Here we present data on vegetation and climate conditions in Syria, including some nc files. The nc files describe the spatial status of Syria, including land cover in 2010, trends in temperature and precipitation, EVI mean and trend, EVI residual analysis and water use efficiency. Detailed information can be found in the paper by Chen et al.

tootsea (toolbox for time series exploration and analysis) is a matlab solftware, developped at lops (laboratoire d'océanographie physique et spatiale), ifremer. this tool is dedicated to analysing datasets from moored oceanographic instruments (currentmeter, ctd, thermistance, ...). tootsea allows the user to explore the data and metadata from various instruments file, to analyse them with multiple plots and stats available, to do some processing/corrections and qualify (automatically and manually) the data, and finally to export the work in a netcdf file.

Function name "cdf2mat" Please use this function to open MS-based chromatographic data from NETCDF (*.CDF) files. Resampling included for non-integer acquisition rates. Outputs nominal mass. Script optimized to process data from comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GCxGC-MS). Updated to remove negative noise signal. INPUT file: Opens the netCDF like 'Sample01.CDF' rate_MS: Desired integer acquisition rate OUTPUT FullMS Full MS chromatogram (second order data tensor) axis_min Retention time axis in minutes axis_mz m/z axis in Daltons I/O: [TIC,FullMS,axis_min,axis_mz] = cdf2mat(file,rate_MS) Compiled with MATLAB R2021b (v.9.11.0.1809720). Requires the Signal Processing Toolbox (v.9.0). Based on netCDFload.m (Murphy, Wenig, Parcsi, Skov e Stuetz) e de iCDF_load (Skov e Bro 2008). K.R. Murphy, P. Wenig, G. Parcsi, T. Skov, R.M. Stuetz (in press) Characterizing odorous emissions using new software for identifying peaks in chemometric models of GC-MS datasets. Chem Intel Lab Sys. doi: 10.1016/j.chemolab.2012.07.006 Skov T and Bro R. (2008) Solving fundamental problems in chromatographic analysis, Analytical and Bioanalytical Chemistry, 390 (1): 281-285. doi: 10.1007/s00216-007-1618-z

the ego data processing chain decodes, processes, formats and performs quality control on glider data and metadata. the decoder performs the following actions for a glider deployment: decode and format the glider deployment data and metadata into an ego netcdf time series file apply real time quality control (rtqc) tests on ego netcdf time series file, for slocum gliders, estimate subsurface currents and store them into the ego file, generate netcdf profile files from ego file data and apply specific rtqc tests to them.the decoder manages slocum, seaglider and seaexplorer gliders observations. it is a matlab code (see groom_gliders_coriolis_matlab_decoder_*.pdf in decglider_doc\decoder_user_manual folder) a compiled version is available that does not require matlab licence (see readme.txt in decglider_soft\soft_compiled folder)

No description is available. Visit https://dataone.org/datasets/e29e0aa8601592a6c952df84a92b45ff for complete metadata about this dataset.

Netcdf data and Matlab processing scripts for the article:

Eabry, Holmes and Sen Gupta (2022): The impact of Indonesian Throughflow constrictions on eastern Pacific upwelling and water-mass transformation. Journal of Geophysical Research: Oceans. https://doi.org/10.1029/2022JC018509

Included are netcdf files with output from the ACCESS-OM2 1-degree ocean model averaged over years 500-600 of the spin-up simulation. CONTROL indicates the control simulation (realistic ITF topography), OPENITF indicates the Open ITF experiment and DIFF indicates difference files between the two. Please refer to the meta-data within the netcdf files for more information. Scripts to help with plotting standard variables are part of the COSIMA cookbook repository at https://github.com/COSIMA/cosima-recipes.

An example script Control_WMT_budget.m is provided to plot the control WMT budget and can be easily modified to plot the Open ITF or anomalous WMT budget. This script uses the Pacific masks found in mask.mat. The small tendency term is provided separately as dV_dt_nrho.mat.

