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39 results for “Geophysical Research Letters”
Simulation data for "Connection between Chorus Wave Amplitude and Background Magnetic Field Inhomogeneity: A Parametric Study" which will be submitted to Geophysical Research Letters
<p>Simulation data for "Connection between Chorus Wave Amplitude and Background Magnetic Field Inhomogeneity: A Parametric Study" which will be submitted to Geophysical Research Letters.</p> <p>Including the simulation input parameter file and the necessary output data for analysis described in the article. The output data consists of waveform data at certain locations (|MLAT| = 3 deg).</p>
Dataset to reproduce the figures in "Revisiting AMOC Transport Estimates from Observations and Models" in Geophysical Research Letters
<p>Reference level assumptions used to calculate the Atlantic meridional overturning circulation transports at the RAPID and MOVE observing arrays are revisited in an eddying ocean model. Observational transport calculation methods are complemented by several alternative approaches. At RAPID, the model transports from the observational method and the model truth (based on the actual model velocities) agree well in their mean and variability. There are substantial differences among the transport estimates obtained with various methods at the MOVE site. These differences result from relatively large and time-varying reference velocities at depth in the model, not supporting a level-of-no-motion. The methods that account for these reference velocities properly at MOVE produce transports that are in good agreement with the model truth. In contrast with the observational estimates, the model transport trends at MOVE and RAPID largely agree with each other on pentadal to multi-decadal time scales. The datasets listed here are output fields from the Meridional ovErTurning ciRculation diagnostIC (METRIC) package which enables consistent calculations of AMOC estimates at the MOVE and RAPID sections from observations and models. The METRIC package is available on GitHub at https://github.com/NCAR/metric. Citation for the code: Castruccio F. S., 2021: NCAR/metric: metric v0.1. doi/10.5281/zenodo.4708277 Citation for the method: Danabasoglu et al. (2021). Revisiting AMOC Transport Estimates from Observations and Models. Geophysical Research Letters.</p>
Data of Fig.3 in Okazaki and Katayama, 2015, Geophysical Research Letters
<p>This dataset is raw data of Figure 3 in Okazaki and Katayama, 2015, Geophysical Research Letters (doi:10.1002/ 2014GL062735). The figure shows the duration of normal/slow stick-slip events as a function of the stress drop in the log-log space. Another dataset is from same mechanical data but recalculated for futher publications.</p>
Dataset for paper "Southward shift and intensification of the intertropical convergence zone in the North Pacific across the mid-Pleistocene transition" submittted to Geophysical Research Letters
<p>Data of SST and SSS from <i>G. ruber</i> 𝛿18O and Mg/Ca of core ODP871 (5°33′N, 172°21′E, water depth 1255 m) in the central equatorial Pacific.</p>
Codes for "Summer westerly wind intensification weakens Southern Ocean seasonal cycle under global warming" - submitted to Geophysical Research Letters
<pre>This repository contains the NCAR Command Language (NCL) codes (*.ncl files) used to produce the related contents of Zhang et al. (2024). For queries about this repository and its contents, please contact me (zhangyiwen2024@gmail.com). Figure 1.ncl: For plotting main Fig.1. Figure 2.ncl: For plotting main Fig.2. Figure 3.ncl: For plotting main Fig.3. Figure 4.ncl: For plotting main Fig.4.<br>Figure 5.ncl: For plotting main Fig.5. References: Zhang et al. Summer westerly wind intensification weakens Southern Ocean seasonal cycle under global warming. Geophysical Research Letters. (2024).</pre>
The datasets for the paper "Spatial and temporal distribution of lobate scarps in the lunar south polar region: Evidence for latitudinal variation of scarp geometry, kinematics and formation ages, continuous tectonic activity in the last 100 million years and seismically safe south pole Artemis human landing site" Geophysical Research Letters.
