Site-adaptation of Solargis data

Combine benefits of satellite-derived and measured irradiance data

If good-quality irradiation measurements for period of at least 9-12 months are available from vicinity of project site, SolarGIS satellite-derived data can be site-adapted with objective of improving overall bias and fit of the frequency distribution function. As a result of improved irradiation inputs, uncertainty of estimated energy output is reduced.

The data adaptation is effective for mitigating systematic problems in the satellite-derived data such as under/over-estimation of local aerosol loads, especially when the magnitude of this deviation is invariant over the time or has a seasonal periodicity. The accuracy-enhancement methods are capable to adapt satellite-derived DNI and GHI data to the local climate conditions that cannot be recorded in the original satellite and atmospheric inputs. However, the methods have to be used carefully, as inappropriate data adaptation approaches may even result in accuracy degradation.

As developers of the SolarGIS model, and with experience of working with irradiation and meteorological measurement from hundreds of sites globally, we are best placed to further improve accuracy of SolarGIS data when on-site measurements are available.

Site adaptation of Solargis data Solargis

The Solargis approach to site adaptation

Detailed quality assessment of ground measurements

Successful site adaptation requires use of irradiation measurements that have substantially lower uncertainty that that of the primary satellite derived data. However, irradiation measurements are subject to several sources of error. Therefore prior to using GHI and DNI measurements for adaptation of SolarGIS data, we assess the quality of the measurements. Data readings that do not pass QA tests are flagged and excluded.

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Adaptation of SolarGIS model inputs

Data parameters that are used as inputs in the SolarGIS model i.e. Aerosol Optical Depth, Water Vapour, and Cloud Index, are adapted with the objective of reducing bias, RMSD, and KSI (between modeled and measured datasets).

Re-computation of GHI and DNI

GHI and DNI data are re-computed using SolarGIS model and the adapted model inputs. As a result, bias of modeled values is typically reduced to within ±1%, and RMSD and KSI are also reduced

Adaptation of modeled GHI and DNI values

After recalculation of GHI and DNI data with adapted model inputs, small bias may still remain. This is removed using statistical adaptation approaches. Modification of model inputs as first step, helps maintain GHI-DNI consistency and diurnal profile of the dataset.