Loop through netcdf files and run calculations - Python or R

Loop through netcdf files and run calculations - Python or R

This is my first time using netCDF and I'm trying to wrap my head around
working with it.
I have multiple version 3 netcdf files (NOAA NARR air.2m daily averages
for an entire year). Each file spans a year between 1979 - 2012. They are
349 x 277 grids with approximately a 32km resolution. Data was downloaded
from here.
The dimension is time (hours since 1/1/1800) and my variable of interest
is air. I need to calculate accumulated days with a temperature < 0. For
example
Day 1 = +4 degrees, accumulated days = 0
Day 2 = -1 degrees, accumulated days = 1
Day 3 = -2 degrees, accumulated days = 2
Day 4 = -4 degrees, accumulated days = 3
Day 5 = +2 degrees, accumulated days = 0
Day 6 = -3 degrees, accumulated days = 1
I need to store this data in a new netcdf file. I am familiar with Python
and somewhat with R. What is the best way to loop through each day, check
the previous days value, and based on that, output a value to a new netcdf
file with the exact same dimension and variable.... or perhaps just add
another variable to the original netcdf file with the output I'm looking
for.
Is it best to leave all the files separate or combine them? I combined
them with ncrcat and it worked fine, but the file is 2.3gb.
Thanks for the input.
My current progress in python:
import numpy
import netCDF4
#Change my working DIR
f = netCDF4.Dataset('air7912.nc', 'r')
for a in f.variables:
print(a)
#output =
lat
long
x
y
Lambert_Conformal
time
time_bnds
air
f.variables['air'][1, 1, 1]
#Output
298.37473
To help me understand this better what type of data structure am I working
with? Is ['air'] the key in the above example and [1,1,1] are also keys?
to get the value of 298.37473. How can I then loop through [1,1,1]?