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This dataset contains the output files of numerical simulations of the model GEOCLIM-DynSoil-steady-state, that were conducted for the study "The rise of New Guinea and the fall of Neogene global temperatures". Those outputs are modeled fields of erosion rate, silicate weathering flux, regolith thickness and primary phases depletion, on the island of New Guinea, at 30 minutes resolution, and for 19 time slices from 15 Ma to present-day. This dataset also contains additional Python scripts for generating inputs of the model (namely, slope field) and for projecting the 2D New Guinea erosion field on the 1D transect highlighted in the above-mentioned study. files description The 19 files "gdss_output_NG_slope_X.X-X.X.nc" are output files from the model GEOCLIM-DynSoil-steady-state. "X.X-X.X" indicates the time slice targeted by the simulation (e.g., "14.4-13.2" is "14.4 Ma -- 13.2 Ma). Metadata in each file (netCDF format) describes the fields computed by the model and outputted in the files. Instruction to reproduce those outputs are given in the corresponding branch of the model's Github repository (https://doi.org/10.5281/zenodo.8245945) "Total_erosion.csv" is a 3-column table indicating, for each time interval targeted by the modeling study, the beginning and ending of the time interval, and the total eroded material during that interval, as computed by the model MOVE2D, on the New Guinea 1D transect (see "Transect_locations" files) Because the transect is 1D, the "total eroded material" during a time interval is a 2D value, and its units is km^2. "make_slope_inputs.py" is the Python script that generates the slope field for each time interval, accordingly to the erosion rate during that interval. It uses, as input, a modern (0.5-0Ma) slope field, that can be found in the model's Github repository https://doi.org/10.5281/zenodo.8245945. "erosion_projection.py": script to project the erosion field computed by GEOCLIM-DynSoil-steady-state on the 1D transect, and generate the 2 figures (already present in the current repertory): "erosion_transect_map.png": map the New Guinea erosion with the transect location. "transect_erosion.pdf": plot of the erosion rate along the transect. "geoclim.py": Python script storing the erosion function taken from the GEOCLIM model. This function may be used by "erosion_projection.py", as an alternative way to recompute erosion "from scratch". "Transect_location.*": shapefile indicating the location of 1D New Guinea transect (line).
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Data from: The role of Southeast Asian island topography on Indo-Pacific climate and silicate weathering
The modern configuration of the South East Asian Islands (SEAI) evolved over the last fifteen million years, as a result of subduction, arc magmatism, and arc-continent collisions, contributing to both increased land area and high topography. The presence of the additional land area has been postulated to enhance convective rainfall, facilitating both increased silicate weathering and the development of the modern-day Walker circulation. Using an Earth System Model in conjunction with a climate-silicate weathering model, we argue instead for a significant role of SEAI topography for both effects. This dataset archives model output used in this investigation, including simulations using the Community Earth System Model version 1.2, and the climate-silicate weathering model GEOCLIM. All data are in Netcdf format, and were generated either by the Community Earth System Model 1.2 (Hurrell et al. 2013) or the climate-silicate weathering model GEOCLIM (Park et al. 2020). Model output is organized into 4 tar files: 1) B1850C5.tar Contains model output for the fully coupled CESM1.2 runs, for 2D fields and for 3D pressure vertical velocity (W) between 10S-10N. Monthly mean data for years 41-110 of the simulations. Naming convention is No SEAI topography: B1850C5_noSEAItopo_y41-110.nc and B1850C5_noSEAItopo_W_y41-110.nc 50% SEAI topography: B1850C5_0.5SEAItopo_y41-110.nc and B1850C5_0.5SEAItopo_W_y41-110.nc 100% SEAI topography: B1850C5_y41-110.nc and B1850C5_W_y41-110.nc 150% SEAO topogaphy: B1850C5_1.5SEAItopo_y41-110.nc and B1850C5_1.5SEAItopo_W_y41-110.nc 2) E1850C5.tar Contains model output for the slab ocean CESM1.2 runs, for 2D fields and for 3D pressure vertical velocity (W) between 10S-10N. Monthly mean data for years 21-50 of the simulations. Naming convention is No SEAI topography: E1850C5_noSEAItopo_y21-50.nc