I have been trying to figure out a problem, reported by two or three users, in which ticking the box in autolearn for using previous years’ data hurt forecast accuracy, when it should have been helping. I’d been sent some files (mainly correc.txt) with puzzling effects of ticking the box, the most consistent being that the diurnal range bias correction value (“rgcor”) would hit its ceiling value of 1.25 when that box was ticked. The effect is mainly to makes the daytime highs a bit too warm and/or nighttime lows too cold.
Thanks to a recent big batch of compare and contrast files Henrik sent to me, I think I’ve figured it out (and am awaiting his test results), but it’s an important enough issue so I’m going public with it now. I realized that in a little temporary file which communicates between autolearn and wret, I had put values on one line separated by commas. However, in countries where commas are used as decimal separators, these get all strung out in one line, so that when wret reads it, it chops it up wrong and gets a mixture of whole numbers and zeros, instead of separate decimal values. I’ve long known about this issue, and have addressed it throughout my programs, but somehow this one slipped through!
Anyway, if I’m right, this is good news, because if you’ve been suffering from this bug, your forecasts may be about to get better than ever! If you think you might be affected (or even if you’re not), here are the new versions to try. They need to be done together:
www.wxsim.com/autolearn.exe
www.wxsim.com/wret.exe
Use these to replace your existing ones. Autolearn is now Version 3.5, and wret is still Build 1.2, but with a “b” after it. If this fixes the problem, you can tell because in correc.txt, a column of 1.25’s may suddenly turn into something closer to 1.
One piece of good news: I do not thing there are many “after-effects” of this which would preclude immediate or continued use of the use of older data in the analysis, because wret “knows” what bias corrections were used in the forecast - even if they were bad ones - and calculates knew ones with that taken into account. It still may take it a while to settle into optimal performance, but it should start to get better right away.
Let me know what you find! And sorry about the bug!!
Tom