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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Zhu, Yanxin; Sang, Yanfang; Wang, Bin; Lutz, Arthur; +3 Authors

    {"references": ["Sang, Y. F. (2012). A practical guide to discrete wavelet decomposition of hydrologic time series. Water resources management, 26(11), 3345-3365.", "Sang, Y. F., Sun, F., Singh, V. P., Xie, P., & Sun, J. (2018). A discrete wavelet spectrum approach for identifying non-monotonic trends in hydroclimate data. Hydrology and Earth System Sciences, 22(1), 757-766.", "Sang, Y. F., Sivakumar, B., & Zhu, Y. (2021). Uniform discrete wavelet spectrum for detection of hydrologic variability at multiple timescales. Journal of Hydro-environment Research, 35, 31-37.", "Takaya, K., & Nakamura, H. (2001). A formulation of a phase-independent wave-activity flux for stationary and migratory quasigeostrophic eddies on a zonally varying basic flow. Journal of the Atmospheric Sciences, 58(6), 608-627.", "Terink, W., Lutz, A. F., Simons, G. W. H., Immerzeel, W. W., & Droogers, P. (2015). SPHY v2. 0: Spatial processes in hydrology. Geoscientific Model Development, 8(7), 2009-2034."]} (1) The uniform discrete wavelet spectrum (UDWS) method can be used to identify and evaluate spatiotemporal of hydroclimatic variability. (2) The wave activity flux (WAF) can be used to measure the horizonal propagation of the quasi-stationary Rossby waves. (3) The Spatial Processes in Hydrology (SPHY) model is a fully distributed, high-resolution cryosphere-hydrological model, including all important hydro-cryospheric processes, and can operate at flexible spatial scales (sub-basin, basin, and regional).

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Software . 2023
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Software . 2023
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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      ZENODO
      Software . 2023
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Software . 2023
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Sáenz, Jon; Carreno-Madinabeitia, Sheila; González-Rojí, Santos J.; Esnaola, Ganix; +2 Authors

    SailoR is an open source R package providing an extension of the Taylor Diagram to two-dimensional vector data. Further details can be found in https://CRAN.R-project.org/package=SailoR Updates: - Version 1.2 (September 2020) All users should update their SailoR package to this new version. A bug affecting ONLY the estimations of the RMSE values has been solved. The rest of the terms in the indices and output from the UVError function were correct. - Version 1.1.2 (May 2020) A new parameter was added to SailoR.Plot() function: bias symbol type. The user can now choose the type of symbol to be used to plot the bias. The Ensembles dataset and its manual page were updated: A new model was added to it. A new example was added to SailoR.Table(). This new example shows how to generate the table in LaTeX. - Version 1.1.1 (May 2020) A new parameter was added to SailoR.plot() function: line type. The user can now choose the type of line to be used to plot the diagram. - Version 1.1 (Feb 2020) Improved visibility of the Sailor diagrams by plotting points on top of ellipses. The kind of character used depends on the type of plot produced (centered or uncentered) in order to improve visibility, too. Added new diagnostics (eccentricity of the ellipses and congruence coefficient of the leading eigenvector) to improve the interpretability of results, particularly the rotation angle of EOFs (congruence coefficient) and its sensitivity to degeneragy of eigenvalues (degeneracy would be higher with eccentricities closer to zero). A new synthetic dataset and new examples were added. The main objective of adding this synthetic dataset is to show the response of the Sailor diagram to different kinds of errors.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: LaCasce, Joseph H.; Brændshøi, Jostein;

    The software constitues a two-layer quasi-gesotrophic basin ocean model solving for the flow in each layer described through the layer streamfunctions. The model solves the full non-linear (non-linearity can be turned off) quasi-geostrophic potential vorticity equation in each layer with no-normal-flow boundary conditions. There is a bottom topography (can be specified by user) and Rayleigh friction on the lower layer relative vorticity. There is also support for upper layer forcing (e.g. wind stress). The model uses third order Adam-Bashforth time-stepping for the potential vorticity and sine transforms for inverting PV to streamfunctions. A 2-D Quadratic Upwind Interpolation for Convective Kinematics (QUICK) scheme is used for advection. The flow is solved in terms of the barotropic an baroclinic streamfunctions, but outputted as the layer streamfunctions. Model originally written by Joseph H. LaCasce in Fortran 77. Model updated to Fortran 2003 and implemented topography by Jostein Brændshøi as part of a master project supervised by LaCasce in 2017/2018. See README.txt for more details on the model. Version 1.0 is the original Fortran 77 model written by LaCasce. This upload is version 2.0 (updated to Fortran 2003 and added topography support).

