Github Netcdf4

NetCDF (Network Common Data Form) is a set of interfaces for array-oriented data access and a freely distributed collection of data access libraries for C, Fortran, C++, Java, and other languages. A Pipeline for Analysis of NetCDF data in Google Earth Engine. What is the FlomKart package? This package is a set a functions developed with the FlomKart flood frequency analysis project at NVE. Sort by Similarity instead of Alphabetically. Begin by setting the following environment variables. NETCDF4_CLASSIC: Data is stored in an HDF5 file, using only netCDF 3 compatible API features. Reading in NetCDF data in R and exporting as a geotiff This definitely passes my “post things that took more than half an hour to work out” as I know Aaron O’Leary was originally basing his posts on. nc文件中的水位elevation(shape:time*node)全部加上0. io/ Sat, 05 Aug 2017 02:56:45 +0000 Sat, 05 Aug 2017 02:56:45 +0000 Jekyll v3. NETCDF4: Data is stored in an HDF5 file, using netCDF4 API features. The HDF4 CF (H4CF) Conversion Toolkit can access various NASA HDF4 and HDF-EOS2 files by following the CF conventions. GitHub is home to over 36 million developers working together to host and review code, manage projects, and build software together. We evaluated use cases representative of analyses commonly performed by atmospheric and oceanic scientists such as. In the previous post , I presented a very simple application of R-Bridge where I built a toolbox to perform k-means clustering on point shapefiles. sample the base run, there. One of those, that is mature and available in the Python Package Index is netcdf4-python. Maintainer: [email protected] io If you are looking for a reference to use in a published paper, please cite our SC2003 paper below. Bottom Line Up Front - It's going to depend on the details of your app Flask? Django? uWSGI? whitenoise and gunicorn seem to be the "go to" frameworks on Heroku, so that's what I used in the example below. I am open to using GDAL or other methods to do this. So, I am trying create a stand-alone program with netcdf4 python module to extract multiple point data. @sckoot - There is some confusion on many fronts about the relationship between NetCDF4 and HDF5, so I wanted to add a bit of information to this discussion. This change does not result in any new restrictions; it is merely the adoption of a standard, well-known and well-understood license in place of the historic NetCDF license written at Unidata. Until next time http://arbennett. from netCDF4 import Dataset: import time """ Want to create a netcdf time dimension of 12 equally spaced mid month dates on a 360-day calendar: The method given on the python netcdf4 homepage for creation of the time variable uses the timedelta method from datetime. Input and output (pyart. Working with Python in Visual Studio Code, using the Microsoft Python extension, is simple, fun, and productive. Robert Schmunk at robert. ) è un dato la cui conoscenza è riservata al/i solo/i destinatario/i indicati dallo scrivente. CODA netCDF Mapping Description. ) and producing PostScript illustrations ranging from simple x-y plots via contour maps to artificially illuminated surfaces and 3D perspective views; the GMT. For details on the latest updates, see the Changelog. In the previous post , I presented a very simple application of R-Bridge where I built a toolbox to perform k-means clustering on point shapefiles. Satpy's Documentation¶. HDF4 CF Conversion Toolkit. The latter simply causes a writing application to fail if it attempts to write a NETCDF4 file that cannot be completely read by the netCDF3 library. xarray: N-D labeled arrays and datasets in Python Edit on GitHub xarray (formerly xray ) is an open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun!. CODA netCDF Mapping Description. This module can read and write files in both the new netCDF 4 and the old netCDF 3 format, and can create files that are readable by HDF5 clients. Let's take our previous large. NETCDF3_64BIT: 64-bit offset version of the netCDF 3 file format, which fully supports 2+ GB files, but is only compatible with clients linked against netCDF version 3. nc') # each variable in the netcdf file is a cube iris. The main decision when picking a type is to think about your user. There's an O'Reilly book, Python and HDF5, written by the lead author of h5py, Andrew Collette. If you find this content useful,. NOTE: The "ncdf" package is designed to work with the netcdf library version 3. Lots of high-end analysis software can be made to support NetCDF and it is indispensable for working with gridded datasets that weigh in at tens of gigabytes or more. Read NetCDF files in the browser or with Node. exe as a third party tool or this python script to save netCDf4 as netCDF_classic (v3) to then read it through. With the 10. Basics of opening NetCDF files with Python. This project is hosted on a GitHub repository where you may access the most up-to-date source. 