---
jupytext:
  text_representation:
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kernelspec:
  display_name: Python 3
  language: python
  name: python3
platform: King Air
flight_id: KA-20240822a
takeoff: "2024-08-22 14:40:00Z"
landing: "2024-08-22 16:40:00Z"
departure_airport: GVNP
arrival_airport: GVNP
crew:
  - name: Tim Carlsen
    job: PI
  - name: Sorin Ghemulet
    job: Instrument operator
  - name: Alex Vlad
    job: Instrument operator
categories: [ec_under, ec_track, spiral, insitu_aerosol]
orphan: true
---

{logo}`CELLO`

# Flight plan - {front}`flight_id`

```{badges}
```

## Crew

The flight is planned to take off at {front}`takeoff`. 

```{crew}
```

## Flight plan

Holding pattern at WP1 until 15:20 UTC at FL200.

At 15:20 UTC: Spiral descent with WP1 at center town to FL010 with 1000 ft/min (right turn).

At 15:41 UTC: Overpass of ATR at FL180/FL200. Overpass of HALO close by at FL430/350. Start spiral ascent with WP1 at center from FL010 up to FL200 with 1000 ft/min (right turn).

Return home to RAI.

```{code-cell} python3
:tags: [hide-input]

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, 22, 0, 0, 0)
issued_time_str = issued_time.strftime('%Y-%m-%d')

flight_time = datetime(2024, 8, 22, 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')
earthcare = LatLon(lat=14.33555556, lon=-23.07972222, label='earthcare')
spiral = LatLon(lat=14.33555556, lon=-23.07972222, label='spirals')


leg_out = [
     airport,
     earthcare
]

leg_calval = [
      earthcare,
      spiral
]

leg_home = [
     spiral,
     earthcare,
     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)

ax.scatter(-23.07972222, 14.33555556, c='red', marker='o', s=200, ec = 'r', alpha = 0.3)

plot_cwv(cwv_flight_time)



```

```{code-cell} python3
:tags: [hide-input]
import pandas as pd
from dataclasses import asdict

pd.DataFrame.from_records(map(asdict, [airport, earthcare, airport])).set_index("label")
```