Data Sources
Last updated
Last updated
WeatherLayers GL can be used either with custom self-hosted data or with WeatherLayers Cloud.
For integrating any custom data (NetCDF, GRIB), the data needs to be transformed by your backend server to a supported data type, data format and map projection.
public data sources - NOAA (GFS, GFS Wave), Copernicus (CMEMS, CAMS)
other public data sources - ECMWF, ICON, Copernicus (ERA5), ...
commercial data sources
custom data sources - your own data from scientific research
Uint8
quantized data into 256 possible values
lower precision, higher compression ratio for lower file size
recommended for visualization purposes
original data bounds need to be provided to unscale the data into the original data, see
Float32
original data
better precision, lower compression ratio and larger file size
recommended for scientific purposes, or for use cases where exact values with no quantization errors are needed
PNG, WebP (Uint8)
scalar - R channel
nodata - 0
in A channel
vector - RG channels
nodata - 0
in A channel
GeoTIFF (Uint8)
scalar - band 1
nodata - 0
in band 2
vector - bands 1 and 2
nodata - 0
in band 4
GeoTIFF (Float32)
scalar - band 1
nodata - NaN
in band 1
vector - bands 1 and 2
nodata - NaN
in bands 1 and 2
equirectangular projection (EPSG:4326)
Data transformation into a supported format can be done on your servers with GDAL.
Scale from [213.15, 325.15] to [0, 255], disable GDAL unit normalization from K to C:
WeatherLayers GL configuration:
imageType: WeatherLayers.ImageType.SCALAR
imageUnscale: [213.15, 325.15]
Calculate vector magnitude:
Merge files:
Scale from [-128, 127] to [0, 255]:
WeatherLayers GL configuration:
imageType: WeatherLayers.ImageType.VECTOR
imageUnscale: [-128, 127]
See for transformations between data types and data formats.
See for transformations between map projections.
See for calculations and for merging files.