Feature request for multiple tolerance values when using nearest method and sel()

import xarray as xr
import numpy as np
import pandas as pd

# Create test data
ds = xr.Dataset()
ds.coords['lon'] = np.arange(-120,-60)
ds.coords['lat'] = np.arange(30,50)
ds.coords['time'] = pd.date_range('2018-01-01','2018-01-30')
ds['AirTemp'] = xr.DataArray(np.ones((ds.lat.size,ds.lon.size,ds.time.size)), dims=['lat','lon','time'])

target_lat = [36.83]
target_lon = [-110]
target_time = [np.datetime64('2019-06-01')]

# Nearest pulls a date too far away
ds.sel(lat=target_lat, lon=target_lon, time=target_time, method='nearest')

# Adding tolerance for lat long, but also applied to time
ds.sel(lat=target_lat, lon=target_lon, time=target_time, method='nearest', tolerance=0.5)

# Ideally tolerance could accept a dictionary but currently fails
ds.sel(lat=target_lat, lon=target_lon, time=target_time, method='nearest', tolerance={'lat':0.5, 'lon':0.5, 'time':np.timedelta64(1,'D')})

Expected Output

A dataset with nearest values to tolerances on each dim.

Problem Description

I would like to add the ability of tolerance to accept a dictionary for multiple tolerance values for different dimensions. Before I try implementing it, I wanted to 1) check it doesn't already exist or someone isn't working on it, and 2) get suggestions for how to proceed.

Output of xr.show_versions()

Start by tracing xarray's sel() nearest-selection path and how its tolerance argument is handled. Use the reproducer in the issue to verify separate latitude, longitude, and time tolerances, and consider the request complete when the per-dimension behavior produces the expected dataset without applying one tolerance to every dimension.