High-resolution terrestrial climate, bioclimate and vegetation for the last 120,000 years
The variability of climate has profoundly impacted a wide range of macroecological processes in the Late Quaternary. Our understanding of these has greatly benefited from palaeoclimate simulations, however, high-quality reconstructions of ecologically relevant climatic variables have thus far been l...
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| Published in | Scientific data Vol. 7; no. 1; p. 236 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
14.07.2020
Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2052-4463 2052-4463 |
| DOI | 10.1038/s41597-020-0552-1 |
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| Abstract | The variability of climate has profoundly impacted a wide range of macroecological processes in the Late Quaternary. Our understanding of these has greatly benefited from palaeoclimate simulations, however, high-quality reconstructions of ecologically relevant climatic variables have thus far been limited to a few selected time periods. Here, we present a 0.5° resolution bias-corrected dataset of global monthly temperature, precipitation, cloud cover, relative humidity and wind speed, 17 bioclimatic variables, annual net primary productivity, leaf area index and biomes, covering the last 120,000 years at a temporal resolution of 1,000–2,000 years. We combined medium-resolution HadCM3 climate simulations of the last 120,000 years with high-resolution HadAM3H simulations of the last 21,000 years, and modern-era instrumental data. This allows for the temporal variability of small-scale features whilst ensuring consistency with observed climate. Our data make it possible to perform continuous-time analyses at a high spatial resolution for a wide range of climatic and ecological applications - such as habitat and species distribution modelling, dispersal and extinction processes, biogeography and bioanthropology.
Measurement(s)
temperature • precipitation process • vegetation layer • atmospheric wind speed • cloud • humidity
Technology Type(s)
computational modeling technique
Factor Type(s)
geographic location • temporal interval
Sample Characteristic - Environment
climate system
Sample Characteristic - Location
Earth (planet)
Machine-accessible metadata file describing the reported data:
https://doi.org/10.6084/m9.figshare.12436484 |
|---|---|
| AbstractList | The variability of climate has profoundly impacted a wide range of macroecological processes in the Late Quaternary. Our understanding of these has greatly benefited from palaeoclimate simulations, however, high-quality reconstructions of ecologically relevant climatic variables have thus far been limited to a few selected time periods. Here, we present a 0.5° resolution bias-corrected dataset of global monthly temperature, precipitation, cloud cover, relative humidity and wind speed, 17 bioclimatic variables, annual net primary productivity, leaf area index and biomes, covering the last 120,000 years at a temporal resolution of 1,000–2,000 years. We combined medium-resolution HadCM3 climate simulations of the last 120,000 years with high-resolution HadAM3H simulations of the last 21,000 years, and modern-era instrumental data. This allows for the temporal variability of small-scale features whilst ensuring consistency with observed climate. Our data make it possible to perform continuous-time analyses at a high spatial resolution for a wide range of climatic and ecological applications - such as habitat and species distribution modelling, dispersal and extinction processes, biogeography and bioanthropology.Measurement(s)temperature • precipitation process • vegetation layer • atmospheric wind speed • cloud • humidityTechnology Type(s)computational modeling techniqueFactor Type(s)geographic location • temporal intervalSample Characteristic - Environmentclimate systemSample Characteristic - LocationEarth (planet)Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12436484 The variability of climate has profoundly impacted a wide range of macroecological processes in the Late Quaternary. Our understanding of these has greatly benefited from palaeoclimate simulations, however, high-quality reconstructions of ecologically relevant climatic variables have thus far been limited to a few selected time periods. Here, we present a 0.5° resolution bias-corrected dataset of global monthly temperature, precipitation, cloud cover, relative