<p>This dataset provides the original data that were used for preparing the illustrations, figures and tables.</p>
Dataset for "Multidecadal regime shifts in North Pacific subtropical mode water formation in a coupled atmosphere-ocean-sea ice model" by Kim et al., 2022 in Geophysical Research Letters
<p>Kiel Climate Model pre-industrial simulation data used in the Geophysical Research Letters publication titled “Multidecadal regime shifts in North Pacific subtropical mode water formation in a coupled atmosphere-ocean-sea ice model” by Kim et al., 2022</p>
Zonal mean of primary production and carbon export in the Southern Ocean (Huang and Fassbender, 2023, Geophysical Research Letters)
<p>This dataset contains zonal means of primary production, export potential of distinct biogenic carbon pools, particle sinking flux, and particle export efficiency in the Southern Ocean. See more details in the relevant publication of Huang and Fassbender (2023, Geophysical Research Letters).</p> <p> </p>
Model data and figure code for results and figures in the manuscript submitted to Geophysical Research Letters "Hysteresis of the Antarctic ice sheet with a coupled ice sheet climate model"
<p>This folder contains the model data and figure code for results and figures in the manuscript submitted to Geophysical Research Letters "Hysteresis of the Antarctic ice sheet with a coupled ice sheet climate model"</p> <p>The code for plotting the figures is the notebook Plot_figures.ipynb</p> <p>Fig1/simulation_output/ : Model output necessary for plotting the first figure </p> <p>The last timestep of each simulation is provided. There is one file for 1D variables (ice volume, ice volume above flotation), and one file for 2D variables (ice sheet thickness for instance).</p> <ul> <li><span>melt_insoPI_output/ : melt branch, pre-industrial insolation. Results for different CO2 levels</span></li> <li><span>growth_insoPI_output/ : growth branch, pre-industrial insolation. Results for different CO2 levels</span></li> <li><span>melt_insoMAX_output/ : melt branch, maximum insolation. Results for different CO2 levels</span></li> <li><span>growth_insoMIN_output/ : growth branch, minimum insolation. Results for different CO2 levels</span></li> </ul> <p><span>compute_SLR_equivalent.py : code to compute the ice sheet volume in SLRe based on model output</span></p> <p><span>Fig1/SLR_files/ : contains the equilibrium ice sheet volume of the different simulations according to the CO2 level</span></p> <p> </p> <p>Fig2/simulation_output/ : Model output necessary for plotting the second figure </p> <p>The last timestep of each simulation is provided. </p> <ul> <li><span>melt_insoPI_enhancedmelt_albfb/ : melt branch, pre-industrial insolation, enhanced melt and albedo feedback. Results for different CO2 levels</span></li> <li><span>growth_insoPI_enhancedmelt_albfb/ : growth branch, pre-industrial insolation, enhanced melt and albedo feedback. Results for different CO2 levels</span></li> <li><span>melt_insoPI_enhancedmelt_fixedalb/ : melt branch, pre-industrial insolation, enhanced melt, no albedo feedback. Results for different CO2 levels</span></li> <li><span>growth_insoPI_enhancedmelt_fixedalb/: growth branch, pre-industrial insolation, enhanced melt, no albedo feedback. Results for different CO2 levels</span></li> </ul> <p><span>compute_SLR_equivalent.py : code to compute the ice sheet volume in SLRe based on model output</span></p> <p><span>Fig2/SLR_files/ : contains the equilibrium ice sheet volume of the different simulations according to the CO2 level</span></p> <p> </p> <p><span>Fig3/simulation_output/ : Model output necessary for plotting the third figure </span></p> <ul> <li><span>1xCO2_nocoupling/ : simulation with pre-industrial CO2 levels and insolation and no coupling to the ice sheet model</span></li> <li><span>8xCO2_nocoupling/ : simulation with 8xpiCO2 (pre-industrial CO2) levels, pre-industrial insolation and no coupling to the ice sheet model</span></li> <li><span>8xCO2_transient_albfb/ : quasi transient simulation, 8xpiCO2 levels, pre-industrial insolation, coupling with the ice sheet model </span></li> <li><span>8xCO2_transient_fixedalb/ : quasi transient simulation, 8xpiCO2 levels, pre-industrial insolation, coupling with the ice sheet model excluding the albedo-melt feedback</span></li> </ul> <p> </p>
Supplementary tables for Geophysical Research Letters_2022GL101947
<p>Data associated with the publication " Evolutionary stasis during the Mesoproterozoic Columbia-Rodinia supercontinent transition"</p>
