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.

import os

# local caching
try:
    from dotenv import load_dotenv

    load_dotenv()

    local_storage = os.environ['INTAKE_CACHE']
except ImportError:
    local_storage = '/tmp/'

kwds = {'simplecache': dict(
    cache_storage=local_storage, 
    same_names=True
)}

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'](storage_options=kwds).to_dask()
ds_2ds
/net/sever/mech/miniconda3/envs/howtoac3/lib/python3.11/site-packages/intake_xarray/base.py:21: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.
  'dims': dict(self._ds.dims),
<xarray.Dataset> Size: 133MB
Dimensions:                        (time: 17554, PN_angles: 56, diam2DS: 252,
                                    diam2DS_AI: 122)
Coordinates:
  * time                           (time) int64 140kB 36107 36108 ... 53660
  * PN_angles                      (PN_angles) int64 448B 3 4 5 ... 165 169 172
  * diam2DS                        (diam2DS) int64 2kB 50 60 70 ... 2550 2560
  * diam2DS_AI                     (diam2DS_AI) int64 976B 50 60 ... 1250 1260
Data variables: (12/49)
    altitude                       (time) float32 70kB ...
    latitude                       (time) float32 70kB ...
    longitude                      (time) float32 70kB ...
    air_temperature                (time) float32 70kB ...
    air_pressure                   (time) float32 70kB ...
    true_air_speed                 (time) float32 70kB ...
    ...                             ...
    Ext_2DSV_Ice                   (time) float32 70kB ...
    IWC_2DSV_BF95                  (time) float32 70kB ...
    Ice_2DSV_MMD_BF95              (time) float32 70kB ...
    PSD_2DSV_DC_DDp_Deq1           (time, diam2DS_AI) float32 9MB ...
    PSD_2DSV_DC_DDp_Dcc1           (time, diam2DS_AI) float32 9MB ...
    PSD_2DSV_DC_Ice_DDp_Dcc1       (time, diam2DS_AI) float32 9MB ...
Attributes:
    description:  Regis Dupuy\nLaboratoire de Meteorologie Physique (LaMP, UM...
    history:      Created 2021/09/22 18:23:53

View variables#