The neutral density code comes as a package of MATLAB and/or FORTRAN routines which enable the user to fit neutral density surfaces to arbitrary hydrographic data. The FORTRAN implementation consists of a FORTRAN subroutine which labels a cast of hydrographic data with neutral density, and another subroutine which then finds the positions of specified neutral density surfaces within the water column. The MATLAB implementation consists of two MATLAB functions performing these same operations, only on sections of hydrographic data. Versions are available for Unix workstations running with the NETCDF data archiving library and PC's not running NETCDF. This latter code is suitable for compilation on Unix workstations or other machines not running the NETCDF library. The MATLAB version for the PC does not require compilation of the underlying FORTRAN code, unlike the UNIX version of the code. All code comes with documentation in the form of Readme files, as well as Makefiles and examples to provide check values for the user. This "in-house" CSIRO software is available under conditions which are attached with the software.

This dataset is associated with a manuscript on river plumes and idealized coastal corners with first author Michael M. Whitney. The dataset includes source code, compilation files, and routines to generate input files for the Regional Ocean Modeling System (ROMS) runs used in this study. ROMS output files in NetCDF format are generated by executing the compiled ROMS code with the input files. The dataset also includes MATLAB routines and datafiles for the analysis of model results and generation of figures in the manuscript. The following zip files are included:

ROMS_v783_Yan_code.zip [ROMS source code branch used in this study] coastalcorner_ROMS_compilation.zip [files to compile ROMS source code and run-specific Fortran-90 built code] coastalcorner_ROMS_input_generate_MATLAB.zip [ROMS ASCII input file and MATLAB routines to generate ROMS NetCDF input files for runs] coastalcorner_MATLAB_output_analysis.zip [MATLAB data files with selected ROMS output fields and custom analysis routines and datafiles in MATLAB formats used in this study] coastalcorner_MATLAB_figures.zip [custom MATLAB routine for manuscript figure generation and MATLAB data files with all data fields included in figures] coastalcorner_tif_figures.zip [TIF image files of each figure in manuscript]

This dataset is associated with a manuscript on Connecticut River plume mixing with first author Michael M. Whitney. The dataset includes source code, compilation files, and input for the Regional Ocean Modeling System (ROMS) runs used in this study. ROMS output files in NetCDF format are generated by executing the compiled ROMS code with the input files. The dataset also includes MATLAB routines and datafiles for the analysis of model results and generation of figures in the manuscript. The following zip files are included:

ROMS_v783_Yan_code.zip [ROMS source code branch used in this study] ctplume_ROMS_compilation.zip [files to compile ROMS source code and run-specific Fortran-90 built code] ctplume_ROMS_input.zip [ROMS ASCII and NetCDF input files for runs] ctplume_MATLAB_analysis.zip [custom analysis routines in MATLAB used in this study] ctplume_MATLAB_figures.zip [custom MATLAB routine for manuscript figure generation and MATLAB data files with all data fields included in figures] ctplume_figures_tif.zip [TIF image files of each figure in manuscript]

We estimated the seafloor topography beneath the Amery Ice Shelf, East Antarctica, from airborne gravity anomaly through a nonlinear inversion method called simulated annealing. The estimation results provide a view of the seafloor beneath the Amery Ice Shelf, where direct bathymetric observations are rare. The model, 'gravity_estimated_seafloor_topography_beneath_the_Amery_Ice_Shelf.nc', is in NetCDF format which can be read through MATLAB commands "ncdisp" and "ncread". Contents of the model can be found in "contents.txt". The MATLAB program "nc2mat.m" reads the NetCDF ".nc" format model and saves the variables in the model to a MATLAB ".mat" format file.

(I) DESCRIPTION:

· A global daily seamless 9-km Vegetation Optical Depth (VOD) product is generated through gap-filling and spatiotemporal fusion model. This daily products start from Jan 01, 2010 to Jul 31, 2021 (about 20GB memory after uncompressing all zip files).

· To further validate the effectiveness of these products, three verification ways are employed as follow: 1) Time series validation; 2) Simulated missing-region validation; And 3) Data comparison validation.

· It is important to note that the original data contain missing dates, and these corresponding gaps are also present in our dataset.

