Recipe - FAAM meets cis¶

CIS Installation¶

Information about installing anaconda2 and cis:

anaconda2: https://www.continuum.io/downloads

cis: http://cistools.net/get-started#installation

Please note that the cis instructions say that you should install python 2.7 and not 3.x. If you are new to python you might be irritated why you would not install the very latest version of some software. In brief: The two versions are not fully compatible and many people decided to stick with 2.7 for the time being, because the benefits are just too small to move on.

FAAM netCDF preparation¶

The FAAM core data do not work with the cis tool straight away. The netCDF data product need a little tweaking to make them fully CF compliant, so that cis interprets the data correctly. The global attributes “Conventions” and “Coordinates” need to be added. A small bash snippet can do the changes using nc utilities. The example netCDF has already been edited and works with cis.

#!/bin/bash

ofile=`echo $1 | sed s/.nc/_editted.nc/`

ncatted \
 -a 'Version,global,c,c,1.5' \
 -a 'conventions,global,m,c,NCAR-RAF/nimbus' \
 -a 'Coordinates,global,c,c,LON_GIN LAT_GIN ALT_GIN Time' \
 -a '_FillValue,LAT_GIN,m,f,0' \
 -a '_FillValue,LON_GIN,m,f,0' \
 -a '_FillValue,ALT_GIN,m,f,0' \
 -o $ofile $1
ncwa -a sps01 -O $ofile $ofile
ncrename -d data_point,Time -O $ofile

Save the above code as faam_edit.sh and make it executable:

chmod u+x faam_edit.sh
./faam_edit.sh core_faam_20161024_v004_r0_b991_1hz.nc

The example data (core_faam_20161024_v004_r0_b991_1hz_editted.nc) are for flight b991 (24-10-2016), when the aircraft was flying downwind of Manchester and Liverpool measuring emissions from the two cities ahead of the Into the Blue event.

Starting cis¶

The next thing to do is to start the cis environment that we installed earlier. Go to the bin directory of your conda installation:

cd ~/anaconda2/bin/

and activate the environment:

source activate cis_env

From now on the shell should have the string ‘(cis_env)’ in front indicating that we are working in the cis environment.

Working with cis and FAAM data¶

Below are several one line examples that show the functionality of the cis tools. Most of the examples have been taken and adapted from the cis online documentation.

Note

All the commands below go on one line in your shell. The page is just too small to get it all printed on one line.

Get information about the netCDF:

cis info TAT_ND_R:core_faam_20161024_v004_r0_b991_1hz_editted.nc

and the true air temperature form the non-deiced sensor:

cis info TAT_ND_R:core_faam_20161024_v004_r0_b991_1hz_editted.nc

Create scatter plot to compare the deiced (TAT_DI_R) and non-deiced (TAT_ND_R) temperature measurements on the ARA:

cis plot TAT_ND_R:core_faam_20161024_v004_r0_b991_1hz_editted.nc \
  TAT_DI_R:core_faam_20161024_v004_r0_b991_1hz_editted.nc \
  --type comparativescatter --grid \
  --title "True air temperature comparison" \
  --xlabel "non deiced sensor (K)" --ylabel "deiced sensor (K)"

And print some statistics about the TAT_DI_R variable:

cis stats TAT_ND_R:core_faam_20161024_v004_r0_b991_1hz_editted.nc \
  TAT_DI_R:core_faam_20161024_v004_r0_b991_1hz_editted.nc

Make a coloured line plot, showing the CO concentration (variable name is CO_AERO) on a map:

cis plot CO_AERO:core_faam_20161024_v004_r0_b991_1hz_editted.nc \
  --xaxis longitude --yaxis latitude --xmin -5 --xmax -2 --ymin 52.2 --ymax 55

Calculate mean, min, max for 1min time intervals for the CO_AERO data for the time interval 11:45 to 14:45. The results are written out to a new NetCDF:

cis aggregate CO_AERO:core_faam_20161024_v004_r0_b991_1hz_editted.nc:kernel=mean \
  t=[2016-10-24T11:45,2016-10-24T14:45,PT1M] -o b991_co_aero_1min_mean.nc

cis aggregate CO_AERO:core_faam_20161024_v004_r0_b991_1hz_editted.nc:kernel=max \
  t=[2016-10-24T11:45,2016-10-24T14:45,PT1M] -o b991_co_aero_1min_max.nc

cis aggregate CO_AERO:core_faam_20161024_v004_r0_b991_1hz_editted.nc:kernel=min \
  t=[2016-10-24T11:45,2016-10-24T14:45,PT1M] -o b991_co_aero_1min_min.nc

Plot the three lines in one figure:

cis plot CO_AERO:b991_co_aero_1min_max.nc \
  CO_AERO:b991_co_aero_1min_mean.nc \
  CO_AERO:b991_co_aero_1min_min.nc

Reproducing an aggregation example from the documentation:: http://cis.readthedocs.io/en/stable/aggregation.html#aircraft-track

The results from the aggregation will be saved to a netCDF (option -o). The following line aggregates over 5 minutes and over altitude in 200 meter steps in the range of 0 to 1000m:

cis aggregate CO_AERO:core_faam_20161024_v004_r0_b991_1hz_editted.nc \
  t=[2016-10-24T11:45,2016-10-24T14:45,PT5M],z=[0,1000,200] \
  -o b991_co_aero_alt_time.nc

Plot a curtain (transect) using the netCDF that we just created:

cis plot CO_AERO:b991_co_aero_alt_time.nc --xaxis time --yaxis altitude

Make a grid plot from the mean, where each grid cell is 0.2 degrees in size. The results are written to a netCDF:

cis aggregate CO_AERO:core_faam_20161024_v004_r0_b991_1hz_editted.nc:kernel=mean \
  x=[-5,0,0.2],y=[52,55,0.2] -o b991_co_aero_grid_mean.nc

Now plot the grid on a map using the netcdf that we just created:

cis plot CO_AERO:b991_co_aero_grid_mean.nc