humidity and wind speed, 17 bioclimatic variables, annual net primary productivity, leaf area index and biomes, covering the last 120,000 years at a temporal resolution of 1,000–2,000 years. We combined medium-resolution HadCM3 climate simulations of the last 120,000 years with high-resolution HadAM3H simulations of the last 21,000 years, and modern-era instrumental data. This allows for the temporal variability of small-scale features whilst ensuring consistency with observed climate. Our data make it possible to perform continuous-time analyses at a high spatial resolution for a wide range of climatic and ecological applications - such as habitat and species distribution modelling, dispersal and extinction processes, biogeography and bioanthropology.Measurement(s)temperature • precipitation process • vegetation layer • atmospheric wind speed • cloud • humidityTechnology Type(s)computational modeling techniqueFactor Type(s)geographic location • temporal intervalSample Characteristic - Environmentclimate systemSample Characteristic - LocationEarth (planet)Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.12436484 The variability of climate has profoundly impacted a wide range of macroecological processes in the Late Quaternary. Our understanding of these has greatly benefited from palaeoclimate simulations, however, high-quality reconstructions of ecologically relevant climatic variables have thus far been limited to a few selected time periods. Here, we present a 0.5° resolution bias-corrected dataset of global monthly temperature, precipitation, cloud cover, relative humidity and wind speed, 17 bioclimatic variables, annual net primary productivity, leaf area index and biomes, covering the last 120,000 years at a temporal resolution of 1,000–2,000 years. We combined medium-resolution HadCM3 climate simulations of the last 120,000 years with high-resolution HadAM3H simulations of the last 21,000 years, and modern-era instrumental data. This allows for the temporal variability of small-scale features whilst ensuring consistency with observed climate. Our data make it possible to perform continuous-time analyses at a high spatial resolution for a wide range of climatic and ecological applications - such as habitat and species distribution modelling, dispersal and extinction processes, biogeography and bioanthropology. Measurement(s) temperature • precipitation process • vegetation layer • atmospheric wind speed • cloud • humidity Technology Type(s) computational modeling technique Factor Type(s) geographic location • temporal interval Sample Characteristic - Environment climate system Sample Characteristic - Location Earth (planet) Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12436484 The variability of climate has profoundly impacted a wide range of macroecological processes in the Late Quaternary. Our understanding of these has greatly benefited from palaeoclimate simulations, however, high-quality reconstructions of ecologically relevant climatic variables have thus far been limited to a few selected time periods. Here, we present a 0.5° resolution bias-corrected dataset of global monthly temperature, precipitation, cloud cover, relative humidity and wind speed, 17 bioclimatic variables, annual net primary productivity, leaf area index and biomes, covering the last 120,000 years at a temporal resolution of 1,000-2,000 years. We combined medium-resolution HadCM3 climate simulations of the last 120,000 years with high-resolution HadAM3H simulations of the last 21,000 years, and modern-era instrumental data. This allows for the temporal variability of small-scale features whilst ensuring consistency with observed climate. Our data make it possible to perform continuous-time analyses at a high spatial resolution for a wide range of climatic and ecological applications - such as habitat and species distribution modelling, dispersal and extinction processes, biogeography and bioanthropology. The variability of climate has profoundly impacted a wide range of macroecological processes in the Late Quaternary. Our understanding of these has greatly benefited from palaeoclimate simulations, however, high-quality reconstructions of ecologically relevant climatic variables have thus far been limited to a few selected time periods. Here, we present a 0.5° resolution bias-corrected dataset of global monthly temperature, precipitation, cloud cover, relative humidity and wind speed, 17 bioclimatic