AEBS products in VirES¶

This notebook demonstrates access to the AEBS products data by means of the vires client.

For each VirES data collection the avaiable variables are listed. In addition, mapping the the variables of the source AEBS products is provided [link to spec TBD].

In [1]:

from viresclient import SwarmRequest

server_url = 'https://staging.viresdisc.vires.services/ows'


if True:
    # setup older client versions without AEBS support
    SwarmRequest.COLLECTIONS.update({
        'AEJ_LPL': ['SW_OPER_AEJ{}LPL_2F'.format(x) for x in 'ABC'],
        'AEJ_LPL:Quality': ['SW_OPER_AEJ{}LPL_2F:Quality'.format(x) for x in 'ABC'],
        'AEJ_LPS': ['SW_OPER_AEJ{}LPS_2F'.format(x) for x in 'ABC'],
        'AEJ_LPS:Quality': ['SW_OPER_AEJ{}LPS_2F:Quality'.format(x) for x in 'ABC'],
        'AEJ_PBL': ['SW_OPER_AEJ{}PBL_2F'.format(x) for x in 'ABC'],
        'AEJ_PBS': ['SW_OPER_AEJ{}PBS_2F'.format(x) for x in 'ABC'],
        'AOB_FAC': ['SW_OPER_AOB{}FAC_2F'.format(x) for x in 'ABC'],
    })
    SwarmRequest.PRODUCT_VARIABLES.update({
        'AEJ_LPL': ['Latitude_QD', 'Longitude_QD', 'MLT_QD', 'J_NE', 'J_QD'],
        'AEJ_LPL:Quality': ['RMS_misfit', 'Confidence'],
        'AEJ_LPS': ['Latitude_QD', 'Longitude_QD', 'MLT_QD', 'J_CF_NE', 'J_DF_NE', 'J_CF_SemiQD', 'J_DF_SemiQD', 'J_R'],
        'AEJ_LPS:Quality': ['RMS_misfit', 'Confidence'],
        'AEJ_PBL': ['Latitude_QD', 'Longitude_QD', 'MLT_QD', 'J_QD', 'Flags', 'PointType'],
        'AEJ_PBS': ['Latitude_QD', 'Longitude_QD', 'MLT_QD', 'J_DF_SemiQD', 'Flags', 'PointType'],
        'AOB_FAC': ['Latitude_QD', 'Longitude_QD', 'MLT_QD', 'Boundary_Flag', 'Quality', 'Pair_Indicator'],
    })

AEJxLPL product¶

Avaiables Variables:

VirES Variable	Source Product Variable	Unit	Dimension	Description
`Timestamp`	`t`	$-$	scalar	UTC time of observation
`Latitude`	`Latitude`	`Latitude`	$\text{deg}$	scalar	ITRF geocentric latitude
`Longitude`	`Longitude`	$\text{deg}$	scalar	ITRF geocentric longitude
`Latitude_QD`	`Latitude_QD`	$\text{deg}$	scalar	Quasi-dipole latitude
`Longitude_QD`	`Longitude_QD`	$\text{deg}$	scalar	Quasi-dipole longitude
`MLT_QD`	`MLT`	$\text{hour}$	scalar	Magnetic local time (QD)
`J_NE`	`J`	$\text{A}\ \text{km}^{-1}$	vector [2]	North and East component of horizontal sheet current density vector in the geocentric frame
`J_QD`	`J_QD`	$\text{A}\ \text{km}^{-1}$	scalar	East component of horizontal sheet current density in QD frame

Note: If the standard VirES QDLat, QDLat and MLT auxialiary variables default to the Latitude_QD, Longitude_QD, MLT_QD stored in AEBS products if they cannot be calculated from the times and locations. (Locations in the AEBS products are incomplete due to the missing Radius and they cannot be used to calucate the magnetic coordinates.)

In [2]:

request = SwarmRequest(server_url)
request.set_collection('SW_OPER_AEJALPL_2F')
request.set_products(
    measurements=['Latitude_QD', 'Longitude_QD', 'MLT_QD', 'J_NE', 'J_QD'],
    auxiliaries=['QDLat', 'QDLon', 'MLT'],
)

data = request.get_between(
    start_time='2015-06-01T00:00:00Z',
    end_time='2015-06-02T00:00:00Z',
).as_xarray()

print(data)

[1/1] Processing:  100%|██████████|  [ Elapsed: 00:01, Remaining: 00:00 ]
      Downloading: 100%|██████████|  [ Elapsed: 00:00, Remaining: 00:00 ] (0.247MB)

<xarray.Dataset>
Dimensions:       (J_NE_dim1: 2, Timestamp: 2412)
Coordinates:
  * Timestamp     (Timestamp) datetime64[ns] 2015-06-01T00:00:15.688632727 ... 2015-06-01T23:33:26.110890627
Dimensions without coordinates: J_NE_dim1
Data variables:
    Spacecraft    (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' 'A'
    QDLon         (Timestamp) float64 -27.39 -31.73 -35.82 ... -74.72 -75.39
    Latitude_QD   (Timestamp) float64 -77.66 -77.26 -76.8 ... -52.17 -51.2
    Longitude_QD  (Timestamp) float64 -27.39 -31.73 -35.82 ... -74.72 -75.39
    J_NE          (Timestamp, J_NE_dim1) float64 58.18 -7.87 ... 6.264 -17.93
    MLT           (Timestamp) float64 17.6 17.32 17.05 ... 14.05 14.01 13.97
    QDLat         (Timestamp) float64 -77.66 -77.26 -76.8 ... -52.17 -51.2
    Latitude      (Timestamp) float64 -79.2 -78.22 -77.24 ... -50.34 -49.34
    Longitude     (Timestamp) float64 178.7 179.9 -179.2 ... -165.0 -164.9
    J_QD          (Timestamp) float64 -58.71 -64.28 -72.47 ... -20.11 -18.99
    MLT_QD        (Timestamp) float64 17.6 17.32 17.05 ... 14.05 14.01 13.97
Attributes:
    Sources:         ['SW_OPER_AEJALPL_2F_20150531T000000_20150531T235959_010...
    MagneticModels:  []
    RangeFilters:    []

AEJxLPL product quality¶

The AEJxLPL quality information is accessible as a separate dataset.

