I tried to find the atmospheric transmission curve for Plateau de Bure Interferometer (PdBI) site the other day. There is no plot/data file showing the atmospheric transmission for the Plateaude Bure Interferometer site! Then I realized that I might be able to plot it in the GILDAS software ASTRO – the observation planning tasks of the bundle. So in this post I will explain how to plot the atmospheric transmission curve at the Plateau de Bure Interferometer (PdBI) using the atmospheric modeling function included in the ASTRO package included in the IRAM GILDAS software bundle, and Python. I guess you can do the same plot in ASTRO using GREG, but I like Python/matplotlib more.

After checking and sending mails back and forth with Jan Martin Winters at IRAM, I realized that there is not direct command to plot the whole transmission curve. What does exist is the command ATMOSPHERE, that calculates τ (the opacity) and a whole bunch of other stuff for a given frequency (running “HELP ATM” gives you the run through of the input/output). This means that I can write a loop that calculates τ for a given frequency. Then I just have to calculate the transmission from I/I0=e-τ and plot it against the frequency.

After each calculation I want to print the frequency and the τ to a file. Thus, the following script produces a file where the first column is frequency and the second the total opacity (τ).

! use the new atm, the 2009 version
! test that it works with “exam atm%version”
! after the command below
set atm new
!
! set observatory, the available names are
! BURE (or PDBI), PICOVELETA (or VELETA) ALMA, APEX,
! ATF, CSO, FCRAO, JCMT, KITTPEAK, KOSMA, SEST,  SMA,
! SMT EFFELSBERG, VLA LASILLA, MAUNAKEA, PARANAL (or VLT),
! IOTA, PTI, GI2T
! if not satisfied, use coordinates as
! OBS [longitude latitude altitude [radius]]
! radius is the sun avoidance zone in degrees, (def 30)
obs pdbi                      !<—- change site here!
!
! which airmass to calculate for 1 = zenith
let airmass 1
! ground temperature in Kelvin
let temperature 273
!
! create variable freq
! and the incremental change in frequency
define real freq
let freq 0.1
define real incr
let incr 0.1
!
! the amount of water vapor in mm
let water 0.3                ! <—- change water vapor here!
!
! the name of the output file
sic out pdbi_atm_0_3.dat
!
for n 0 to 16000
let freq_sig = freq
let freq_ima = freq
atm
! write to file
say ‘freq’ ‘tau_tot’
! add incr to the frequency and
! restart the loop
let freq = freq+incr
next
sic out

Just run this with

astro -nw @script_name.astro

After this you are left with the file pdbi_atm_0_3.dat in this case. Run this script for different amount of water vapor, say 0.3, 0.8 and 1.5. Then you jump into Python and do the following in the same directory as your files

# general imports
import matplotlib.pyplot as pl

# various settings
pl.ion()
pl.rcParams[‘font.size’] = 15

# calculate the transmission in percent
transm_percent = lambda tau : exp(-1*tau)*100

# initialize the figure
pl.figure(1,(11,6))

# plot the graphs
pl.plot(data0_3, transm_percent(data0_3))

pl.plot(data0_8, transm_percent(data0_8))
pl.plot(data1_5, transm_percent(data1_5))

# get some label action going
pl.legend([‘0.3mm’, ‘0.8mm’, ‘1.5mm’])

pl.xlabel(‘Frequency [GHz]’)
pl.ylabel(‘Transmission (%)’)
pl.title(‘Atmospheric Transmission at PdBI’)