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opencc-by-4.0Apr 2022View details →

Holocene temperature reconstruction using paleoclimate data assimilation

A reconstruction of Holocene temperature made using paleoclimate data assimilation.  Spatial and mean quantities are presented, as well as information about the experimental design and proxies.  The code used to make this reconstruction is available at https://github.com/Holocene-Reconstruction/Holocene-code.

opencc-by-4.0Mar 2024View details →

Models and Datasets for "Extracting Paleoweather from Paleoclimate: A Deep Learning Reconstruction of Northern Hemisphere Summertime Atmospheric Blocking over the Last Millennium"

Associated publication: Karamperidou, C., Extracting Paleoweather from Paleoclimate: A Deep Learning Reconstruction of Northern Hemisphere Summertime Atmospheric Blocking over the Last Millennium, Nature Communications Earth & Environment, (2024)   This repository contains: <ul> <li>the architecture and weights of PaleoBlockNet v1.0</li> <li>the following ensemble DL reconstructions of JJA frequency of blocked days inferred by PaleoBlockNet: <ol> <li>the 10-member NTREND-based DL reconstruction; uses as input the NTREND DA N.Hemisphere MJJA surface temperature anomaly by King et al. (2021)</li> <li>the 100-member PHYDA-based DL reconstruction; uses as input the PHYDA JJA surface temperature anomaly by Steiger et al. (2018)</li> <li>the 12-member LME-based DL reconstruction; uses as input the CESM-LME surface temperature anomaly; this is a sensitivity experiment (see publication for details).</li> </ol> </li> <li>Integrated Gradients that assign importance to the input features for PaleoblockNet's blocking inferences </li> <li>train-validate-test samples to use with sample scripts from the Gituhub repo github/ckaramp-research/paleoblocknet</li> </ul>   If you use this dataset, please cite the associated publication and the present repository. To interactively explore the datasets, a web interface has been developed and can be accessed at <a href="https://www2.hawaii.edu/~ckaramp/paleoblocknet">https://www2.hawaii.edu/~ckaramp/paleoblocknet</a> Contact the author Christina Karamperidou (<a title="Karamperidou Research Group" href="https://www2.hawaii.edu/~ckaramp" target="_blank" rel="noopener">https://www2.hawaii.edu/~ckaramp</a>) for more information about the details of these datasets.

opencc-by-4.0Aug 2024View details →

Cretaceous-scope supplementary material to "The Cretaceous World: Plate Tectonics, Paleogeography, and Paleoclimate"

Cretaceous Supplemental Materials for the study ‘The Cretaceous World: Plate Tectonics, Paleogeography and Paleoclimate’ by C.R. Scotese C. Vérard, L. Burgener, R. P. Elling and A.T. Kocsis (<a href="https://doi.org/10.1144/sp544-2024-28">https://doi.org/10.1144/sp544-2024-28</a>). Please cite this article if you use any material here in your publication. Please see the included 'Cretaceous Supplemental Materials Explanation.docx' document for description of supplementary items and table of contents.

opencc-by-4.0Aug 2024View details →

Phanerozoic-scope supplementary material to "The Cretaceous World: Plate Tectonics, Paleogeography, and Paleoclimate" from the PALEOMAP project

Phanerozoic Supplemental Materials for the study ‘The Cretaceous World: Plate Tectonics, Paleogeography and Paleoclimate’ by C.R. Scotese C. Vérard, L. Burgener, R. P. Elling and A.T. Kocsis (<a href="https://doi.org/10.1144/sp544-2024-28">https://doi.org/10.1144/sp544-2024-28</a>). Please cite this article if you use any material here in your publication. Please see the included 'Phanerozoic Supplemental Materials Explanation.docx' document for description of supplementary items and table of contents.

opencc-by-nc-4.0Jun 2021View details →

Paleoclimate signals and groundwater age distributions from 39 public water works in the Netherlands; insights from noble gases and carbon, hydrogen and oxygen isotope tracers [Data set].

