WND (Thermospheric crosswinds)

SERVER_URL = "https://vires.services/ows"

%load_ext watermark
%watermark -i -v -p viresclient,pandas,xarray,matplotlib,cartopy

Python implementation: CPython
Python version       : 3.11.6
IPython version      : 8.18.0

viresclient: 0.12.0
pandas     : 2.1.3
xarray     : 2023.12.0
matplotlib : 3.8.2
cartopy    : 0.22.0

from viresclient import SwarmRequest
import datetime as dt

Product information

Thermospheric crosswind products are available through the following collections, from non-Swarm spacecraft via the TOLEOS project

• CHAMP:
  CH_OPER_WND_ACC_2_

• GRACE 1 & 2:
  GR_OPER_WNDxACC_2_

• GRACE-FO 1:
  GF_OPER_WNDxACC_2_

We can check the available parameter names with:

request = SwarmRequest(SERVER_URL)
for collection in ("CH_OPER_WND_ACC_2_", "GR_OPER_WND1ACC_2_", "GF_OPER_WND1ACC_2_"):
    print(f"{collection}:\n{request.available_measurements(collection)}\n")

CH_OPER_WND_ACC_2_:
['Height_GD', 'Latitude_GD', 'Longitude_GD', 'crosswind', 'crosswind_direction', 'local_solar_time', 'validity_flag']

GR_OPER_WND1ACC_2_:
['Height_GD', 'Latitude_GD', 'Longitude_GD', 'crosswind', 'crosswind_direction', 'local_solar_time', 'validity_flag']

GF_OPER_WND1ACC_2_:
['Height_GD', 'Latitude_GD', 'Longitude_GD', 'crosswind', 'crosswind_direction', 'local_solar_time', 'validity_flag']

request.available_times("GF_OPER_WND1ACC_2_")

	starttime	endtime	bbox	identifier
0	2023-01-01 00:00:00+00:00	2023-01-01 23:59:50.001000+00:00	(-90,-180,90,180)	GF_OPER_WND1ACC_2__20230101T000000_20230101T23...
1	2023-01-02 00:00:00+00:00	2023-01-02 23:59:50.001000+00:00	(-90,-180,90,180)	GF_OPER_WND1ACC_2__20230102T000000_20230102T23...
2	2023-01-03 00:00:00+00:00	2023-01-03 23:59:50.001000+00:00	(-90,-180,90,180)	GF_OPER_WND1ACC_2__20230103T000000_20230103T23...
3	2023-01-04 00:00:00+00:00	2023-01-04 23:59:50.001000+00:00	(-90,-180,90,180)	GF_OPER_WND1ACC_2__20230104T000000_20230104T23...
4	2023-01-05 00:00:00+00:00	2023-01-05 23:59:50.001000+00:00	(-90,-180,90,180)	GF_OPER_WND1ACC_2__20230105T000000_20230105T23...
...	...	...	...	...
512	2024-05-27 00:00:00+00:00	2024-05-27 23:59:50.001000+00:00	(-90,-180,90,180)	GF_OPER_WND1ACC_2__20240527T000000_20240527T23...
513	2024-05-28 00:00:00+00:00	2024-05-28 23:59:50.001000+00:00	(-90,-180,90,180)	GF_OPER_WND1ACC_2__20240528T000000_20240528T23...
514	2024-05-29 00:00:00+00:00	2024-05-29 23:59:50.001000+00:00	(-90,-180,90,180)	GF_OPER_WND1ACC_2__20240529T000000_20240529T23...
515	2024-05-30 00:00:00+00:00	2024-05-30 23:59:50.001000+00:00	(-90,-180,90,180)	GF_OPER_WND1ACC_2__20240530T000000_20240530T23...
516	2024-05-31 00:00:00+00:00	2024-05-31 23:59:50.001000+00:00	(-90,-180,90,180)	GF_OPER_WND1ACC_2__20240531T000000_20240531T23...

517 rows × 4 columns

Fetching and plotting data

start_time = dt.datetime(2023, 1, 1)
end_time = dt.datetime(2023, 1, 8)

request = SwarmRequest(SERVER_URL)
request.set_collection("GF_OPER_WND1ACC_2_")
request.set_products(
    measurements=["crosswind", "crosswind_direction", "validity_flag"],
)
data = request.get_between(start_time, end_time)
ds = data.as_xarray()
ds