Datasets, scripts and Jupyter Notebook for "Two distinct magma storage regions at Ambrym volcano detected by satellite geodesy", Geophysical Research Letters
<p>This repository includes scripts and files necessary to create Figure 1 (<strong>S1.zip </strong>and <strong>plot_TS_Ambrym_2019_2022.py</strong>) in "Two distinct magma storage regions at Ambrym volcano detected by satellite geodesy", <em>Geophysical Research Letters</em>. We also include the Jupyter Notebook used to run the EnKF data assimilation (<strong>enkf_notebook.zip) </strong>and produce Figures 2 and 3. The Jupyter Notebook and files used to produce Figure 4b,c can be found on <a href="http://github.com/tshreve/jupyterNBs/">GitHub</a>.</p> <p>This version corrects a bug in the code used to plot the cross-sections in Figure 3 with <strong>enkf_notebook.zip</strong>.</p>
Dataset for paper "Equatorial Pacific sea-air CO2 exchange modulated by upper ocean circulation during the last deglaciation" submittted to Geophysical Research Letters
<p>Data of the <em>p</em>CO<sub>2</sub> and ∆<em>p</em>CO<sub>2_sw-atm</sub> from <em>G. ruber</em> 𝛿<sup>11</sup>B, 𝛿<sup>11</sup>B of <em>G. sacculifer</em>, 𝛿<sup>18</sup>O of <em>G. ruber</em> and <em>P. obliquiloculata</em>, ∆𝛿<sup>18</sup>O<sub>P-G</sub>, bulk 𝛿<sup>15</sup>N in core MD10-3340 (0º31.0’S, 128º43.5’E, water depth 1094 m), and upper Ocean Heat Content (OHC) in the Western Equatorial Pacific (WEP).</p>
Supplementary dataset for Bastin et al. (2020), Geophysical Research Letters
<p>Supplementary dataset for:</p> <p>Bastin, S., M. Claus, P. Brandt, and R. J. Greatbatch, 2020: Equatorial deep jets and their influence on the mean equatorial circulation in an idealized ocean model forced by intraseasonal momentum flux convergence. <em>Geophysical Research Letters</em>, <strong>47</strong>, doi: 10.1029/2020GL087808</p>
Part of the dataset and trained models in "A Physics-Enhanced Neural Network for Estimating Longitudinal Dispersion Coefficient and Average Solute Transport Velocity in Porous Media" by Meng et al. in Geophysical Research Letters
<p><strong>This repository is created to contain part of the data, codes and trained models in the research project titled "A Physics-Enhanced Neural Network for Estimating Longitudinal Dispersion Coefficient and Average Solute Transport Velocity in Porous Media".</strong></p> <p> </p>
Supplementary text and data for Cao et al. reviewed in Geophysical Research Letters
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All data of the manuscript "A self-sustained charge neutrality intracloud lightning parameterization containing channel decay and reactivation" submitted to Geophysical Research Letters
<p>The data support the manuscript entitled "A self-sustained charge neutrality intracloud lightning parameterization containing channel decay and reactivation". Microsoft Notepad can open the *.txt files, they contain the channel information of two intracloud flashes (IC1 and IC2) and the channel elctrical parameters at the first fork of positive or negative leader channels. A normal video player software can open Movie_S1.avi, and it shows the entire development process of IC1 discharge.</p> <p>The data can be used freely for scientific purposes with the appropriate citation.</p>
Dataset used in "Estimating Dispersion Coefficient in Flow Through Heterogeneous Porous Media by a Deep Convolutional Neural Network" by Kamrava et al. in Geophysical Research Letters.
<p>Morphology of Heterogeneous Porous Media</p>
Data in support "Turbidity hysteresis in an estuary and tidal river following an extreme discharge event", manuscript submitted to Geophysical Research Letters,
<p>Data set in support of manuscript "Turbidity hysteresis in an estuary and tidal river following an extreme discharge event" submitted to Geophysical Research Letters. Submitted March 2020, revised and resubmitted April 2020. Matlab script (makeFigs_hysteresis_upload.m) is used to generate the figures from the manuscript. Data files (*.mat) correspond with each figure (*.png). For questions or additional information please contact D. Ralston. </p>
Data for "The role of cloud in the transportation of dust into basin area: a case study in Sichuan Basin, southwesten China" submitted to Geophysical Research Letters
<p>Data for "The role of cloud in the transportation of dust into basin area: a case study in Sichuan Basin, southwesten China" submitted to Geophysical Research Letters.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.