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Software . 2018
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Software . 2018
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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      ZENODO
      Software . 2018
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Software . 2018
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: ANNEN Catherine;

    Code Matlab that simulates the growth and solidification of a magma body and compute temperatures, melt fractions, dissolved and exsolved volatiles.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Software . 2020
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Software . 2020
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Software . 2020
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Software . 2020
      License: CC BY
      Data sources: ZENODO
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    This repository contains two scripts to analyse drone Digital Elevation Models (DEMs) against RTK GPS Ground Control Points. The script was prepared to illustrate the results of Casella et al. (under review), that compare the performance of different drone flight altitudes and different cameras. The two required inputs are: an Excel file containing Ground Control Points (used in Agisoft Photoscan or similar software to georeference the DEM) and Control Points (indipendent RTK GPS points used as control). The excel file needs to be formatted as in the example. a folder containing the DEMs (geotiff format) derived from each drone flight. The file name will serve as label for each figure. Drone_data_extract.m - This script compares Control Points and DEM elevations, and produces a figure showing the result of the comparison for each DEM in the dataset. The script also writes the results of the DEM analysis as text, comma separated files. This script needs the Matlab 'Mapping Toolbox', 'Image Processing Toolbox' and 'Statistics and Machine Learning Toolbox' Data_analysis.m - This script takes the results of the previous step and plots them together into a summary figure. Before the final figure is produced, the user needs to insert manually the picture overlap, that is usually available in the processing reports of photogrammetric software. This script needs the Matlab 'Statistics and Machine Learning Toolbox' Version 1.0 Version released upon acceptance of the related MS. Version 1.1 Update of Ver.1.0. Added all Digital Elevation Models and Agisoft Photoscan reports. No modifications to the code.

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    ZENODO
    Software . 2019
    Data sources: Datacite
    ZENODO
    Software . 2019
    Data sources: ZENODO
    ZENODO
    Software . 2019
    Data sources: ZENODO
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      ZENODO
      Software . 2019
      Data sources: Datacite
      ZENODO
      Software . 2019
      Data sources: ZENODO
      ZENODO
      Software . 2019
      Data sources: ZENODO
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    Authors: Akhlaghi, Mohammad; Bacon, Roland; Inami, Hanae;

    Reproduction pipeline and necessary data for Sections 7.3 and 3.4 of Bacon et al., (2017) and Inami et al., (2017) respectively (papers I and II of the series of papers on "The MUSE Hubble Ultra Deep Field Survey", published in Astronomy & Astrophysics, 608, A1 and A2). This pipeline will estimate the Hubble Space Telescope (HST) segmentation maps (for paper 1) and make the necessary measurements (for paper 2) for objects that were detected in the MUSE 3D cubes, but didn't correspond to any detection in the Rafelski et al. (2015) catalog. This repository on Zenodo contains all the necessary input data, software and reproduction pipeline (containing the scripts, configuration files and settings to exactly reproduce the results in Sections 7.3 and 3.4 of the papers above). Below is a description of the contents: gnuastro-0.2.51-bc64-bugfix.tar.gz: Gnuastro version 0.2.51 with a small bug fix only relevant to this analysis. The base Gnuastro 0.2.51 was used for this pipeline when it was written, similar to zenodo.1163746. However, a bug relating to estimation of upper-limit magnitudes was later found. This bug was fixed, but along with many other changes that made the whole Gnuastro package incompatible with this pipeline. Hence, this bug-fixed copy of Gnuastro 0.2.51 was used in the catalog of Inami et al. (2017). The reproduction pipeline below contains the fixed file and instructions on how to make this version from version 0.2.51 that is available in the official Gnuastro version controlled history. The library dependencies of this version of Gnuastro can be downloaded from zenodo.1163746 (gnuastro-dependencies.tar.gz). IMPORTANT NOTE: Since version 0.2.51 of Gnuastro was released, CFITSIO (one of Gnuastro's dependencies) has added a dependency for the cURL library (to read https URLs). Therefore, to install Gnuastro 0.2.51, please install CFITSIO version 3.41 or earlier. hst-uvudf.tar.gz: images and weight maps in 0.06 arcsec/pixel resolution from the HST-UVUDF survey. These images are not necessary to run the reproduction pipeline (they will be downloaded from the HST archives if not present). They are stored here for the self-sufficiency of this repository and faster download: in this lossless compressed format, they are roughly 1/4th the volume of the same files in HST archives. hst-xdf.tar.gz: images and weight maps in 0.06 arcsec/pixel resolution from the HST-XDF survey. These are also available from the HST archives and are kept here with similar reasons to above (with a compression ratio of almost 1/3rd). output-v4-2-gf97e.tar.gz: output of the reproduction pipeline. reproduce-v4-2-gf97e.tar.gz: The reproduction pipeline (version 4-2-gf97e) that produces the results (tables) plotted in the paper. The full Git version controlled history of this repository is available on git-cral.univ-lyon1.fr or gitlab.com. We recommend cloning from the Git repository if it is available. This tarball is kept here in case those servers don't work or Git is no longer in common use. Please see the README file in this repository for instructions on how to run the reproduction pipeline and exactly reproduce the results. This pipeline will download all the necessary data if they aren't already present on the system (it is probably just necessary to install the required version of Gnuastro). The Creative Commons Attribution-NonCommercial 4.0 copyright mentioned in the Zenodo webpage is only applicable to files that don't have an explicit copyright within them. The copyright of other files (mainly scripts and software) is mentioned within them (all are free licenses). For any issues with the pipeline/processing, please contact Mohammad Akhlaghi. {"references": ["Illingworth et al. (2013), Astrophysical Journal Supplement, Volume 209, Issue 1, article id. 6", "Rafelski et al. (2015), Astronomical Journal, Volume 150, Issue 1, article id. 31"]}

