A simple way to find all the breaks in the time stamp, i.e., changes in consecutive times longer than some fixed threshold

find_intervals.py

import xarray as xr

ds = xr.open_dataset('data.nc')

# find temporal breaks that are larger than a given threshold
thrsh = 300  # threshold in seconds
interval_ends = ds.time.diff('time').dt.seconds > thrsh   # gives a boolean array with True at the end of each interval longer than the threshold

# plot the intervals
import matplotlib.pyplot as plt
plt.figure(figsize=(20,6))
ds.z.plot()
ds.where(interval_ends).z.plot(marker='<')
ds.where(interval_ends.shift(time=-1)).z.plot(marker='>')   # .shift(time=-1) shifts the array along the axis/dimension 'time', hence, takes the index one step before, i.e. at the start of the interval

# label phases
## first, set edge markers for start and end of each break phase
ds['edges'] = interval_ends + interval_ends.shift(time=-1)
### optionally: you might need to convert this into numeric values
ds['edges'] = ds.edges.astype(float)

## now label each phase with a unique number
ds['phases'] = ds.edges.cumsum()

# group by phases
ds.groupby('phases'])