  Characterization of the redshift distribution of ensembles of galaxies is
pivotal for large scale structure cosmological studies. In this work, we focus
on improving the Self-Organizing Map (SOM) methodology for photometric redshift
estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year
6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES
Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the
underlying redshift distribution. We investigate three strategies for enhancing
the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM
algorithm with one tailored for redshift estimation challenges; 2)
Incorporating $\textit{g}$-band flux information to refine redshift estimates
(i.e. using $\textit{griz}$ fluxes as opposed to only $\textit{riz}$); 3)
Augmenting redshift data for galaxies where available. These methods are
applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our
analysis indicates significant improvements with the first two strategies,
notably reducing the overlap between redshift bins. By combining strategies 1
and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by
up to 66$\%$. Conversely, the third strategy, involving the addition of
redshift data for selected galaxies as an additional feature in the method,
yields inferior results and is abandoned. Our findings contribute to the
advancement of weak lensing redshift characterization and lay the groundwork
for better redshift characterization in DES Year 6 and future stage IV surveys,
like the Rubin Observatory.
