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Python Iris

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  Analyzed 3 months ago

A powerful, easy to use, and community-driven Python library for analysing and visualising meteorological and oceanographic data sets. http://scitools.org.uk/iris/docs/latest

140K lines of code

29 current contributors

3 months since last commit

3 users on Open Hub

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0.0
 

Alpine3D

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  Analyzed 2 months ago

Alpine3D is a spatially distributed (surface), three dimensional (atmospheric) model for analyzing and predicting dynamics of snow-dominated surface processes in mountainous topography. It includes models for snow cover (SNOWPACK), vegetation and soil, snow transport, radiation transfer and runoff ... [More] which can be enabled or disabled on demand. [Less]

14.1K lines of code

3 current contributors

3 months since last commit

2 users on Open Hub

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0.0
 

MeteoIO

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  Analyzed 2 months ago

The MeteoIO library aims at making data access easy and safe for numerical simulations in environmental sciences requiring general meteorological data. It is a C++ library provided with complete documentation (tutorials, code examples, API's documentation) under the LGPL v3 license.

41.3K lines of code

2 current contributors

2 months since last commit

2 users on Open Hub

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0.0
 

Debian Science

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Claimed by Debian Analyzed 7 months ago

The main goal of the Debian Science project is to provide a system with all the most important free scientific software in each scientific field.

73.4M lines of code

71 current contributors

8 months since last commit

2 users on Open Hub

Activity Not Available
4.0
   

Snowpack

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  Analyzed 8 months ago

The SNOWPACK model ([Lehning 2002a], [Lehning 2002b]) is the operational model of the Swiss avalanche warning service and is available as an integrated software package.

24.2K lines of code

2 current contributors

8 months since last commit

2 users on Open Hub

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0.0
 

metar

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  Analyzed 3 months ago

Trivial weather report.

146 lines of code

1 current contributors

4 months since last commit

1 users on Open Hub

Activity Not Available
5.0
 

wradlib

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  Analyzed 3 months ago

wradlib - An Open Source Library for Weather Radar Data Processing The wradlib project has been initiated in order facilitate the use of weather radar data as well as to provide a common platform for research on new algorithms. wradlib is an open source library which is well documented and easy ... [More] to use. It is written in the free programming language Python. Weather radar data is potentially useful in meteorology, hydrology and risk management. Its ability to provide information on precipitation with high spatio-temporal resolution over large areas makes it an invaluable tool for short term weather forecasting or flash flood forecasting. [Less]

