{
"cells": [
{
"cell_type": "markdown",
"id": "f1074f1f",
"metadata": {},
"source": [
"# This notebook demonstrates how to read in and plot version 2.0 of the UMass FMCW data from VORTEX-SE 2016.\n",
"This version of the data have been reprocessed to reduce the impact of spurious power spikes from the high-voltage power supply in the UMass FMCW's TWT amplifier. In 2017 and subsequent seasons, the transmitter was upgraded to solid state, and this problem was no longer present.\n",
"\n",
"The FMCW data are stored in NetCDF format. A great deal of analysis and visualization can be accomplished via the commonly-used XArray package for Python."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "4efad07e",
"metadata": {},
"outputs": [],
"source": [
"import xarray as xr\n",
"from glob import glob\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"from functools import partial"
]
},
{
"cell_type": "markdown",
"id": "425d9edb",
"metadata": {},
"source": [
"# Plot a single file of UMass FMCW observations.\n",
"Each file contains approximately one hour of data."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "27a3172b",
"metadata": {},
"outputs": [],
"source": [
"path_to_files = './' # Adjust this path to match your system\n",
"fmcwFile = path_to_files + 'S20160307T180001.nc'"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "a92e27fb",
"metadata": {},
"outputs": [
{
"data": {
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