  A workshop was recently held at Nagoya University (31 October - 02 November
2017), sponsored by the Center for International Collaborative Research, at the
Institute for Space-Earth Environmental Research, Nagoya University, Japan, to
quantitatively compare the performance of today's operational solar flare
forecasting facilities. Building upon Paper I of this series (Barnes et al.
2016), in Paper II (Leka et al. 2019) we described the participating methods
for this latest comparison effort, the evaluation methodology, and presented
quantitative comparisons. In this paper we focus on the behavior and
performance of the methods when evaluated in the context of broad
implementation differences. Acknowledging the short testing interval available
and the small number of methods available, we do find that forecast
performance: 1) appears to improve by including persistence or prior flare
activity, region evolution, and a human "forecaster in the loop"; 2) is hurt by
restricting data to disk-center observations; 3) may benefit from long-term
statistics, but mostly when then combined with modern data sources and
statistical approaches. These trends are arguably weak and must be viewed with
numerous caveats, as discussed both here and in Paper II. Following this
present work, we present in Paper IV a novel analysis method to evaluate
temporal patterns of forecasting errors of both types (i.e., misses and false
alarms; Park et al. 2019). Hence, most importantly, with this series of papers
we demonstrate the techniques for facilitating comparisons in the interest of
establishing performance-positive methodologies.
