitation trends in past and future climate can be partly attributed to the strength of the Agulhas Current system, the current along the east and south coasts of southern Africa.
Kai Bellinghausen, Birgit Hünicke, and Eduardo Zorita
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-21, https://doi.org/10.5194/nhess-2023-21, 2023
Manuscript not accepted for further review
Short summary
Short summary
The prediction of extreme coastal sea level, e.g. caused by a storm surge, is operationally carried out with dynamical computer models. These models are expensive to run and still display some limitations in predicting the height of extremes. We present a successful purely data-driven machine learning model to predict extreme sea levels along the Baltic Sea coast a few days in advance. The method is also able to identify the critical predictors for the different Baltic Sea regions.
Zeguo Zhang, Sebastian Wagner, Marlene Klockmann, and Eduardo Zorita
Clim. Past, 18, 2643–2668, https://doi.org/10.5194/cp-18-2643-2022, https://doi.org/10.5194/cp-18-2643-2022, 2022
Short summary
Short summary
A bidirectional long short-term memory (LSTM) neural network was employed for the first time for past temperature field reconstructions. The LSTM method tested in our experiments using a limited calibration and validation dataset shows worse reconstruction skills compared to traditional reconstruction methods. However, a certain degree of reconstruction performance achieved by the nonlinear LSTM method shows that skill can be achieved even when using small samples with limited datasets.
H. E. Markus Meier, Madline Kniebusch, Christian Dieterich, Matthias Gröger, Eduardo Zorita, Ragnar Elmgren, Kai Myrberg, Markus P. Ahola, Alena Bartosova, Erik Bonsdorff, Florian Börgel, Rene Capell, Ida Carlén, Thomas Carlund, Jacob Carstensen, Ole B. Christensen, Volker Dierschke, Claudia Frauen, Morten Frederiksen, Elie Gaget, Anders Galatius, Jari J. Haapala, Antti Halkka, Gustaf Hugelius, Birgit Hünicke, Jaak Jaagus, Mart Jüssi, Jukka Käyhkö, Nina Kirchner, Erik Kjellström, Karol Kulinski, Andreas Lehmann, Göran Lindström, Wilhelm May, Paul A. Miller, Volker Mohrholz, Bärbel Müller-Karulis, Diego Pavón-Jordán, Markus Quante, Marcus Reckermann, Anna Rutgersson, Oleg P. Savchuk, Martin Stendel, Laura Tuomi, Markku Viitasalo, Ralf Weisse, and Wenyan Zhang
Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, https://doi.org/10.5194/esd-13-457-2022, 2022
Short summary
Short summary
Based on the Baltic Earth Assessment Reports of this thematic issue in Earth System Dynamics and recent peer-reviewed literature, current knowledge about the effects of global warming on past and future changes in the climate of the Baltic Sea region is summarised and assessed. The study is an update of the Second Assessment of Climate Change (BACC II) published in 2015 and focuses on the atmosphere, land, cryosphere, ocean, sediments, and the terrestrial and marine biosphere.
Marcus Reckermann, Anders Omstedt, Tarmo Soomere, Juris Aigars, Naveed Akhtar, Magdalena Bełdowska, Jacek Bełdowski, Tom Cronin, Michał Czub, Margit Eero, Kari Petri Hyytiäinen, Jukka-Pekka Jalkanen, Anders Kiessling, Erik Kjellström, Karol Kuliński, Xiaoli Guo Larsén, Michelle McCrackin, H. E. Markus Meier, Sonja Oberbeckmann, Kevin Parnell, Cristian Pons-Seres de Brauwer, Anneli Poska, Jarkko Saarinen, Beata Szymczycha, Emma Undeman, Anders Wörman, and Eduardo Zorita
Earth Syst. Dynam., 13, 1–80, https://doi.org/10.5194/esd-13-1-2022, https://doi.org/10.5194/esd-13-1-2022, 2022
Short summary
Short summary
As part of the Baltic Earth Assessment Reports (BEAR), we present an inventory and discussion of different human-induced factors and processes affecting the environment of the Baltic Sea region and their interrelations. Some are naturally occurring and modified by human activities, others are completely human-induced, and they are all interrelated to different degrees. The findings from this study can largely be transferred to other comparable marginal and coastal seas in the world.
Lukas Jonkers, Oliver Bothe, and Michal Kucera
Clim. Past, 17, 2577–2581, https://doi.org/10.5194/cp-17-2577-2021, https://doi.org/10.5194/cp-17-2577-2021, 2021
Ralf Weisse, Inga Dailidienė, Birgit Hünicke, Kimmo Kahma, Kristine Madsen, Anders Omstedt, Kevin Parnell, Tilo Schöne, Tarmo Soomere, Wenyan Zhang, and Eduardo Zorita
Earth Syst. Dynam., 12, 871–898, https://doi.org/10.5194/esd-12-871-2021, https://doi.org/10.5194/esd-12-871-2021, 2021
Short summary
Short summary
The study is part of the thematic Baltic Earth Assessment Reports – a series of review papers summarizing the knowledge around major Baltic Earth science topics. It concentrates on sea level dynamics and coastal erosion (its variability and change). Many of the driving processes are relevant in the Baltic Sea. Contributions vary over short distances and across timescales. Progress and research gaps are described in both understanding details in the region and in extending general concepts.