(II) DATA FORMATTING AND FILE NAMES

For the convenience of our readers, we have two formats of data available for download.

1) MAT file (Version v1)

Data from 2010 to 2021 are stored separately into folders for the corresponding years, with each folder containing daily .mat files. The naming convention for the data is “YYYYXXZZ,” where YYYY is the 4-digit year, XX is the 2-digit month, and ZZ is the 2-digit date. The geographic scope is global and the grid size is 4000*2000.

MATFILES (.mat): The folders with matfiles contain individual files for:

1. Vegetation Optical Depth: VOD_seamless_9km_ YYYYXXZZ.mat

2. Latitude/Longitude: VOD_9km_Coordinates.mat

2) NetCDF file (Version v2)

The year-by-year daily data from 2010 to 2021 are stored in the ‘.nc’ files for the corresponding years. The daily data within each year into one NetCDF file. The variable names are named as VOD_xxxxyydd, where xxxx represents the year, yy represents the month, and dd represents the day. The longitude variable is named “lon” with a dimension of 4000×1, and the latitude variable is named “lat” with a dimension of 2000×1.

It should be noted that these NetCDF files are saved using the netCDF4 library in Python, with the dimension order being (lat, lon). When reading these NetCDF files in MATLAB, the default data dimension order is (lon, lat). Therefore, it is necessary to transpose the variables to match the correct dimension order.

The netCDF file included here corresponds to datasets used in the Biogeosciences paper entitled "Evaluating the Arabian Sea as a regional source of atmospheric CO2: seasonal variability and drivers" by Alain de Verneil, Zouhair Lachkar, Shafer Smith, and Marina Levy The data included here comprises of model output used in the paper to generate figures in the main manuscript. Many of the figures also contain data from publicly available sources, which is detailed in the "Data availability" section at the end of the paper. The data are in standard netCDF file format, readily readable using netCDF tools (i.e. netCDF4 package in Python, ncread function in Matlab, etc.). Variables names, dimensions, and units are described in the metadata within the netCDF file. Questions regarding this dataset and how it can be used to reproduce the results in the article can be forwarded to Alain de Verneil through email at ajd11@nyu.edu

Abstract: The bathymetry was mapped with a Simrad EM122 multibeam system (1° x 2° system, 12 kHz swath mapping) in Nov/Dec 2019, and processed for quality control through QIMERA software while onboard the vessel. In addition to tracks between ocean bottom seismometer drop sites associated with the Old ORCA experiment (a US contribution to the PacificArray initiative), this data set contains multibeam swath passes within the field region, and on transits to/from Tahiti, and to/from a rescue at ~30S,153W. Sippican MK-21/PC-based XBT measurements were conducted at least daily to account for varying sound speed throughout the experiment, and processed through Simrad SIS software. The final bathymetric maps and grids were created using MATLAB and GMT. The data files are in GMT-compatible netCDF grid format suitable for import to GMT scripts. The km1922_all.grd file contains bathymetry for the entire cruise mapped at 50 m resolution, and the obs_array.grd file contains bathymetry for just the OBS array region, at 100 m resolution. The data files were generated as part of a project called Imaging small-scale convection and structure of the mantle in the south Pacific: a US contribution to international collaboration PacificArray, and Seismological Components of the MELT Experiment on the Southern East Pacific Rise. Funding was provided by NSF awards OCE16-58491, OCE16-58214 and OCE94-02375.

CO2_netCDF.zip includes 3 files, readme_nc.txt is the descrition file of the rest 2 files. The format of data file is .nc, and demension description of the netCDF file is .xlsx. CO2_mat.zip includes 5 files, readme_mat.txt is the descrition file of the rest 4 data files. The format of data files is .mat, which could be load using matlab.

description: This is a 12-hr time series of CTD profiles of water temperature and salinity taken from near-shore well in Puerto Morelos from 2014-03-27 to 2014-03-28. Data were provided in Matlab (MAT) format and converted by NCEI to netcdf format.; abstract: This is a 12-hr time series of CTD profiles of water temperature and salinity taken from near-shore well in Puerto Morelos from 2014-03-27 to 2014-03-28. Data were provided in Matlab (MAT) format and converted by NCEI to netcdf format.