7.59K lines of code

8 current contributors

3 months since last commit

1 users on Open Hub

Activity Not Available
5.0
 

netcdf4-python

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  Analyzed 9 months ago

netCDF version 4 has many features not found in earlier versions of the library and is implemented on top of HDF5. 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. The API modelled after ... [More] Scientific.IO.NetCDF, and should be familiar to users of that module. Most new features of netCDF 4 are implemented, such as multiple unlimited dimensions, groups and zlib data compression. All the new numeric data types (such as 64 bit and unsigned integer types) are implemented. Compound and variable length (vlen) data types are supported, but the enum and opaque data types are not. Mixtures of compound and vlen data types (compound types containing vlens, and vlens containing compound types) are not supported. NEWS: 20100226 There is a bug writing netCDF-4 files on big-endian platforms with more than 8 attributes attached to a variable or group. It is described here: http://www.hdfgroup.org/HDF5/release/known_problems/index.html That bug is fixed by release HDF5 1.8.4 Patch 1, available from the HDF5 downloads page: http://www.hdfgroup.org/downloads/index.html Building any version of netcdf-4 with HDF5 1.8.4 Patch 1 fixes that bug. A separate, unrelated bug in netcdf-4.1 requires the conditions described here: http://www.unidata.ucar.edu/mailing_lists/archives/netcdfgroup/2010/msg00070.html That bug is fixed in the forthcoming netcdf-4.1.1 release. 20100209: Version 0.9 released (bugfixes, netcdf-4.1 compatibility). 20090818: Version 0.8.2 released. vlen and compound types fully supported with netcdf-4.1-beta2 or higher. 20090621: Version 0.8.1 released with experimental variable-length (vlen) data type support. 20090603: Compound types now work properly since the netcdf-4.1-beta-20090603 snapshot. I've disabled the compound types tests until 4.1 is released. 20090421: The initial compound data type support is 0.8 is broken (it only works correctly if all the members of the compound type have the same bit width). I'm trying to figure out if this is a bug in the netcdf library, the extension module, or both. So, if you are concerned about the test failures, just move tst_compoundvar.py out of the way. 20090418: version 0.8 released with support for compound data types (which map to numpy structured, i.e. 'record', arrays). 20090402: tst_dap.py in version 0.7.7 will fail due to a bug in the newly released netcdf-4.0.1 final. To skip the dap test, just rename test/tst_dap.py to test/tst_dap.py.skip and run test/run_all.py again. 20090217: version 0.7.7 released. David Huard has re-worked 'fancy indexing', adding new features and making it less of a memory hog. However, it is now no longer compatible with numpy fancy indexing - 1d arrays of boolean or integer indices work independently on each dimension (similar to the way vector subscripts work in fortran). This enables things like: >>> tempdat = temp[[0,1,3],lats>0,lons>0](retrieves 1st, 2nd and 4th levels, all Northern Hem. and Eastern Hem. grid points - note that this would raise an error in numpy). 20090124: netcdf4-python now included in the Enthought Python Distribution (v4.1.30101). 20081223: If built against netcdf-4.0.1-beta2 (compiled with --enable-dap), you can access remote opendap datasets by specifying a URL instead of a filename when creating a Dataset instance. 20080922: Version 0.7.6 released. See Changelog. 20080801: Version 0.7.5 released. Bugfixes, mainly in MFDataset. Some new features in MFDataset. 20080508: Version 0.7.4 released. Use with netcdf-4.0 and HDF5 1.8.1. 20080414: Version 0.7.3.1 does not work with recent snapshots of the netCDF4 library. Click the 'Source' tab to download the latest source from SVN instead. I'm waiting the netcdf-4-beta2 (due any day now) before making a new source release. 20080101: As of version 0.7.3, a netCDF3 module is now included, for those who don't want to install bleeding-edge versions of the netcdf-4 and HDF5 libraries. Some features not found the Scientific.IO.NetCDF module: ability to read multi-file netCDF Datasets, making variables spanning multiple files appear as if they were in one file. support for masked arrays, automatic packing and unpacking of packed integer data. supports more complicated slicing (including numpy 'fancy indexing'). includes convenience functions for converting to and from datetime objects to numeric time values, using all the calendars in the CF metadata standard. convenience functions for converting arrays of characters to arrays of strings, and vice-versa. can use numpy dtype objects to specify netCDF variable datatype. [Less]

58.1K lines of code

0 current contributors

almost 3 years since last commit

0 users on Open Hub

Activity Not Available
0.0
 

pyfluid

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  Analyzed 9 months ago

Procedures to study fluids on Python, focused for oceanography, meteorology and related sciences.

0 lines of code

0 current contributors

almost 9 years since last commit

0 users on Open Hub

Activity Not Available
0.0
 
Mostly written in language not available
Licenses: MIT

miyoshi

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  Analyzed 9 months ago

What is LETKF?LETKF stands for Local Ensemble Transform Kalman Filter, invented by Hunt et al. (2007) at the University of Maryland. It is an advanced data assimilation method for many possible applications. It has been tested with numerical weather prediction (NWP) models, storm to global scales. ... [More] What is available here?LETKF source codes and run scripts Some documentation FeatureAll-in-one package to run SPEEDY-LETKF, a great tool to learn and play with. Written by Fortran 90/95 language and B-shell scripting Parallel processing with the MPI (Message Passing Interface) library and OpenMP directives, making most use of parallel architecture computers including multi-core processors, cluster environment, and even supercomputer (tested with the Japanese Earth Simulator). It would be relatively easy to adapt to other applications. Any kinds of computer simulations of real world that we can observe. Possible collaborators, please contact me! Getting StartedI recommend general users start with SPEEDY-LETKF. Those who are already familiar with the codes may go directly to Source. Mailing listsAnnouncements of important changes: miyoshi-code-announce This is just for announcements. Users cannot post emails. Discussions (comments, questions, etc.): miyoshi-code-discussions This is for exchanging comments. User's comments and questions are welcome. Anyone can answer. I would like to see users help each other. About this google codeMaintained by Takemasa Miyoshi. All contents are provided "as-is" without warranties of any kind. I welcome feedbacks, but please do not expect support. [Less]

45.3K lines of code

1 current contributors

over 1 year since last commit

0 users on Open Hub

Activity Not Available
0.0