The 10 most important parameters when choosing the best meteorological database for your projects
🗺️ Location. Databases usually cover a specific region of the planet. The same platform often provides different databases depending on the location.
⏰ Temporal resolution or frequency of measurements. It is advisable to use an hourly frequency. Higher frequencies (30, 15, or 5 minutes) can help make your simulations more precise, although they are not always available.
🛰️ Data source. Typically satellite images on which different validated models are applied to infer meteorological variables, although you can also find data measured at ground stations.
📐 Spatial resolution. Higher spatial resolution means that data is available in more detail. It is common to find databases with a resolution of at least 5 x 5 km².
⏳ Time interval. Refers to the time span covered by historical data. If you are using a typical meteorological year (TMY), it is recommended to use databases with at least 10 years of historical data available (according to the ISO 15927-4 standard).
🧮 Variables. It is advisable to have irradiance (global, direct, and diffuse), ambient temperature, and ground-level wind, although a greater number of variables such as aerosols or precipitation can increase the precision of the results.
🏔️ Horizon. It is important to consider this for locations with nearby mountains. Some databases like PVGIS take it into account, but others like NSRDB do not consider it automatically.
🏦 Bankability. Refers to the reliability and accuracy of the database. In financeable projects or power purchase agreements (PPAs), it is necessary to ensure generation to guarantee the profitability of the investment.
💵 Price. There are both free and paid databases. Paid databases usually offer greater guarantees (bankability) and are often a mandatory requirement for large-scale projects and solar farms.
🥇 Version. There may be several available versions of the same database. Whenever possible, use the most updated version, as it often contains improvements and corrections that make it more reliable than previous versions.
We have compiled a detailed table with the main meteorological databases available and their characteristics, including both free (PVGIS, NSRDB, ...) and paid ones (3E, Solargis, ...).