variables, annual net primary productivity, leaf area index and biomes, covering the last 120,000 years at a temporal resolution of 1,000–2,000 years. We combined medium-resolution HadCM3 climate simulations of the last 120,000 years with high-resolution HadAM3H simulations of the last 21,000 years, and modern-era instrumental data. This allows for the temporal variability of small-scale features whilst ensuring consistency with observed climate. Our data make it possible to perform continuous-time analyses at a high spatial resolution for a wide range of climatic and ecological applications - such as habitat and species distribution modelling, dispersal and extinction processes, biogeography and bioanthropology. Measurement(s) temperature • precipitation process • vegetation layer • atmospheric wind speed • cloud • humidity Technology Type(s) computational modeling technique Factor Type(s) geographic location • temporal interval Sample Characteristic - Environment climate system Sample Characteristic - Location Earth (planet) Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.12436484 The variability of climate has profoundly impacted a wide range of macroecological processes in the Late Quaternary. Our understanding of these has greatly benefited from palaeoclimate simulations, however, high-quality reconstructions of ecologically relevant climatic variables have thus far been limited to a few selected time periods. Here, we present a 0.5° resolution bias-corrected dataset of global monthly temperature, precipitation, cloud cover, relative humidity and wind speed, 17 bioclimatic variables, annual net primary productivity, leaf area index and biomes, covering the last 120,000 years at a temporal resolution of 1,000-2,000 years. We combined medium-resolution HadCM3 climate simulations of the last 120,000 years with high-resolution HadAM3H simulations of the last 21,000 years, and modern-era instrumental data. This allows for the temporal variability of small-scale features whilst ensuring consistency with observed climate. Our data make it possible to perform continuous-time analyses at a high spatial resolution for a wide range of climatic and ecological applications - such as habitat and species distribution modelling, dispersal and extinction processes, biogeography and bioanthropology.The variability of climate has profoundly impacted a wide range of macroecological processes in the Late Quaternary. Our understanding of these has greatly benefited from palaeoclimate simulations, however, high-quality reconstructions of ecologically relevant climatic variables have thus far been limited to a few selected time periods. Here, we present a 0.5° resolution bias-corrected dataset of global monthly temperature, precipitation, cloud cover, relative humidity and wind speed, 17 bioclimatic variables, annual net primary productivity, leaf area index and biomes, covering the last 120,000 years at a temporal resolution of 1,000-2,000 years. We combined medium-resolution HadCM3 climate simulations of the last 120,000 years with high-resolution HadAM3H simulations of the last 21,000 years, and modern-era instrumental data. This allows for the temporal variability of small-scale features whilst ensuring consistency with observed climate. Our data make it possible to perform continuous-time analyses at a high spatial resolution for a wide range of climatic and ecological applications - such as habitat and species distribution modelling, dispersal and extinction processes, biogeography and bioanthropology. |
| ArticleNumber | 236 |
| Author | Beyer, Robert M. Krapp, Mario Manica, Andrea |
| Author_xml | – sequence: 1 givenname: Robert M. orcidid: 0000-0003-2673-3096 surname: Beyer fullname: Beyer, Robert M. email: rb792@cam.ac.uk organization: Department of Zoology, University of Cambridge – sequence: 2 givenname: Mario orcidid: 0000-0002-2599-0683 surname: Krapp fullname: Krapp, Mario organization: Department of Zoology, University of Cambridge – sequence: 3 givenname: Andrea orcidid: 0000-0003-1895-450X surname: Manica fullname: Manica, Andrea organization: Department of Zoology, University of Cambridge |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32665576$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1017/9781107588783 10.1007/s00382-010-0904-1 10.17864/1947.99 10.1038/s41597-020-0453-3 10.1046/j.1466-822X.2003.00042.x 10.1038/sdata.2018.254 10.17161/bi.v10i0.4955 10.1145/800186.810616 10.1175/1520-0442(1999)012<0829:RTCSTC>2.0.CO;2 10.1017/CBO9781107415324.020 10.5194/cpd-11-3699-2015 10.1111/j.1466-8238.2009.00476.x 10.1073/pnas.1209494109 10.1016/j.quascirev.2015.06.021 10.3354/cr021001 10.1002/joc.3711 10.3133/ds691 10.6084/m9.figshare.12293345.v3 10.5194/essd-2016-58 10.17605/osf.io/p86rt 10.1016/j.quascirev.2009.10.011 10.1016/j.quascirev.2011.06.012 10.5194/cp-2019-11 10.1029/2002JD002782 10.1029/2002JD002559 10.1002/joc.1276 10.1126/science.1190653 10.1002/2014JB011176 10.1145/321607.321609 10.5194/gmd-10-3715-2017 10.1038/nature19365 10.1002/jqs.1423 |
