Prospect
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Forecast services are now providing predictions up to 15 days ahead. This is related to the recent integration of input parameters from the GFS model, which have been extended to day +15.
Within the release of this new version, improvement on data post-processing methods affecting forecasting of atmospheric pressure (AP) has been implemented too.
GOES-R satellite located at 75º West longitude (East location) covering mostly the West coast of continental US and Canada was updated in our historical time series for the period of May to December 2019.
Bug fixes:
Previously, time series data were incorrectly calculated for late afternoon hours for the 1st and last day of the month for the whole period of May to December 2019. It resulted in an underestimation of the cloud coverage for corresponding time series data.
This issue is now fixed in the updated version of our model v2.2.12. All data previously impacted for the west coast of continental US and Canada (approximately 0.5-1%) were correctly recalculated.
For Europe, forecasts for lead time from 2 hours up to 120 hours is now based on blending of forecasts from 2 NWP models - IFS (ECMWF) and ICON-EU (DWD). In general, IFS is considered as the best performing global NWP model. Yet, we've seen many instances when the IFS forecasts error was quite high. To limit the occurrence of large forecast errors, henceforth a blended forecasts of IFS and ICON-EU models will be used.
Overall, the new approach is expected to improve accuracy of both intra-day and day-ahead solar power forecasts.
Currently, forecasts from the ICON-EU model is being used only for Europe. We are working on implementation of forecasts of ICON model also for other regions.
For a more detailed explanation see this update on our Productboard.
Solar radiation data for West Coast of USA and Canada, and Hawaii, for late afternoon hours on first and last day of each month in 2020 was incorrectly calculated, resulting in underestimation of cloud coverage. The issue was fixed and data for all affected days in 2020 was recalculated. Approximately 1% of all 2020 data in the west coast of continental US and Canada, and 2% of 2020 data for Hawaii was affected. Central and Eastern parts of Canada and US were not affected by this issue.
New parameters on ultra-violet radiation are now available within Solargis historic time series. A set of two parameters is provided, UVA (ultraviolet A, from 315 to 400 nm wavelength) and UVB (ultraviolet B, from 280 to 315 nm wavelength).
This new data is based on spectral splitting of ERA5 broadband UV data, so there is no direct connection to the irradiance model used for GHI, DNI and DIF. Available for global coverage.
Improved blending of satellite-based nowcasts with forecasts based on NWP models. Previously, nowcasts were used for forecast lead time of 0-4 hours, and NWP based forecasts were used for forecast lead times of 4+ hours. However, in some regions NWP forecasts already gives better results for forecast lead time of 3-4 hours. Thus a new blending method was implemented. Now, by default, full nowcasts is used up to hour 2, from hour 2 up to hour 4 the weight of nowcasts decreases from 1 to 0. From hour 4 only NWP forecasts are used. The default settings can be customized on per site basis where needed.
Key features:
Bug fixes:
Improved aggregation of 10 minute time series (native resolution) to 15 minute time step. Previously implemented aggregation resulted in 'steppy' profile during cloudless situations. A new aggregation method was introduced to avoid these features.
Improved merging of multiple data sources for a given parameter. As example, data merging methodology of historical and recent temperature data from 3 different sources, ERA5, CFSv2, and GFS, was updated. This update has been made to allow improved data handling that is required for advanced blending of multiple forecast models. The impact on historical data values will be negligible.
We achieved global coverage (between latitudes 60N and 50S) for recent and historic data already few years back. Yet, there were some gaps in the coverage for operational data services. These gaps were in overlapping satellite zones, where we had satellite imagery from more than 1 satellite mission. As a result a decision making process was required to define which satellite data source should be use.
The simple solution would have been to draw a straight line to define the coverage for different satellites. But this was not an acceptable solution, as it would result in spatial inconsistency of the solar radiation outputs. As a solution, we have carefully defined the border of the satellite coverage zone to be along physical and political borders. This way the spatial consistency is mostly maintained and our customers can now request data for any location between 60N and 50S latitudes via API. Also the delivery time for historic data via climData online app in these regions is now 5-10 minutes instead of 1 working day.
