Gallery#
PaleoBooks is a compendium of digital resources to bridge the gap between paleoclimate observations and models, and between past, present and future. The goal is as much to encourage adoption of open-source, free languages like R and Python by the observational paleoscience community as it is to encourage the modeling community to leverage the unique information coming from paleo archives.
The scholarly objects shown below are of several types:
Tutorials on how to overcome a particular technical difficulty (“Life Hacks”)
Tutorials on how to leverage open-source code to achieve easier, more transparent, or more powerful scientific workflows (“Science Bits”)
Examples of novel paleoscience using the Python ecosystem e.g. as turn-key supplementary material from recent publications (“Papers”)
In the following, “PaleoBooks” refers to curated collections of Jupyter Notebooks organized around various themes. “Chapters” refers to the components of these PaleoBooks. A system of tags allows both PaleoBooks and individual chapters to be associated with one another based on individual themes or methodologies, in addition to their host PaleoBook. These tags enable searching along 3 directions:
“Domains” refers to scientific themes or methodologies
“Formats” refers to the type of resource (Life Hacks, Science Bits, or Papers)
“Packages” refers to the packages being used in each notebook (e.g. Xarray)
The gallery below is a work in progress, and we encourage you to contribute your own analyses if you think they might bring enlightenment to, and/or ease the life of, fellow scientists.
PaleoBooks#
Paleoceanography watermass geometry tracers coordinate systems machine learning eNd clustering C14 Mystery Interval model output oceanography data viz Deglaciation, seaborn matplotlib pandas scikit-learn xarray cartopy intake, Lifehacks Science Bits
proxy composite temperature, seaborn numpy pyleoclim pandas cfr, Science Bits
endmember mixing tracers watermass geometry clustering, basemap matplotlib sqlalchemy pandas scikit-learn scipy, Science Bits
data viz, ammonyte matplotlib pyleoclim, Main Analysis Extras
age uncertainty wavelet analysis paleoclimate insolation spectral analysis paleoceanography model-data comparison correlation model output cross-wavelet analysis, pylipd pyleoclim xarray climlab cartopy, Science Bits
coral Statistics Bayesian Statistics paleoceanography Calibration Sr/Ca Paleocenography calibration, matplotlib pyleoclim Great Tables pymc statsmodel pandas arviz, Getting Started Calibration
PCA paleoceanography modeling, eofs matplotlib pyleoclim pandas xarray cartopy, Science Bits
PMIP statistics reconstruction Common Era data assimilation PaMoDaCo paleoclimatology data viz timeseries modeling, seaborn matplotlib pyleoclim statsmodels pens pandas scipy, Temporal Interpretation Plume Distance Motivation Paleoclimate Applications
data analysis data wrangling data viz, pylipd pyLiPD matplotlib basemap pyleoclim ammonyte, Loading Data Main Analysis Exploring the Data
dimension reduction ensemble age uncertainty age modeling wavelets data wrangling uncertainty quantification regression visualization tidyverse spectral analysis mapping PCA correlation LiPD calibration, readr lipdR ggplot2 purrr oxcAAR dplyr, Extensions Core Methods Data Manipulation
geospatial signal processing statistics data wrangling paleoclimate data analysis data viz, pylipd matplotlib numpy pyleoclim climlab cartopy, Heuristic Examples Correlation Analysis Global Coherence Analysis Exploring the Data
climate sensitivity data supplement data viz, statsmodels scipy matplotlib pyleoclim, Main Analysis Supplement EC Calculations
data assimilation data analysis data wrangling data viz, pens cfr xarray matplotlib, Validation and Comparison Data Assembly Data Assimilation
data assimilation data analysis data wrangling data viz, pylipd matplotlib pens cfr cartopy, Validation and Comparison Data Assembly Data Assimilation
Chapters#
oceanography tracers data viz, xarray matplotlib cartopy pandas seaborn, Lifehacks
model output oceanography coordinate systems, xarray matplotlib cartopy pandas intake, Lifehacks
model output eNd, xarray matplotlib cartopy pandas, Science Bits
clustering machine learning watermass geometry, xarray matplotlib cartopy scikit-learn, Science Bits
C14 Paleoceanography Deglaciation Mystery Interval, xarray matplotlib cartopy pandas, Science Bits
AWS cloud-ready data data viz CMIP6, intake AWS xarray pandas, Lifehacks
model output CMIP6 coordinate systems, xarray matplotlib cartopy pandas, Lifehacks
model output LMR CMIP6, xarray matplotlib cartopy pandas pyleoclim, Science Bits
proxy composite temperature, numpy seaborn pandas pyleoclim cfr, Science Bits
watermass geometry tracers endmember mixing, basemap scipy matplotlib pandas sqlalchemy, Science Bits
clustering watermass geometry, basemap scikit-learn matplotlib, Science Bits
data viz, matplotlib pyleoclim ammonyte, Main Analysis, published
data viz, matplotlib pyleoclim ammonyte, Main Analysis, published
