⛈ K-Index#
The K-Index is one indicator of thunderstorm potential
\[K = (T_{850} - T_{500}) + Td_{850} - (T_{700} - Td_{700})\]
Where \(T\) is temperature and \(Td\) is dew point temperature at the level in hPa.
K values +20 indicate some potential for air mass thunderstorms.
K values +40 indicate almost 100% chance for air mass thunderstorms,
with values over +30 to indicate potential MCC’s.
Cool temperatures aloft and warm temperatures below are associated with instability at the surface (resulting in rising motion). Dry air aloft will lower the K value because when dry air entrains in a cumulus cloud it restricts it’s thunderstorm growth.
[1]:
from herbie import Herbie
from herbie.toolbox import EasyMap, pc
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
[2]:
ds = Herbie("2021-04-28 23:00").xarray("(TMP|DPT):(500|700|850) mb")
✅ Found ┊ model=hrrr ┊ product=sfc ┊ 2021-Apr-28 23:00 UTC F00 ┊ GRIB2 @ aws ┊ IDX @ aws
C:\Users\blaylock\_GITHUB\Herbie\herbie\archive.py:722: UserWarning: This pattern is interpreted as a regular expression, and has match groups. To actually get the groups, use str.extract.
logic = df.search_this.str.contains(search)
C:\Users\blaylock\_GITHUB\Herbie\herbie\archive.py:1041: UserWarning: sorry, on windows I couldn't remove the file.
warnings.warn("sorry, on windows I couldn't remove the file.")
[3]:
ds
[3]:
<xarray.Dataset>
Dimensions: (isobaricInhPa: 3, y: 1059, x: 1799)
Coordinates:
time datetime64[ns] 2021-04-28T23:00:00
step timedelta64[ns] 00:00:00
* isobaricInhPa (isobaricInhPa) float64 850.0 700.0 500.0
latitude (y, x) float64 21.14 21.15 21.15 ... 47.86 47.85 47.84
longitude (y, x) float64 237.3 237.3 237.3 ... 299.0 299.0 299.1
valid_time datetime64[ns] 2021-04-28T23:00:00
Dimensions without coordinates: y, x
Data variables:
t (isobaricInhPa, y, x) float32 281.0 281.0 ... 248.5
dpt (isobaricInhPa, y, x) float32 276.0 275.9 ... 236.7
gribfile_projection object None
Attributes:
GRIB_edition: 2
GRIB_centre: kwbc
GRIB_centreDescription: US National Weather Service - NCEP
GRIB_subCentre: 0
Conventions: CF-1.7
institution: US National Weather Service - NCEP
model: hrrr
product: sfc
description: High-Resolution Rapid Refresh - CONUS
remote_grib: https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr....
local_grib: C:\Users\blaylock\data\hrrr\20210428\subset_2eef...
search: (TMP|DPT):(500|700|850) mb[4]:
T850 = ds.t.sel(isobaricInhPa=850)
T500 = ds.t.sel(isobaricInhPa=500)
D850 = ds.dpt.sel(isobaricInhPa=850)
T700 = ds.t.sel(isobaricInhPa=700)
D700 = ds.dpt.sel(isobaricInhPa=700)
[5]:
K = (T850 - T500) + D850 - (T700 - D700) - 273.15
[6]:
K.plot()
[6]:
<matplotlib.collections.QuadMesh at 0x1fdfa1c7d90>
[7]:
# Make a custom colormap
cmap = mcolors.LinearSegmentedColormap.from_list("k-index", ["w", "orange", "r"], 3)
cmap.set_over("k")
cmap.set_under("#3333ff10")
norm = mcolors.BoundaryNorm([0, 20, 30, 40], 3)
[8]:
ax = EasyMap(crs=ds.herbie.crs, figsize=[10, 5]).STATES().ax
K.plot(x="longitude", y="latitude", ax=ax, cmap=cmap, norm=norm, transform=pc)
str_date = K.valid_time.dt.strftime("%H:%M UTC %d %b %Y").item()
plt.title("K Index", loc="left")
plt.title(str_date, loc="right")
plt.title("HRRR", loc="center")
[8]:
Text(0.5, 1.0, 'HRRR')
