Abstract
Reconstructing Quaternary regional glaciations throughout the Himalaya, Tibet, and the adjoining mountains in Central Asia is challenging due to geological biases towards limited preservation of glacial deposits and chronological uncertainties. Here, we offer several statistical and mathematical model codes in R, in excel, and in MATLAB useful to develop regional glacial chronostratigraphies, especially in areas with distinct orographically-modulated climate. A complete R code is provided to generate a regional climate map using Cluster Analysis (CA) and Principal Component Analysis (PCA). Additional R codes include reduced chi-squared, Chauvenet's criterion, radial plotter/abanico plot, finite mixture model, and Student's t-test. These methods are useful in reconstructing the timing of local and regional glacial chronologies. An excel code to calculate equilibrium-line altitudes (ELAs) and steps to reconstruct glacier hypsometry are also made available to further aid to our understanding of the extent of paleoglaciations. A MATLAB code of the linear glacier flow model is included to reconstruct paleotemperatures using the length and slope of a glacier during past advances.•R statistical codes can be used/modified without restrictions for other researchers.•Easy steps to calculate ELAs and glacier hypsometry from the same data.•Paleo-temperature reconstruction utilizes already developed glacial chronologies and maps.
Highlights
Reconstructing Quaternary regional glaciations throughout the Himalaya, Tibet, and the adjoining mountains in Central Asia is challenging due to geological biases towards limited preservation of glacial deposits and chronological uncertainties
Component Analysis (PCA), reduced chi-squared test (χ 2), Chauvenet’s criterion, radial plotter, abanico plot, finite mixture model, Student’s t-test, equilibrium-line altitudes (ELAs) and glacier hypsometry, and linear glacier flow model. These methods may be broadly categorized into climate statistics (e.g., Cluster Analysis (CA), Principal Component Analysis (PCA)), age statistics (e.g., χ 2, Chauvenet’s criterion, radial plotter, abanico plot, finite mixture model, t-test), and morphometric models (e.g., ELAs, hypsometry, flow model)
Our objectives are (i) to identify climatically distinct groups of glaciers that are modulated by topography and orography; and (ii) to develop robust regional glacial stages in each climatic region for spatiotemporal comparison
Summary
Reconstructing Quaternary regional glaciations throughout the Himalaya, Tibet, and the adjoining mountains in Central Asia is challenging due to geological biases towards limited preservation of glacial deposits and chronological uncertainties. We offer several statistical and mathematical model codes in R, in excel, and in MATLAB useful to develop regional glacial chronostratigraphies, especially in areas with distinct orographicallymodulated climate. A complete R code is provided to generate a regional climate map using Cluster Analysis (CA) and Principal Component Analysis (PCA). Additional R codes include reduced chi-squared, Chauvenet’s criterion, radial plotter/abanico plot, finite mixture model, and Student’s t-test. These methods are useful in reconstructing the timing of local and regional glacial chronologies. A MATLAB code of the linear glacier flow model is included to reconstruct paleotemperatures using the length and slope of a glacier during past advances
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