Documentation

Documentation Methodology

Source of meteorological data in the Solargis database

Meteorological data in the Solargis database are derived from numerical weather models. A summary of meteorological models from which Solargis sources data is given below.

 

 

Data Source Time period Original spatial resolution Original time resolution
ERA5, the fifth generation ECMWF atmospheric reanalysis of the global climate 1994 to D-9 0.25° by 0.25° 1 hour
Climate Forecast System (CFSv2) D-8 to D-2 0.205° by ~0.205° 1 hour
Global Forecast System (GFSprod) D-1 to D+9 0.12° by ~0.12° 1 hour (first 72h)
3 hours (up to D+9)
GPCC Global Precipitation Climatology version 2018 1891 to 2016 0. 25° by ~0.25° Monthly means

Given that the original spatial resolution of the meteorological data from these models is in the range of 0.12 to 0.25 degrees, the data characterize a wider geographic region rather than a specific site. The original spatial resolution of the models is enhanced to 1 km for air temperature and atmospheric pressure by spatial disaggregation and use of the Digital Elevation Model SRTM-3. The spatial resolution of other parameters remains unchanged.

If meteorological measurements are available from the vicinity of a solar project site, the measurements can be used for accuracy enhancement of the historical data derived from meteorological models.

 

Time step and spatial resolution of Solargis meteorological parameters

 

Meteorological parameter Acronym Unit Time resolution Original spatial resolution of model Final spatial resolution after post-processing Data source(s)
Air temperature at 2 metres (dry bulb) TEMP °C 1 hour 0.25°, 0.205° and 0.12° 1 km ERA5, CFSv2, and GFSprod
Monthly means 0.25° ERA5
Relative humidity RH % 1 hour 0.25°, 0.205° and 0.12° 25 km ERA5, CFSv2, and GFSprod
Atmospheric pressure AP hPa 1 hour 0.25°, 0.205° and 0.12° 1 km ERA5, CFSv2, and GFSprod
Wind speed at 10 metres and 100 metres WS, WS100 m/s 1 hour 0.25°, 0.205° and 0.12° 25 km ERA5, CFSv2, and GFSprod
Monthly means 0. 25° 25 km ERA5
Wind direction at 10 metres and 100 metres WD, WD100 ° 1 hour 0.25°, 0.205° and 0.12° 25 km ERA5, CFSv2, and GFSprod
Wind gust WG m/s   0.25°, and 0.12° 25 km ERA5, GFSprod
Precipitable Water PWAT kg/m2 1 hour 0.25°,
0.205° and 0.12°
25 km ERA5, CFSv2, and GFSprod
Monthly means 0. 25° 25 km ERA5
Snow water equivalent SWE kg/m2 1 hour 0.25°,
0.205° and 0.12°
25 km ERA5, CFSv2, and GFSprod
Precipitation PREC kg/m2 1 hour 0.25°,
0.205° and 0.12°
25 km CFSR, CFSv2, and GFSprod
Monthly means 0. 25° 25 km GPCC v2018
Module temperature TMOD °C 10/15/30 mins N.A. 1 km Derived from TEMP and Global Tilted Irradiation data
Cooling Degree Days and Heating Degree Days CDD, HDD degree days Monthly means N.A. 1 km Derived from TEMP. Base temperature
18°C (64 °F)

Post-processing of air temperature data

Temperature data derived from the meteorological models are post-processed by Solargis to achieve improved accuracy and homogeneity over long time period. Overview of the post-processing methods applied is given below.

Elevation correction

The original spatial resolution of temperature data derived from numerical weather models is too coarse to accurately represent the temperature in regions with variations in elevation. This problem can be overcome if the vertical rate of change in temperature is known. This rate is known as the lapse rate. The lapse rate can change with time and from one location to another, it is influenced by weather patterns and local micro-climatic and topographic features. Normally, the temperature decreases as the site's altitude increases. However, near the surface, occurrence of temperature inversion (temperature increase with increasing altitude) is not uncommon. This is the typical case over cold surfaces, for instance.

In addition to temperature at 2 meters over the surface, weather models also provide temperature data at every model layer from the surface to the top of the atmosphere. Using the vertical profiles of temperature, a simplified parameterization of the vertical change of temperature is devised. The lapse rate calculated is then used for spatial downscaling of temperature data to 1 km resolution.

Homogeneization of ERA5 and CFSv2 datasets

The historical archive of air temperature data in the Solargis database is derived from 2 numerical weather models – ERA5 (for period 1994 up to D-9) and CFSv2 (D-8 to D-2). At many locations worldwide, there is a non-negligible jump between the ERA5 and the CFSv2 temperature trends which appears unreal. In order to achieve a homogenized time series of temperature data (from 1994 to present time) a pixel-wise linear transformation of the CFSv2 data to match the ERA5 values has been done. This has been accomplished using the ERA5 dataset as an underlying reference since it also covers the period for which CFSv2 outputs are available.

Ground measured temperature data from reliable sources have been used as a reference to calculate accuracy statistics. The local-scale biases can also be corrected by Solargis - however this is a time-intensive exercise and therefore only done on request as part of site-specific resource assessment studies (offered as a consultancy service by Solargis).