Cited articles
Anand, P., Elderfield, H., and Conte, M. H.: Calibration of Mg/Ca thermometry
in planktonic foraminifera from a sediment trap time series,
Paleoceanography, 18, 1050, https://doi.org/10.1029/2002PA000846, 2003. a
Annan, J. D. and Hargreaves, J. C.: Identification of climatic state with limited proxy data, Clim. Past, 8, 1141–1151, https://doi.org/10.5194/cp-8-1141-2012, 2012. a, b, c, d
Bartlein, P. J. and Shafer, S. L.: Paleo calendar-effect adjustments in time-slice and transient climate-model simulations (PaleoCalAdjust v1.0): impact and strategies for data analysis, Geosci. Model Dev., 12, 3889–3913, https://doi.org/10.5194/gmd-12-3889-2019, 2019. a
Bendle, J. and Rosell-Melé, A.: High-resolution alkenone sea surface
temperature variability on the North Icelandic Shelf: implications for Nordic
Seas palaeoclimatic development during the Holocene, Holocene, 17,
9–24, https://doi.org/10.1177/0959683607073269, 2007. a
Bothe, O.: Reconstruction data and information about valid analogues for “Technical Note: Considerations on using uncertain proxies in the analogue method for spatiotemporal reconstructions of millennial-scale climate”, Open Science Framework, https://doi.org/10.17605/OSF.IO/PJ9EG, 2019. a
Bothe, O. and Zorita, E.: Proxy surrogate reconstructions for Europe and the estimation of their uncertainties, Clim. Past, 16, 341–369, https://doi.org/10.5194/cp-16-341-2020, 2020. a
Bothe, O., Wagner, S., and Zorita, E.: Simple noise estimates and pseudoproxies for the last 21k years, Open Science Framework, https://doi.org/10.17605/OSF.IO/ZBEHX, 2019b. a
Braconnot, P., Harrison, S. P., Otto-Bliesner, B., Abe-Ouchi, A., Jungclaus,
J., and Peterschmitt, J. Y.: The Paleoclimate Modeling Intercomparison
Project contribution to CMIP5, CLIVAR Exchanges, 56, 15–19, 2011. a
Braconnot, P., Harrison, S. P., Kageyama, M., Bartlein, P. J., Masson-Delmotte,
V., Abe-Ouchi, A., Otto-Bliesner, B., and Zhao, Y.: Evaluation of climate
models using palaeoclimatic data, Nat. Clim. Change, 2, 417–424,
https://doi.org/10.1038/nclimate1456, 2012. a
Budich, R., Giorgetta, M., Jungclaus, J. H., and Reick, C. H.: The MPI-M
Millennium Earth System Model: An Assembling Guide for the COSMOS
Configuration, Technical Report, available at:
https://pure.mpg.de/rest/items/item_2193290/component/file_2193291/content
(last access: 29 December 2020), 2010. a
Cacho, I., Grimalt, J. O., Canals, M., Sbaffi, L., Shackleton, N. J.,
Schönfeld, J., and Zahn, R.: Variability of the western Mediterranean
Sea surface temperature during the last 25,000 years and its connection with
the Northern Hemisphere climatic changes, Paleoceanography, 16, 40–52,
https://doi.org/10.1029/2000PA000502, 2001. a, b, c
Cacho, I., Grimalt, J. O., Canals, M., Sbaffi, L., Shackleton, N. J., Schönfeld, J., and Zahn, R.: Western Mediterranean d18O and Uk37 Data and SST Reconstructions, World Data Center for Paleoclimatology Data Contribution Series 2006-106, available at: https://www.ncdc.noaa.gov/paleo-search/study/6374 (last access: 13 January 2020), 2006. a, b, c
Calvo, E., Grimalt, J., and Jansen, E.: High resolution U37K sea surface
temperature reconstruction in the Norwegian Sea during the Holocene,
Quaternary Sci. Rev., 21, 1385–1394,
https://doi.org/10.1016/S0277-3791(01)00096-8, 2002. a, b
Came, R. E., Oppo, D. W., and McManus, J. F.: Amplitude and timing of
temperature and salinity variability in the subpolar North Atlantic over the
past 10 k.y., Geology, 35, 315–318, https://doi.org/10.1130/G23455A.1, 2007a. a
Castañeda, I. S., Schefuß, E., Pätzold, J., Sinninghe
Damsté, J. S., Weldeab, S., and Schouten, S.: Millennial-scale sea
surface temperature changes in the eastern Mediterranean (Nile River Delta
region) over the last 27,000 years, Paleoceanography, 25, PA1208,
https://doi.org/10.1029/2009PA001740, 2010a. a
Castañeda, I. S., Schefuß, E., Pätzold, J., Sinninghe
Damsté, J. S., Weldeab, S., and Schouten, S.: Isoprenoidal GDGT and
alkenone-based proxies of sediment core GeoB7702-3, PANGAEA,
https://doi.org/10.1594/PANGAEA.736909, 2010b. a, b
Collins, M., Tett, S. F., and Cooper, C.: The internal climate variability of
HadCM3, a version of the Hadley Centre coupled model without flux
adjustments, Clim. Dynam., 17, 61–81, https://doi.org/10.1007/s003820000094,
2001. a
Dee, S., Emile-Geay, J., Evans, M. N., Allam, A., Steig, E. J., and Thompson,
D.: PRYSM: An open-source framework for PRoxY System Modeling, with
applications to oxygen-isotope systems, J. Adv. Model.
