On acceptance: Acceptance of names depends on who you want them to be accepted by. Bland-Altman plots are simply Tukey mean-difference plots (and Tukey was there much earlier), so if you want statisticians to accept the name you possibly wouldn't name it after Bland and Altman. On the other hand, in some application areas (medicine or chemistry, perhaps), you'd probably get quizzical looks if you called mean-difference plots anything but Bland-Altman. [However, chances are someone was there before Tukey as well, many of these ideas are quite old.]
On a suitable name: If those things you're calling "truth" are actually "truth" (not just observations with error, say), I'd probably just call what you have a residual plot (though it looks like those differences are negative residuals); depending on how your truth was obtained you might hyphenate in a descriptive noun after "residual" (e.g. if it was based on some gold-standard calibration you might call it a residual-standard plot).
If your truth is really truth (and not just observations or even some higher-quality estimate) then you could even argue that error should be used in place of residual.
On the suitability of the plot as a diagnostic: How were those "truth" values obtained? Are those just the actual data? If so "truth" is arguably a misnomer, and in that case you'd expect there to be some negative correlation in that plot; it wouldn't necessarily suggest a problem at all. We have many threads which explain (or even prove) that plots of $y-\hat{y}$ vs $y$ will have a positive correlation, if your "difference" axis is $\hat{y}-y$ then you'd expect a negative linear trend when the regression model was appropriate.
What is the aim of the plot? How are you interpreting it?
Here's a few of the existing posts relating to the issue of plotting residuals vs data:
Trend in residuals vs dependent - but not in residuals vs fitted
Does it make sense to study plots of residuals with respect to the dependent variable?
What is the expected correlation between residual and the dependent variable?