Tristan Salles
University of Sydney
| Subject Areas: | landscape evolution model, source-to-sink system, sedimentary systems, surface and the biosphere |
Recent Activity
ABSTRACT:
The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).
The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).
Jupyter workflows to extract information from the resources using Hydroshare THREDDS Data Service: https://github.com/Geodels/paleoPhysiography
ABSTRACT:
The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).
The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).
ABSTRACT:
The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).
The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).
ABSTRACT:
The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).
The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).
ABSTRACT:
The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).
The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).
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Created: Oct. 3, 2022, 4:56 a.m.
Authors: Tristan Salles · Laurent Husson · Manon Lorcery · Beatriz Hadler Boggiani
ABSTRACT:
The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).
The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).
Created: Oct. 5, 2022, 12:01 a.m.
Authors: Tristan Salles · Laurent Husson · Manon Lorcery · Beatriz Hadler Boggiani
ABSTRACT:
The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).
The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).
Jupyter workflows to extract information from the resources using Hydroshare THREDDS Data Service: https://github.com/Geodels/paleoPhysiography
Created: Oct. 5, 2022, 8:04 a.m.
Authors: Tristan Salles · Husson, Laurent · Manon Lorcery · Beatriz Hadler Boggiani
ABSTRACT:
The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).
The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).
Created: Oct. 6, 2022, 9:50 a.m.
Authors: Salles, Tristan · Lorcery, Manon · Laurent Husson · Beatriz Hadler Boggiani
ABSTRACT:
The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).
The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).
Created: Oct. 6, 2022, 10:27 a.m.
Authors: Salles, Tristan · Husson, Laurent · Lorcery, Manon · Beatriz Hadler Boggiani
ABSTRACT:
The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).
The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).
Created: Oct. 7, 2022, 5:19 a.m.
Authors: Salles, Tristan · Husson, Laurent · Lorcery, Manon · Halder Boggiani, Beatriz
ABSTRACT:
The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).
The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).
Created: Oct. 12, 2022, 1:02 a.m.
Authors: Salles, Tristan · Husson, Laurent · Lorcery, Manon · Halder Boggiani, Beatriz
ABSTRACT:
The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).
The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).
ABSTRACT:
The dataset contains netcdf outputs from global-scale landscape evolution model assimilating paleo-elevation and paleo-climate reconstructions over the past 541 Myr. The results are provided as global 0.05 degree resolution grids and include high resolution paleo-physiography maps, water and sediment fluxes, long-term erosion/deposition rates, and several morphometrics related to landscape dynamics (i.e., drainage basin ids, topographic position index, physiographic diversity).
The simulations are performed using goSPL model (Global Scalable Paleo Landscape Evolution - https://gospl.readthedocs.io) and rely on the paleo-elevation reconstructions from Scotese & Wright (2018) (PALEOMAP Project - https://doi.org/10.5281/zenodo.5460860) and precipitation grids from Valdes et al. (2021) (https://doi.org/10.5194/cp-17-1483-2021 | data available from the Bristol Research Initiative for the Dynamic Global Environment. Model ref: https://www.paleo.bristol.ac.uk/ummodel/scripts/html_bridge/scotese_02.html).
Jupyter workflows to extract information from the resources using Hydroshare THREDDS Data Service: https://github.com/Geodels/paleoPhysiography