Weather Data for Agriculture
Provides historic, current, and forecast weather data for agriculture globally.
Description
A data block that provides historic, current and forecast data for agriculture through the Meteomatics Weather API. These datasets are available worldwide starting with 1979.
See this block on the marketplace.
Technical information
Compatible blocks
- NetCDF → GeoTIFF Conversion
Geographic coverage
The geographic coverage is global.
Dataset information
Specifications | Description |
---|---|
Spatial resolution | To avoid reaching the query limit provided by the Meteomatics Weather API, the spatial resolution (in decimal degrees) for retrieving the time series of a weather parameter will be set based on the AOI size. The minimum resolution is 90 m (0.001 decimal degrees): 0.001 decimal degrees (AOI < 100 km2) 0.01 decimal degrees (AOI 100 - 10000 km2) 0.1 decimal degrees (AOI 10000 - 100000 km2) 1 decimal degree (AOI > 100000 km2) |
Dataset type | Optical and radar |
Satellite sensors | The dataset is a satellite composite that merges images acquired by the following geostationary sensors: GOES 16 GOES 17 Himawari 8 Meteosat 8 Meteosat 11 Meteosat MSG For more information, see Satellite Imagery. |
Revisit frequency | sub-hourly |
Data availability | Historical data: starting with 1979 Forecast data: up until 2100 |
Global weather forecasting model | mix |
File format | NetCDF |
Bit depth per pixel | 64-bit (float) |
Coordinate system | EPSG:4326 |
Can be reused in an UP42 workflow | No |
Limitations
The AOI must be minimum 0.01 km2.
Weather and climate parameters
Weather and climate parameters | Meteomatics parameter name | Example |
---|---|---|
Amount of precipitation in the previous interval [mm] | precip_<interval>:mm | precip_5min:mm |
Max. diameter of hail in the previous interval [cm] | hail_<interval>:cm | hail_6h:cm |
Instantaneous temperature AGL | t_<level>:<unit> | t_1000hPa:K |
Frost depth [cm] | frost_depth:cm | frost_depth:cm |
Chance for soil frost occurrence [%] | soil_frost:p | soil_frost:p |
Soil moisture deficit - a measure for droughts - deviation from long year average [mm] | soil_moisture_deficit:mm | soil_moisture_deficit:mm |
Soil moisture index at a certain depth [cm] | soil_moisture_index_<depth>:idx | soil_moisture_index_-15cm:idx |
Evapotranspiration of previous interval [mm] | evapotranspiration_<interval>:mm | evapotranspiration_1h:mm |
Accumulated growing degree days [gdd] | growing_degree_days_accumulated:gdd | growing_degree_days_accumulated:gdd |
Sum of grass land temperature [°C] | grass_land_temperature_sum:<unit> | grass_land_temperature_sum:C |
Leaf wetness index | leaf_wetness:idx | leaf_wetness:idx |
Phytophthora negative prognosis (index for safety measures against potato blight) | phytophthora_negative:idx | phytophthora_negative:idx |
Most similar year [y] | most_similar_year:y | most_similar_year:y |
For a complete list, see Agricultural Parameters.
How it works
Supported JSON parameters | Default value | Min | Max | Examples |
---|---|---|---|---|
time | "2020-01-01T00:00:00+00:00/2021-12-31T23:59:59+00:00" | 1979 | 2100 | "time": "2020-01-01T00:00:00+00:00/2021-12-31T23:59:59+00:00" |
variables | [ "precip_3h:mm", "soil_moisture_index_-15cm:idx", "grass_land_temperature_sum:C" ] | n.a. | n.a. | "variables": [ "frost_depth:cm", "soil_moisture_index_-15cm:idx","soil_moisture_deficit:mm", "grass_land_temperature_sum:C", "soil_frost:p", "precip_5min:mm"] |
time_series | null | 1979 | 2100 | "time_series": ["2021-03-31T00:00:00+00:00/2021-04-01T00:00:00+00:00", "2021-04-30T00:00:00+00:00/2021-05-01T00:00:00+00:00" ] |
time_interval | 3 | 1 | - | "time_interval": 6 |
bbox /intersects | null | 0.01 km2 | n.a. | Please check the examples from the JSON parameters. |
Disclaimer
It is not possible to run a test query in the job configuration window. The length of the forecasting period and the spatial resolution depend on the model from which the requested parameters originate.
Examples
Example of a workflow created with the data block Weather Data for Agriculture, based on a set of weather parameters:
Example of a workflow created with the data block Weather Data for Agriculture, based on a set of weather parameters:
Capabilities
Output
raster
custom | |
---|---|
variables | ${variables} |
up42_standard | |
---|---|
dtype | float |
format | NetCDF |
sensor | Meteomatics |
processing_level | l3 |