Earth Sy., 7, 1220–1247, https://doi.org/10.1002/2015MS000447, 2015. a, b
Dee, S., Parsons, L., Loope, G., Overpeck, J., Ault, T., and Emile-Geay, J.:
Improved spectral comparisons of paleoclimate models and observations via
proxy system modeling: Implications for multi-decadal variability, Earth
Planet. Sci. Lett., 476, 34–46, https://doi.org/10.1016/J.EPSL.2017.07.036,
2017. a
Dee, S. G., Steiger, N. J., Emile-Geay, J., and Hakim, G. J.: On the utility
of proxy system models for estimating climate states over the common era,
J. Adv. Model. Earth Sy., 8, 1164–1179, https://doi.org/10.1002/2016MS000677,
2016. a, b, c
Dee, S. G., Russell, J. M., Morrill, C., Chen, Z., and Neary, A.: PRYSM v2.0:
A Proxy System Model for Lacustrine Archives, Paleoceanography and
Paleoclimatology, 33, 1250–1269, https://doi.org/10.1029/2018PA003413, 2018. a, b
Digerfeldt, G.: Pollen profile FLARKTOT, Lake Flarken, Sweden, PANGAEA,
https://doi.org/10.1594/PANGAEA.711884, 2009. a
Digerfeldt, G.: Age determination of sediment core FLARKTOT, Lake Flarken,
Sweden, PANGAEA, https://doi.org/10.1594/PANGAEA.740343, 2010. a
Dolman, A. M. and Laepple, T.: Sedproxy: a forward model for sediment-archived climate proxies, Clim. Past, 14, 1851–1868, https://doi.org/10.5194/cp-14-1851-2018, 2018. a, b, c, d
Dolven, J. K., Cortese, G., and Bjørklund, K. R.: A high-resolution
radiolarian-derived paleotemperature record for the Late Pleistocene-Holocene
in the Norwegian Sea, Paleoceanography, 17, 1–13,
https://doi.org/10.1029/2002pa000780, 2002. a
Dufresne, J. L., Foujols, M. A., Denvil, S., Caubel, A., Marti, O., Aumont, O., Balkanski, Y., Bekki, S., Bellenger, H., Benshila, R., Bony, S., Bopp, L., Braconnot, P., Brockmann, P., Cadule, P., Cheruy, F., Codron, F., Cozic, A., Cugnet, D., de Noblet, N., Duvel, J. P., Ethé, C., Fairhead, L.,
Fichefet, T., Flavoni, S., Friedlingstein, P., Grandpeix, J. Y., Guez, L.,
Guilyardi, E., Hauglustaine, D., Hourdin, F., Idelkadi, A., Ghattas, J.,
Joussaume, S., Kageyama, M., Krinner, G., Labetoulle, S., Lahellec, A.,
Lefebvre, M. P., Lefevre, F., Levy, C., Li, Z. X., Lloyd, J., Lott, F.,
Madec, G., Mancip, M., Marchand, M., Masson, S., Meurdesoif, Y., Mignot, J.,
Musat, I., Parouty, S., Polcher, J., Rio, C., Schulz, M., Swingedouw, D.,
Szopa, S., Talandier, C., Terray, P., Viovy, N., and Vuichard, N.: Climate
change projections using the IPSL-CM5 Earth System Model: From CMIP3 to
CMIP5, Clim. Dynam., 40, 2123–2165, https://doi.org/10.1007/s00382-012-1636-1,
2013. a
ESGF: ESGF Node at DKRZ, available at: https://esgf-data.dkrz.de/projects/esgf-dkrz/, last access: 22 March 2021.
Emeis, K.-C., Struck, U., Schulz, H.-M., Rosenberg, M., Bernasconi, S. M., Erlenkeuser, H., Sakamoto, T., and Martinez-Ruiz, F. C.: Sea surface temperature reconstruction for Mediterranean Sea samples, PANGAEA, https://doi.org/10.1594/PANGAEA.735959, 2000a. a, b
Emeis, K.-C., Struck, U., Schulz, H.-M., Rosenberg, R., Bernasconi, S.,
Erlenkeuser, H., Sakamoto, T., and Martinez-Ruiz, F.: Temperature and
salinity variations of Mediterranean Sea surface waters over the last 16,000
years from records of planktonic stable oxygen isotopes and alkenone
unsaturation ratios, Palaeogeogr. Palaeoecol., 158,
259–280, https://doi.org/10.1016/S0031-0182(00)00053-5, 2000b. a
Emeis, K.-C., Struck, U., Blanz, T., Kohly, A., and Voß, M.: Salinity
changes in the central Baltic Sea (NW Europe) over the last 10 000 years,
Holocene, 13, 411–421, https://doi.org/10.1191/0959683603hl634rp,
2003a. a, b
Emeis, K.-C., Struck, U., Blanz, T., Kohly, A., and Voss, M.: Sea-surface
temperature reconstruction of sediment cores from the Skagerrak, PANGAEA,
https://doi.org/10.1594/PANGAEA.738458, 2003b. a, b, c
Emile-Geay, J., McKay, N. P., Kaufman, D. S., Von Gunten, L., Wang, J.,
Anchukaitis, K. J., Abram, N. J., Addison, J. A., Curran, M. A., Evans,
M. N., Henley, B. J., Hao, Z., Martrat, B., McGregor, H. V., Neukom, R.,
Pederson, G. T., Stenni, B., Thirumalai, K., Werner, J. P., Xu, C., Divine,
D. V., Dixon, B. C., Gergis, J., Mundo, I. A., Nakatsuka, T., Phipps, S. J.,
Routson, C. C., Steig, E. J., Tierney, J. E., Tyler, J. J., Allen, K. J.,
Bertler, N. A., Björklund, J., Chase, B. M., Chen, M. T., Cook, E., De
Jong, R., DeLong, K. L., Dixon, D. A., Ekaykin, A. A., Ersek, V., Filipsson,
H. L., Francus, P., Freund, M. B., Frezzotti, M., Gaire, N. P., Gajewski, K.,
Ge, Q., Goosse, H., Gornostaeva, A., Grosjean, M., Horiuchi, K., Hormes, A.,
Husum, K., Isaksson, E., Kandasamy, S., Kawamura, K., Kilbourne, K. H.,
