In order to facilitate comprehensive economic modeling of CSP/STE power plants realistic long-term meteorological datasets with temporal resolution down to 1 minute is a main premise. Currently available standard datasets do not fulfil this premise. The datasets also need to combine the high quality of well-maintained ground-based irradiance measurements and the global coverage of satellite-derived data. Even with the best available data it is necessary to account for the uncertainty in this and the sampling uncertainty from finite time-series to enable the optimal statistical characterization. It is a general challenge that satellite-derived data lack the required temporal resolution, and also often does not cover periods with major volcanic eruptions. Here we see prospects in synthetically generated realistic datasets, although research and development work is required on how to optimally produce and quality assure these.