...
- BSSA_14 - As mentioned above, COEFFS table is not quite the same, so this is the expected result.
- This is because of
_get_basin_depth_term. Within the OQ, with our usage, Global a.k.a nobasin in OQ term, basin_depth_term is basically 0 but within EE, we get something. - Unfortunately, paper was not really clear, it did indicate to add basin_depth_term for California and Japan, but any other region was not mentioned.
- This is because of
- CB_14 - This is also expected because in the EE version of CB_14 when they estimate width, instead of using either the provided Ztor or estimated one, they estimate Ztor again to calculate width and then set Zhyp(hypo_depth) to 9.0. In contrast, with OQ(once our changes apply), the model will not estimate Ztor again while estimating width, and we do not set Zhyp to 9.0 while calculating width.
- K_20_NZ -
This is something different. Previously(calc_emp_ds), we also used the OQ's K_20 model, so nothing to do with EE. The K_20 is fine, but K_20_NZ is different. We need some investigation into this.- The mystery is solved now, when we generated GNZL, we did not multiply by 1000 on Z1.0.
ZA_06 - This is expected because of the following behaviour:
Code Block language py theme Midnight # In the EE version of ZA_06 # convert to median in g sa = np.exp(log_sa) / 981 # In the OQ version of ZA_06 from scipy.constants import g sa = np.exp(log_sa) * 1e-2 / g # where g = 9.80665
...