and E1850C5_noSEAItopo_W_y21-50.nc 50% SEAI topography: E1850C5_0.5SEAItopo_y21-50.nc and E1850C5_0.5SEAItopo_W_y21-50.nc 100% SEAI topography: E1850C5_y21-50.nc and E1850C5_W_y21-50.nc 150% SEAO topogaphy: E1850C5_1.5SEAItopo_y21-50.nc and E1850C5_1.5SEAItopo_W_y21-50.nc 3) GEOCLIM.tar Contains model output from the climate-silicate weathering model GEOCLIM. Data is provided for all 573 parameter combinations. All values are climatological annual means. All files contain these variables: GMST: global mean surface temperature (in K) atm_CO2_level: atmospheric pCO2 (in ppm) degassing: globally-integrated CO2 flux (in mol/yr) The files ending with 1xCO2.nc also contain these spatial fields: lithology fraction: fraction of land covered by a lithology class erosion: Regolith erosion rate (m/yr) weathering: Ca-Mg weathering rate (mol/m^2/yr) E1850C5_1xCO2.nc - GEOCLIM output using the Modern SEAI simulation as input, and for CO2 fixed to 286.7ppm. E1850C5_noSEAI_1xCO2.nc - GEOCLIM output using the no SEAI simulation as input, and for CO2 fixed to 286.7ppm. E1850C5_noSEAItopo_1xCO2.nc - GEOCLIM output using the flat SEAI simulation as input, and for CO2 fixed to 286.7ppm. E1850C5_noSEAI_equil.nc - GEOCLIM output using the no SEAI simulation as input, and CO2 adjusted so that system is in carbon flux equilibrium. E1850C5_noSEAItopo_flatSEAIslope_equil.nc - GEOCLIM output using the flat SEAI simulation as input, and CO2 adjusted so that system is in carbon flux equilibrium. 4) Surface.tar Contains land fraction and surface geopotential fields for the modern SEAI (Landfrac.nc) and no SEAI (Landfrac_noSEAI.nc) simulations References Hurrell, J.W., Holland, M.M., Gent, P.R., Ghan, S., Kay, J.E., Kushner, P.J., Lamarque, J.F., Large, W.G., Lawrence, D., Lindsay, K. and Lipscomb, W.H., 2013. The community earth system model: a framework for collaborative research. Bulletin of the American Meteorological Society, 94(9), pp.1339-1360. Park, Y., Maffre, P., Goddéris, Y., Macdonald, F.A., Anttila, E.S. and Swanson-Hysell, N.L., 2020. Emergence of the Southeast Asian islands as a driver for Neogene cooling. Proceedings of the National Academy of Sciences, 117(41), pp.25319-25326.
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- Award ID(s):
- 1925990
- PAR ID:
- 10431447
- Publisher / Repository:
- Dryad
- Date Published:
- Edition / Version:
- 5
- Subject(s) / Keyword(s):
- FOS: Earth and related environmental sciences
- Format(s):
- Medium: X Size: 22163909902 bytes
- Size(s):
- 22163909902 bytes
- Sponsoring Org:
- National Science Foundation
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GEOCLIM model as it was used for the experiments presented in Maffre, P., Swanson-Hysell, N.L., and Godd\'eris, Y. (2021), Limited carbon cycle response to increased sulfide weathering due to oxygen feedback, ]Geophysical Research Letters, doi:10.1029/2021GL094589. GEOCLIM is cluster of models, more or less adaptable, computing geochemical cycles of several species (C, O...) at geological timescale. The core of the model is an ocean-atmosphere chemistry model (advection-reaction) COMBINE. Ocean an atmosphere are discretized in 10 reservoirs (boxes). This core is closely associated to an early diagenesis module computing the "output" fluxes (burial of elements in marine sediments) for each box. It is also associated to an continental weathering module computing the "input" fluxes. This weathering module is spatially-resolved (using a geographic mesh grid), its resolution is adaptable, and several options exist for the silicate weathering part. This triplet is indirectly coupled to a climate model (GCM). Climate simulations must be run before using GEOCLIM, for a range of CO2 levels. Any climate model can be used, as long as it computes surface air temperature and continental runoff. Oceanic temperature from the climate model can be used, or parameterized if not available. Climate fields are then interpolated on the "CO2 dimension", at the current atmospheric CO2 computed by GEOCLIM, and used to compute continental weathering, and oceanic boxes temperature. The resolution (ie, the spatial grid) of the continental weathering module must be the same than the GCM. How to run the model: After downloading the present repository, type ./make_test testname (testname being one of "ERA5", "GFDL", "CESM", "paleo" and "ascii"). This command will compile and execute a short GEOCLIM run and compare the output to a reference template. This allows to verify that the compilation and execution of the model are performed