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This section demonstrates how to convert the FLEXPART output to net CDF4 format.

In order to do that the create_ncfile script will be invoked.

The ability to read this data directly is forthcoming, but for now reflexible still only works with the raw unformatted binary Fortran data FLEXPART has traditionally used for output.

See the documents for information regarding FLEXPART .

This script is copied into a directory in your path when reflexible is installed, so you should not worry about copying it manually. -H HEADER_KEY, --header-key HEADER_KEY Print the contents of H[HEADER_KEY]. root group (NETCDF4 data model, file format HDF5): Conventions: CF-1.6 title: FLEXPART model output institution: NILU source: Version 10.0beta (2015-05-01) model output history: 2016-02-02 0100 created by on compute-8-16.local references: Stohl et al., Atmos. Phys., 2005, doi:10.5194/acp-5-2461-200 outlon0: -179.0 outlat0: -90.0 dxout: 0.5 dyout: 0.5 ldirect: -1 ibdate: 20150405 ibtime: 103500 iedate: 20150426 ietime: 130500 loutstep: -10800 loutaver: -10800 loutsample: -900 itsplit: 9999999 lsynctime: -900 ctl: -0.2 ifine: 1 iout: 5 ipout: 0 lsubgrid: 1 lconvection: 1 lagespectra: 1 ipin: 0 ioutputforeachrelease: 1 iflux: 0 mdomainfill: 0 ind_source: 1 ind_receptor: 1 mquasilag: 0 nested_output: 1 surf_only: 0 linit_cond: 0 dimensions(sizes): time(168), longitude(720), latitude(360), height(3), numspec(1), pointspec(31), nageclass(1), nchar(45), numpoint(31) variables(dimensions): int32 time(time), float32 longitude(longitude), float32 latitude(latitude), float32 height(height), |S1 RELCOM(numpoint,nchar), float32 RELLNG1(numpoint), float32 RELLNG2(numpoint), float32 RELLAT1(numpoint), float32 RELLAT2(numpoint), float32 RELZZ1(numpoint), float32 RELZZ2(numpoint), int32 RELKINDZ(numpoint), int32 RELSTART(numpoint), int32 RELEND(numpoint), int32 RELPART(numpoint), float32 RELXMASS(numspec,numpoint), int32 LAGE(nageclass), int32 ORO(latitude,longitude), float32 spec001_mr(nageclass,pointspec,time,height,latitude,longitude) groups: : name = 'numpoint', size = 31 )]) In [6]: rootgrp.variables.keys() Out[11]: odict_keys(['time', 'longitude', 'latitude', 'height', 'RELCOM', 'RELLNG1', 'RELLNG2', 'RELLAT1', 'RELLAT2', 'RELZZ1', 'RELZZ2', 'RELKINDZ', 'RELSTART', 'RELEND', 'RELPART', 'RELXMASS', 'LAGE', 'ORO', 'spec001_mr']) float32 longitude(longitude) long_name: longitude in degree east axis: Lon units: degrees_east standard_name: grid_longitude description: grid cell centers unlimited dimensions: current shape = (720,) filling on, default _Fill Value of 9.969209968386869e 36 used which, besides of being memory-efficient, they are what you normally use in your analysis tasks.

Before processing the data in stads2_V10we have to uncompress that file: $ fprun -n -C /tmp/stads2_V10/pathnames $ Flexpart('/tmp/stads2_V10/pathnames', nested=True) $ Command: Ordered Dict([('CBLFLAG', 0), ('CTL', -5), ('IBDATE', 20150405), ('IBTIME', 103500), ('IEDATE', 20150426), ('IETIME', 130500), ('IFINE', 4), ('IFLUX', 0), ('IND_RECEPTOR', 1), ('IND_SOURCE', 1), ('IOUT', 13), ('IOUTPUTFOREACHRELEASE', 1), ('IPIN', 0), ('IPOUT', 0), ('ITSPLIT', 9999999), ('LAGESPECTRA', 1), ('LCONVECTION', 1), ('LDIRECT', -1), ('LINIT_COND', 0), ('LOUTAVER', 10800), ('LOUTSAMPLE', 900), ('LOUTSTEP', 10800), ('LSUBGRID', 1), ('LSYNCTIME', 900), ('MDOMAINFILL', 0), ('MQUASILAG', 0), ('NESTED_OUTPUT', 1), ('SURF_ONLY', 0)]) $ fprun -h usage: fprun [-h] [-n] [-C] [-R] [-S] [-H HEADER_KEY] [-K] [pathnames] positional arguments: pathnames The Flexpart pathnames file stating where options and output are. Also, each variable can have attached different attributes meant to add more information about what they are about: In [23]: longitude.ncattrs() Out[23]: ['long_name', 'axis', 'units', 'standard_name', 'description'] In [24]: longitude.long_name Out[24]: u'longitude in degree east' In [25]: longitude.units Out[25]: u'degrees_east' Once you have checked out the code and have a sufficient FLEXPART dataset to work with you can begin to use the module. Depending on how you checked out the code, you can accomplish this in a few different way, but the preferred is as follows: In [4]: fprun.

reflexible is undergoing modifications and is not particularly stable or backward compatible code.

Let's start with the "C" attribute, which is similar to the "FD" dictionary described above, but contains the Cumulative sensitivity at each time step, so you can use it for plotting retroplumes. These release IDs correspond to the times in H.releasetimes which is a list of the release times.A users guide for FLEXPART is available which explains the model output.If you are interested in contributing functionality for other FLEXPART versions, please contact me.Let's look at the data stores returned in each of these two dictionaries: There is no longer a fifth dimension corresponding to the release time. This is a dictionary where each numz level is packaged as a 2-d numpy array keyed by it's level index: This is redundant data to the grid, and will likely change in future versions of reflexible.However, the important point to note is that the 0th element is the Total Column.

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