Update of Prospect database to v1.1

The underlying database in the Solargis Prospect has been completely updated (previously version 0.98, now version 1.1). The period for statistics calculation was extended with two recent years for all solar resource and relevant meteorological parameters. Previously, data were calculated for the period up to 2018. The updated data represents the period up to 2020.

The relative differences of the long-term average of yearly totals for GHI and DNI (two main solar resource parameters) between the actual and previous database versions are shown in the maps below.

For most of the areas, the difference between the two versions is within ±0.5% and ±1.5% for GHI and DNI respectively. More significant variations occur in some regions, specifically:

• Most of Australia: GHI and DNI totals in the last two years were extraordinarily high. Therefore, the long-term average of GHI and DNI are higher by more than 1% and 2% respectively (see Fig. 3).
• Central China: GHI and DNI totals in the last two years were extraordinarily low. Therefore, the long-term average of GHI and DNI are lower by more than 1% and 2% respectively (see Fig. 4).
• Mountainous areas and far Northeast in Asia: availability of multi-spectral data from Himawari (operable from 2016) and MSG (operable over Asia from 2017) satellites enable more accurate snow identification and cloud properties in these geographically complex regions.

In general, we observe larger variations in the long-term average data in Australia and the East Asia region. Note that the relevant satellite data in those regions are available from 2007, thus the recent 14 years are involved in the calculation. Unlike in Europe or Africa, where the Solargis database goes back to 1994 (recent 27 years), in Australia we see that one or two extreme years can notably influence the long-term average.

Besides the extension of the data period, further enhancements were implemented to the Solargis model. Notable:

• Monthly long-term averages of ground albedo are implemented in the calculation of GTI, GHI, and PV electricity output
• Improved solar resource modeling of losses/gain due to terrain horizon