2D-S#

In-situ measurements of arctic cloud particle size distribution and volumic cloud particle diffusion properties using the 2D stereoscopic (2D-S, SPEC Inc.) and Polar Nephelometer (Gayet et al., 1997) probes.

Each NetCDF file contains the data obtained during a single flight. The file contains the time, location and XXX of the measurements.

The following example demonstrates the use of the 2D-S data collected during the MOSAIC-ACA and AFLUX campaign.

If you have questions or if you would like to use the data for a publication, please don’t hesitate to get in contact with the dataset authors as stated in the dataset attributes contact or author.

Data access#

  • To analyse the data they first have to be loaded by importing the (AC)³airborne meta data catalogue. To do so the ac3airborne package has to be installed. More information on how to do that and about the catalog can be found here.

Get data#

import ac3airborne

List of flights, where 2D-S is available:

cat = ac3airborne.get_intake_catalog()

datasets = []
for campaign in ['AFLUX','MOSAiC-ACA']:
    datasets.extend(list(cat[campaign]['P5']['2D_SPEC']))
datasets
['AFLUX_P5_RF02',
 'AFLUX_P5_RF03',
 'AFLUX_P5_RF04',
 'AFLUX_P5_RF05',
 'AFLUX_P5_RF06',
 'AFLUX_P5_RF07',
 'AFLUX_P5_RF08',
 'AFLUX_P5_RF09',
 'AFLUX_P5_RF10',
 'AFLUX_P5_RF11',
 'AFLUX_P5_RF12',
 'AFLUX_P5_RF13',
 'AFLUX_P5_RF14',
 'AFLUX_P5_RF15',
 'MOSAiC-ACA_P5_RF05',
 'MOSAiC-ACA_P5_RF06',
 'MOSAiC-ACA_P5_RF07',
 'MOSAiC-ACA_P5_RF08',
 'MOSAiC-ACA_P5_RF09',
 'MOSAiC-ACA_P5_RF10',
 'MOSAiC-ACA_P5_RF11']

Dataset#

To get an overview of the variables recorded by the 2D-S, we load the dataset of the first AFLUX flight AFLUX_P5_RF02.

ds_2ds = cat['AFLUX']['P5']['2D_SPEC']['AFLUX_P5_RF05'].to_dask()
ds_2ds
<xarray.Dataset>
Dimensions:                        (time: 17554, PN_angles: 56, diam2DS: 252,
                                    diam2DS_AI: 122)
Coordinates:
  * time                           (time) int64 36107 36108 ... 53659 53660
  * PN_angles                      (PN_angles) int64 3 4 5 5 ... 162 165 169 172
  * diam2DS                        (diam2DS) int64 50 60 70 ... 2540 2550 2560
  * diam2DS_AI                     (diam2DS_AI) int64 50 60 70 ... 1250 1260
Data variables: (12/49)
    altitude                       (time) float32 30.0 31.0 31.0 ... 31.0 31.0
    latitude                       (time) float32 78.24 78.24 ... 78.24 78.24
    longitude                      (time) float32 15.49 15.49 ... 15.5 15.5
    air_temperature                (time) float32 -7.062 -7.148 ... -8.406
    air_pressure                   (time) float32 988.7 988.5 ... 989.1 989.1
    true_air_speed                 (time) float32 44.48 44.83 ... 9.117 9.453
    ...                             ...
    Ext_2DSV_Ice                   (time) float32 0.0 0.04498 0.0 ... nan nan
    IWC_2DSV_BF95                  (time) float32 0.0 0.001404 0.0 ... nan nan
    Ice_2DSV_MMD_BF95              (time) float32 nan 230.2 nan ... nan nan nan
    PSD_2DSV_DC_DDp_Deq1           (time, diam2DS_AI) float32 ...
    PSD_2DSV_DC_DDp_Dcc1           (time, diam2DS_AI) float32 ...
    PSD_2DSV_DC_Ice_DDp_Dcc1       (time, diam2DS_AI) float32 ...
Attributes:
    description:  Regis Dupuy\nLaboratoire de Meteorologie Physique (LaMP, UM...
    history:      Created 2021/09/22 18:23:53

View variables#