2; osx-64 v1. Introduction. The toolkit includes a conversion library for application developers and a conversion utility for NetCDF users. NetCDF (Network Common Data Form) is a machine-independent,. NETCDF:"filename":subdataset:index0:index1::indexN where the indexes are for the various netcdf dimensions, rather than GDAL band number. asc2cdf, nc2asc, ncmerge, ncav ncextr, ncReorder. $ sudo apt-get install m4 csh netcdf-bin hdf4-tools hdf5-tools zlib* jasper libpng-dev build-essential ncl-ncarg gcc gfortran libnetcdf-dev mpich. When getting netCDF from a software repository, you should get a development version that includes the netcdf. I wonder is there any option (in xarray or other python module) to read in subset of a NetCDF file by providing indices of dimensions (lat, lon)? That way I can directly apply functions to the subset file without using the dask. Web Archive. Writing a netcdf4 file is 6-times slower than writing a netcdf3_classic file and the file is 8-times as big? file-io,netcdf. About MZmine 2 Download Report issue MZmine 2 is an open-source software for mass-spectrometry data processing, with the main focus on LC-MS data. collaborators. Unidata's C, C++, and Fortran implementations of NetCDF are available at Unidata NetCDF, and the Unidata Java reader for NetCDF is available at Unidata NetCDF Java. from the netCDF format to the raster format) related to such things as the indexing of grid-cell locations: netCDF coordinates refer to the center of grid cells, while raster coordinates refer to cell corners. 1 NetCDF using a polygon that represents a region of interest, which can significantly reduce data storage size and speed up regional data access. 2; To install this package with conda run one of the following: conda install -c conda-forge netcdf4. Designed and implemented systems in C, C++, Fortran, Perl. Open source code is available to download from GitHub as well. Work is in progress to allow users to import native HCAST/HSD. When i extract data, result values are all the same! All values are -9. All development for h5py takes place on GitHub. This page provides a variety of resources for creating, submitting and using ORNL DAAC data. FORAY netCDF is based on NetCdf version 3, i. Spyder IDE is a complex but usually stable Python program. python,heroku,gzip,deflate. The Unidata network Common Data Form (netCDF) is an interface for scientific data access and a set of freely-distributed software libraries that provide an implementation of the interface. This website contains the full text of the Python Data Science Handbook by Jake VanderPlas; the content is available on GitHub in the form of Jupyter notebooks. The NWS makes its precipitation data available for download in NetCDF format, specifically we wanted to look at the April 18, 2013 data. In the previous post , I presented a very simple application of R-Bridge where I built a toolbox to perform k-means clustering on point shapefiles. NOTE: The "ncdf" package is designed to work with the netcdf library version 3. Checkout the Published Demos Gallery. If you would like to use the same NetCDF files, they can be retrieved from ECMWF using their web API. The Python ARM Radar Toolkit What is Py-ART? Py-ART is used by the Atmospheric Radiation Measurement (ARM) Climate Research Facility for working with data from a number of its precipitation and cloud radars, but has been designed so that it can be used by others in the radar and atmospheric communities to examine, processes, and analyze data. GitHub is home to over 36 million developers working together to host and review code, manage projects, and build software together. In particular, it does not run in parallel, so will likely be slow on very large datasets (if it runs at all). It can easily be installed via pip i. netcdf_variable objects behave much like array objects defined in numpy, except that their data resides in a file. TIMREX also stored the radial data in DORADE format. Upadate any packages if necessary by typing y to proceed. amber package¶. 