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| References | Arnell, N. W., Hudson, D. & Jones, R. Climate change scenarios from a regional climate model: Estimating change in runoff in southern Africa. Journal of Geophysical Research: Atmospheres108 (2003). Pearson, R. G. & Dawson, T. P. Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global Ecology and Biogeography12 (2003). Klein Goldewijk, K., Beusen, A., Doelman, J. & Stehfest, E. New anthropogenic land use estimates for the Holocene: HYDE 3.2. Earth System Science Data9 (2017). Harris, I., Osborn, T. J., Jones, P., & Lister, D. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Scientific Data7, 109 (2020). Timmermann, A. & Friedrich, T. Late Pleistocene climate drivers of early human migration. Nature538 (2016). Spratt, R. M. & Lisiecki, L. E. A Late Pleistocene sea level stack. Climate of the Past12 (2016). AkimaHA new method of interpolation and smooth curve fitting based on local proceduresJournal of the ACM19701758960210.1145/321607.321609 Eriksson, A. et al. Late Pleistocene climate change and the global expansion of anatomically modern humans. Proceedings of the National Academy of Sciences109 (2012). Flato, G. et al. Evaluation of Climate Models. In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assess-ment Report of the Intergovernmental Panel on Climate Change (eds. Stocker, T. F. et al.) 741–866 (Cambridge University Press, 2013). Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology25 (2005). Kaplan, J. O. et al. Climate change and Arctic ecosystems: 2. Modeling, paleodata-model comparisons, and future projections. Journal of Geophysical Research: Atmospheres108 (2003). New, M., Hulme, M. & Jones, P. Representing twentieth-century space–time climate variability. Part I: Development of a 1961–90 mean monthly terrestrial climatology. Journal of Climate12 (1999). Singarayer, J. S. & Valdes, P. J. High-latitude climate sensitivity to ice-sheet forcing over the last 120 kyr. Quaternary Science Reviews29 (2010). Hudson, D. & Jones, R. Regional climate model simulations of present-day and future climates of southern Africa (Hadley Centre for Climate Prediction and Research, 2002). Peltier, W., Argus, D. & Drummond, R. Space geodesy constrains ice age terminal deglaciation: The global ICE-6G_C (VM5a) model. Journal of Geophysical Research: Solid Earth120 (2015). Lacis, A. A., Schmidt, G. A., Rind, D. & Ruedy, R. A. Atmospheric CO2: Principal control knob governing Earth’s temperature. Science330 (2010). Lorenzen, E. D. et al. Species-specific responses of Late Quaternary megafauna to climate and humans. Nature479 (2011). New, M., Lister, D., Hulme, M. & Makin, I. A high-resolution data set of surface climate over global land areas. Climate Research21 (2002). Svenning, J.-C., Fløjgaard, C., Marske, K. A., Nógues-Bravo, D. & Normand, S. Applications of species distribution modeling to paleobiology. Quaternary Science Reviews30 (2011). Turney, C. S. & Jones, R. T. Does the Agulhas Current amplify global temperatures during super-interglacials? Journal of Quaternary Science25 (2010). Nogués-Bravo, D. Predicting the past distribution of species climatic niches. Global Ecology and Biogeography18 (2009). O’Donnell, M. S. & Ignizio, D. A. Bioclimatic predictors for supporting ecological applications in the conterminous United States. US Geological Survey Data Series691 (2012). Lima-Ribeiro, M. S. et al. Ecoclimate: a database of climate data from multiple models for past, present, and future for macroecologists and biogeographers. Biodiversity Informatics10 (2015). BeyerRLate Quaternary Environment202010.17605/osf.io/p86rtOpen Science Framework Brown, J. L., Hill, D. J., Dolan, A. M., Carnaval, A. C. & Haywood, A. M. PaleoClim, high spatial resolution paleoclimate surfaces for global land areas. Scientific Data5 (2018). Bartlein, P. et al. Pollen-based continental climate reconstructions at 6 and 21 ka: a global synthesis. Climate Dynamics37 (2011). ValdesPJThe BRIDGE HadCM3 family of climate models: HadCM3@ Bristol v1. 