Koç, N., Leduc, G., Linderholm, H. W., Lorrey, A. M., Mikhalenko, V.,
Mortyn, P. G., Motoyama, H., Moy, A. D., Mulvaney, R., Munz, P. M., Nash,
D. J., Oerter, H., Opel, T., Orsi, A. J., Ovchinnikov, D. V., Porter, T. J.,
Roop, H. A., Saenger, C., Sano, M., Sauchyn, D., Saunders, K. M.,
Seidenkrantz, M. S., Severi, M., Shao, X., Sicre, M. A., Sigl, M., Sinclair,
K., St George, S., St Jacques, J. M., Thamban, M., Thapa, U. K., Thomas,
E. R., Turney, C., Uemura, R., Viau, A. E., Vladimirova, D. O., Wahl, E. R.,
White, J. W., Yu, Z., and Zinke, J.: A global multiproxy database for
temperature reconstructions of the Common Era, Scientific Data, 4, 170088,
https://doi.org/10.1038/sdata.2017.88, 2017. a
Evans, M. N., Tolwinski-Ward, S. E., Thompson, D. M., and Anchukaitis, K. J.:
Applications of proxy system modeling in high resolution paleoclimatology,
Quaternary Sci. Rev., 76, 16–28,
https://doi.org/10.1016/j.quascirev.2013.05.024, 2013. a, b
Franke, J., González-Rouco, J. F., Frank, D., and Graham, N. E.:
200 years of European temperature variability: insights from and tests of
the proxy surrogate reconstruction analog method, Clim. Dynam., 37,
133–150, https://doi.org/10.1007/s00382-010-0802-6, 2010. a, b, c, d
Giorgetta, M. A., Jungclaus, J., Reick, C. H., Legutke, S., Bader, J.,
Böttinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Glushak,
K., Gayler, V., Haak, H., Hollweg, H.-D., Ilyina, T., Kinne, S., Kornblueh,
L., Matei, D., Mauritsen, T., Mikolajewicz, U., Mueller, W., Notz, D.,
Pithan, F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H.,
Schnur, R., Segschneider, J., Six, K. D., Stockhause, M., Timmreck, C.,
Wegner, J., Widmann, H., Wieners, K.-H., Claussen, M., Marotzke, J., and
Stevens, B.: Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM
simulations for the Coupled Model Intercomparison Project phase 5, J.
Adv. Model. Earth Sy., 5, 572–597, https://doi.org/10.1002/jame.20038,
2013. a
Giunta, S. and Emeis, K.-C.: Age and alkenone-derived Holocene sea-surface
temperature records of sediment core AD91-17, PANGAEA, https://doi.org/10.1594/PANGAEA.438366,
2006. a, b
Giunta, S., Emeis, K. C., and Negri, A.: Sea surface temperatures reconstruction of the last 16,000 years in the eastern Mediterranean Sea,
Rivista italiana di Paleontologia e Stratigrafia, 107, 463–476, https://doi.org/10.13130/2039-4942/5447, 2001. a
Gómez-Navarro, J., Werner, J., Wagner, S., Zorita, E., and Luterbacher, J.: Precipitation in the Past Millennium in Europe – Extension to Roman Times, in: Integrated Analysis of Interglacial Climate Dynamics (INTERDYNAMIC), edited by: Schulz, M. and Paul, A., Springer, Cham, 133–139,
https://doi.org/10.1007/978-3-319-00693-2_22, 2015a. a
Gómez-Navarro, J. J., Werner, J., Wagner, S., Luterbacher, J., and
Zorita, E.: Establishing the skill of climate field reconstruction
techniques for precipitation with pseudoproxy experiments, Clim. Dynam.,
45, 1395–1413, https://doi.org/10.1007/s00382-014-2388-x, 2015b. a, b, c
Graham, N., Hughes, M., Ammann, C., Cobb, K., Hoerling, M., Kennett, D.,
Kennett, J., Rein, B., Stott, L., Wigand, P., and Xu, T.: Tropical Pacific
– mid-latitude teleconnections in medieval times, Climatic Change, 83,
241–285, https://doi.org/10.1007/s10584-007-9239-2, 2007. a
Grimalt, J. O. and Calvo, E.: Age and alkenone-derived Holocene sea-surface
temperature records of sediment core MD95-2011, PANGAEA, https://doi.org/10.1594/PANGAEA.438810,
2006. a, b
Grimalt, J. O. and Marchal, O.: Age and alkenone-derived Holocene sea-surface
temperature records of sediment core MD95-2015, PANGAEA, https://doi.org/10.1594/PANGAEA.438814,
2006. a, b
Hakim, G. J., Emile-Geay, J., Steig, E. J., Noone, D., Anderson, D. M., Tardif, R., Steiger, N., and Perkins, W. A.: The last millennium climate reanalysis
project: Framework and first results, J. Geophys. Res., 121,
6745–6764, https://doi.org/10.1002/2016JD024751, 2016. a
He, F.: Simulating Transient Climate Evolution of the Last Deglaciation with
CCSM3, PhD thesis, University of Wisconsin-Madison, Madison, USA, available at:
http://www.cgd.ucar.edu/ccr/TraCE/doc/He_PhD_dissertation_UW_2011.pdf
(last access: 29 December 2020), 2011. a
Jensen, M. F., Nummelin, A., Nielsen, S. B., Sadatzki, H., Sessford, E., Risebrobakken, B., Andersson, C., Voelker, A., Roberts, W. H. G., Pedro, J., and Born, A.: A spatiotemporal reconstruction of sea-surface temperatures in the North Atlantic during Dansgaard–Oeschger events 5–8, Clim. Past, 14, 901–922, https://doi.org/10.5194/cp-14-901-2018, 2018. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q
