What is the difference between reconstruction error and variance explained?

Reconstruction error measures loss after compression; variance explained measures retained information.

In PCA, variance explained quantifies how much of total data variability is captured by selected components. Reconstruction error measures how accurately original data can be reconstructed from reduced dimensions. They are mathematically related but differ in interpretation: one is informational, the other is geometric error.