Data set covering the meta data of the 39 well fields, the macro chemistry data and the data of the noble gases and carbon, hydrogen and oxygen isotope tracers used for assessing the paleoclimate signals and age distributions in the publication in Water Resources Research (2021) Paleoclimate signals and groundwater age distributions from 39 public water works in the Netherlands; insights from noble gases and carbon, hydrogen and oxygen isotope tracers Hans Peter Broers, Jürgen Sültenfuß , Werner Aeschbach, Arne Kersting,, Armin Menkovich, Jasperien de Weert and Jeroen Castelijns

FIGURE 8 in Paleoclimate and paleoecology of the Upper Oligocene Tehuacán Formation, Puebla State, Mexico, as determined from wood anatomical characters

FIGURE 8. Projection of the first two principal components displaying the contribution (cos2) of each tracheal characteristic. Vmm2= vessels per square millimeter; VD= mean vessel diameter; VL= mean vessel length; VG= mean vessel grouping; BAR= mean number of bars per perforation plate; T= tracheid proportion; SE= proportion of helical sculpture (latewood+early wood proportions); GR= growing rings; MESO= mesomorphy index.

FIGURE 6 in Paleoclimate and paleoecology of the Upper Oligocene Tehuacán Formation, Puebla State, Mexico, as determined from wood anatomical characters

FIGURE 6. Distance dendogram displaying the comparison of the tracheal elements of the Tehuacán Fm. paleoflora with extant communities, fossil ones and Southern California ecological categories in the tracheal elements comparison. *Fossil paleofloras.

FIGURE 5 in Paleoclimate and paleoecology of the Upper Oligocene Tehuacán Formation, Puebla State, Mexico, as determined from wood anatomical characters

FIGURE 5. Projection of the first two principal components displaying the contribution (cos2) of each anatomical character. (X1) Growth rings, (X2) Vessel grouping, (X3) Vessel frequency, (X4) Vessel diameter, (X5) Vessel wall thickness, (X6) Helical sculpture, (X7) Intervascular pit aperture diameter, (X8) Alternate intervessel pits, (X9) Opposite intervessel pits, (X10) Scalariform intervessel pits, (X11) Simple perforation plates, (X12) Scalariform perforation plates, (X13) Fibre Wall thickness, (X14) Fibre lumen diameter, (X15) Tracheids, (X16) Fibrotracheids, (X17) Libriform fibres, (X18) Parenchyma diffuse in aggregates, (X19) Vasicentric parenchyma, (X20) Aliform parenchyma, (X21) Apotracheal parenchyma bands, (X22) Concentric parenchyma bands, (X23) Marginal parenchyma, (X24) Height of uniseriate ray (µm), (X25) Height of uniseriate ray (Nº cells), (X26) Percentage of uniseriate rays, (X27) Exclusively uniseriate rays, (X28) Width of multiseriate ray (µm), (X29) Width of multiseriate ray (Nº cells), (X30) Length of uniseriate extensions (µm), (X31) Length of uniseriate extensions (Nº cells), (X32) Storied structure, (X33) Heterocellular rays, (X34) Homocellular rays.

FIGURE 3 in Paleoclimate and paleoecology of the Upper Oligocene Tehuacán Formation, Puebla State, Mexico, as determined from wood anatomical characters

FIGURE 3. Distance dendogram showing the anatomical similarity between extant communities, fossil ones and the Tehuacán Fm. paleoflora. *Fossil paleofloras.

FIGURE 7 in Paleoclimate and paleoecology of the Upper Oligocene Tehuacán Formation, Puebla State, Mexico, as determined from wood anatomical characters

FIGURE 7. Projection of the first two principal components that displays the contribution (contrib) and spatial position of each communities within the PCA.

FIGURE 4 in Paleoclimate and paleoecology of the Upper Oligocene Tehuacán Formation, Puebla State, Mexico, as determined from wood anatomical characters

FIGURE 4. Projection of the first two principal components displaying the contribution (contrib) and spatial position of each community within the PCA.

FIGURE 2 in Paleoclimate and paleoecology of the Upper Oligocene Tehuacán Formation, Puebla State, Mexico, as determined from wood anatomical characters

FIGURE 2. Morpho-anatomic diversity of the paleoflora of the Tehuacán Fm. - A: Morphotype 2. Diffuse porosity with solitary and aggregates of vessels (2-3) with tylosis (TS). - B: Morphotype 16. Diffuse porosity with solitary and aggregate vessels (2), vasicentric and banded parenchyma bands (white arrows) (TS). - C: Morphotype 6. Detail of solitary and aggregate vessel elements with dark contents, thick walls and parenchyma bands (TS). - D: Morphotype 12. Long and wide vessel elements and multiseriate rays (RSL). - E: Morphotype 1. Vessel elements with alternate intervascular pits (RSL). - F: Morphotype 4. Short and wide vessel elements with alternating intervascular pits (TSL). - G: Morphotype 3. Biseriate rays (TSL). -H: Morphotype 19. Multiseriate rays and abundant axial parenchyma (TSL). - I: Morphotype 14. Rays mostly biseriate, some uniseriate (white arrows). Scale bar: 250 µm in A, B; 100 µm in C, D, E, G, H, I; 50 µm in F.

