DOI: 10.5061/dryad.8kprr4xwr
title: Data from: India-Eurasia convergence speed-up by passive-margin sediment subduction

description: This dataset provides data and visualization code of the numerical
 experiments on India-Eurasia convergence speed-up by passive-margin
 sediment subduction. The repository contains six main subfolders, one for
 each model with different sediment thickness and pore pressure. Each
 subfolder contains hdf5 output files. Each hdf5 file has three main
 groups: Group 1-ModelGroup, which includes two datasets and an additional
 group with 5 model parameters; Group 2-NodeGroup, which contains velocity,
 stress, strain rate, and temperature datasets, as well as datasets of
 physical and rheological properties on the nodes; Group 3-VisMarkerGroup,
 which contains one dataset. The dataset, named Mtype, includes the rock
 type number of each marker (see details of the README file). Numerical
 experiments suggest that subduction of &gt;1 km-thick sediments
 covering a ~1000 km-wide ocean basin abutting the northern Indian passive
 margin could have spurred the increased convergence rate and further led
 to significant crustal extension, consistent with empirical
 observations. This dataset also provides compiled major and trace
 elements and Sr-Nd isotope compositions of the Late Cretaceous-Early
 Cenozoic magmatic rocks from the Gangdese arc (Supplementary Table 1).
 Through isotope and trace element analysis, we find an enhanced
 contribution of terrigenous-sediment melt to the mantle source of the
 Gangdese magmatic rocks around 65 Ma, concurrent with the acceleration of
 India-Eurasia convergence. The fast increase of convergence rate
 between India and Eurasia around 65 million years ago — from ~8 cm/year to
 a peak rate of ~18 cm/year — remains a complex geological event to
 explain, given the inherent uncertainty surrounding the tectonic history
 and the intricate interplay of forces influencing plate speed. Here, we
 use a combination of geochemical analysis and geodynamic modeling to
 propose that this rapid convergence can be explained by sediment
 subduction derived from the northern Indian passive margin. Our study
 implies that the acceleration of India-Eurasia convergence marks the
 arrival of passive-margin-derived sediments, constraining the initial
 India-Eurasia collision to be around 60 Ma. It further suggests that
 temporary accelerations in subduction rates might be a common feature at
 the final stage of continental assembly.
description: # Data from: India-Eurasia convergence speed-up by passive-margin sediment
 subduction
 [https://doi.org/10.5061/dryad.8kprr4xwr](https://doi.org/10.5061/dryad.8kprr4xwr) ## Description of the data and file structure This repository provides data and visualization code of the models with an incoming plate sediment thickness of 0 km and 1 km, and pore pressure of the sediment of 0.60 and 0.99. The following conventions are used in the codes:  1. the x-axis is positive right;  2. the y-axis is positive downward;  3. pressure (the negative mean stress) is positive in compression;  4. stress is positive in extension  This dataset also provides compiled major and trace elements and Sr-Nd isotope compositions of the Late Cretaceous-Early Cenozoic magmatic rocks from the Gangdese arc. Empty cells in some columns of Excel data indicate test results without the data. For details, see the references corresponding to the data.  ### Files and variables #### File: gangdese\_model01.zip **Description:** No incoming plate sediment #### File: gangdese\_model02.zip **Description:** 1 km thickness sediment with pore pressure of 0.60 #### File: gangdese\_model03.zip **Description:** 1 km thickness sediment with pore pressure of 0.70 #### File: gangdese\_model04.zip **Description:** 1 km thickness sediment with pore pressure of 0.80 #### File: gangdese\_model05.zip **Description:** 1 km thickness sediment with pore pressure of 0.90 #### File: gangdese\_model06.zip **Description:** 1 km thickness sediment with pore pressure of 0.99 #### File: vis\_stm.m **Description:** visualization code #### File: Supplementary\_Table\_1.xlsx **Description:** Compiled major and trace elements and Sr-Nd isotope compositions of the Late Cretaceous-Early Cenozoic magmatic rocks from the Gangdese arc. Empty cells in some columns of Excel data indicate test results without the data. For details, see the references corresponding to the data. ### \*\*Structure of the output files \*\* The repository contains six main subfolders, one for each model with different sediment thickness and pore pressure:  Each subfolder contains hdf5 output files. Each hdf5 file has three main groups:  Group 1: *ModelGroup* contains two datasets and an additional group with 5 model parameters. The datasets are:  * *gx*: x-coordinates of the models (m);  * *gy*: y-coordinates of the models (m)  The additional group is named Model and contains the following parameters in the following order:  * time (year);  * model length (m);  * model depth (m);  * number of nodes in the x-direction;  * number of nodes in the y-direction  Group 2: *NodeGroup*, which contains velocity, stress, strain rate, and temperature datasets, as well as datasets of physical and rheological properties on the nodes. The datasets are:  * ro: density (kg/m^3)  * tk: temperature (K);  * pr: pressure (Pa);  * sxx: deviatoric stress tensor component *σʹxx *(Pa);  * sxy: deviatoric stress tensor component *σʹxy *(Pa);  * nu: viscosity for sxy in Stokes equation (Pa s)  * exx: deviatoric strain-rate tensor component *ϵʹxx *(s−1);  * exy: deviatoric strain-rate tensor component *ϵʹxy *(s−1);  * gg: shear modulus (Pa);  * nd: viscosity for sxx and syy in Stokes equation (Pa s)  * sbrit: yield stress (Pa)  Group 3: *VisMarkerGroup*, which contains one dataset. The dataset, named Mtype, includes the rock type number of each marker. Rock-type numbers are as follows:  * 0 is for the stick air layer  * 2 is for incoming plate sediments;  * 5 and 16 are for upper and lower continental crust, respectively;  * 7 and 8 are for upper and lower oceanic crust, respectively;  * 9 is for the lithospheric mantle;  * 10 is for the asthenospheric mantle.  ## Code/software The visualization code is written in Matlab. First, change the path to the location of the model. Then, choose the field you want to map (e.g., composition, temperature, viscosity, etc.). Finally, run the *vis_stm.m* code to start the run of the visualization. ## Update log Compared to the previous version, we have rechecked the data of the references cited for the geochemical analyses and updated Supplementary Table 1.