  Solution intervals are often used to improve the signal-to-noise ratio during
radio interferometric gain calibration. This work investigates how factors such
as the noise level, intrinsic gain variability, degree of model incompleteness,
and the presence of radio frequency interference impact the selection of
solution intervals for calibration. We perform different interferometric
simulations to demonstrate how these factors, in combination with the choice of
solution intervals, affect calibration and imaging outputs and discuss
practical guidelines for choosing optimal solution intervals. Furthermore, we
present an algorithm capable of automatically selecting suitable solution
intervals during calibration. By applying the algorithm to both simulated and
real data, we show that it can successfully choose solution intervals that
strike a good balance between capturing intrinsic gain variability and not
fitting noise as long as the data are not too inhomogeneously flagged.
Furthermore, we elaborate on several practical aspects that emphasize the need
to develop regularised calibration algorithms that do not require solution
intervals.