5281/zenodo. Installation: with help from a sysadmin, it took us a full day to install this on our central server (SUSE 64-bit). This question is unlikely to help others as it appears to be a site-specific problem related to the interplay between netcdf libraries and the python netCDF4 module. The ‘examples’ directory provides example experiments that can be run with RNNLIB. Fix Spyder IDE not visible 14 August, 2019. dotnet add package netcdf-ikvm --version 4. This guide will also cover use of the Intel® C++ Compiler, although it is not required to build NetCDF. You'll then change the display by selecting a different time step. install cdo with grib2, hdf5, netcdf4. View project onGitHub For many big datasets, location is a crucial component to truly understand underlying patterns and trends. The NetCDF-Java Library is a Java interface to NetCDF files, as well as to many other types of scientific data formats. It is all HDF5. gz file, nws_precip_conus_20130418. 9 - Python binding to netCDF4 (network Common Data Form), a set of software libraries and machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data GDAL 1. Reading WRF NetCDF files with GDAL python Since I work at a meteorological service I have to deal quite often with numerical weather prediction models. 2 or later, because routines such as NCCLOS() are no longer in that library. This allows nctoolbox to access NetCDF, OPeNDAP, HDF5, GRIB, GRIB2, HDF4 and many (15+) other file formats and services using the same API. 将边界强迫文件cjk_obc. Design Considerations and Overview. nc" Importing NetCDF and Numpy ( a Python library that supports large multi-dimensional arrays or matrices): import netCDF4 import numpy as np Now, let us open a NetCDF Dataset. MetPy can also be found on Twitter. All current and historic releases of the netCDF C library source code, including pre-release code. MC Kernel needs a recent Fortran compiler (gfortran 4. ARPACK software is capable of solving large scale symmetric, nonsymmetric, and generalized eigenproblems from significant application areas. In addition to data chunking, you can compress netCDF/HDF variables on the fly. See GitHub #296 for more information. Getting and Building netCDF > Getting and Building netCDF Table of Contents * Getting netCDF-CGetting pre-built netCDF-C libraries. Take a look at the WIKI Documentation. The Unidata network Common Data Form (netCDF) is an interface for scientific data access and a set of freely-distributed software libraries that provide an implementation of the interface. 三、netCDF4的使用实例 1. Under the hood, nctoolbox uses NetCDF-Java as the data access layer. 1 - Geospatial Data Abstraction Library. Unidata’s Python Training Workshop. Climate model output files are available for CMIP5 in the netCDF file format. • It provides a simple interface to the NetCDF structure. Updated to use version 2 of _NCProperties attribute. A Pipeline for Analysis of NetCDF data in Google Earth Engine. Includes tools for data translation (asc2cdf, n2asc nc2asc), merging netcdf files, editing netcdf files. NetCDF CF Metadata Conventions. Finally, CMhyd extracts time series of the relevant grid cells by reading from the netCDF les. h header file. netcdf and in that case I would set nc. The HDF4 CF (H4CF) Conversion Toolkit can access various NASA HDF4 and HDF-EOS2 files by following the CF conventions. % It then creates an index based on the minimum distance between % chronologies and field grid points, which is then used to index into the % cropped (trimmed) netCDF file. The R – ArcGIS Community is a community driven collection of free, open source projects making it easier and faster for R users to work with ArcGIS data, and ArcGIS users to leverage the analysis capabilities of R. Jul 30, 2017. Includes tools for data translation (asc2cdf, n2asc nc2asc), merging netcdf files, editing netcdf files. Analyzing or producing higher-level gridded data products stored in the netCDF file format can be challenging for researchers not experienced with netCDF data. It is based on a hierarchical design targeted at federations of clusters. NetCDF4-python has moved to github: Unidata NetCDF4-python. from the netCDF format to the raster format) related to such things as the indexing of grid-cell locations: netCDF coordinates refer to the center of grid cells, while raster coordinates refer to cell corners. HDF Compass is also by the HDF Group. So, I am trying create a stand-alone program with netcdf4 python module to extract multiple point data. 0 For projects that support PackageReference , copy this XML node into the project file to reference the package. io)¶SciPy has many modules, classes, and functions available to read data from and write data to a variety of file formats. Introduction. Netcdf is a collection of self-describing, machine-independent binary data formats and software tools that facilitate the creation, access and sharing of scientific data stored in N-dimensional arrays, along with metadata describing the contents of each array. 