---
jupytext:
  text_representation:
    extension: .md
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kernelspec:
  display_name: Python 3
  language: python
  name: python3
platform: ATR
flight_id: ATR-20240910a
takeoff: "2024-09-10 12:30:00Z"
landing: "2024-09-10 16:00:00Z"
departure_airport: GVAC
arrival_airport: GVAC
crew:
  - name: Guillaum Seurat
    job: Pilot
  - name: Dominique Duchanoy
    job: Pilot
  - name: Thierry André
    job: Mechanics
  - name: Michel Cluzeau
    job: Expé Principal
  - name: Claude Lainard
    job: Expé 
  - name: Basile Poujol
    job: PI
  - name: Emmeline François
    job: LNG
  - name: Laurent Forges
    job: aWALI
  - name: Pierre Coutris
    job: Microphys 1
  - name: Guy Febvre
    job: Microphys 2
  - name: Christophe Legac
    job: RASTA
  - name: Emma Chauvin
    job: BASTA
categories: []
orphan: true
---

{logo}`MAESTRO`

# Flight plan - {front}`flight_id`

```{badges}
```

## Flight plan
* The flight is planned to take off at {front}`takeoff` UTC and land at {front}`landing` UTC.
* Standard MAESTRO flight track designed to sample the mesoscale convective system to the southeast of Sal.

```{code-cell} python3
:tags: [hide-input]
from orcestra.flightplan import sal, bco, LatLon, IntoCircle, path_preview, plot_cwv
from datetime import datetime
import intake

cat = intake.open_catalog("https://tcodata.mpimet.mpg.de/internal.yaml")

date_time = datetime(2024, 9, 9, 12, 0, 0)
date_time_str = date_time.strftime('%Y-%m-%d')
flight_time = datetime(2024, 10, 10, 12, 0, 0)

airport = sal
wp1 = LatLon(lat=16.765, lon=-22.73, label='wp1')
wp2 = LatLon(lat=15.0, lon=-21.2, label='wp2')
wp3 = LatLon(lat=16.03, lon=-22.09, label='wp3')

path = [airport, wp1, wp2, wp3, wp2, wp3, wp2, wp1, airport]

ds = cat.HIFS(refdate=date_time_str, reftime=date_time.hour).to_dask()
cwv_flight_time = ds["tcwv"].sel(time=flight_time, method = "nearest")

ax = path_preview(path)
ax.set_extent([-24, -20, 13.5, 18])

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, path)).set_index("label")
```

## Crew

```{crew}
```