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    Authors: Pease, Gailin; Keller, C. Brenhin;

    Code (plus data needed to run code) supporting the paper "A Bayesian formulation for estimating the composition of Earth’s crust" (currently in prep). Includes a script to run a minimal example. Note: data in `resources` comes from other sources. For full citation list see paper.

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    Authors: Jimenez Rodriguez, Ceasar; Coenders, Miriam; Schilperoort, Bart; Gonzalez-Angarita, A.P. (Adriana del Pilar);

    This script was used to characterize the micro-meteorological conditions when visible vapor plumes form in tropical ecosystems. The script runs in the open-source software R, and the require packages are mentioned on the script.

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    Authors: Vicent, Jorge; Sabater, Neus; Verrelst, Jochem; Rivera-Caicedo, Juan Pablo; +2 Authors

    The Atmospheric Look-up table Generator (ALG) toolbox is a standalone software package that can be used independently of ARTMO. ALG allows generating and analyzing look-up tables based on a suite of atmospheric RTMs, facilitating consistent and intuitive user interaction, thereby streamlining model setup, running and storing RTM data for any spectral configuration in the optical domain. Principally, ALG allows users to: Configure and run atmospheric RTMs in an intuitive way through a single graphical user interface with input options to insert single values or value ranges. This includes the definition of multiple combinations of key input atmospheric (e.g., aerosol-related, gas concentration profiles, clouds) and geometric (e.g., sensor height, surface height, illumination/viewing angles) variables. Couple atmospheric RTMs with the OPAC aerosol database. Set the spectral range and resolution of the output RTM data at non-contiguous spectral intervals. Run efficiently parallel executions of multiple instances of an atmospheric RTM as a third-party software. Note: ALG toolbox does not provide the compiled nor the source-code of the atmospheric RTM third-party software. Process and store a massive quantity of spectral output data based on a look-up table (LUT) approach in a relational database. Release matching the code for the GMD publication https://www.geosci-model-dev-discuss.net/gmd-2019-188 Updates on the ALG toolbox are published in www.artmotoolbox.com. Contact: Jorge Vicent (jorviser@gmail.com or artmo.toolbox@gmail.com)

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    Authors: Julie Therese Pasquier; Jan Henneberger; Fabiola Ramelli; Jörg Wieder; +5 Authors

    This repository contains the scripts to produce the figures in the paper: Pasquier, J. T., Henneberger, J., Ramelli, F., Korolev, A.,Wieder, J., Lauber, A., Li, G., David, R. O., Carlsen, T., Gierens, R., Maturilli, M., and Lohmann, U.: Understanding the history of two complex ice crystal habits deduced from a holographic imager, Geophys. Res. Lett., accepted, 2022 More information can be found in the README files. Note that the data is to be found in an accompanying package.

