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#
tracers clustering model output Deglaciation coordinate systems eNd data viz C14 oceanography watermass geometry Mystery Interval Paleoceanography machine learning, cartopy xarray scikit-learn intake seaborn matplotlib pandas, Lifehacks Science Bits
proxy composite temperature, cfr pyleoclim numpy seaborn pandas, Science Bits
watermass geometry endmember mixing tracers clustering, scipy sqlalchemy basemap scikit-learn matplotlib pandas, Science Bits
data viz, ammonyte pyleoclim matplotlib, Main Analysis Extras
spectral analysis insolation model output wavelet analysis paleoceanography cross-wavelet analysis correlation model-data comparison paleoclimate age uncertainty, cartopy pyleoclim pylipd climlab xarray, Science Bits
Calibration paleoceanography Paleocenography coral Bayesian Statistics Statistics Sr/Ca calibration, arviz pyleoclim pymc Great Tables statsmodel matplotlib pandas, Getting Started Calibration
paleoceanography modeling PCA, cartopy pyleoclim xarray eofs matplotlib pandas, Science Bits
timeseries modeling paleoclimatology PMIP data viz statistics reconstruction PaMoDaCo data assimilation Common Era, scipy pens pyleoclim statsmodels seaborn matplotlib pandas, Paleoclimate Applications Temporal Interpretation Motivation Plume Distance
data analysis data wrangling data viz, ammonyte pyleoclim pyLiPD basemap pylipd matplotlib, Exploring the Data Main Analysis Loading Data
mapping tidyverse regression spectral analysis correlation ensemble uncertainty quantification wavelets LiPD dimension reduction visualization data wrangling age uncertainty PCA age modeling calibration, dplyr purrr oxcAAR ggplot2 lipdR readr, Data Manipulation Core Methods Extensions
signal processing data viz statistics data wrangling paleoclimate geospatial data analysis, cartopy pyleoclim numpy pylipd climlab matplotlib, Correlation Analysis Global Coherence Analysis Heuristic Examples Exploring the Data
data supplement data viz climate sensitivity, statsmodels scipy pyleoclim matplotlib, Supplement Main Analysis EC Calculations
data analysis data assimilation data wrangling data viz, pens cfr matplotlib xarray, Validation and Comparison Data Assimilation Data Assembly
data analysis data assimilation data wrangling data viz, cartopy pens cfr pylipd matplotlib, Validation and Comparison Data Assimilation Data Assembly
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