As long as you don't admit that the models are wrong, you're opposed to science.
Oh the irony.
Sigh. Fine, we'll do this again. Yes, of course the models are not perfect - they do not (and cannot) predict every last short-term wiggle. To a "black and white" viewpoint then that means they're *always* wrong - even when they reliably nail the long-term trend for over thirty years. This of course does not mean they are not still very useful to climatologists that know how to use them (and as long as you don't admit that, you're opposed to science, yes?)
So with that out of the way, when the models don't match closely to what we observe, we want to know why, so that we can improve them. From your own first link (again):
..both internal variability and external forcing contribute to the ‘slowdown’. The externally forced contribution is due to the combined cooling effects of a succession of moderate early twenty-first century eruptions, a long and anomalously low solar minimum during the last solar cycle, increased atmospheric burdens of anthropogenic sulfate aerosols, and a decrease in stratospheric water vapour
As you point out, internal variability (ENSO etc) alone is very unlikely to account for the discrepancies, but your own citation says that internal variability and the short-term external forcings listed above are responsible for the so-called "pause" (in tropospheric warming specifically), and the models do not adequately account for these (again, no surprise to actual climatologists). Meanwhile, other (and more important) climate models are tracking nicely; for example, "ocean warming estimates over a range of times and depths agree well with results from the latest generation of climate models" (which is accelerating rapidly).
if you think the cause was volcanoes and solar activity, this paper talks to you. You'll have to find some other explanation.
So when your first link from 2017 explicitly calls out volcanoes and solar activity (among other things) as significant factors, you cite a paper from 2013 (four years out of date) to claim that it can't be those - despite that same paper explicitly not ruling out external forcings like those as being a factor. You really need to read your own citations more closely.
Seriously, do you look at this and say, "Oh yeah, that's right"? If so, what is wrong with you?
I look at that and say, "I see it's 5 years out of date, big surprise". Then I say "what is that graph even representing? There's no labels". Then I look at more up-to-date data. (NB I'm assuming from your example that you're fine with linking to images on blogs, but at least try to use something current and well-sourced?)