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    Authors: Zhu, Yanxin; Sang, Yanfang; Wang, Bin; Lutz, Arthur; +3 Authors

    {"references": ["Sang, Y. F. (2012). A practical guide to discrete wavelet decomposition of hydrologic time series. Water resources management, 26(11), 3345-3365.", "Sang, Y. F., Sun, F., Singh, V. P., Xie, P., & Sun, J. (2018). A discrete wavelet spectrum approach for identifying non-monotonic trends in hydroclimate data. Hydrology and Earth System Sciences, 22(1), 757-766.", "Sang, Y. F., Sivakumar, B., & Zhu, Y. (2021). Uniform discrete wavelet spectrum for detection of hydrologic variability at multiple timescales. Journal of Hydro-environment Research, 35, 31-37.", "Takaya, K., & Nakamura, H. (2001). A formulation of a phase-independent wave-activity flux for stationary and migratory quasigeostrophic eddies on a zonally varying basic flow. Journal of the Atmospheric Sciences, 58(6), 608-627.", "Terink, W., Lutz, A. F., Simons, G. W. H., Immerzeel, W. W., & Droogers, P. (2015). SPHY v2. 0: Spatial processes in hydrology. Geoscientific Model Development, 8(7), 2009-2034."]} (1) The uniform discrete wavelet spectrum (UDWS) method can be used to identify and evaluate spatiotemporal of hydroclimatic variability. (2) The wave activity flux (WAF) can be used to measure the horizonal propagation of the quasi-stationary Rossby waves. (3) The Spatial Processes in Hydrology (SPHY) model is a fully distributed, high-resolution cryosphere-hydrological model, including all important hydro-cryospheric processes, and can operate at flexible spatial scales (sub-basin, basin, and regional).

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    Authors: Sáenz, Jon; Carreno-Madinabeitia, Sheila; González-Rojí, Santos J.; Esnaola, Ganix; +2 Authors

    SailoR is an open source R package providing an extension of the Taylor Diagram to two-dimensional vector data. Further details can be found in https://CRAN.R-project.org/package=SailoR Updates: - Version 1.2 (September 2020) All users should update their SailoR package to this new version. A bug affecting ONLY the estimations of the RMSE values has been solved. The rest of the terms in the indices and output from the UVError function were correct. - Version 1.1.2 (May 2020) A new parameter was added to SailoR.Plot() function: bias symbol type. The user can now choose the type of symbol to be used to plot the bias. The Ensembles dataset and its manual page were updated: A new model was added to it. A new example was added to SailoR.Table(). This new example shows how to generate the table in LaTeX. - Version 1.1.1 (May 2020) A new parameter was added to SailoR.plot() function: line type. The user can now choose the type of line to be used to plot the diagram. - Version 1.1 (Feb 2020) Improved visibility of the Sailor diagrams by plotting points on top of ellipses. The kind of character used depends on the type of plot produced (centered or uncentered) in order to improve visibility, too. Added new diagnostics (eccentricity of the ellipses and congruence coefficient of the leading eigenvector) to improve the interpretability of results, particularly the rotation angle of EOFs (congruence coefficient) and its sensitivity to degeneragy of eigenvalues (degeneracy would be higher with eccentricities closer to zero). A new synthetic dataset and new examples were added. The main objective of adding this synthetic dataset is to show the response of the Sailor diagram to different kinds of errors.

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    Authors: LaCasce, Joseph H.; Brændshøi, Jostein;

    The software constitues a two-layer quasi-gesotrophic basin ocean model solving for the flow in each layer described through the layer streamfunctions. The model solves the full non-linear (non-linearity can be turned off) quasi-geostrophic potential vorticity equation in each layer with no-normal-flow boundary conditions. There is a bottom topography (can be specified by user) and Rayleigh friction on the lower layer relative vorticity. There is also support for upper layer forcing (e.g. wind stress). The model uses third order Adam-Bashforth time-stepping for the potential vorticity and sine transforms for inverting PV to streamfunctions. A 2-D Quadratic Upwind Interpolation for Convective Kinematics (QUICK) scheme is used for advection. The flow is solved in terms of the barotropic an baroclinic streamfunctions, but outputted as the layer streamfunctions. Model originally written by Joseph H. LaCasce in Fortran 77. Model updated to Fortran 2003 and implemented topography by Jostein Brændshøi as part of a master project supervised by LaCasce in 2017/2018. See README.txt for more details on the model. Version 1.0 is the original Fortran 77 model written by LaCasce. This upload is version 2.0 (updated to Fortran 2003 and added topography support).

