Solargis

Key Takeaways

• Solargis = premium global solar resource database.
• Satellite-derived hourly GHI/DNI/POA.
• Used for bankable EYA, especially tropical/desert sites.
• More accurate than Meteonorm for many regions.
• Commercial license.

How Solargis Fits Into a Yield Simulation

Every bankable Energy Yield Assessment starts from a weather file, and Solargis is the premium option when the site sits somewhere the default source can’t be trusted. Instead of interpolating from ground stations the way Meteonorm does, Solargis builds its hourly GHI, DNI, DHI, and POA dataset almost entirely from satellite imagery, cross-checked against a global network of ground reference stations.

That satellite-first approach is what makes it especially strong in tropical and desert regions, exactly the places where sparse ground-station coverage leaves Meteonorm’s interpolation carrying more uncertainty. A designer pulls the Solargis dataset for the project coordinates, feeds it into PVsyst as the weather source, and runs the same transposition, temperature, and loss models that ultimately produce the P50/P90 numbers a lender signs off on.

Worked Example

Consider a utility-scale ground-mount project in a tropical location with only sparse ground-weather-station coverage nearby. Rather than defaulting to Meteonorm’s interpolated TMY, the engineer purchases a Solargis dataset for the exact site coordinates, since its satellite-derived hourly data is generally considered more reliable in regions like this one.

That dataset becomes the weather input for the PVsyst simulation, and because the lender’s independent engineer will want to see the weather-source choice justified, the final EYA typically documents why Solargis was selected over the default option for this specific geography, often alongside a Meteonorm cross-check run to show how much the choice of weather source actually moves the yield number.

Related Reading

Weather-source selection is one of the highest-leverage decisions in a bankable yield study, because it directly shapes the P50/P90 range a lender will underwrite against.

Our advanced PVsyst analysis guide on how accurate yield predictions save millions walks through how weather-source uncertainty flows into that final number, and the bankable PVsyst reports guide covers what an independent engineer expects to see documented when Solargis is used instead of the default source.

If you’re still comparing simulation platforms and weather-data workflows more broadly, the best solar design software roundup for 2026 is a useful next stop, and for engineering teams outgrowing residential-only tools, Arka360 alternatives for India EPCs touches on how bankable weather-data sourcing factors into that decision.