Jones, C. D., Hughes, J. K., Bellouin, N., Hardiman, S. C., Jones, G. S., Knight, J., Liddicoat, S., O'Connor, F. M., Andres, R. J., Bell, C., Boo, K.-O., Bozzo, A., Butchart, N., Cadule, P., Corbin, K. D., Doutriaux-Boucher, M., Friedlingstein, P., Gornall, J., Gray, L., Halloran, P. R., Hurtt, G., Ingram, W. J., Lamarque, J.-F., Law, R. M., Meinshausen, M., Osprey, S., Palin, E. J., Parsons Chini, L., Raddatz, T., Sanderson, M. G., Sellar, A. A., Schurer, A., Valdes, P., Wood, N., Woodward, S., Yoshioka, M., and Zerroukat, M.: The HadGEM2-ES implementation of CMIP5 centennial simulations, Geosci. Model Dev., 4, 543–570, https://doi.org/10.5194/gmd-4-543-2011, 2011. a, b
Jones, M. D. and Dee, S. G.: Global-scale proxy system modelling of oxygen
isotopes in lacustrine carbonates: New insights from isotope-enabled-model
proxy-data comparison, Quaternary Sci. Rev., 202, 19–29,
https://doi.org/10.1016/J.QUASCIREV.2018.09.009, 2018. a, b, c
Jonkers, L. and Kučera, M.: Quantifying the effect of seasonal and vertical habitat tracking on planktonic foraminifera proxies, Clim. Past, 13, 573–586, https://doi.org/10.5194/cp-13-573-2017, 2017. a, b
Jonkers, L. and Kučera, M.: Sensitivity to species selection indicates the effect of nuisance variables on marine microfossil transfer functions, Clim. Past, 15, 881–891, https://doi.org/10.5194/cp-15-881-2019, 2019. a
Jungclaus, J. H., Lorenz, S. J., Timmreck, C., Reick, C. H., Brovkin, V., Six, K., Segschneider, J., Giorgetta, M. A., Crowley, T. J., Pongratz, J., Krivova, N. A., Vieira, L. E., Solanki, S. K., Klocke, D., Botzet, M., Esch, M., Gayler, V., Haak, H., Raddatz, T. J., Roeckner, E., Schnur, R., Widmann, H., Claussen, M., Stevens, B., and Marotzke, J.: Climate and carbon-cycle variability over the last millennium, Clim. Past, 6, 723–737, https://doi.org/10.5194/cp-6-723-2010, 2010 (data available at: https://cera-www.dkrz.de/WDCC/ui/cerasearch/project?acronym=MILLENNIUM_COSMOS, last access: ). a, b, c
Kageyama, M., Braconnot, P., Harrison, S. P., Haywood, A. M., Jungclaus, J. H., Otto-Bliesner, B. L., Peterschmitt, J.-Y., Abe-Ouchi, A., Albani, S., Bartlein, P. J., Brierley, C., Crucifix, M., Dolan, A., Fernandez-Donado, L., Fischer, H., Hopcroft, P. O., Ivanovic, R. F., Lambert, F., Lunt, D. J., Mahowald, N. M., Peltier, W. R., Phipps, S. J., Roche, D. M., Schmidt, G. A., Tarasov, L., Valdes, P. J., Zhang, Q., and Zhou, T.: The PMIP4 contribution to CMIP6 – Part 1: Overview and over-arching analysis plan, Geosci. Model Dev., 11, 1033–1057, https://doi.org/10.5194/gmd-11-1033-2018, 2018. a, b, c
Kim, J.-H., Rimbu, N., Lorenz, S. J., Lohmann, G., Nam, S.-I., Schouten, S.,
Rühlemann, C., and Schneider, R. R.: North Pacific and North Atlantic
sea-surface temperature variability during the Holocene, Quaternary Sci.
Rev., 23, 2141–2154, https://doi.org/10.1016/j.quascirev.2004.08.010,
2004a. a, b, c
Kim, J.-H., Rimbu, N., Lorenz, S. J., Lohmann, G., Nam, S.-I., Schouten, S.,
Rühlemann, C., and Schneider, R. R.: Age and alkenone-derived Holocene
sea-surface temperature records of sediment core GeoB5901-2, PANGAEA,
https://doi.org/10.1594/PANGAEA.438384, 2004b. a, b
Kim, J.-H., Schouten, S., Hopmans, E. C., Donner, B., and Sinninghe
Damsté, J. S.: Global sediment core-top calibration of the TEX86
paleothermometer in the ocean, Geochim. Cosmochim. Ac., 72,
1154–1173, https://doi.org/10.1016/j.gca.2007.12.010, 2008. a
Konecky, B., Dee, S. G., and Noone, D.: WaxPSM: A forward model of leaf wax
hydrogen isotope ratios to bridge proxy and model estimates of past climate,
J. Geophys. Res.-Biogeo., 124, 2107–2125, https://doi.org/10.1029/2018JG004708, 2019. a
Kretschmer, K., Kucera, M., and Schulz, M.: Modeling the distribution and
seasonality of Neogloboquadrina pachyderma in the North Atlantic Ocean during
Heinrich Stadial 1, Paleoceanography, 31, 986–1010,
https://doi.org/10.1002/2015PA002819, 2016. a
Kretschmer, K., Jonkers, L., Kucera, M., and Schulz, M.: Modeling seasonal and vertical habitats of planktonic foraminifera on a global scale, Biogeosciences, 15, 4405–4429, https://doi.org/10.5194/bg-15-4405-2018, 2018. a, b
Larocque, I. and Hall, R. I.: Holocene temperature estimates and chironomid
community composition in the Abisko Valley, northern Sweden, Quaternary
Sci. Rev., 23, 2453–2465, https://doi.org/10.1016/j.quascirev.2004.04.006, 2004. a, b, c