0Geoscientific Model Development201710371537432017GMD....10.3715V1:CAS:528:DC%2BC1MXmt1Chsr0%3D10.5194/gmd-10-3715-2017 Singarayer, J. S. & Burrough, S. L. Interhemispheric dynamics of the African rainbelt during the late Quaternary. Quaternary Science Reviews124 (2015). Shepard, D. A two-dimensional interpolation function for irregularly-spaced data. In Proceedings of the 1968 23rd ACM national conference, 517–524 (1968). Beyer, R., Krapp, M. & Manica, A. An empirical evaluation of bias correction methods for paleoclimate simulations. Climate of the Past. In press (2020). Harris, I., Jones, P. D., Osborn, T. J. & Lister, D. H. Updated high-resolution grids of monthly climatic observations–the CRU TS3. 10 Dataset. International Journal of Climatology34 (2014). Amante, C. & Eakins, B. W. ETOPO1 arc-minute global relief model: procedures, data sources and analysis (2009). HarrisonSBIOME 6000 DB classified plotfile version 1201710.17864/1947.99University of Reading Maraun, D. & Widmann, M. Statistical downscaling and bias correction for climate research (Cambridge University Press, 2018). 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| References_xml | – reference: Timmermann, A. & Friedrich, T. Late Pleistocene climate drivers of early human migration. Nature538 (2016). – reference: Brown, J. L., Hill, D. J., Dolan, A. M., Carnaval, A. C. & Haywood, A. M. PaleoClim, high spatial resolution paleoclimate surfaces for global land areas. Scientific Data5 (2018). – reference: Eriksson, A. et al. Late Pleistocene climate change and the global expansion of anatomically modern humans. Proceedings of the National Academy of Sciences109 (2012). – reference: Lima-Ribeiro, M. S. et al. Ecoclimate: a database of climate data from multiple models for past, present, and future for macroecologists and biogeographers. Biodiversity Informatics10 (2015). – reference: BeyerRKrappMManicaALate Quaternary climate, bioclimate and vegetation202010.6084/m9.figshare.12293345.v3figshare – reference: Beyer, R., Krapp, M. & Manica, A. An empirical evaluation of bias correction methods for paleoclimate simulations. Climate of the Past. In press (2020). – reference: Hudson, D. & Jones, R. Regional climate model simulations of present-day and future climates of southern Africa (Hadley Centre for Climate Prediction and Research, 2002). – reference: Lacis, A. A., Schmidt, G. A., Rind, D. & Ruedy, R. A. Atmospheric CO2: Principal control knob governing Earth’s temperature. Science330 (2010). – reference: Bartlein, P. et al. Pollen-based continental climate reconstructions at 6 and 21 ka: a global synthesis. Climate Dynamics37 (2011). – reference: Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology25 (2005). – reference: Flato, G. et al. Evaluation of Climate Models. In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assess-ment Report of the Intergovernmental Panel on Climate Change (eds. Stocker, T. F. et al.) 741–866 (Cambridge University Press, 2013). – reference: Shepard, D. A two-dimensional interpolation function for irregularly-spaced data. In Proceedings of the 1968 23rd ACM national conference, 517–524 (1968). – reference: Pearson, R. G. & Dawson, T. P. Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global Ecology and Biogeography12 (2003). – reference: Harris, I., Osborn, T. J., Jones, P., & Lister, D. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Scientific Data7, 109 (2020). – reference: HarrisonSBIOME 6000 DB classified plotfile version 1201710.17864/1947.99University of Reading – reference: Peltier, W., Argus, D. & Drummond, R. Space geodesy constrains ice age terminal deglaciation: The global ICE-6G_C (VM5a) model. Journal of Geophysical Research: Solid Earth120 (2015). – reference: Svenning, J.-C., Fløjgaard, C., Marske, K. A., Nógues-Bravo, D. & Normand, S. Applications of species distribution modeling to paleobiology. Quaternary Science Reviews30 (2011). – reference: Lorenzen, E. D. et al. Species-specific responses of Late Quaternary megafauna to climate and humans. Nature479 (2011). – reference: AkimaHA new method of interpolation and smooth curve fitting based on local proceduresJournal of the ACM19701758960210.1145/321607.321609 – reference: New, M., Hulme, M. & Jones, P. Representing twentieth-century space–time climate variability. Part I: Development of a 1961–90 mean monthly terrestrial climatology. Journal of Climate12 (1999). – reference: Harris, I., Jones, P. D., Osborn, T. J. & Lister, D. H. Updated high-resolution grids of monthly climatic observations–the CRU TS3. 