  In this work we analyse a set of benchmark methods for solar irradiance
forecasting based on the clear-sky index, namely, persistence, climatology,
smart-persistence and convex combination (CC) of persistence and climatology.
To assess the boundaries of the benchmarks, we include in the analysis a simple
least squares regression technique that uses the last five past samples. For
the methods that need data adjustment, we also analyze their variation with
different training sets. This work is done for intra-day forecast of global
solar horizontal irradiance with 10-minutes and hourly forecast horizons. Our
results, obtained in the south-east region of South America known as Pampa
H\'umeda, confirm the benchmark recommendation, showing that the CC method is
exigent for RMSD as it achieves almost the same performance of the more complex
linear combination of past measurements. We also observe that the benchmarks
have different behavior depending on the metric, as the most exigent benchmark
for one metric is not necessarily the most exigent for another.
