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The first, and fastest, way to do this is through the GRIB Filter icon. This allows GRIB Filter and Regrid icons allow you to change the resolution and area of a GRIB field - see this tutorial for an example.

# ----------------------------------------------------------------------
# grid_to_grid
# converts the data_source fieldset onto the same grid as in data_target
# NOTE: all the GRIB meta-data is taken from data_target
# ----------------------------------------------------------------------
function grid_to_grid(data_source:fieldset, data_target:fieldset)
    result = nil
    data_target_gpt = grib_to_geo(data : data_target[1]) # convert the target grid to geopoints
    for i = 1 to count(data_source) do
        data_target_gpt_interpolated = interpolate(data_source[i], data_target_gpt) # interpolate to these grid points
import metview as mv

t = mv.retrieve(param='t', grid=[0.5, 0.5], area=[50, 10, 80, 40])
lsm = mv.retrieve(param='lsm', levtype='sfc', grid=[0.2, 0.2])

regridded_lsm = mv.regrid(data=lsm,
               new_values = values(data_target_gpt_interpolated) # extract the interpolated values
        new_data_target = set_values(data_target[i], new_values) # put the interpolated values into the target gridgrid_definition_mode='template',
        result = result & new_data_target
    end for
    return result
end grid_to_grid

# usage
a = read('mygrib_grid1.grib')
b = read('mygrib_grid2.grib')
b = grid_to_grid(b, a)  # regrid b to be the same as a
diff = a - btemplate_data=t)