## 2 Experimental Set-up
The map is based on [37], irradiation data are obtained from Global Solar Atlas 2.0, a free, web-based application developed and operated by Solargis s.r.o. on behalf of the World Bank Group, with funding provided by the Energy Sector Management Assistance Program (ESMAP). For additional information: [[https://globalsolaratas.info](https://globalsolaratas.info)]([https://globalsolaratas.info](https://globalsolaratas.info)). where \(\rho\) is the ground albedo, and \(\beta\) is the tilted angle of the PV array. Albedo is the fraction of \(\mathrm{G_{PROA}}\) and GHI on the ground that is reflected by a surface, with a value that can be significant, reaching up to 100 W/m\({}^{2}\). Albedo is close to zero when the surface is very dark, and albedo is 1 when the surface is bright white, metallic, or a mirror. A ground albedo value of 0.2 is widely accepted and is used in the modeling of PV systems [40]. To estimate \(\mathrm{G_{dpOA}}\), Equation (6) is used by assuming that the sky is a uniform source of diffused irradiance [41]. Thus, \(\mathrm{G_{dpOA}}\) can be found from DHI and the tilt angle of the PV array. \[\mathrm{G_{dpOA}}=\mathrm{DHI}\times\frac{1+\cos(\beta)}{2} \tag{6}\]  
If the PV module temperature, \(\mathrm{T_{m}}\), was not available, it can be estimated using the Sandia module temperature model shown in Equation (7). \[\mathrm{T_{m}}=\mathrm{G_{POA}}\left(\mathrm{e^{a+b\cdot v}}\right)+\mathrm{T_ {amb}} \tag{7}\]  
where \(v\) is the wind speed in m/s, a and b are parameters that depend on the module construction and materials, as well as the mounting configuration of the module. The table that lists representative values for a and b for various common module types and configurations is provided in [42]. The estimations of \(\mathrm{G_{POA}}\) and \(\mathrm{T_{m}}\) were implemented using PVLIB Python, initiated by Sandia National Laboratories and developed by the PVLIB community [43]. PVLIB calculations are documented on Sandia's PV Performance Modelling Collaborative (PVPMC). If no meteorological data were available, the meteorological data from PVGIS were used [44]. PVGIS provides historical satellite data from many locations in the world and has been extensively used in scientific publications. Monitoring sensors for PV systems in Alice Springs are cleaned fortnightly. The monitoring sensors in Italy are not cleaned periodically due to enough rain and low soiling rates. However, information regarding the sensors used in the monitoring system and maintenance of the sensors is not given for systems in Indonesia. The history of the plants and the record of the inverter failures are also available for systems in Alice Springs. Accordingly, we translated the moments of inverter failure into missing values and later dropped them from the analysis. Of all systems, only the system in Cirata is known to be free from any obstacles causing shading on the PV arrays throughout the year. The PV system in Italy has shading from the surrounding mountains, but that holds for the systems as well as for the irradiance sensors and simple filter-detected moments, where one is shaded but the others are not. For the other systems, there is no information available about shading. The climates are classified according to Koppen-Geiger, which takes differences in temperature and rainfall as the basis for classification [45; 46; 47]. In the Koppen-Geiger classification, the Earth is classified into five main climate classes and 30 subtypes. The codification of the climate classes uses two or three letters (Figure 2). The first letter represents the five climate groups, where A is for equatorial or tropical, B is for arid, C is for warm temperate, D is for cold or snow, and E is for polar. Furthermore, subgroups are assigned as the second letter, which indicates the type of precipitation (water vapor condensation product in the atmosphere). The third letter, if applicable, represents the air temperature. Countries around the equator are covered by climate A.