This looks essentially the same to @stefraynaud's answer, but I came across this stackoverflow response here: https://stackoverflow.com/questions/52094320/with-xarray-how-to-parallelize-1d-operations-on-a-multidimensional-dataset.

@andersy005, I imagine you're far past this now. And this might have been related to discussions with Genevieve and I anyways.

```python def new_linregress(x, y): # Wrapper around scipy linregress to use in apply_ufunc slope, intercept, r_value, p_value, std_err = stats.linregress(x, y) return np.array([slope, intercept, r_value, p_value, std_err])

return a new DataArray

stats = xr.apply_ufunc(new_linregress, ds[x], ds[y], input_core_dims=[['year'], ['year']], output_core_dims=[["parameter"]], vectorize=True, dask="parallelized", output_dtypes=['float64'], output_sizes={"parameter": 5}, ) ```