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4 results for “Atmospheric diversity”

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zenodo36/100

The data for "The feasibility of asynchronous rotation via thermal tides for diverse atmospheric compositions"

<p>Supporting code and data for Salazar &amp; Wordsworth, 2024&nbsp;</p> <p><strong>Description of Jupyter Notebook files:</strong></p> <p>(Figure_X.ipynb) Contains code for recreating all figures appearing in S&amp;W, 2024 (labeled by figure number, X)</p> <p>(ExoTides_analytic.ipynb) Contains functions from the analytic model for calculating torque and rotation states as a function of orbital and atmospheric paramters</p> <p>(LMDZ_Processing.ipynb) Code for processing raw LMDZ data, including centering at the substellar point, spherical harmonic decomposition, and calculation of torque, amplitude, and lag</p> <p>(ExoTides_int.ipynb) Demonstrates solutions by integrating Equation (7) numerically (not done in paper). Also includes a comparison with the analytic model</p> <p><strong>Description of Numpy array files:</strong></p> <p>These files contain numpy arrays of the torque (im_q), amplitude (amp), lag angle (lag), and parameter values (list) for each of the GCM sensitivity tests performed in S&amp;W, 2024. These files were created using the LMDZ_Processing.ipynb file, which takes raw GCM output and outputs the torque information. Full details are available in the publication.</p> <p>The beginning of each .npy file name signifies which sensitivity test the file is (ex: taulw indicates the longwave optical depth sensitivity test). The Figure_2.ipynb file shows how these .npy files are used.&nbsp;</p> <p><strong>Descrition of .csv file:</strong></p> <p>The nasa_exoplanet.csv file contains output from the NASA Exoplanet Archive (DOI: 10.26133/NEA12) and is used in the creation of Figure 7.&nbsp;</p> <p>&nbsp;</p>

opencc-zeroAug 2024View details →
zenodo36/100

The data for "The feasibility of asynchronous rotation via thermal tides for diverse atmospheric compositions"

<p>This repo contains the processed LMD Generic model output data needed to reproduce figures in Salazar &amp; Wordsworth, 2024: "The feasibility of asynchronous rotation via thermal tides for diverse atmospheric compositions". Raw GCM data can be made available upon request.</p> <p>&nbsp;</p> <p>The processed data is saved as numpy arrays. For each sensitivity test detailed in Salazar &amp; Wordsworth, 2024, the GCM data was processed by taking surface temperature and surface pressure output and phase folding the data so that the substellar point is the origin of longitudes. Full details are available in the paper.</p>

opencc-zeroAug 2024View details →
dryad32/100

Data from: Conditional vulnerability of plant diversity to atmospheric nitrogen deposition across the United States

Open the record for dataset details and reuse information.

publicMar 2017View details →
zenodo28/100

Supplementary material 1 from: Balestrini R, Delconte C, Buffagni A, Fumagalli A, Freppaz M, Calvo E, Buzzetti I (2019) Dynamic of nitrogen and dissolved organic carbon in an alpine forested catchment: atmospheric deposition and soil solution trends. In: Mazzocchi MG, Capotondi L, Freppaz M, Lugliè A, Campanaro A (Eds) Italian Long-Term Ecological Research for understanding ecosystem diversity and functioning. Case studies from aquatic, terrestrial and transitional domains. Nature Conservation 34: 41-66. https://doi.org/10.3897/natureconservation.34.30738

: Data type: statistical data

opencc-zeroMay 2019View details →

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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.

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Last verified 2026-04-29Open record

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Last verified 2026-04-29Open record