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    Authors: ANNEN Catherine;

    Code Matlab that simulates the growth and solidification of a magma body and compute temperatures, melt fractions, dissolved and exsolved volatiles.

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    This repository contains two scripts to analyse drone Digital Elevation Models (DEMs) against RTK GPS Ground Control Points. The script was prepared to illustrate the results of Casella et al. (under review), that compare the performance of different drone flight altitudes and different cameras. The two required inputs are: an Excel file containing Ground Control Points (used in Agisoft Photoscan or similar software to georeference the DEM) and Control Points (indipendent RTK GPS points used as control). The excel file needs to be formatted as in the example. a folder containing the DEMs (geotiff format) derived from each drone flight. The file name will serve as label for each figure. Drone_data_extract.m - This script compares Control Points and DEM elevations, and produces a figure showing the result of the comparison for each DEM in the dataset. The script also writes the results of the DEM analysis as text, comma separated files. This script needs the Matlab 'Mapping Toolbox', 'Image Processing Toolbox' and 'Statistics and Machine Learning Toolbox' Data_analysis.m - This script takes the results of the previous step and plots them together into a summary figure. Before the final figure is produced, the user needs to insert manually the picture overlap, that is usually available in the processing reports of photogrammetric software. This script needs the Matlab 'Statistics and Machine Learning Toolbox' Version 1.0 Version released upon acceptance of the related MS. Version 1.1 Update of Ver.1.0. Added all Digital Elevation Models and Agisoft Photoscan reports. No modifications to the code.

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    Authors: Akhlaghi, Mohammad; Bacon, Roland; Inami, Hanae;

    Reproduction pipeline and necessary data for Sections 7.3 and 3.4 of Bacon et al., (2017) and Inami et al., (2017) respectively (papers I and II of the series of papers on "The MUSE Hubble Ultra Deep Field Survey", published in Astronomy & Astrophysics, 608, A1 and A2). This pipeline will estimate the Hubble Space Telescope (HST) segmentation maps (for paper 1) and make the necessary measurements (for paper 2) for objects that were detected in the MUSE 3D cubes, but didn't correspond to any detection in the Rafelski et al. (2015) catalog. This repository on Zenodo contains all the necessary input data, software and reproduction pipeline (containing the scripts, configuration files and settings to exactly reproduce the results in Sections 7.3 and 3.4 of the papers above). Below is a description of the contents: gnuastro-0.2.51-bc64-bugfix.tar.gz: Gnuastro version 0.2.51 with a small bug fix only relevant to this analysis. The base Gnuastro 0.2.51 was used for this pipeline when it was written, similar to zenodo.1163746. However, a bug relating to estimation of upper-limit magnitudes was later found. This bug was fixed, but along with many other changes that made the whole Gnuastro package incompatible with this pipeline. Hence, this bug-fixed copy of Gnuastro 0.2.51 was used in the catalog of Inami et al. (2017). The reproduction pipeline below contains the fixed file and instructions on how to make this version from version 0.2.51 that is available in the official Gnuastro version controlled history. The library dependencies of this version of Gnuastro can be downloaded from zenodo.1163746 (gnuastro-dependencies.tar.gz). IMPORTANT NOTE: Since version 0.2.51 of Gnuastro was released, CFITSIO (one of Gnuastro's dependencies) has added a dependency for the cURL library (to read https URLs). Therefore, to install Gnuastro 0.2.51, please install CFITSIO version 3.41 or earlier. hst-uvudf.tar.gz: images and weight maps in 0.06 arcsec/pixel resolution from the HST-UVUDF survey. These images are not necessary to run the reproduction pipeline (they will be downloaded from the HST archives if not present). They are stored here for the self-sufficiency of this repository and faster download: in this lossless compressed format, they are roughly 1/4th the volume of the same files in HST archives. hst-xdf.tar.gz: images and weight maps in 0.06 arcsec/pixel resolution from the HST-XDF survey. These are also available from the HST archives and are kept here with similar reasons to above (with a compression ratio of almost 1/3rd). output-v4-2-gf97e.tar.gz: output of the reproduction pipeline. reproduce-v4-2-gf97e.tar.gz: The reproduction pipeline (version 4-2-gf97e) that produces the results (tables) plotted in the paper. The full Git version controlled history of this repository is available on git-cral.univ-lyon1.fr or gitlab.com. We recommend cloning from the Git repository if it is available. This tarball is kept here in case those servers don't work or Git is no longer in common use. Please see the README file in this repository for instructions on how to run the reproduction pipeline and exactly reproduce the results. This pipeline will download all the necessary data if they aren't already present on the system (it is probably just necessary to install the required version of Gnuastro). The Creative Commons Attribution-NonCommercial 4.0 copyright mentioned in the Zenodo webpage is only applicable to files that don't have an explicit copyright within them. The copyright of other files (mainly scripts and software) is mentioned within them (all are free licenses). For any issues with the pipeline/processing, please contact Mohammad Akhlaghi. {"references": ["Illingworth et al. (2013), Astrophysical Journal Supplement, Volume 209, Issue 1, article id. 6", "Rafelski et al. (2015), Astronomical Journal, Volume 150, Issue 1, article id. 31"]}