TABLE 5 in Paleoclimate estimates for the Paleogene-Neogene in southern South America using fossil leaves as proxies

TABLE 5 — Fossil locations from Southern South America and age in million of years.Studied geological formations and sites used for comparison in the discussion.<table><thead><tr><th>Fossil Site</th><th>Geological Formation</th><th>Age (Ma)</th><th>Source</th></tr></thead><tbody><tr><th>Pico Quemado</th><td>Ñirihuau</td><td>middle Miocene?</td><td>Caviglia 2018</td></tr><tr><th>Cancha Carreras, Estancia Tres Marías</th><td>Río Guillermo</td><td>≤21.7 ± 0.3 to ≤23.5 ± 0.3</td><td>Fosdick et al. 2011; 2015a, b</td></tr><tr><th>Aluminé Basin</th><td>Rancahué</td><td>25.0 ± 1.4 to 26.0 ± 1.5</td><td>Brea et al. 2015; Franzese et al. 2011</td></tr><tr><th>Sierra Baguales</th><td>Río Leona</td><td>33.0 ± 2.8</td><td>Gutiérrez et al. 2017, 2019</td></tr><tr><th>Upper Río Turbio</th><td>Río Turbio</td><td>≤26.6 ± 0.2 to ≤33.4 to</td><td>Fosdick et al. 2015a</td></tr><tr><th>Lower Río Turbio</th><td>Río Turbio</td><td>≤46.3 ± 1.3 to ≤47.1 ± 2.7</td><td>Fosdick et al. 2015a</td></tr><tr><th>Río Pichileufú</th><td>Ventana</td><td>47.46 ± 0.05</td><td>Wilf et al. 2005</td></tr><tr><th>Laguna del Hunco</th><td>La Huitrera</td><td>51.91 ± 0.22</td><td>Wilf et al. 2005</td></tr><tr><th>Ligorio Márquez</th><td>Ligorio Márquez</td><td><57</td><td>Suárez et al. 2000; Hinojosa 2005</td></tr><tr><th>Palacio de los Loros</th><td>Salamanca</td><td>61.7</td><td>Iglesias et al. 2007</td></tr></tbody></table>

TABLE 2 in Paleoclimate estimates for the Paleogene-Neogene in southern South America using fossil leaves as proxies

TABLE 2 — Estimated values of temperature and precipitation for the upper Río Turbio Formation member. *Scarce fossil material.<table><thead><tr><th>Upper RTF</th><th></th><th>Equation</th><th>Dataset</th><th>R 2</th><th>Error</th><th>Source</th></tr></thead><tbody><tr><th>Temperature (°C)</th><td>15.3</td><td colspan="2">MAT = 3.25 + 0.24*% non-tooth CLAMP 3B SA</td><td>0.9</td><td>2.1°C</td><td>Hinojosa 2005; Hinojosa & Villagrán 2005</td></tr><tr><th>Temperature (°C)</th><td>14.3</td><td>MAT = 26.03pE + 1.31</td><td>SA</td><td>0.82</td><td>2.8°C</td><td>Hinojosa et al. 2011</td></tr><tr><th>Temperature (°C)</th><td>14.8</td><td>MAT = 0.204*E + 4.6</td><td>LMA</td><td>0.58</td><td>4.8°C</td><td>Peppe et al. 2011</td></tr><tr><th>Precipitation (mm)</th><td>*</td><td>Ln(MAP) = 1.63 + 0.49*MLnA</td><td>CLAMP 3B SA</td><td>0.6</td><td>Ln(0.5) cm</td><td>Hinojosa 2005; Hinojosa & Villagrán 2005</td></tr><tr><th>Precipitation (mm)</th><td>*</td><td>lnMAP = 0.283(MlnA) + 2.92</td><td>LAA</td><td>0.23</td><td>0.61</td><td>Peppe et al. 2011</td></tr></tbody></table>

