Flight plan - KA-20240905a

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Flight plan - KA-20240905a#

ec_under ec_track in_cloud insitu_aerosol spiral_mindelo

Crew#

The flight is planned to take off at 2024-09-05 14:00:00+00:00.

Job

Name

PI

Robert Oscar David

Instrument operator

Sorin Ghemulet

Instrument operator

Marius Corbu

Flight plan#

Leg 1: RAI -> WP1 (arrive @FL180 at 15:30 UTC | 14:30 LT)

Leg 2: Holding pattern at WP1 until 15:40 UTC (assessing cloud situation).

Leg 3 (Start 15:40 UTC): WP1 -> WP3 (via WP2) - around FL180 - 180 kt (~30min) - in-cloud if possible - Note: Be at WP2 at 15:55 UTC | 14:55 LT for satellite overpass

Leg 4: WP3 -> WP4, descend on the way, arrive at WP4 @FL040

Leg 5: Ascent as race track pattern with one straight leg between WP4 and WP5 from FL040 up to FL150 Notes: - if possible with VXE airport Mindelo - WP5: 16.91 N | 25W - 1000 ft/min, right turn - Alternate WP4 (16.99N | 24.83W): in case WP4 not possible

Leg 6: WP4 -> RAI (~1h)

Hide 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, 4, 0, 0, 0)
issued_time_str = issued_time.strftime('%Y-%m-%d')

flight_time = datetime(2024, 9, 5, 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=16.019557, lon= -26.555969, label='wp1')
wp2 = LatLon(lat=16.796737, lon=-26.402921, label='wp2 (ec-meet)')
wp3 = LatLon(lat=17.573813, lon=-26.249023, label='wp3')
mindelo = LatLon(lat=16.877772, lon=-24.995374, label='mindelo')


leg_out = [
     airport,
     wp1
]

leg_calval = [
      wp1,
      wp2,
      wp3
]

leg_mindelo = [
     wp3,
     mindelo
]

leg_home = [
     mindelo,
     airport
]

path = leg_out + leg_calval + leg_mindelo + 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: 2024-09-04
Flight date: 2024-09-05
Flight index: KA-20240905a
../_images/3408447aaba3650a2909a5a32c3daf1e99c8c262f8c925a48fb70a90dbb72a90.png

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import pandas as pd
from dataclasses import asdict

pd.DataFrame.from_records(map(asdict, [airport, wp1, wp2, wp3, mindelo, airport])).set_index("label")
lat lon fl time note
label
RAI 14.945000 -23.486389 None None None
wp1 16.019557 -26.555969 None None None
wp2 (ec-meet) 16.796737 -26.402921 None None None
wp3 17.573813 -26.249023 None None None
mindelo 16.877772 -24.995374 None None None
RAI 14.945000 -23.486389 None None None
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