1 as soon as is possible to avoid a potential, albeit rare, data loss issue in ncgen (as described below or detailed at #323). Panoply uses the following third-party, open-source Java code libraries, provided under various licenses as listed. This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library. Once you have created an account with ECMWF, you can find the Python retrieval scripts for U and V wind components on my Github here. USGS Earthquake Hazards Program, responsible for monitoring, reporting, and researching earthquakes and earthquake hazards. grb -netcdf data_halfdeg. This page was last modified on 21 September 2016, at 14:31. Python - NetCDF reading and writing example with plotting. 1 as soon as is possible to avoid a potential, albeit rare, data loss issue in ncgen (as described below or detailed at #323). NetCDF is an open file format commonly used to store oceanographic (and other) data such as sea surface temperature (SST), sea level pressure (SLP), and much more. 2 or later, because routines such as NCCLOS() are no longer in that library. Previously, we were converting HDF5 data files to rasters in R and processing them this way, but this method is really inefficient and I am sure there is a better solution in python using the current NetCDF files. Source-code zip and tar. The ‘examples’ directory provides example experiments that can be run with RNNLIB. asc2cdf, nc2asc, ncmerge, ncav ncextr, ncReorder. This module can read and write files in both the new netCDF 4 and the old netCDF 3 format, and can create files that are readable by HDF5 clients. Simply download the CentOS HDFView binary-it will work on Ubuntu / Debian as well. The NetCDF-4 classic model format attempts to bridge gaps between the original NetCDF file and NetCDF-4. 0 data access page. 2; win-32 v1. So, when people are using netCDF, they are getting to the actual data through the HDF library with the netCDF conventions. Understands and utilizes CF Conventions to facilitate reading coordinate data (lon, lat, depth, time). pynco - Use Python to access the power of NCO. This python library enables users to subset NWM Ver1. A quick way to copy variables and metadata from one netcdf file to another using netcdf4-python - Converter. Lots of high-end analysis software can be made to support NetCDF and it is indispensable for working with gridded datasets that weigh in at tens of gigabytes or more. MetPy has a Gitter chatroom for more "live" communication. An important distinction from the Extended XYZ format is the names of some properties:. This page was last modified on 21 September 2016, at 14:31. Here's a full working example:. It has a filename extension of. Any opinions, findings and conclusions or recommendations expressed in this material do not necessarily reflect the views of the National Science Foundation. 1 as soon as is possible to avoid a potential, albeit rare, data loss issue in ncgen (as described below or detailed at #323). Open source code is available to download from GitHub as well. The first part, which is covered in sections Section 3. In particular, it does not run in parallel, so will likely be slow on very large datasets (if it runs at all). 9 - Python binding to netCDF4 (network Common Data Form), a set of software libraries and machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data GDAL 1. hyfo Easy Start Hydrology and Climate Forecasting R Package View on GitHub Download. Extracting data from a netCDF file Does anyone know how to extract values from a netCDF? I dowloaded temperature data for the whole Mediterranean Sea from MYOCEAN database for a range of depths (1. It's GUI wizard provides a guided, step-wise process for conversion and augmentation of file metadata by user. Back to Climate Data Tools Contents. The scientific publication Nature recently featured an article on the benefits of Jupyter Notebooks for scientific research. Input and output (scipy. This would be. I cannot read this file all at once since its dimensions (1200 x 720 x 1440) are too big for the entire file to be in memory at once. Netcdf Visualization Tutorial Video. GeoSpark supports several programming languages: Scala, Java, and R. MetPy has a Gitter chatroom for more "live" communication. The variable names inside whp netCDF files will be the parameter names as described by the parameters section above. 