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#
C14 oceanography eNd tracers machine learning Deglaciation coordinate systems data viz watermass geometry clustering model output Paleoceanography Mystery Interval, cartopy seaborn matplotlib xarray scikit-learn pandas intake, Science Bits Lifehacks
proxy composite temperature, pyleoclim seaborn cfr pandas numpy, Science Bits
clustering endmember mixing tracers watermass geometry, matplotlib scipy sqlalchemy scikit-learn pandas basemap, Science Bits
data viz, pyleoclim ammonyte matplotlib, Figures Extras
paleoclimate correlation paleoceanography age uncertainty spectral analysis model-data comparison cross-wavelet analysis insolation wavelet analysis model output, pyleoclim cartopy climlab xarray pylipd, Science Bits
Calibration Statistics paleoceanography coral calibration Paleocenography Sr/Ca Bayesian Statistics, pyleoclim Great Tables matplotlib statsmodel pymc pandas arviz, Calibration Getting Started
paleoceanography modeling PCA, pyleoclim cartopy eofs matplotlib xarray pandas, Science Bits
Common Era PaMoDaCo data assimilation paleoclimatology timeseries modeling statistics data viz reconstruction PMIP, pyleoclim statsmodels pens seaborn matplotlib scipy pandas, Plume Distance Motivation Paleoclimate Applications Temporal Interpretation
Chapters#
C-iTRACE
oceanography tracers data viz, xarray matplotlib cartopy pandas seaborn, Lifehacks
C-iTRACE
model output oceanography coordinate systems, xarray matplotlib cartopy pandas intake, Lifehacks
C-iTRACE
model output eNd, xarray matplotlib cartopy pandas, Science Bits
C-iTRACE
clustering machine learning watermass geometry, xarray matplotlib cartopy scikit-learn, Science Bits
C-iTRACE
C14 Paleoceanography Deglaciation Mystery Interval, xarray matplotlib cartopy pandas, Science Bits
LMR-CMIP6
AWS cloud-ready data data viz CMIP6, intake AWS xarray pandas, Lifehacks
LMR-CMIP6
model output CMIP6 coordinate systems, xarray matplotlib cartopy pandas, Lifehacks
LMR-CMIP6
model output LMR CMIP6, xarray matplotlib cartopy pandas pyleoclim, Science Bits
2k Proxy Composite
proxy composite temperature, numpy seaborn pandas pyleoclim cfr, Science Bits
AncientWMG
watermass geometry tracers endmember mixing, basemap scipy matplotlib pandas sqlalchemy, Science Bits
AncientWMG
clustering watermass geometry, basemap scikit-learn matplotlib, Science Bits
Detecting Paleoclimate Transitions with LERM
data viz, matplotlib pyleoclim ammonyte, Figures
Detecting Paleoclimate Transitions with LERM
data viz, matplotlib pyleoclim ammonyte, Figures
Detecting Paleoclimate Transitions with LERM
data viz, matplotlib pyleoclim ammonyte, Figures
Detecting Paleoclimate Transitions with LERM
data viz, matplotlib pyleoclim ammonyte, Figures
Detecting Paleoclimate Transitions with LERM
data viz, matplotlib pyleoclim ammonyte, Figures
Detecting Paleoclimate Transitions with LERM
data viz, matplotlib pyleoclim ammonyte, Figures
Detecting Paleoclimate Transitions with LERM
data viz, matplotlib pyleoclim ammonyte, Figures
Detecting Paleoclimate Transitions with LERM
data viz, matplotlib pyleoclim ammonyte, Figures
Detecting Paleoclimate Transitions with LERM
data viz, matplotlib pyleoclim ammonyte, Extras
Detecting Paleoclimate Transitions with LERM
data viz, matplotlib pyleoclim ammonyte, Extras
Detecting Paleoclimate Transitions with LERM
data viz, matplotlib pyleoclim ammonyte, Extras
Pyleoclim science
spectral analysis wavelet analysis cross-wavelet analysis insolation paleoceanography, xarray pyleoclim pylipd climlab, Science Bits
Pyleoclim science
model output spectral analysis model-data comparison paleoclimate, xarray pyleoclim, Science Bits
Pyleoclim science
paleoclimate correlation age uncertainty, xarray pyleoclim cartopy pylipd, Science Bits
Coral Sr/Ca calibration
paleoceanography Sr/Ca coral calibration, matplotlib pyleoclim pandas, Getting Started
Coral Sr/Ca calibration
Statistics Calibration Paleocenography, statsmodel Great Tables, Calibration
Coral Sr/Ca calibration
Bayesian Statistics Calibration Paleocenography, pymc arviz, Calibration
PaleoPCA
paleoceanography PCA modeling, xarray pyleoclim cartopy matplotlib pandas eofs, Science Bits
PaleoEnsembles
paleoclimatology data assimilation data viz, matplotlib pens pyleoclim, Motivation
PaleoEnsembles
data assimilation PaMoDaCo, matplotlib pens, Temporal Interpretation
PaleoEnsembles
data assimilation timeseries modeling, matplotlib pens statsmodels seaborn, Temporal Interpretation
PaleoEnsembles
data assimilation timeseries modeling, matplotlib pens pyleoclim, Temporal Interpretation
PaleoEnsembles
statistics PaMoDaCo, matplotlib pens seaborn, Plume Distance
PaleoEnsembles
statistics PaMoDaCo, matplotlib pens seaborn, Plume Distance
PaleoEnsembles
reconstruction statistics Common Era, matplotlib seaborn pens scipy, Paleoclimate Applications
PaleoEnsembles
reconstruction statistics Common Era, matplotlib pens, Paleoclimate Applications
PaleoEnsembles
data assimilation PaMoDaCo PMIP, matplotlib pens pyleoclim pandas, Paleoclimate Applications