Create time-series from OMI L3 daily average

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That might be a while, so for the short term you could either use the L2 products.

Or, and that might be easier, is to create your own HARP importer.
This is similar to my reply on the MODIS topic. You would use the HDF5 library or CODA to read the data in Python as numpy arrays. This is really easy:

import coda
import harp

pf = coda.open('/Users/sander/Downloads/OMI-Aura_L3-OMSO2e_2020m0610_v003-2020m0612t031446.he5')
try:
    latitude = coda.fetch(pf, '/HDFEOS/GRIDS/OMI_Total_Column_Amount_SO2/Data_Fields/Latitude')
    latitude = latitude[:,0]
    longitude = coda.fetch(pf, '/HDFEOS/GRIDS/OMI_Total_Column_Amount_SO2/Data_Fields/Longitude')
    longitude = longitude[0,:]
    so2 = coda.fetch(pf, '/HDFEOS/GRIDS/OMI_Total_Column_Amount_SO2/Data_Fields/ColumnAmountSO2_PBL')
finally:
    coda.close(pf)

product = harp.Product()
product.latitude = harp.Variable(latitude, ["latitude"])
product.latitude.unit = "degree_north"
product.longitude = harp.Variable(longitude, ["longitude"])
product.longitude.unit = "degree_east"
product.so2_column_number_density = harp.Variable(so2, ["latitude", "longitude"])
product.so2_column_number_density.unit = "DU"
harp.export_product(product, "omi-so2-20200610.nc")