5m,获得用于模拟海平面上升情况下新的水位强迫文件. Detailed information about the release is available in the Release Notes. NetCDF gives scientific programmers a self-describing and portable means for storing data. In, say, Java, you can use Collections. Starting today, you will see warnings if you push large files to your GitHub repository. ¶ Social impact¶. This allows nctoolbox to access NetCDF, OPeNDAP, HDF5, GRIB, GRIB2, HDF4 and many (15+) other file formats and services using the same API. PnetCDF Source Code Downloads The latest stable release of PnetCDF is version 1. Conda Files; Labels; Badges; License: OSI Approved and MIT Home: http://github. 0 (April XX, 2019) Installation; Getting started. It works with Matlab 2008a and later. GIS NEXRAD layers The NEXRAD layer used in these images are available in a georeferenced RASTER format. This website contains the full text of the Python Data Science Handbook by Jake VanderPlas; the content is available on GitHub in the form of Jupyter notebooks. We will also reject pushes which add or modify files that are larger than our generous hard limit. I am not that familiar with using matlab for netcdf file, I have more than 1000 netcdf files (LOOP) and I wanted to extract two variables and put them in the formula to calculate an index. save(cubes[0],'output. A limited number of tools, mainly netCDF-Java based tools, support these features of NcML. hyfo is an R package, initially designed for the European Project EUPORIAS, and cooperated with DHI Denmark, which was then extended to other uses in hydrology, hydraulics and climate. Python bindings for NCO. grb -netcdf data_halfdeg. Installation Tutorial Creating a SeaDAS Environment. While ArviZ supports plotting from familiar datatypes, such as dictionaries and numpy arrays, there are a couple data structures central to ArviZ that are useful to know when using the library. In particular, it does not run in parallel, so will likely be slow on very large datasets (if it runs at all). Python/numpy interface to the netCDF C library. Theme based on Twitter Bootstrap. Data Management in the Ocean, Weather, and Climate Sciences. Following https://ncar. HDF Compass is also by the HDF Group. The CF conventions are increasingly gaining acceptance and have been adopted by a number of projects and groups as a primary standard. An introduction to netCDF and the netCDF4 python module. In this user manual, we show you how to use the climate access tools to create and use your own datasets. Unidata's C, C++, and Fortran implementations of NetCDF are available at Unidata NetCDF, and the Unidata Java reader for NetCDF is available at Unidata NetCDF Java. An experimental utility package, axi-tools, for conversion of Himawari-8 AHI scenes to NetCDF4 files readable by SIFT, is also available for Linux-compatible systems. We provide guidance on preparing a data management plan and properly formatting data for long-term archive, guidance and tutorials on various access tools and services, and information on using and analyzing data in popular software packages. Skip to content. Anaconda python has conda packages for most if not all the modules on the list. Does anyone have any suggestions here? Originally I was using netCDF4 rather than scipy. Leaflet-providers preview. One should almost always use a Python context manager when working with file I/O in Python. While this is automatically done by the underlying C API for netCDF-4 files, the netCDF-3 files still need this call. HDF5 can usually reach easily very good compression level when using szip library (to get this functionality, netCDF-4 and HDF5 need to be compiled with sziplibrary). 3 years ago. shp -cl clip -crop_to_cutline input_raster output_raster_clipped. nc conversion. Python bindings for NCO. Skip to content. II is a free, open-source library to solve partial differential equations using the finite element method. collaborators. To install: ``pip install netcdf_segy`` To convert a SEG-Y file to NetCDF from the command line: ``segy2netcdf ``. 