The National Solar Radiation Database (NSRDB) has provided solar resource data for over 25 years. Its most recent update, namely, physical solar model (PSM) version 3, generates half-hourly, gridded, satellite-derived irradiance data with a spatial resolution of 4 km x 41cm, covering most of America. The total volume of the data is over 40 TB. Since the main method to access the data is using API with a daily limit of 2000 requests, it would require 1000 days to obtain one year of PSM data from approximately 2 million pixels. Furthermore, such a big dataset is difficult to store and manipulate. In this regard, this paper empirically investigates the accuracies of various kriging methods, so that a suitable, dimension-reduced (in space) dataset can be opted during various spatio-temporal analyses, such as forecasting or monitoring network design.