Flight plan - KA-20240907a#
ec_under ec_track in_cloud insitu_aerosolCrew#
The flight is planned to take off at 2024-09-07 14:30:00+00:00.
Job |
Name |
---|---|
PI |
Tim Carlsen |
Instrument operator |
Sorin Ghemulet |
Instrument operator |
Alex Vlad |
Flight plan#
Leg 1: RAI -> WP1 (arrive @FL060 at 15:05 UTC | 14:05 LT)
Leg 2: Holding pattern at WP1 until 15:25 UTC (assessing cloud situation)
Leg 3 (Start 15:25 UTC): WP1 -> WP3 (via WP2) - around FL020-FL060 - 140 kt (~40min) - in-cloud if possible Note: Be at WP2 at 15:45 UTC | 14:45 LT for satellite overpass
Leg 6: WP3 -> RAI (~25min).
Show code cell source
from orcestra.flightplan import sal, bco, LatLon, IntoCircle, path_preview, plot_cwv
from datetime import datetime
import intake
import easygems.healpix as egh
cat = intake.open_catalog("https://tcodata.mpimet.mpg.de/internal.yaml")
# Define dates for forecast initialization and flight
issued_time = datetime(2024, 9, 5, 0, 0, 0)
issued_time_str = issued_time.strftime('%Y-%m-%d')
flight_time = datetime(2024, 9, 7, 12, 0, 0)
flight_time_str = flight_time.strftime('%Y-%m-%d')
flight_index = f"KA-{flight_time.strftime('%Y%m%d')}a"
print("Initalization date of IFS forecast: " + issued_time_str + "\nFlight date: " + flight_time_str + "\nFlight index: " + flight_index)
airport = LatLon(lat=14.945, lon=-23.4863889, label='RAI')
wp1 = LatLon(lat=15.750969, lon= -23.810386, label='wp1')
wp2 = LatLon(lat=14.973537, lon=-23.962397, label='wp2 (ec-meet)')
wp3 = LatLon(lat=14.131217, lon=-24.126245, label='wp3')
leg_out = [
airport,
wp1
]
leg_calval = [
wp1,
wp2,
wp3
]
leg_home = [
wp3,
airport
]
path = leg_out + leg_calval + leg_home
cat = intake.open_catalog("https://tcodata.mpimet.mpg.de/internal.yaml")
ds = cat.HIFS(datetime=issued_time).to_dask().pipe(egh.attach_coords)
cwv_flight_time = ds["tcwv"].sel(time=flight_time, method = "nearest")
ax = path_preview(path)
plot_cwv(cwv_flight_time)
Initalization date of IFS forecast: 2024-09-05
Flight date: 2024-09-07
Flight index: KA-20240907a
Show code cell source
import pandas as pd
from dataclasses import asdict
pd.DataFrame.from_records(map(asdict, [airport, wp1, wp2, wp3, airport])).set_index("label")
lat | lon | fl | time | note | |
---|---|---|---|---|---|
label | |||||
RAI | 14.945000 | -23.486389 | None | None | None |
wp1 | 15.750969 | -23.810386 | None | None | None |
wp2 (ec-meet) | 14.973537 | -23.962397 | None | None | None |
wp3 | 14.131217 | -24.126245 | None | None | None |
RAI | 14.945000 | -23.486389 | None | None | None |