3 release, a new Python library, netCDF4, began shipping as part of the ArcGIS platform. asc2cdf, nc2asc, ncmerge, ncav ncextr, ncReorder. The former gives text representation of your netCDF dataset (basically metadata and the data itself), while the latter is a very powerful graphical interface for instant data visualization. NetCDF started to support parallel I/O from version 4, whose parallel I/O feature was at first built on top of parallel HDF5. See GitHub #296 for more information. This chapter is divided into two main parts. dotnet add package netcdf-ikvm --version 4. io)¶SciPy has many modules, classes, and functions available to read data from and write data to a variety of file formats. Prior editions of the I/O API will have link errors with netCDF-Fortran 4. An experimental utility package, axi-tools, for conversion of Himawari-8 AHI scenes to NetCDF4 files readable by SIFT, is also available for Linux-compatible systems. Conda Files; Labels; Badges; License: OSI Approved and MIT Home: http://github. Python NetCDF to JSON. We use a superset of the AMBER conventions, so that our trajectory file can be read directly by VMD. netcdf_variable objects behave much like array objects defined in numpy, except that their data resides in a file. asc2cdf, nc2asc, ncmerge, ncav ncextr, ncReorder. The extension makes VS Code an excellent IDE, and works on any operating system with a variety of Python interpreters. $ sudo apt-get install m4 csh netcdf-bin hdf4-tools hdf5-tools zlib* jasper libpng-dev build-essential ncl-ncarg gcc gfortran libnetcdf-dev mpich. For this, you can use the netcdf-fortran library. If the DataArray has no name, or if the name is the same as a co-ordinate name, then it is given the name '__xarray_dataarray_variable__'. PTSA builds on xarray functionality and provides several convenience tools that significantly simplify analysis of EEG data. WBB Carbon Dioxide. NetCDF was developed and is maintained at Unidata. LROSE is a co-operative project between: Dept. GitHub Gist: instantly share code, notes, and snippets. Together, the. Only xarray. The R interface is closely based on the C API of the NetCDF library, and it includes calendar conversions from the Unidata UDUNITS library. Provides an object-oriented python interface to the netCDF version 4 library. 三、netCDF4的使用实例 1. NetCDF, and should be familiar to users of that module. Plotting the netcdf data files. hyfo is an R package, initially designed for the European Project EUPORIAS, and cooperated with DHI Denmark, which was then extended to other uses in hydrology, hydraulics and climate. Have a question about NCL itself? Subscribe to ncl-talk and then email your question to [email protected] Citing NCL NCL has a DOI. The library is freely available and the source code is released under the (MIT-style) NetCDF C library license. Is there any way for. The NetCDF-4 classic model format attempts to bridge gaps between the original NetCDF file and NetCDF-4. io/ Sat, 05 Aug 2017 02:56:45 +0000 Sat, 05 Aug 2017 02:56:45 +0000 Jekyll v3. It is all HDF5. Using netCDF in Python. The 1st dimension represents time, and the next 2 represent latitude and longitude respectively. I then derive a Trilinos image from the NetCDF largefiles image. Storage requirements are on the order of n*k locations. An important distinction from the Extended XYZ format is the names of some properties:. gz archives can be found on Unidata's NetCDF-C GitHub site. GitHub is home to over 28 million developers working together to host and review code, manage projects, and build software together. Various raw data and product files (netCDF, grib, BUFR, ASCII text, gini, AREA) are decoded and stored as HDF5 and Postgres metadata by EDEX, which serves products and data over http. NetCDF (Network Common Data Form) is a machine-independent,. Reading WRF NetCDF files with GDAL python Since I work at a meteorological service I have to deal quite often with numerical weather prediction models. What is NetCDF? NetCDF is a set of software libraries and self-describing, machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. These tools will reduce the need for the GEOS-Chem user community to rely on IDL (and GAMAP), which can be prohibitively expensive for some user groups. Its purpose is to help scientific programmers used to interpreted languages (such as MATLAB or IDL) or compiled languages (C/C++ or Fortran) to switch to Python. ncpp: Post flight viewing of processed aircraft netCDF time-series data files. For specific installation instructions, see GitHub. To use these functions, prefix the function name with the package name, netcdf. What is the fitdistrib package? This package is a set a functions developed with the FlomKart flood frequency analysis project at NVE. Please send bug reports, feature requests, etc. Test with RunKit. To install: ``pip install netcdf_segy`` To convert a SEG-Y file to NetCDF from the command line: ``segy2netcdf ``. This allows nctoolbox to access NetCDF, OPeNDAP, HDF5, GRIB, GRIB2, HDF4 and many (15+) other file formats and services using the same API. The NetCDF datafiles