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    Authors: Pease, Gailin; Keller, C. Brenhin;

    Code (plus data needed to run code) supporting the paper "A Bayesian formulation for estimating the composition of Earth’s crust" (currently in prep). Includes a script to run a minimal example. Note: data in `resources` comes from other sources. For full citation list see paper.

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    ZENODO
    Software . 2022
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      ZENODO
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    Authors: Jimenez Rodriguez, Ceasar; Coenders, Miriam; Schilperoort, Bart; Gonzalez-Angarita, A.P. (Adriana del Pilar);

    This script was used to characterize the micro-meteorological conditions when visible vapor plumes form in tropical ecosystems. The script runs in the open-source software R, and the require packages are mentioned on the script.

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    4TU.ResearchData
    Software . 2021
    License: CC 0
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      4TU.ResearchData
      Software . 2021
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    Authors: Vicent, Jorge; Sabater, Neus; Verrelst, Jochem; Rivera-Caicedo, Juan Pablo; +2 Authors

    The Atmospheric Look-up table Generator (ALG) toolbox is a standalone software package that can be used independently of ARTMO. ALG allows generating and analyzing look-up tables based on a suite of atmospheric RTMs, facilitating consistent and intuitive user interaction, thereby streamlining model setup, running and storing RTM data for any spectral configuration in the optical domain. Principally, ALG allows users to: Configure and run atmospheric RTMs in an intuitive way through a single graphical user interface with input options to insert single values or value ranges. This includes the definition of multiple combinations of key input atmospheric (e.g., aerosol-related, gas concentration profiles, clouds) and geometric (e.g., sensor height, surface height, illumination/viewing angles) variables. Couple atmospheric RTMs with the OPAC aerosol database. Set the spectral range and resolution of the output RTM data at non-contiguous spectral intervals. Run efficiently parallel executions of multiple instances of an atmospheric RTM as a third-party software. Note: ALG toolbox does not provide the compiled nor the source-code of the atmospheric RTM third-party software. Process and store a massive quantity of spectral output data based on a look-up table (LUT) approach in a relational database. Release matching the code for the GMD publication https://www.geosci-model-dev-discuss.net/gmd-2019-188 Updates on the ALG toolbox are published in www.artmotoolbox.com. Contact: Jorge Vicent (jorviser@gmail.com or artmo.toolbox@gmail.com)

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    ZENODO
    Software . 2019
    License: CC BY
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    ZENODO
    Software . 2019
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      ZENODO
      Software . 2019
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      ZENODO
      Software . 2019
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    Authors: Julie Therese Pasquier; Jan Henneberger; Fabiola Ramelli; Jörg Wieder; +5 Authors

    This repository contains the scripts to produce the figures in the paper: Pasquier, J. T., Henneberger, J., Ramelli, F., Korolev, A.,Wieder, J., Lauber, A., Li, G., David, R. O., Carlsen, T., Gierens, R., Maturilli, M., and Lohmann, U.: Understanding the history of two complex ice crystal habits deduced from a holographic imager, Geophys. Res. Lett., accepted, 2022 More information can be found in the README files. Note that the data is to be found in an accompanying package.

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