COMPEX-EC

Clouds over cOMPlEX environment - EarthCARE COMPEX-EC - Polar 5 EarthCARE validation campaign out of Kiruna (2.-16.4.2025).

Detailed flight logs

RF#	Date	Description	TO	TD	HH	EC	Track (jpg)	Track (KML)	Flight report
RF00	26.3.2025	EarthCARE during test flight in Bremen	13:21	14:32	1:11	13:58	jpg	KML
RF01	4.4.2025	EarthCARE - MSI track and direct underflight	11:03	16:03	5:00	13:51	jpg	KML	RF
RF02	6.4.2025	EarthCARE - MSI track and direct underflight	12:20	16:22	4:02	13:40	jpg	KML	RF
RF03	7.4.2025	EarthCARE - MSI track and direct underflight	12:06	16:00	3:54	14:20	jpg	KML	RF
RF04	8.4.2025	EarthCARE - back and forth	11:59	15:59	4:00	13:30	jpg	KML	RF
RF05	11.4.2025	EarthCARE - back and forth	12:05	15:28	3:23	13:58	jpg	KML	RF
RF06	13.4.2025	EarthCARE - back and forth	10:37	15:41	5:04	13:47	jpg	KML	RF
RF07	15.4.2025	EarthCARE - back and forth	10:54	15:44	4:50	13:35	jpg	KML	RF

Fig. 3 Flight tracks of the COMPEX-EC campaign.

%matplotlib inline
import ac3airborne
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import numpy as np
plt.style.use("../mplstyle/book")

# load intake catalog and flight segments
cat = ac3airborne.get_intake_catalog()
meta = ac3airborne.get_flight_segments()

ancillary = ['AMSR2_SIC']

def data_availability(mission, platform):
    """
    Plot data availability matrix
    """
    
    # store data availability in a matrix
    data_availability = np.zeros(shape=(len(list(cat[mission][platform])),
                                        len(list(meta[mission][platform]))))
    for i, dataset in enumerate(list(cat[mission][platform])):
        data_availability[i, :] = np.isin(list(meta[mission][platform]), 
                                          list(cat[mission][platform][dataset]))

    # plot data availability
    yscale = data_availability.shape[1]
    fig, ax = plt.subplots(1, 1, figsize=(5, 2+0.4*yscale))
    
    ax.pcolormesh(range(data_availability.shape[0]), 
                  range(data_availability.shape[1]), 
                  data_availability.T, 
                  shading='nearest',
                  vmin=0, 
                  vmax=1, 
                  cmap='RdYlGn', 
                  edgecolors='#eeeeee')

    ax.set_xticks(range(data_availability.shape[0]))
    ax.set_yticks(range(data_availability.shape[1]))

    xlabels = []
    for ds_name in list(cat[mission][platform]):
        if ds_name in ancillary:
            ds_name += '\n(ancillary)'
        xlabels.append(ds_name)

    ax.set_xticklabels(xlabels, rotation=90)
    y_labels = [flight_id+', '+flight['date'].strftime('%Y-%m-%d') 
                for flight_id, flight in meta[mission][platform].items()]
    ax.set_yticklabels(y_labels)

    ax.tick_params(labeltop=True)
    ax.invert_yaxis()

    available = mpatches.Patch(color='green', label='Data available')
    not_flown = mpatches.Patch(color='red', label='Data missing or\ninstrument failed')

    ax.legend(handles=[available, not_flown], ncol=1,
              bbox_to_anchor=(0, 1.01), loc='lower right')

    plt.show()

Polar 5

data_availability(mission='COMPEX-EC', platform='P5')