  Recently, a set of graph-based tools have been introduced for the
identification of singular events of O3, NO2 and temperature time series, as
well as description of their dynamics. These are based on the use of the
Visibility Graphs (VG). In this work, an improvement of the original approach
is proposed, being called Upside-Down Visibility Graph (UDVG). It adds the
possibility of investigating the singular lowest episodes, instead of the
highest. Results confirm the applicability of the new method for describing the
multifractal nature of the underlying O3, NO2, and temperature. Asymmetries in
the NO2 degree distribution are observed, possibly due to the interaction with
different chemicals. Furthermore, a comparison of VG and UDVG has been
performed and the outcomes show that they describe opposite subsets of the time
series (low and high values) as expected. The combination of the results from
the two networks is proposed and evaluated, with the aim of obtaining all the
information at once. It turns out to be a more complete tool for singularity
detection in photochemical time series, which could be a valuable asset for
future research.
