A couple of years ago, Anthony observed a gross discontinuity at Lampasas TX arising from a change in station location. Let’s see how the Berkeley algorithm deals with this gross discontinuity.
At the time, I discussed the difference between Lampasas and nearby Blanco under various USHCN (v1) versions, the one below using their “adjusted: (filnet) version. As Anthony had observed, the USHCN adjustment algorithm was unequal to the task of identifying a gross discontinuity.
Here is the corresponding result from BEST. The BEST algorithm fails to pick up the Lampasas discontinuity. In fact, its hard to see precisely what the algorithm does other than introducing “off-centered” monthly normals. [Update – a reader points out below that the homogenization method appears to be applied to this data i.e. this data might well be split in the homogenization step. This seems plausible to me.]