Lenton, T.: QUEST Quaternary: FAMOUS glacial cycle model data, NCAS British Atmospheric Data Centre, https://catalogue.ceda.ac.uk/uuid/a43dcfaccfae4824ab9ab2b572703e72 (last access: 30 December 2019), 2008. a
Liu, Z., Otto-Bliesner, B. L., He, F., Brady, E. C., Tomas, R., Clark, P. U.,
Carlson, A. E., Lynch-Stieglitz, J., Curry, W., Brook, E., Erickson, D.,
Jacob, R., Kutzbach, J., and Cheng, J.: Transient simulation of last
deglaciation with a new mechanism for Bolling-Allerod warming, Science, 325, 310–314, https://doi.org/10.1126/science.1171041, 2009. a, b, c
Malevich, S. B., Vetter, L., and Tierney, J. E.: Global Core Top Calibration
of δ18O in Planktic Foraminifera to Sea Surface Temperature,
Paleoceanogr. Paleoclimatol., 34, 1292–1315,
https://doi.org/10.1029/2019PA003576, 2019. a
Marchal, O., Cacho, I., Stocker, T. F., Grimalt, J. O., Calvo, E., Martrat, B., Shackleton, N., Vautravers, M., Cortijo, E., van Kreveld, S., Andersson, C., Koç, N., Chapman, M., Sbaffi, L., Duplessy, J.-C., Sarnthein, M.,
Turon, J.-L., Duprat, J., and Jansen, E.: Apparent long-term cooling of the
sea surface in the northeast Atlantic and Mediterranean during the Holocene,
Quaternary Sci. Rev., 21, 455–483,
https://doi.org/10.1016/S0277-3791(01)00105-6, 2002. a
Marcott, S. A., Shakun, J. D., Clark, P. U., and Mix, A. C.: A reconstruction of regional and global temperature for the past 11,300 years, Science, 339, 1198–201, https://doi.org/10.1126/science.1228026, 2013 (data available at: https://science.sciencemag.org/content/suppl/2013/03/07/339.6124.1198.DC1,
last access: 30 December 2019). a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u
Matulla, C., Zhang, X., Wang, X. L., Wang, J., Zorita, E., Wagner, S., and
Storch, H.: Influence of similarity measures on the performance of the
analog method for downscaling daily precipitation, Clim. Dynam., 30,
133–144, https://doi.org/10.1007/s00382-007-0277-2, 2008. a
Murdoch, D. J. and Chow, E. D.: A Graphical Display of Large Correlation
Matrices, Am. Stat., 50, 178–180,
https://doi.org/10.1080/00031305.1996.10474371, 1996. a
NCAR: Climate Data Gateway, available at: https://www.earthsystemgrid.org/, last access: 22 March 2021.
Neukom, R., Steiger, N., Gómez-Navarro, J. J., Wang, J., and Werner,
J. P.: No evidence for globally coherent warm and cold periods over the
preindustrial Common Era, Nature, 571, 550–554,
https://doi.org/10.1038/s41586-019-1401-2, 2019. a, b
Otto-Bliesner, B. L., Brady, E. C., Fasullo, J., Jahn, A., Landrum, L.,
Stevenson, S., Rosenbloom, N., Mai, A., and Strand, G.: Climate Variability
and Change since 850 CE: An Ensemble Approach with the Community Earth System
Model, B. Am. Meteorol. Soc., 97, 735–754,
https://doi.org/10.1175/bams-d-14-00233.1, 2015. a, b
Phipps, S. J., Rotstayn, L. D., Gordon, H. B., Roberts, J. L., Hirst, A. C., and Budd, W. F.: The CSIRO Mk3L climate system model version 1.0 – Part 1: Description and evaluation, Geosci. Model Dev., 4, 483–509, https://doi.org/10.5194/gmd-4-483-2011, 2011. a
R Core Team: R: A Language and Environment for Statistical Computing, R
Foundation for Statistical Computing, Vienna, Austria, available at:
https://www.R-project.org/, last access: 27 November 2019. a
Rebotim, A., Voelker, A. H. L., Jonkers, L., Waniek, J. J., Meggers, H., Schiebel, R., Fraile, I., Schulz, M., and Kucera, M.: Factors controlling the depth habitat of planktonic foraminifera in the subtropical eastern North Atlantic, Biogeosciences, 14, 827–859, https://doi.org/10.5194/bg-14-827-2017, 2017. a
Reschke, M., Rehfeld, K., and Laepple, T.: Empirical estimate of the signal content of Holocene temperature proxy records, Clim. Past, 15, 521–537, https://doi.org/10.5194/cp-15-521-2019, 2019. a, b, c
Rodrigues, T., Grimalt, J. O., Abrantes, F. G., Flores, J. A., and Lebreiro,
S. M.: Holocene interdependences of changes in sea surface temperature,
productivity, and fluvial inputs in the Iberian continental shelf (Tagus mud
patch), Geochem. Geophy. Geosy., 10, Q07U06,
https://doi.org/10.1029/2008GC002367, 2009. a
Rodrigues, T., Grimalt, J. O., Abrantes, F. F., Naughton, F., and Flores,
J.-A.: Sea surface temperature reconstruction from sediment core D13882, PANGAEA,
https://doi.org/10.1594/PANGAEA.761811, 2010. a, b
Rosell-Melé, A., Bard, E., Emeis, K.-C., Grimalt, J. O., Müller,
P., Schneider, R., Bouloubassi, I., Epstein, B., Fahl, K., Fluegge, A.,
Freeman, K., Goñi, M., Güntner, U., Hartz, D., Hellebust, S.,
