1. It's fast.
2. It's tolerant of poor programmers.
Regarding item 2: People who want to specialize in scientific computing intentionally avoid becoming good programmers. Most of them are not in CS, but in some other engineering or in science. They want to focus on their discipline (e.g. climate science as this example gives). They don't care about code quality, or even SW practices (e.g. when I was in grad school a little over a decade ago, I couldn't get a single one of my colleagues to use version control - and some of them had codebases in the tens of thousands of lines).
They are not judged by the quality of their code, but by the results their code produces. They don't show their code in their papers, but the plots/tables. So they'll use the language that puts up the least barriers, and is performant. Hence, Fortran.
(Incidentally, many of them don't care about reproducibility. They'll modify their large codebase, spit out some results, publish them, and then add new features, and will never check if the modified codebase will continue to give the same results for the same inputs).
All the other reasons in the article? Insignificant factors.
Edit: Note that I'm not saying that if you code in Fortran you're a poor programmer or use poor practices. And I'm sure there are good Fortran code bases around.