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")