How can I convert 3d variable in array with regridded another 1d variable(which is in same array) from netCDF4?

Question

I'm trying to handle netCDF4 file and it has dimensions and variables like this.

<xarray.DataArray '/' ()>
array(<class 'netCDF4._netCDF4.Dataset'>
root group (NETCDF3_CLASSIC data model, file format NETCDF3):
    Title: Monthly version of HadISST sea surface temperature component
    description: HadISST 1.1 monthly average sea surface temperature
    institution: Met Office Hadley Centre
    source: HadISST
    reference: Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., Kaplan, A.  Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century J. Geophys. Res.Vol. 108, No. D14, 4407 10.1029/2002JD002670
    Conventions: CF-1.0
    history: 8/12/2021 converted to netcdf from pp format
    supplementary_information: Updates and supplementary information will be available from http://www.metoffice.gov.uk/hadobs/hadisst
    comment: Data restrictions: for academic research use only. Data are Crown copyright see (http://www.opsi.gov.uk/advice/crown-copyright/copyright-guidance/index.htm)
    dimensions(sizes): time(1822), latitude(180), longitude(360), nv(2)
    variables(dimensions): float32 time(time), float32 time_bnds(time, nv), float32 latitude(latitude), float32 longitude(longitude), float32 sst(time, latitude, longitude)
    groups: , dtype=object)

Here, I wanted to regrid the longitude grid from (-180, 180) to (0, 360), so I did it using numpy.

And the problem is,

In [10]: print(DATA1['sst'])
<class 'netCDF4._netCDF4.Variable'>
float32 sst(time, latitude, longitude)
    _FillValue: -1e+30
    standard_name: sea_surface_temperature
    long_name: sst
    units: C
    cell_methods: time: lat: lon: mean
    missing_value: -1e+30
unlimited dimensions: time
current shape = (1822, 180, 360)
filling on

that changed longitude affects sst, which is another variable. So I have to do something to SST too, as I've done to longitude. But I do not know what I have to do... (I'd like to make this with only numpy as long as possible!)

Here, it's what I've made so far

from netCDF4 import Dataset
import cartopy.crs as ccrs
from sys import exit    
import numpy as np
import pickle

file1= 'HadISST_sst.nc'
DATA1 = Dataset(file1, 'r')
hd_lat = DATA1.variables['latitude'][:] 
hd_lon0 = DATA1.variables['longitude'][:] 
hd_sst0 = DATA1.variables['sst'][1320:,:,:]
DATA1.close()

#Regridding longitude
id = np.where(hd_lon0 == 0)[0]  # <-- id = 180
a = hd_lon0[:180] + 360
b = hd_lon0[180:]
hd_lon = np.zeros_like[hd_lon0]
hd_lon[:180] = b
hd_lon[180:] = a