Herbert, T., Ikehara, M., Ishiwatari, R., Kawamura, K., Kenig, F., de Leeuw,
J., Lehman, S., Mejanelle, L., Ohkouchi, N., Pancost, R. D., Pelejero, C.,
Prahl, F., Quinn, J., Rontani, J.-F., Rostek, F., Rullkötter, J.,
Sachs, J., Blanz, T., Sawada, K., Schulz-Bull, D., Sikes, E., Sonzogni, C.,
Ternois, Y., Versteegh, G., Volkman, J. K., and Wakeham, S.: Precision of
the current methods to measure the alkenone proxy U 37 K' and absolute
alkenone abundance in sediments: Results of an interlaboratory comparison
study, Geochem. Geophy. Geosy., 2, 1046,
https://doi.org/10.1029/2000GC000141, 2001. a
Sarnthein, M., Van Kreveld, S., Erlenkeuser, H., Grootes, P. M., Kucera, M.,
Pflauman, U., and Schulz, M.: Centennial-to-millennial-scale periodicities
of Holocene climate and sediment injections off the western Barents shelf,
75∘ N, Boreas, 32, 447–461, https://doi.org/10.1111/j.1502-3885.2003.tb01227.x,
2003a. a, b, c
Sarnthein, M., Van Kreveld, S., Erlenkeuser, H., Grootes, P. M., Kucera, M., Pflauman, U., and Schulz, M.: Sea surface temperatures of sediment core
GIK23258-2, PANGAEA, https://doi.org/10.1594/PANGAEA.114683,
2003b. a, b, c
Schmidt, G. A.: Forward modeling of carbonate proxy data from planktonic
foraminifera using oxygen isotope tracers in a global ocean model,
Paleoceanography, 14, 482–497, https://doi.org/10.1029/1999PA900025, 1999. a
Schmidt, G. A., Annan, J. D., Bartlein, P. J., Cook, B. I., Guilyardi, E., Hargreaves, J. C., Harrison, S. P., Kageyama, M., LeGrande, A. N., Konecky, B., Lovejoy, S., Mann, M. E., Masson-Delmotte, V., Risi, C., Thompson, D., Timmermann, A., Tremblay, L.-B., and Yiou, P.: Using palaeo-climate comparisons to constrain future projections in CMIP5, Clim. Past, 10, 221–250, https://doi.org/10.5194/cp-10-221-2014, 2014a. a
Schmidt, G. A., Kelley, M., Nazarenko, L., Ruedy, R., Russell, G. L., Aleinov, I., Bauer, M., Bauer, S. E., Bhat, M. K., Bleck, R., Canuto, V., Chen, Y.-H., Cheng, Y., Clune, T. L., Del Genio, A., de Fainchtein, R., Faluvegi, G., Hansen, J. E., Healy, R. J., Kiang, N. Y., Koch, D., Lacis, A. A., LeGrande, A. N., Lerner, J., Lo, K. K., Matthews, E. E., Menon, S., Miller, R. L., Oinas, V., Oloso, A. O., Perlwitz, J. P., Puma, M. J., Putman, W. M., Rind, D., Romanou, A., Sato, M., Shindell, D. T., Sun, S., Syed, R. A., Tausnev, N., Tsigaridis, K., Unger, N., Voulgarakis, A., Yao, M.-S., and Zhang, J.: Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive, J. Adv. Model. Earth Sy., 6, 141–184,
https://doi.org/10.1002/2013MS000265, 2014b. a
Seppä, H. and Birks, H.: July mean temperature and annual precipitation trends during the Holocene in the Fennoscandian tree-line area: pollen-based climate reconstructions, Holocene, 11, 527–539,
https://doi.org/10.1191/095968301680223486, 2001. a, b
Seppä, H., Hammarlund, D., and Antonsson, K.: Low-frequency and
high-frequency changes in temperature and effective humidity during the
Holocene in south-central Sweden: implications for atmospheric and oceanic
forcings of climate, Clim. Dynam., 25, 285–297,
https://doi.org/10.1007/s00382-005-0024-5, 2005. a, b
Smerdon, J. E.: Climate models as a test bed for climate reconstruction
methods: pseudoproxy experiments, WIREs Clim. Change, 3, 63–77,
https://doi.org/10.1002/wcc.149, 2012. a
Steiger, N. J., Hakim, G. J., Steig, E. J., Battisti, D. S., and Roe, G. H.:
Assimilation of Time-Averaged Pseudoproxies for Climate Reconstruction,
J. Climate, 27, 426–441, https://doi.org/10.1175/JCLI-D-12-00693.1, 2014. a
Sundqvist, H. S., Kaufman, D. S., McKay, N. P., Balascio, N. L., Briner, J. P., Cwynar, L. C., Sejrup, H. P., Seppä, H., Subetto, D. A., Andrews, J. T., Axford, Y., Bakke, J., Birks, H. J. B., Brooks, S. J., de Vernal, A.,
Jennings, A. E., Ljungqvist, F. C., Rühland, K. M., Saenger, C., Smol,
J. P., and Viau, A. E.: Arctic Holocene Proxy Climate Database, World Data Center for Paleoclimatology Data, available at: https://www.ncdc.noaa.gov/paleo-search/study/15444 (last access: 13 January 2020), 2014a. a, b, c, d
Sundqvist, H. S., Kaufman, D. S., McKay, N. P., Balascio, N. L., Briner, J. P., Cwynar, L. C., Sejrup, H. P., Seppä, H., Subetto, D. A., Andrews, J. T., Axford, Y., Bakke, J., Birks, H. J. B., Brooks, S. J., de Vernal, A., Jennings, A. E., Ljungqvist, F. C., Rühland, K. M., Saenger, C., Smol, J. P., and Viau, A. E.: Arctic Holocene proxy climate database – new approaches to assessing geochronological accuracy and encoding climate variables, Clim. Past, 10, 1605–1631, https://doi.org/10.5194/cp-10-1605-2014, 2014b.
