Atmospheric Lidar Package: readme.md@a0b073b1f684 (annotated)

readme.md@a0b073b1f684 (annotated)

readme.md

Mon, 18 Feb 2013 12:21:05 +0100

author: ulalume3 <binietoglou@imaa.cnr.it>
date: Mon, 18 Feb 2013 12:21:05 +0100
changeset 15: a0b073b1f684
parent 12: f3ab222acc38
permissions: -rw-r--r--

Added the option to subtrackt dark profiles from raw data. This could be useful for non-scc use of the netcdf files (ex. LIRIC).

 Basic instructions
 ==================
 These classes can be used to handle lidar input data. They are still in a very initial stage. There are many features probably not working, but they work for some specific tasks. They work with Licel input files (and also with the Raymetrics modified format).
 Set up
 ------
 ### Parameter file
 Before using the classes you need to setup some channel parameters, that are used when converting the lidar data to Single Calculus Chain format.
 All the parameters are read from an external file stored in the same folder as the code. You can start by changing the file “cf_netcdf_parameters.py” that describe such parameters for the Clermont Ferrand  lidar.
 ### System class
 The next thing you need to create a class that describes you system. This is very simple if your lidar data are in the Licel format, as you only need to specify the external file with the extra SCC parameters. You can use as an example the file “cf_raymetrics.py”:
     :::python
     from licel import LicelLidarMeasurement
     import cf_netcdf_parameters
     class CfLidarMeasurement(LicelLidarMeasurement):
        extra_netcdf_parameters = cf_netcdf_parameters
 Using the class
 -------------
 Once you have made the above setup you can start using it. The best way to understand how it works is through an interactive shell (I suggest [ipython](http://ipython.org/)).  In the following example I use the cf_raymetrics setup:
     :::python
     import glob # This is needed to read a list of filenames
     from lidar import cf_raymetrics #If you have saved the files in a directrory called “lidar”
     # Go to the folder where you files are stored
     cd /path/to/lidar/files
     # Read the filenames
     files  = glob.glob("*") # The * reads all the files in the folder.
     #Read the files
     my_measurement = cf_raymetrics.CfLidarMeasurement(files)
     #Now the data have been read, and you have a measurement object to work with:
     # See what channels are present
     print my_measurement.channels
     #Quicklooks of all the channels
     my_measurements.plot()
 Converting to SCC format
 ---------------------
 There are some extra info you need to put in before converting to SCC format, "Measurement_ID", "Temperature", "Pressure":
     :::python
     my_measurement.info["Measurement_ID"] = "20101229op00"
     my_measurement.info["Temperature"] = "14"
     my_measurement.info["Pressure"] = "1010"
 You can use standard values of temperature and pressure by just calling:
     :::python
     my_measurement.get_PT()
 The standard values can be changed in generic.py. Search the  get_PT method and change of what is appropriate for your station. If you have an external source of temperature and pressure information (a meteorological station) you can automate this by overriding the get_PT method in your system"s class (in our example in the cf_raymetrics.py file).
 After you have used this extra input, you save the file using this command:
     :::python
     my_measurement.save_as_netcdf("filename")
 where you change the filename to the filename you want to use.

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readme.md@a0b073b1f684 (annotated)

readme.md