There's been one little error in UAH's new data for the lower troposphere -- the baseline (1981-2010) for the global lower troposphere didn't have an average anomaly of zero. That's pretty trivial.
It's being fixed. The data is a beta version, after all. This is why you put it out there
But this raises a larger question. How can we trust any dataset that's put out there -- not just UAH's, but any and all of them, dozens if not hundreds?
The algorithms now are so complex that to be sure -- really sure -- I'd have to acquire the raw data, construct a data model (algorithm), and run it. Obviously I cannot do this, likely even if I had the time, certainly not for 99% of the data out there, and you can't either.
If I had to guess, I would say that none of the datasets is exactly right. All of them will contain errors. The big errors are easy to catch, because they're big, but anyone who's ever coded and worked with data knows there is the possibility of a zillions of little errors where your computer spits out numbers and that makes you happy.
At some point, when you get results that look plausible -- no obvious errors, lots of internal checks, reasonable agreement with other work (if there is such) -- you stop and say, here are my results. But judgement necessarily includes your own biases -- you simply cannot help it. But that doesn't mean there are no more errors.
It'd be wonderful if there were observations or experimental results to compare to. But that's very rare, and if such data did exist, you'd have checked yourself and not published it if there wasn't agreement.
This is a big problem in science, or in any field that does data analysis, especially when the science has public implications. We all believe the data we think supports our views, and have to struggle mightily to deal with data that doesn't. But it is always going to involve trust, and past results, and reputations, and more.
So when I point out some big changes in UAH's dataset, I really have no idea whether their version 6.0beta is better than v5.6 or now. It agrees better with RSS, so that's a strong point in its favor. On the other hand, some of its corrections are greater than 1 C, which is bigger than the warming expected since the start of their dataset.
Science moves a lot slower than public opinion. That should be a good thing, except in an environment like today's.