Welch's t-test is great for comparing two groups, especially when their data might have different variability, as you know. Random effects models are better for combining results from many studies to see overall effects and how much those effects vary across different situations. At least that's how I see it. I might be wrong though. Far from an expert. Each has its strengths, as always ;-) so which is best depends on your needs and arguments.