TABLE 3 in Paleoclimate estimates for the Paleogene-Neogene in southern South America using fossil leaves as proxies

TABLE 3 — Estimated values of temperature and precipitation for the Río Guillermo Formation.<table><thead><tr><th>RGF</th><th></th><th>Equation</th><th>Dataset</th><th>R 2</th><th>Error</th><th>Source</th></tr></thead><tbody><tr><th>Temperature (°C)</th><td>5.3</td><td>MAT = 3.25 + 0.24*% non-tooth</td><td>CLAMP 3B SA</td><td>0.9</td><td>2.1°C</td><td>Hinojosa 2005; Hinojosa & Villagrán 2005</td></tr><tr><th>Temperature (°C)</th><td>3.5</td><td>MAT = 26.03pE + 1.31</td><td>SA</td><td>0.82</td><td>2.8°C</td><td>Hinojosa et al. 2011</td></tr><tr><th>Temperature (°C)</th><td>6.3</td><td>MAT = 0.204E + 4.6</td><td>LMA</td><td>0.58</td><td>4.8°C</td><td>Peppe et al. 2011</td></tr><tr><th>Precipitation (mm)</th><td>682</td><td>Ln(MAP) = 1.63 + 0.49*MLnA</td><td>CLAMP 3B SA</td><td>0.6</td><td>Ln(0.5) cm</td><td>Hinojosa 2005; Hinojosa & Villagrán 2005</td></tr><tr><th>Precipitation (mm)</th><td>829</td><td>lnMAP = 0.283(MlnA) + 2.92</td><td>LAA</td><td>0.23</td><td>0.61</td><td>Peppe et al. 2011</td></tr></tbody></table>

TABLE 1 in Paleoclimate estimates for the Paleogene-Neogene in southern South America using fossil leaves as proxies

TABLE 1 — Estimated values of temperature and precipitation for the lower Río Turbio Formation member.<table><thead><tr><th>Lower RTF</th><th></th><th>Equation</th><th>Dataset</th><th>R 2</th><th>Error</th><th>Source</th></tr></thead><tbody><tr><th>Temperature (°C)</th><td>16.5</td><td>MAT = 3.25 + 0.24*% non-tooth</td><td>CLAMP 3B SA</td><td>0.9</td><td>2.1°C</td><td>Hinojosa 2005; Hinojosa & Villagrán 2005</td></tr><tr><th>Temperature (°C)</th><td>15.7</td><td>MAT = 26.03pE + 1.31</td><td>SA</td><td>0.82</td><td>2.8°C</td><td>Hinojosa et al. 2011</td></tr><tr><th>Temperature (°C)</th><td>15.6</td><td>MAT = 0.204E + 4.6</td><td>LMA</td><td>0.58</td><td>4.8°C</td><td>Peppe et al. 2011</td></tr><tr><th>Temperature (°C)</th><td>16.9</td><td>See manuscript (1)</td><td>DiLP</td><td>0.7</td><td>4°C</td><td>Peppe et al. 2011</td></tr><tr><th>Precipitation (mm)</th><td>1764</td><td>Ln(MAP) = 1.63 + 0.49*MLnA</td><td>CLAMP 3B SA</td><td>0.6</td><td>Ln(0.5) cm</td><td>Hinojosa 2005; Hinojosa & Villagrán 2005</td></tr><tr><th>Precipitation (mm)</th><td>1435</td><td>lnMAP = 0.283(MlnA) + 2.92</td><td>LAA</td><td>0.23</td><td>0.61 cm</td><td>Peppe et al. 2011</td></tr><tr><th>Precipitation (mm)</th><td>1303</td><td>See manuscript (2)</td><td>DiLP</td><td>0.27</td><td>0.6 cm</td><td>Peppe et al. 2011</td></tr></tbody></table>

openother-openNov 2021View details →

Data & code repository for "A re-appraisal of the ENSO response to volcanism with paleoclimate data assimilation"

This repository includes the data and code that can be used to reproduce the figures for the paper entitled A re-appraisal of the ENSO response to volcanism with paleoclimate data assimilation.

opencc-by-4.0Jan 2022View details →

Terrestrial paleoclimate reconstruction of the UK Neogene (?Langhian to Piacenzian) comparing CREST, CRACLE and the Co-existence Approach