10 Dataset. International Journal of Climatology34 (2014). – reference: ValdesPJThe BRIDGE HadCM3 family of climate models: HadCM3@ Bristol v1. 0Geoscientific Model Development201710371537432017GMD....10.3715V1:CAS:528:DC%2BC1MXmt1Chsr0%3D10.5194/gmd-10-3715-2017 – reference: Singarayer, J. S. & Valdes, P. J. High-latitude climate sensitivity to ice-sheet forcing over the last 120 kyr. Quaternary Science Reviews29 (2010). – reference: Singarayer, J. S. & Burrough, S. L. Interhemispheric dynamics of the African rainbelt during the late Quaternary. Quaternary Science Reviews124 (2015). – reference: Kaplan, J. O. et al. Climate change and Arctic ecosystems: 2. Modeling, paleodata-model comparisons, and future projections. Journal of Geophysical Research: Atmospheres108 (2003). – reference: Maraun, D. & Widmann, M. Statistical downscaling and bias correction for climate research (Cambridge University Press, 2018). – reference: BeyerRLate Quaternary Environment202010.17605/osf.io/p86rtOpen Science Framework – reference: Nogués-Bravo, D. Predicting the past distribution of species climatic niches. Global Ecology and Biogeography18 (2009). – reference: Amante, C. & Eakins, B. W. ETOPO1 arc-minute global relief model: procedures, data sources and analysis (2009). – reference: Turney, C. S. & Jones, R. T. Does the Agulhas Current amplify global temperatures during super-interglacials? Journal of Quaternary Science25 (2010). – reference: New, M., Lister, D., Hulme, M. & Makin, I. A high-resolution data set of surface climate over global land areas. Climate Research21 (2002). – reference: O’Donnell, M. S. & Ignizio, D. A. Bioclimatic predictors for supporting ecological applications in the conterminous United States. US Geological Survey Data Series691 (2012). – reference: Spratt, R. M. & Lisiecki, L. E. A Late Pleistocene sea level stack. Climate of the Past12 (2016). – reference: Arnell, N. W., Hudson, D. & Jones, R. Climate change scenarios from a regional climate model: Estimating change in runoff in southern Africa. Journal of Geophysical Research: Atmospheres108 (2003). – reference: Klein Goldewijk, K., Beusen, A., Doelman, J. & Stehfest, E. New anthropogenic land use estimates for the Holocene: HYDE 3.2. Earth System Science Data9 (2017). – ident: 552_CR14 doi: 10.1017/9781107588783 – ident: 552_CR32 doi: 10.1007/s00382-010-0904-1 – ident: 552_CR3 – year: 2017 ident: 552_CR34 doi: 10.17864/1947.99 – ident: 552_CR23 doi: 10.1038/s41597-020-0453-3 – ident: 552_CR11 doi: 10.1046/j.1466-822X.2003.00042.x – ident: 552_CR10 doi: 10.1038/sdata.2018.254 – ident: 552_CR16 – ident: 552_CR8 doi: 10.17161/bi.v10i0.4955 – ident: 552_CR20 doi: 10.1145/800186.810616 – ident: 552_CR21 doi: 10.1175/1520-0442(1999)012<0829:RTCSTC>2.0.CO;2 – ident: 552_CR7 doi: 10.1017/CBO9781107415324.020 – ident: 552_CR25 doi: 10.5194/cpd-11-3699-2015 – ident: 552_CR1 doi: 10.1111/j.1466-8238.2009.00476.x – ident: 552_CR5 doi: 10.1073/pnas.1209494109 – ident: 552_CR12 doi: 10.1016/j.quascirev.2015.06.021 – ident: 552_CR24 doi: 10.3354/cr021001 – ident: 552_CR26 – ident: 552_CR22 doi: 10.1002/joc.3711 – ident: 552_CR27 doi: 10.3133/ds691 – year: 2020 ident: 552_CR31 doi: 10.6084/m9.figshare.12293345.v3 – ident: 552_CR30 doi: 10.5194/essd-2016-58 – year: 2020 ident: 552_CR35 doi: 10.17605/osf.io/p86rt – ident: 552_CR6 doi: 10.1016/j.quascirev.2009.10.011 – ident: 552_CR2 doi: 10.1016/j.quascirev.2011.06.012 – ident: 552_CR15 doi: 10.5194/cp-2019-11 – ident: 552_CR17 doi: 10.1029/2002JD002782 – ident: 552_CR28 doi: 10.1029/2002JD002559 – ident: 552_CR9 doi: 10.1002/joc.1276 – ident: 552_CR19 doi: 10.1126/science.1190653 – ident: 552_CR29 doi: 10.1002/2014JB011176 – volume: 17 start-page: 589 year: 1970 ident: 552_CR18 publication-title: Journal of the ACM doi: 10.1145/321607.321609 – volume: 10 start-page: 3715 year: 2017 ident: 552_CR13 publication-title: Geoscientific Model Development doi: 10.5194/gmd-10-3715-2017 – ident: 552_CR4 doi: 10.1038/nature19365 – ident: 552_CR33 doi: 10.1002/jqs.1423 |
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| Title | High-resolution terrestrial climate, bioclimate and vegetation for the last 120,000 years |
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