without error, and yield the same results than reference runs. If not, the command should tell what type of error was encountered (see also section Frequent issues at the end of this file). You could try the 5 tests to make sure everything works as excepted. If the tests are conclusive, follow those step to create your run: Compile the code with build_GEOCLIM (specifying the model set of components and resolution). Try ./build_GEOCLIM --help for more information. This command create an executable file in 'executable/' Configure the run by editing the files 'config/IO_CONDITIONS' and 'config/cond_p20.dat' (name of the run, initial condition, forcing fields, solver parameters...). This post-compilation configuration must be consistent with the specified set of components and resolution. Run the model with executable/exec_name (name of the executable created at the compilation step). Alternatively, and if you are running the model on a cluster, you can use the files in 'job/' to submit the run as a batch process. 'job/submit_chain.sh' is a script designed for submitting a series of runs, each new one starting from the end of the previous one. See also section Multiple runs and job submission in Run GEOCLIM.more » « less
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This dataset stores the data of the article The effect of Pliocene regional climate changes on silicate weathering: a potential amplifier of Pliocene-Pleistocene cooling P. Maffre, J. Chiang & N. Swanson-Hysell, Climate of the Past). This study uses a climate model (GCM) to reproduce an estimate of Pliocene Sea Surface Temperature (SST). The main GCM outputs of this modeling (with a slab ocean model) are stored in "GCM_outputs_for_GEOCLIM/", as well as the climatologies from ERA5 reanalysis. The other GCM outputs that were used in intermediary steps (coupled ocean-atmosphere, and fixed SST simulations) are stored in "other_GCM_outputs/". The forcing files (Q-flux) and other boundary conditions to run the "main" GCM simulations can be found in "other_GCM_outputs/Q-flux_derivation/", as well as the scripts used to generate them. Secondly, the mentioned study uses the GCM outputs in "GCM_outputs_for_GEOCLIM/" as inputs for the silicate weathering model GEOCLIM-DynSoil-Steady-State (https://github.com/piermafrost/GEOCLIM-dynsoil-steady-state/tree/PEN), to investigate weathering and equilibrium CO2 changes due to Pliocene SST conditions. The results of these simulations are stored in "GEOCLIM-DynSoil-Steady-State_outputs/". The purpose of this dataset is to provide the raw outputs used to draw the conclusions of Maffre et al. (2023), and to allow the experiments to be reproduced, by providing the scripts to generate the boundary conditions.more » « less
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Abstract The geography of the Southeast Asian Islands (SEAI) has changed over the last 15 million years, as a result of tectonic processes contributing to both increased land area and high topography. The presence of the additional land area has been postulated to enhance convective rainfall, facilitating both increased silicate weathering and the development of the modern‐day Walker circulation. Using an Earth System Model in conjunction with a climate‐silicate weathering model, we argue instead for a significant role of SEAItopographyfor both effects. SEAI topography increases orographic rainfall over land, through intercepting moist Asian‐Australian monsoon winds and enhancing land‐sea breezes. Large‐scale atmospheric uplift over the SEAI region increases by ∼14% as a consequence of increased rainfall over the SEAI and enhancement through dynamical ocean‐atmosphere feedback. The atmospheric zonal overturning circulation over the Indo‐Pacific increases modestly arising from dynamical ocean‐atmosphere feedback, more strongly over the tropical Indian Ocean. On the other hand, the effect of the SEAI topography on global silicate weathering is substantial, resulting in a ∼109 ppm reduction in equilibriumpCO2and decrease in global mean temperature by ∼1.7ºC. The chemical weathering increase comes from both enhanced physical erosion rates and increased rainfall due to the presence of SEAI topography. The lowering ofpCO2by SEAI topography also enhances the Indo‐Pacific atmospheric zonal overturning circulation. Our results support a significant role for the progressive emergence of SEAI topography in global cooling over the last several million years.more » « less
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