ds = xr.open_zarr("https://data.dynamical.org/noaa/gfs/analysis-hourly/latest.zarr")
ds["temperature_2m"].sel(time="2024-04-01T00:00").plot()
ds["temperature_2m"] \
.sel(time="2024-04-01T00:00") \
.plot()
tmp_april_mean = ds["temperature_2m"] \
.sel(time=ds.time.dt.month == 4) \
.mean(dim="time")
tmp_april_2024 = ds["temperature_2m"] \
.sel(time="2024-04") \
.mean(dim="time")
(tmp_april_2024 - tmp_april_mean).plot()
(
ds["precipitation_surface"].sel(
latitude=slice(70, 20),
longitude=slice(-150, -30)
)
.mean(dim="time") # take the average over ~all time~
.plot()
)
(
ds["precipitation_surface"].sel(
latitude=slice(70, 20),
longitude=slice(-150, -30)
)
.mean(dim="time") # take the average over ~all time~
.plot()
)
import numpy as np
wind_speed = np.sqrt(
ds["wind_u_10m"] ** 2 +
ds["wind_v_10m"] ** 2
)
wind_speed \
.sel(time="2024-04-10T00") \
.plot(cmap="YlGnBu_r")