HS3 CPL Attenuated Total Backscatter Quickview

The Hurricane and Severe Storm Sentinel (HS3) airborne field campaign used the Cloud Precipitation Lidar (CPL) instrument to collect measurements of cloud, precipitation, and aerosol features of tropical cyclones. This data recipe instructs users on how to generate vertical time-height plots of HS3 CPL attenuated total backscatter measurements using a Python plotting routine. The Python routine requires users to define the GHRC OPeNDAP path to a datafile and the spectral channel the measurements were collected. To run this Python routine, a pre-installed version of Python and additional Python packages are required. Advanced users may alter the code to plot other data variables. 

Data Recipe Type
VisualizationDefault title
Supporting Software Information
iPython Notebook Open Source
Python Script Location
This data recipe uses the Hurricane and Severe Storm Sentinel (HS3) Global Hawk Cloud Physics Lidar (CPL) HDF-EOS5 dataset. More information and additional resources about this dataset can be accessed here.
In addition, this data recipe is available as a Python script and an iPython Notebook, which is an interactive Python environment for the web and shell. To run the Python script and iPython Notebook, please install the following Python modules: matplotlib, NumPy, Pydap, SciPy, and mpmath
Step 1

Follow the location link on this page to access the GHRC DAAC data-recipe GitHub folder. The HS3 CPL Attenuated Total Backscatter Quick View has two separate files available for download: an iPython Notebook and Python Script.
You can preview each by clicking the file name. To download, select the green “Clone or download” button located on the right side of the webpage to download both scripts as a zipped file or to open them on your desktop. Save both or either files to the desired folder location on your computer.

Step 2
Open the Python environment installed on your computer and make sure the required Python packages outlined in the “How to Use” section are installed. 
Navigate to the location on your computer where the data recipe Python file is saved and open the file within your Python environment.
Step 3
The Python script provides a series of editable fields used to plot desired parameters and locations recorded within each HS3 CPL data file. This data recipe uses OPeNDAP to access the data so that users do not need to download and save data files to their computers.  
To define the datafile you want to use, navigate to the GHRC HS3 CPL OPeNDAP directory.  The HS3 CPL datafiles are organized by year.  Select 2012 to plot the figure in this example.
Then select the link for “hdf/” as shown below.
The next directory contains files organized by date in YYYYMMDD format. Select your date of interest, or September 6th, 2012 to generate the example plot created for this data recipe. Copy the desired file name as shown.
Step 4

Within the Python script, to change the default data file to one you want to use, simply paste your file name to the "datafile" variable in the region highlighted below. Make sure to update the OPeNDAP URL path to reflect the year and day of the datefile.

Step 5
This data recipe plots the CPL attenuated total backscatter (ATB) for 532 nm, 1064 nm, and 355 nm. For the example plot shown, the 532 nm data are used to create the plot.  
To change the desired channel, simply change the variable “var_ATB” in the code within the highlighted section below to “ATB_1064” to plot the 1064 nm channel, or “ATB_355” to plot the 355 nm channel.
Step 6
The proceeding code extracts and formats the necessary parameters within the HDF-EOS5 datafile to create a vertical time-height plot of the HS3 CPL data.
The final section of the code formats the plot. You may alter the code to tailor the color scale, text size, text content, and plot parameters to your liking. Note that the current title of the generated plot states the 532 nm channel was used. When creating a plot of another channel remember to change the highlighted title text below.
Step 7

To create the data plot, simply run the script. A window will pop up containing the desired plot.

This data requires additional processing to quality control and remove erroneous data values.  Please refer to the User Guide and PI Documentation for additional information on data quality. 

Step 8

If you would like the run this data recipe as an iPython Notebook, run externally through the Jupyter Notebook web application. More information on Jupyter can be found here.

The Python script and iPython Notebook may be reused and altered to plot additional CPL data variables not used in this data recipe. Additional documentation is provided within the code to help walk you through the content.

Dataset Name Hurricane and Severe Storm Sentinel (HS3) Global Hawk Cloud Physics Lidar (CPL)
Platform Global Hawk Unmanned Aerial Vehicle (UAV)
Instrument Cloud Precipitation Lidar (CPL)
Science Parameter Attenuated Total Backscatter
Format HDF-EOS5
Data Information Data information


Variable Description Dimension Units Scale Factor
time Time n/a seconds none
bin_Alt Altitude in km for each vertical bin 1D kilometer none
Dec_JDay Decimal day of year to 5 decimal places (second) for current profile 1D days since 2012-01-01T00:00:00Z none
Date Date for flight 1D text none
ATB_1064 Attenuated total backscatter collected for 1064 nm channel 2D km-1 sr-1 none
ATB_355 Attenuated total backscatter collected for 355 nm channel 2D km-1 sr-1 none
ATB_532 Attenuated total backscatter collected for 532 nm channel 2D km-1 sr-1 none


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