openmeteo_get_ensemble

io.github.cyanheads/open-meteo-mcp-server · Verify this server

Probabilistic ensemble weather forecast — up to 64 ensemble members, up to 16 days ahead with optional past_days (0–92). Each member's values appear as separate columns named with a member suffix (e.g. temperature_2m_member01, temperature_2m_member02). Use the spread across members to compute exceedance probabilities, quantify forecast uncertainty, and build decision thresholds. Available models: ecmwf_ifs025_ensemble (51 members, global 0.25°), ecmwf_aifs025_ensemble (51, global 0.25°), ecmwf_ifs_europe_ensemble (51, Europe 9 km), ecmwf_aifs_europe_ensemble (51, Europe 31 km), google_weathernext2_ensemble (64, global 0.25°), ncep_gefs_seamless (31, global blend), ncep_gefs025 (31, global 0.25°), ncep_gefs05 (31, global 50 km, 35 days), ncep_aigefs025 (31, global 0.25°), icon_seamless_eps (20–40, global/Europe blend), icon_global_eps (40, global 26 km), icon_eu_eps (40, Europe 13 km), icon_d2_eps (20, Central Europe 2 km), gem_global_ensemble (21, global 0.25°), bom_access_global_ensemble (18, global 40 km), ukmo_global_ensemble_20km (18, global 20 km), ukmo_uk_ensemble_2km (3, UK 2 km), meteoswiss_icon_ch1_ensemble (11, Central Europe 1 km), meteoswiss_icon_ch2_ensemble (21, Central Europe 2 km). Omit models to use the API default blend. A regional model returns no data outside the area it covers; that comes back as an input error naming the coverage gap, not a transient failure, so pick a global model or move the coordinate inside the region rather than retrying. A model name this list does not carry is still sent upstream, so a newly added one keeps working. Large multi-member, multi-day pulls produce thousands of records and spill to DataCanvas when canvas is enabled, returning a bounded preview with truncated: true when it is not. At least one of hourly_variables or daily_variables is required.