With rapid advances in HPC resources, more complex simulations have resulted
in larger data size, with higher resolution and many variables. Visualizing
large multivariate datasets is a challenging problem that often requires
high-end clusters. Consequently, novel visualization techniques are needed to
explore such complex data. Explorable image (EI) is a novel approach that
provides limited interactive visualization without the need to rerender from
the original data. In this work, we used the concept of EI to create a
workflow that generates explorable iso-surfaces for scalar fields in a
multivariate, time-varying dataset. We present a run-time tool that allows
the user to interactively browse and calculate a combination of iso-surfaces
superimposed on each other. The result is the same as calculating multiple
iso-surfaces from the original data but without the memory and processing
overhead. Our tool also allows the user to change the (scalar) values
superimposed on each of the surfaces, modify their color map, and
interactively re-light the surfaces. We demonstrate the effectiveness of our
approach over a multi-terabyte combustion dataset. We also illustrate the
efficiency and accuracy of our technique by comparing our results with those
from a more traditional visualisation pipelines.