are converted from PREPBUFR format using the pb2nc utility in the Model Evaluation Tools (MET) software package. The operators are primarily designed to aid manipulation and analysis of gridded scientific data. This module can read and write files in both the new netCDF 4 and the old netCDF 3 format, and can create files that are readable by HDF5 clients. netcdf module. User Guide. Enabling compression on Heroku using python. The netCDF libraries support a machine-independent format for representing scientific data. HDF4 CF Conversion Toolkit. The summary file format is described by chapter 3 of the woce manual. nc" Importing NetCDF and Numpy ( a Python library that supports large multi-dimensional arrays or matrices): import netCDF4 import numpy as np Now, let us open a NetCDF Dataset. nc file and rewrite it with compression:. Extracting data from a netCDF file Does anyone know how to extract values from a netCDF? I dowloaded temperature data for the whole Mediterranean Sea from MYOCEAN database for a range of depths (1. The NetCDF-4 classic model format attempts to bridge gaps between the original NetCDF file and NetCDF-4. Let’s take our previous large. 8 or later), an MPI installation, the NetCDF library for accessing the wavefield files, the FFTW library for Fourier transforms and LAPACK, because we were too lazy to write a matrix inversion routine ourselves. Need the R Statistical Software? Download it now. Satpy is a python library for reading, manipulating, and writing data from remote-sensing earth-observing meteorological satellite instruments. The R - ArcGIS Community is a community driven collection of free, open source projects making it easier and faster for R users to work with ArcGIS data, and ArcGIS users to leverage the analysis capabilities of R. From their own page. ¶ Social impact¶. Create a raster layer from a netCDF file. hyfo Easy Start Hydrology and Climate Forecasting R Package View on GitHub Download. Panoply uses the following third-party, open-source Java code libraries, provided under various licenses as listed. Documentation for using this software is contained within the GitHub repository. Source-code zip and tar. ) • Use Perl, gnuplot and crontab to supervise disk usage by users, and automatically generate. NCO (netCDF Operators) is a suite of programs designed to facilitate manipulation and analysis of self-describing data stored in the netCDF format. NcML is similar to the netCDF CDL (network Common data form Description Language), except, of course, it uses XML syntax. An introduction to netCDF and the netCDF4 python module. Netcdf is a collection of self-describing, machine-independent binary data formats and software tools that facilitate the creation, access and sharing of scientific data stored in N-dimensional arrays, along with metadata describing the contents of each array. The fact-checkers, whose work is more and more important for those who prefer facts over lies, police the line between fact and falsehood on a day-to-day basis, and do a great job. Today, my small contribution is to pass along a very good overview that reflects on one of Trump’s favorite overarching falsehoods. Namely: Trump describes an America in which everything was going down the tubes under  Obama, which is why we needed Trump to make America great again. And he claims that this project has come to fruition, with America setting records for prosperity under his leadership and guidance. “Obama bad; Trump good” is pretty much his analysis in all areas and measurement of U.S. activity, especially economically. Even if this were true, it would reflect poorly on Trump’s character, but it has the added problem of being false, a big lie made up of many small ones. Personally, I don’t assume that all economic measurements directly reflect the leadership of whoever occupies the Oval Office, nor am I smart enough to figure out what causes what in the economy. But the idea that presidents get the credit or the blame for the economy during their tenure is a political fact of life. Trump, in his adorable, immodest mendacity, not only claims credit for everything good that happens in the economy, but tells people, literally and specifically, that they have to vote for him even if they hate him, because without his guidance, their 401(k) accounts “will go down the tubes.” That would be offensive even if it were true, but it is utterly false. The stock market has been on a 10-year run of steady gains that began in 2009, the year Barack Obama was inaugurated. But why would anyone care about that? It’s only an