Talento, S., Schneider, L., Werner, J., and Luterbacher, J.: Millennium-length precipitation reconstruction over south-eastern Asia: a pseudo-proxy approach, Earth Syst. Dynam., 10, 347–364, https://doi.org/10.5194/esd-10-347-2019, 2019. a, b, c, d
Tardif, R., Hakim, G. J., Perkins, W. A., Horlick, K. A., Erb, M. P., Emile-Geay, J., Anderson, D. M., Steig, E. J., and Noone, D.: Last Millennium Reanalysis with an expanded proxy database and seasonal proxy modeling, Clim. Past, 15, 1251–1273, https://doi.org/10.5194/cp-15-1251-2019, 2019. a
Telford, R. J., Li, C., and Kucera, M.: Mismatch between the depth habitat of planktonic foraminifera and the calibration depth of SST transfer functions may bias reconstructions, Clim. Past, 9, 859–870, https://doi.org/10.5194/cp-9-859-2013, 2013. a
Thompson, D. M., Ault, T. R., Evans, M. N., Cole, J. E., and Emile-Geay, J.:
Comparison of observed and simulated tropical climate trends using a forward
model of coral δ18O, Geophys. Res. Lett., 38, L14706,
https://doi.org/10.1029/2011gl048224, 2011. a
Thornalley, D. J. R., Elderfield, H., and McCave, I. N.: Holocene oscillations in temperature and salinity of the surface subpolar North Atlantic, Nature, 457, 711–7144, https://doi.org/10.1038/nature07717, 2009a. a
Thornalley, D. J. R., Elderfield, H., and McCave, I. N.: Subpolar North
Atlantic Holocene Temperature and Salinity Reconstructions, iGBP
PAGES/World Data Center for Paleoclimatology Data Contribution Series,
2009-097, available at: https://www.ncdc.noaa.gov/paleo-search/study/8623 (last
access: 13 January 2020), 2009b. a, b
Tierney, J. E. and Tingley, M. P.: A TEX 86 surface sediment database and
extended Bayesian calibration, Scientific Data, 2, 150029,
https://doi.org/10.1038/sdata.2015.29, 2015. a, b
Tierney, J. E. and Tingley, M. P.: BAYSPLINE: A New Calibration for the
Alkenone Paleothermometer, Paleoceanography and Paleoclimatology, 33,
281–301, https://doi.org/10.1002/2017PA003201, 2018. a, b
Tierney, J. E., Malevich, S. B., Gray, W., Vetter, L. and Thirumalai, K.: Bayesian Calibration of the Mg/Ca Paleothermometer in Planktic Foraminifera, Paleoceanography and Paleoclimatology, 34, 2005–2030, https://doi.org/10.1029/2019pa003744, 2019. a, b
Tolwinski-Ward, S. E., Evans, M. N., Hughes, M. K., and Anchukaitis, K. J.: An efficient forward model of the climate controls on interannual variation in tree-ring width, Clim. Dynam., 36, 2419–2439,
https://doi.org/10.1007/s00382-010-0945-5, 2011.
a
Trouet, V., Esper, J., Graham, N. E., Baker, A., Scourse, J. D., and Frank,
D. C.: Persistent Positive North Atlantic Oscillation Mode Dominated the
Medieval Climate Anomaly, Science, 324, 78–80,
https://doi.org/10.1126/science.1166349, 2009. a
Van den Dool, H. M.: Searching for analogues, how long must we wait?,
Tellus A, 46, 314–324, https://doi.org/10.1034/j.1600-0870.1994.t01-2-00006.x, 1994. a
Voeltzel, D.: Age determination of sediment core TSUOLJVR, Lake
Tsuolbmajavri, Finland, PANGAEA, https://doi.org/10.1594/PANGAEA.740821, 2010a. a
Voeltzel, D.: Pollen profile TSUOLJVR, Lake Tsuolbmajavri, Finland,
PANGAEA, https://doi.org/10.1594/PANGAEA.739916, 2010b. a
Voldoire, A., Sanchez-Gomez, E., Salas y Mélia, D., Decharme, B.,
Cassou, C., Sénési, S., Valcke, S., Beau, I., Alias, A.,
Chevallier, M., Déqué, M., Deshayes, J., Douville, H., Fernandez,
E., Madec, G., Maisonnave, E., Moine, M. P., Planton, S., Saint-Martin, D.,
Szopa, S., Tyteca, S., Alkama, R., Belamari, S., Braun, A., Coquart, L., and
Chauvin, F.: The CNRM-CM5.1 global climate model: Description and basic
evaluation, Clim. Dynam., 40, 2091–2121,
https://doi.org/10.1007/s00382-011-1259-y, 2013. a
Weitzel, N., Wagner, S., Sjolte, J., Klockmann, M., Bothe, O., Andres, H.,
Tarasov, L., Rehfeld, K., Zorita, E., Widmann, M., Sommer, P.,
Schädler, G., Ludwig, P., Kapp, F., Jonkers, L., García-Pintado,
J., Fuhrmann, F., Dolman, A., Dallmeyer, A., and Brücher, T.: Diving
into the Past: A Paleo Data-Model Comparison Workshop on the Late Glacial
and Holocene, B. Am. Meteorol. Soc., 100,
1–4, https://doi.org/10.1175/bams-d-18-0169.1, 2018. a
Zanchettin, D., Bothe, O., Müller, W., Bader, J., and Jungclaus, J.:
Different flavors of the Atlantic Multidecadal Variability, Clim.
Dynam., 42, 381–399, https://doi.org/10.1007/s00382-013-1669-0, 2014. a, b
Zorita, E. and von Storch, H.: The Analog Method as a Simple Statistical
Downscaling Technique: Comparison with More Complicated Methods, J. Climate,
12, 2474–2489, https://doi.org/10.1175/1520-0442(1999)012<2474:tamaas>2.0.co;2,
1999. a
Short summary
The similarity between indirect observations of past climates and information from climate simulations can increase our understanding of past climates. The further we look back, the more uncertain our indirect observations become. Here, we discuss the technical background for such a similarity-based approach to reconstruct past climates for up to the last 15 000 years. We highlight the potential and the problems.
The similarity between indirect observations of past climates and information from climate...