The data are stored as compressed netCDF4 files (compression level 1).

Profile data from WireWalker deployments at Mission Beach, California in 2016 at a 50m depth.

The default data format served through the BCO-DMO data system is tabular. These data are available to download as matrices in NetCDF (.nc) and Matlab (.mat) files in the "Data Files" section of this page.

Related Datasets (Jun 2016, Mission Beach, CA)

* Thermistor chain https://www.bco-dmo.org/dataset/742137
* ADCP https://www.bco-dmo.org/dataset/742132

The modeled data in these archives are in the NetCDF format (https://www.unidata.ucar.edu/software/netcdf/). NetCDF (Network Common Data Form) is a set of software libraries and machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. It is also a community standard for sharing scientific data. The Unidata Program Center supports and maintains netCDF programming interfaces for C, C++, Java, and Fortran. Programming interfaces are also available for Python, IDL, MATLAB, R, Ruby, and Perl. Data in netCDF format is: • Self-Describing. A netCDF file includes information about the data it contains. • Portable. A netCDF file can be accessed by computers with different ways of storing integers, characters, and floating-point numbers. • Scalable. Small subsets of large datasets in various formats may be accessed efficiently through netCDF interfaces, even from remote servers. • Appendable. Data may be appended to a properly structured netCDF file without copying the dataset or redefining its structure. • Sharable. One writer and multiple readers may simultaneously access the same netCDF file. • Archivable. Access to all earlier forms of netCDF data will be supported by current and future versions of the software. Pub_figures.tar.zip Contains the NCL scripts for figures 1-5 and Chesapeake Bay Airshed shapefile. The directory structure of the archive is ./Pub_figures/Fig#_data. Where # is the figure number from 1-5. EMISS.data.tar.zip This archive contains two NetCDF files that contain the emission totals for 2011ec and 2040ei emission inventories. The name of the files contain the year of the inventory and the file header contains a description of each variable and the variable units. EPIC.data.tar.zip contains the monthly mean EPIC data in NetCDF format for ammonium fertilizer application (files with ANH3 in the name) and soil ammonium concentration (files with NH3 in the name) for historical (Hist directory) and future (RCP-4.5 directory) simulations. WRF.data.tar.zip contains mean monthly and seasonal data from the 36km downscaled WRF simulations in the NetCDF format for the historical (Hist directory) and future (RCP-4.5 directory) simulations. CMAQ.data.tar.zip contains the mean monthly and seasonal data in NetCDF format from the 36km CMAQ simulations for the historical (Hist directory), future (RCP-4.5 directory) and future with historical emissions (RCP-4.5-hist-emiss directory).

This dataset is associated with the following publication: Campbell, P., J. Bash, C. Nolte, T. Spero, E. Cooter, K. Hinson, and L. Linker. Projections of Atmospheric Nitrogen Deposition to the Chesapeake Bay Watershed. Journal of Geophysical Research - Biogeosciences. American Geophysical Union, Washington, DC, USA, 12(11): 3307-3326, (2019).

Water column acoustic data collected in the Scotia Sea (from 2012-11-15 to 2012-12-11) during cruise JR280. Multi-frequency (38,120 and 200 kHz) acoustic data were collected using a Simrad EK60 echo sounder. The dataset comprises of calibrated and processed 38 kHz volume backscattering strength (Sv, dB re 1m-1). Data processing was undertaken using Echoview and Matlab. Processed netCDF data files are made available as part of the NERC Southern Ocean Network of Acoustics (SONA) and the EU MESOPP project.

Sea surface temperature data analyzed in Johnson et al. (2019). The data are provided as .mat files (produced from the original NetCDF files through Matlab scripts provided in another file). The original NetCDF data are freely available on the web: https://www.ncdc.noaa.gov/data-access/marineocean-data/extended-reconstructed-sea-surface-temperature-ersst-v5https://www.metoffice.gov.uk/hadobs/hadisst/