Our tag description for heteroskedasticity says
Heteroscedasticity refers to the property of a random process that has non-constant variance along some continuum. This most commonly presents in regression where the error variance increases as a function of one or more predictors, but also commonly refers to a time series whose variance changes over time.
(Emphasis is mine.)
Q1: What does along some continuum mean here? I wonder if this could be rephrased in simpler terms without altering the meaning.
Q2: How does unconditional heteroskedasticity fit this description? It seems that the description requires conditioning on the continuum, and the examples given are these of conditional heteroskedasticity where the conditioning is w.r.t. one or more predictors or the time index.