Flight plan - KA-20240829a#
ec_under ec_track in_cloud spiral_mindelo insitu_aerosolCrew#
The flight is planned to take off at 2024-08-29 14:20:00+00:00.
Job |
Name |
---|---|
PI |
Tim Carlsen |
Instrument operator |
Sorin Ghemulet |
Instrument operator |
Alex Vlad |
Flight plan#
Arrive @FL050 at WP1 at 15:00 UTC (14:00 LT)
Holding pattern at WP1 until 15:28 UTC (assessing cloud situation) Note: Communication with ATR (F-HMTO) via 123.45 MHz to get cloud information
Start 15:28 UTC: WP1 -> WP3 (via WP 2) - around FL030-FL050 - 140 kt (~40min) - in-cloud if possible Note: Be at WP2 at 15:48 UTC | 14:48 LT for satellite overpass and ATR meet
WP3 -> WP4, ascend to FL150
Descent as race-track pattern with one straight leg between WP4 and WP5 from FL150 down to FL040 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
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
Return home to RAI.
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, 8, 28, 0, 0, 0)
issued_time_str = issued_time.strftime('%Y-%m-%d')
flight_time = datetime(2024, 8, 29, 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')
ec_south = LatLon(lat=14.368185, lon=-25.148931, label='ec_south')
ec_meet = LatLon(lat=15.22805556, lon=-24.9691667, label='EC_ATR_meet')
ec_north = LatLon(lat=16.116939, lon=-24.807302, label='ec_north')
mindelo = LatLon(lat=16.877772, lon=-24.995374, label='mindelo')
leg_out = [
airport,
ec_south
]
leg_calval = [
ec_south,
ec_meet,
ec_north
]
leg_transfer = [
ec_north,
mindelo
]
leg_home = [
mindelo,
airport
]
path = leg_out + leg_calval + leg_transfer + 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)
ax.scatter(-24.995374, 16.877772, c='red', marker='o', s=200, ec = 'r', alpha = 0.3)
plot_cwv(cwv_flight_time)
Initalization date of IFS forecast: 2024-08-28
Flight date: 2024-08-29
Flight index: KA-20240829a
Show code cell source
import pandas as pd
from dataclasses import asdict
pd.DataFrame.from_records(map(asdict, [airport, ec_south, ec_meet, ec_north, mindelo, airport])).set_index("label")
lat | lon | fl | time | note | |
---|---|---|---|---|---|
label | |||||
RAI | 14.945000 | -23.486389 | None | None | None |
ec_south | 14.368185 | -25.148931 | None | None | None |
EC_ATR_meet | 15.228056 | -24.969167 | None | None | None |
ec_north | 16.116939 | -24.807302 | None | None | None |
mindelo | 16.877772 | -24.995374 | None | None | None |
RAI | 14.945000 | -23.486389 | None | None | None |