data viz, matplotlib pyleoclim ammonyte, Main Analysis, published
data viz, matplotlib pyleoclim ammonyte, Main Analysis, published
data viz, matplotlib pyleoclim ammonyte, Main Analysis, published
data viz, matplotlib pyleoclim ammonyte, Main Analysis, published
data viz, matplotlib pyleoclim ammonyte, Main Analysis, published
data viz, matplotlib pyleoclim ammonyte, Main Analysis, published
data viz, matplotlib pyleoclim ammonyte, Extras, published
data viz, matplotlib pyleoclim ammonyte, Extras, published
data viz, matplotlib pyleoclim ammonyte, Extras, published
spectral analysis wavelet analysis cross-wavelet analysis insolation paleoceanography, xarray pyleoclim pylipd climlab, Science Bits, published
model output spectral analysis model-data comparison paleoclimate, xarray pyleoclim, Science Bits, published
paleoclimate correlation age uncertainty, xarray pyleoclim cartopy pylipd, Science Bits, published
paleoceanography Sr/Ca coral calibration, matplotlib pyleoclim pandas, Getting Started
Statistics Calibration Paleocenography, statsmodel Great Tables, Calibration
Bayesian Statistics Calibration Paleocenography, pymc arviz, Calibration
paleoceanography PCA modeling, xarray pyleoclim cartopy matplotlib pandas eofs, Science Bits
paleoclimatology data assimilation data viz, matplotlib pens pyleoclim, Motivation, published
data assimilation PaMoDaCo, matplotlib pens, Temporal Interpretation, published
data assimilation timeseries modeling, matplotlib pens statsmodels seaborn, Temporal Interpretation, published
data assimilation timeseries modeling, matplotlib pens pyleoclim, Temporal Interpretation, published
statistics PaMoDaCo, matplotlib pens seaborn, Plume Distance, published
statistics PaMoDaCo, matplotlib pens seaborn, Plume Distance, published
reconstruction statistics Common Era, matplotlib seaborn pens scipy, Paleoclimate Applications, published
reconstruction statistics Common Era, matplotlib pens, Paleoclimate Applications, published
data assimilation PaMoDaCo PMIP, matplotlib pens pyleoclim pandas, Paleoclimate Applications, published
data wrangling, pyLiPD, Loading Data, published
data wrangling, pylipd pyleoclim, Loading Data, published
data viz data analysis, pyleoclim matplotlib, Exploring the Data, published
data viz data analysis, pyleoclim basemap, Exploring the Data, published
data viz data analysis, pyleoclim matplotlib, Main Analysis, published
data analysis data viz, matplotlib pyleoclim, Main Analysis, published
data viz data analysis, pyleoclim ammonyte matplotlib, Main Analysis, published
data viz data analysis, pyleoclim matplotlib, Main Analysis, published
age modeling uncertainty quantification, geoChronR lipdR, Core Methods, published
correlation age uncertainty, geoChronR ggplot2, Core Methods, published
regression calibration, geoChronR readr ggplot2, Core Methods, published
spectral analysis wavelets, geoChronR, Core Methods, published
PCA dimension reduction, geoChronR, Core Methods, published
visualization, geoChronR ggplot2, Data Manipulation, published
data wrangling mapping, geoChronR, Data Manipulation, published
data wrangling tidyverse, geoChronR dplyr purrr, Data Manipulation, published
age modeling, geoChronR oxcAAR, Extensions, published
LiPD ensemble, geoChronR, Extensions, published
data wrangling, pylipd pyleoclim, Exploring the Data, published
geospatial data viz, cartopy pyleoclim matplotlib, Exploring the Data, published
data viz, matplotlib pyleoclim, Exploring the Data, published
data viz data analysis, pyleoclim matplotlib climlab, Heuristic Examples, published
paleoclimate data analysis data viz, matplotlib climlab pyleoclim, Heuristic Examples, published
data viz data analysis paleoclimate, matplotlib pyleoclim climlab, Global Coherence Analysis, published
paleoclimate signal processing, pyleoclim climlab matplotlib, Global Coherence Analysis, published
statistics data analysis, numpy matplotlib, Global Coherence Analysis, published
statistics paleoclimate, pyleoclim climlab matplotlib, Correlation Analysis, published
statistics paleoclimate, climlab pyleoclim matplotlib, Correlation Analysis, published
climate sensitivity, statsmodels, EC Calculations, published
data viz, scipy matplotlib, EC Calculations, published
data viz, scipy matplotlib, Main Analysis, published
data viz, scipy matplotlib, Main Analysis, published
data viz, scipy matplotlib, Main Analysis, published
data viz data supplement, pyleoclim matplotlib, Supplement, published
data wrangling, cfr, Data Assembly
data wrangling, cfr, Data Assembly
data assimilation data analysis, cfr, Data Assimilation
data viz data analysis, cfr xarray matplotlib pens, Validation and Comparison
data viz data analysis, cfr matplotlib, Validation and Comparison
data wrangling, cfr pylipd, Data Assembly
data wrangling, cfr pylipd, Data Assembly
data assimilation data analysis, cfr, Data Assimilation
data viz data analysis, cfr matplotlib cartopy pens, Validation and Comparison
data viz data analysis, cfr matplotlib cartopy pens, Validation and Comparison