unarguable, stubborn fact. Still, speaking of facts, there are so many measurements and indicators of how the economy is doing, that those not committed to an honest investigation can find evidence for whatever they want to believe. Trump and his most committed followers want to believe that everything was terrible under Barack Obama and great under Trump. That’s baloney. Anyone who believes that believes something false. And a series of charts and graphs published Monday in the Washington Post and explained by Economics Correspondent Heather Long provides the data that tells the tale. The details are complicated. Click through to the link above and you’ll learn much. But the overview is pretty simply this: The U.S. economy had a major meltdown in the last year of the George W. Bush presidency. Again, I’m not smart enough to know how much of this was Bush’s “fault.” But he had been in office for six years when the trouble started. So, if it’s ever reasonable to hold a president accountable for the performance of the economy, the timeline is bad for Bush. GDP growth went negative. Job growth fell sharply and then went negative. Median household income shrank. The Dow Jones Industrial Average dropped by more than 5,000 points! U.S. manufacturing output plunged, as did average home values, as did average hourly wages, as did measures of consumer confidence and most other indicators of economic health. (Backup for that is contained in the Post piece I linked to above.) Barack Obama inherited that mess of falling numbers, which continued during his first year in office, 2009, as he put in place policies designed to turn it around. By 2010, Obama’s second year, pretty much all of the negative numbers had turned positive. By the time Obama was up for reelection in 2012, all of them were headed in the right direction, which is certainly among the reasons voters gave him a second term by a solid (not landslide) margin. Basically, all of those good numbers continued throughout the second Obama term. The U.S. GDP, probably the single best measure of how the economy is doing, grew by 2.9 percent in 2015, which was Obama’s seventh year in office and was the best GDP growth number since before the crash of the late Bush years. GDP growth slowed to 1.6 percent in 2016, which may have been among the indicators that supported Trump’s campaign-year argument that everything was going to hell and only he could fix it. During the first year of Trump, GDP growth grew to 2.4 percent, which is decent but not great and anyway, a reasonable person would acknowledge that — to the degree that economic performance is to the credit or blame of the president — the performance in the first year of a new president is a mixture of the old and new policies. In Trump’s second year, 2018, the GDP grew 2.9 percent, equaling Obama’s best year, and so far in 2019, the growth rate has fallen to 2.1 percent, a mediocre number and a decline for which Trump presumably accepts no responsibility and blames either Nancy Pelosi, Ilhan Omar or, if he can swing it, Barack Obama. I suppose it’s natural for a president to want to take credit for everything good that happens on his (or someday her) watch, but not the blame for anything bad. Trump is more blatant about this than most. If we judge by his bad but remarkably steady approval ratings (today, according to the average maintained by 538.com, it’s 41.9 approval/ 53.7 disapproval) the pretty-good economy is not winning him new supporters, nor is his constant exaggeration of his accomplishments costing him many old ones). I already offered it above, but the full Washington Post workup of these numbers, and commentary/explanation by economics correspondent Heather Long, are here. On a related matter, if you care about what used to be called fiscal conservatism, which is the belief that federal debt and deficit matter, here’s a New York Times analysis, based on Congressional Budget Office data, suggesting that the annual budget deficit (that’s the amount the government borrows every year reflecting that amount by which federal spending exceeds revenues) which fell steadily during the Obama years, from a peak of $1.4 trillion at the beginning of the Obama administration, to $585 billion in 2016 (Obama’s last year in office), will be back up to $960 billion this fiscal year, and back over $1 trillion in 2020. (Here’s the New York Times piece detailing those numbers.) Trump is currently floating various tax cuts for the rich and the poor that will presumably worsen those projections, if passed. As the Times piece reported: