| Hi bernulli, 1) Data are coming from multiple weather models. Primary data source is the German Weather service DWD with the ICON weather model. In my past experiences, the DWD ICON model performs best for many regions. DWD ICON has a global (~13 km), European (7 km) and a Central Europe (1-2 km) "domain". A higher resolution can improve forecast accuracy, but this is not guaranteed. For Open-Meteo APIs, multiple models are mixed together. Typically high resolution domains only provide 3-5 days of forecast, afterwards they are combined with a global model. For North American locations, I am going to add high resolution domains from NOAA as-well. 2) For now, only couple of months archive are available. There will be no limit of how much data can be stored. Data is fairly well compressed while still maintaining good read performance. I am working on a long term archive as well. ECMWF provides a reanalysis dataset called ERA5 [1] with data from 1959. It will still take me a couple of weeks to process it. With 23 weather variables, it requires around 20 TB disk space (Gridded float32 with deflate compression). [1] https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysi... |
I don’t think I understand the resolution then, could you explain a bit more? Say, I request data along a 100km line, every 10m. Do I get the same numbers if it’s in the same mesh cell with a sudden change when it’s crossed, or do I get some (bilinear?) interpolation?