Abstract  The first detailed reconstruction of the terrestrial paleoclimate development of the UK Neogene (?Langhian to Piacenzian) is presented. The paleoclimate data are derived from the paleobotanical record using two probability-based reconstruction techniques CREST (Climate REconstruction SofTware) (Chevalier et al. 2014) and CRACLE (Climate Reconstruction Analysis using Coexistence Likelihood Estimation) (Harbert & Nixon 2015) that use Bayesian and likelihood estimation probability respectively. The results of these reconstructions are presented alongside reconstructions using the widely-applied Co-existence Approach (CA) (Utescher et al. 2014) for comparison. While all three techniques use the climate requirements of their Nearest Living Relatives as the basis of their reconstruction, they use different database observations. CREST and CRACLE use the GBIF (Global Biodiverstiy Information Facility) (GBIF, 2021) as well as WorldClim inputs for the 19 bioclimate variables used by BIOCLIM (<a href="http://www.worldclim.org/bioclim">http://www.worldclim.org/bioclim</a>). Meanwhile, the CA uses the Palaeoflora database, meaning the input for the three models is different. The reconstructions for the UK Neogene palaeoclimate come from 4 localities (12 samples total) spanning the Middle Miocene (Langhian) to Pliocene (Piacenzian): Trwyn y Parc, Anglesey (Middle Miocene), Brassington Formation, Derbyshire (Serravallian-Tortonian), Coralline Crag Formation (latest Zanclean-earliest Piacenzian) and Red Crag Formation (Piacenzian-Gelasian) of southeast England. We present CREST and CRACLE reconstructions of Mean Annual Temperature (MAT), Mean Temperature of Warmest Quarter (MTWQ), Mean Temperature of Coldest Quarter (MTCQ), Mean Annual Precipitation (MAP) and precipitation seasonality (CoV ×100). The CA does not reconstruct MTWQ, MTCQ or precipitation seasonality. Instead, the CA reconstructs Warmest Month Mean Temperature (WMMT) and Coldest Month Mean Temperature (CMMT). The proportion of rainfall falling in the wettest months of the year (RMPwet(%)) was used as a proxy for precipitation seasonality following the methodology of Jacques et al. (2011) and Utescher et al. (2015). The CREST R-code output provides 0.5 and 0.95 (2-σ) uncertainties as well as an optimum and mean for each variable. The CRACLE R-code output provides both parametric and non-parametric joint likelihoods (P-CRACLE and N-CRACLE) with 0.95 (2-σ) uncertainties and a mean that is based on P-CRACLE. The CA generates a minimum and maximum likelihood which together comprise the coexistence interval. The Neogene climate reconstruction of the UK shows a cooling trend from the Langhian to the Pliocene-Pleistocene boundary. CREST and CRACLE produce trends and values consistent with Co-existence Approach data with 0.95 uncertainties overlapping with the CA coexistence interval. File Descriptions  Table S1 displays the complete reconstruction for the UK Neogene using CREST, CRACLE and the Co-existence Approach. Table S2 displays detailed site information including: modern and paleo latitude and longitude, dating technique, modern climatology and fossil assemblage diversity (number of fossil taxa versus number of NLRs used for climate reconstruction). Modern climatology has been included to serve as a comparison to the reconstructed Neogene climate. This data has been extracted from WorldClim 2.1 (Fick & Hijmans, 2017). Data Set S1 contains the list of fossil spore and pollen taxa per site and associated Nearest Living Relatives (NLRs), where identifiable, used as the input for CREST, CRACLE and the Co-existence Approach. Relic taxa are included and highlighted in red. Data Set S2 is included to show the effect relic taxa have on paleoclimate reconstructions. The relic taxa are removed following the protocol of Utescher et al. (2014) whereby known relic taxa are removed from analyses to avoid biased reconstructions. Relic taxa removed from analyses include Cathaya, Cryptomeria, Pinus sylvestris and Sciadopitys when present. Data Set S3 is included to show the effects of removing family-level identifications in CRACLE reconstructions. Removing families is shown to generate a less informative reconstruction. Including both genera- and family-level classifications of NLR (Nearest Living Relative) is recommended, however we suggest identifying NLRs (Nearest Living Relatives) to genera-level wherever possible.