<xarray.Dataset>
Dimensions:              (Timestamp: 60480, crosswind_direction_dim1: 3)
Coordinates:
  * Timestamp            (Timestamp) datetime64[ns] 2023-01-01 ... 2023-01-07...
Dimensions without coordinates: crosswind_direction_dim1
Data variables:
    Spacecraft           (Timestamp) object '1' '1' '1' '1' ... '1' '1' '1' '1'
    validity_flag        (Timestamp) int8 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0
    crosswind            (Timestamp) float64 21.81 19.39 23.24 ... 88.45 87.06
    Longitude            (Timestamp) float64 -89.54 -89.56 ... 83.87 83.84
    Radius               (Timestamp) float64 6.868e+06 6.868e+06 ... 6.876e+06
    crosswind_direction  (Timestamp, crosswind_direction_dim1) float64 0.0187...
    Latitude             (Timestamp) float64 -42.21 -41.57 ... -14.43 -15.07
Attributes:
    Sources:         ['GF_OPER_WND1ACC_2__20230101T000000_20230101T235959_000...
    MagneticModels:  []
    AppliedFilters:  []

xarray.Dataset

• Dimensions:
  • Timestamp: 60480
  • crosswind_direction_dim1: 3
• Coordinates: (1)
  • Timestamp
    (Timestamp)
    datetime64[ns]
    2023-01-01 ... 2023-01-07T23:59:50

    description :

    array(['2023-01-01T00:00:00.000000000', '2023-01-01T00:00:10.000000000',
           '2023-01-01T00:00:20.000000000', ..., '2023-01-07T23:59:30.000000000',
           '2023-01-07T23:59:40.000000000', '2023-01-07T23:59:50.000000000'],
          dtype='datetime64[ns]')

• Data variables: (7)
  • Spacecraft
    (Timestamp)
    object
    '1' '1' '1' '1' ... '1' '1' '1' '1'

    units :

    -

    description :

    Spacecraft identifier (values: 'A', 'B', 'C' or '-' if not available).

    array(['1', '1', '1', ..., '1', '1', '1'], dtype=object)

  • validity_flag
    (Timestamp)
    int8
    0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0

    units :

    -

    description :

    array([0, 0, 0, ..., 0, 0, 0], dtype=int8)

  • crosswind
    (Timestamp)
    float64
    21.81 19.39 23.24 ... 88.45 87.06

    units :

    m/s

    description :

    array([ 21.81092809,  19.39201064,  23.23595609, ..., 118.69763613,
            88.44896281,  87.05955587])

  • Longitude
    (Timestamp)
    float64
    -89.54 -89.56 ... 83.87 83.84

    units :

    deg

    description :

    Position in ITRF - Longitude

    array([-89.53962309, -89.56114323, -89.58305775, ...,  83.9044201 ,
            83.87457042,  83.84478903])

  • Radius
    (Timestamp)
    float64
    6.868e+06 6.868e+06 ... 6.876e+06

    units :

    m

    description :

    Position in ITRF - Radius

    array([6868119.60402215, 6868075.57428291, 6868031.86607512, ...,
           6876152.38497076, 6876132.54415121, 6876111.59384447])

  • crosswind_direction
    (Timestamp, crosswind_direction_dim1)
    float64
    0.0187 0.9998 ... 0.9986 -0.001664

    units :

    -

    description :

    array([[ 0.01870137,  0.99982447,  0.00113267],
           [ 0.01944086,  0.99981032,  0.00117454],
           [ 0.02058709,  0.99978732,  0.00121935],
           ...,
           [-0.05611221,  0.99842309, -0.0016618 ],
           [-0.05380657,  0.99855   , -0.00165591],
           [-0.05372241,  0.99855452, -0.00166401]])

  • Latitude
    (Timestamp)
    float64
    -42.21 -41.57 ... -14.43 -15.07

    units :

    deg

    description :

    Position in ITRF - Latitude

    array([-42.20894554, -41.57362238, -40.93827782, ..., -13.80033639,
           -14.43458019, -15.0688225 ])

• Indexes: (1)
  • Timestamp
    PandasIndex

    PandasIndex(DatetimeIndex(['2023-01-01 00:00:00', '2023-01-01 00:00:10',
                   '2023-01-01 00:00:20', '2023-01-01 00:00:30',
                   '2023-01-01 00:00:40', '2023-01-01 00:00:50',
                   '2023-01-01 00:01:00', '2023-01-01 00:01:10',
                   '2023-01-01 00:01:20', '2023-01-01 00:01:30',
                   ...
                   '2023-01-07 23:58:20', '2023-01-07 23:58:30',
                   '2023-01-07 23:58:40', '2023-01-07 23:58:50',
                   '2023-01-07 23:59:00', '2023-01-07 23:59:10',
                   '2023-01-07 23:59:20', '2023-01-07 23:59:30',
                   '2023-01-07 23:59:40', '2023-01-07 23:59:50'],
                  dtype='datetime64[ns]', name='Timestamp', length=60480, freq=None))

• Attributes: (3)

  Sources :

  ['GF_OPER_WND1ACC_2__20230101T000000_20230101T235959_0003', 'GF_OPER_WND1ACC_2__20230102T000000_20230102T235959_0003', 'GF_OPER_WND1ACC_2__20230103T000000_20230103T235959_0003', 'GF_OPER_WND1ACC_2__20230104T000000_20230104T235959_0003', 'GF_OPER_WND1ACC_2__20230105T000000_20230105T235959_0003', 'GF_OPER_WND1ACC_2__20230106T000000_20230106T235959_0003', 'GF_OPER_WND1ACC_2__20230107T000000_20230107T235959_0003']

  MagneticModels :

  []

  AppliedFilters :

  []

ds.plot.scatter(x="Timestamp", y="Latitude", hue="crosswind", s=2, edgecolors="face", figsize=(10, 4));