Avaiables Variables:

VirES Variable	Source Product Variable	Unit	Dimension	Description
`Timestamp`	`t_qual`	$-$	scalar	UTC timestamp of the quality record
`RMS_misfit`	`RMS_misfit`	$\text{nT}$	scalar	Root Mean Square error misfit between observations and model values for the oval crossing
`Confidence`	`Confidence`	$-$	scalar	Goodness of fit computed as 1 - (residual RMS / signal RMS) for the oval crossing

In [3]:

request = SwarmRequest(server_url)
request.set_collection('SW_OPER_AEJALPL_2F:Quality')
request.set_products(
    measurements=['RMS_misfit', 'Confidence'],
)

data = request.get_between(
    start_time='2015-06-01T00:00:00Z',
    end_time='2015-06-02T00:00:00Z'
).as_xarray()

print(data)

[1/1] Processing:  100%|██████████|  [ Elapsed: 00:01, Remaining: 00:00 ]
      Downloading: 100%|██████████|  [ Elapsed: 00:00, Remaining: 00:00 ] (0.037MB)

<xarray.Dataset>
Dimensions:     (Timestamp: 61)
Coordinates:
  * Timestamp   (Timestamp) datetime64[ns] 2015-06-01T00:05:37 ... 2015-06-01T23:30:25
Data variables:
    Spacecraft  (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' 'A'
    RMS_misfit  (Timestamp) float64 0.3433 0.5879 0.5471 ... 0.04362 0.07308
    Confidence  (Timestamp) float64 0.9642 0.9695 0.9793 ... 0.9834 0.9809
Attributes:
    Sources:         ['SW_OPER_AEJALPL_2F_20150531T000000_20150531T235959_010...
    MagneticModels:  []
    RangeFilters:    []

AEJxLPS product¶

Avaiables Variables:

VirES Variable	Source Product Variable	Unit	Dimension	Description
`Timestamp`	`t`	$-$	scalar	UTC time of observation
`Latitude`	`Latitude`	`Latitude`	$\text{deg}$	scalar	ITRF geocentric latitude
`Longitude`	`Longitude`	$\text{deg}$	scalar	ITRF geocentric longitude
`Latitude_QD`	`Latitude_QD`	$\text{deg}$	scalar	Quasi-dipole latitude
`Longitude_QD`	`Longitude_QD`	$\text{deg}$	scalar	Quasi-dipole longitude
`MLT_QD`	`MLT`	$\text{hour}$	scalar	Magnetic local time (QD)
`J_CF_NE`	`J_CF`	$\text{A}\ \text{km}^{-1}$	vector [2]	North and East component of the curl-free horizontal sheet current density vector in geocentric frame
`J_DF_NE`	`J_DF`	$\text{A}\ \text{km}^{-1}$	vector [2]	North and East component of the divergence-free horizontal sheet current density vector in geocentric frame
`J_CF_SemiQD`	`J_CF_SemiQD`	$\text{A}\ \text{km}^{-1}$	scalar	North component of the curl-free horizontal sheet current density in semi-QD frame
`J_DF_SemiQD`	`J_DF_SemiQD`	$\text{A}\ \text{km}^{-1}$	scalar	East component of the divergence-free horizontal sheet current density in semi-QD frame
`J_R`	`J_r`	$\text{A}\ \text{km}^{-2}$	scalar	Radial ionospheric current density at 110 km altitude in SemiQD frame

Note: If the standard VirES QDLat, QDLat and MLT auxialiary variables default to the Latitude_QD, Longitude_QD, MLT_QD stored in AEBS products if they cannot be calculated from the times and locations. (Locations in the AEBS products are incomplete due to the missing Radius and they cannot be used to calucate the magnetic coordinates.)

In [4]:

request = SwarmRequest(server_url)
request.set_collection('SW_OPER_AEJALPS_2F')
request.set_products(
    measurements=[
        'Latitude_QD', 'Longitude_QD', 'MLT_QD',
        'J_CF_NE', 'J_DF_NE', 'J_CF_SemiQD', 'J_DF_SemiQD', 'J_R',
    ],
    auxiliaries=['QDLat', 'QDLon', 'MLT'],
)

data = request.get_between(
    start_time='2015-06-01T00:00:00Z',
    end_time='2015-06-02T00:00:00Z'
).as_xarray()

print(data)

[1/1] Processing:  100%|██████████|  [ Elapsed: 00:01, Remaining: 00:00 ]
      Downloading: 100%|██████████|  [ Elapsed: 00:00, Remaining: 00:00 ] (4.836MB)

<xarray.Dataset>
Dimensions:       (J_CF_NE_dim1: 2, J_DF_NE_dim1: 2, Timestamp: 37416)
Coordinates:
  * Timestamp     (Timestamp) datetime64[ns] 2015-06-01 ... 2015-06-01T23:59:59
Dimensions without coordinates: J_CF_NE_dim1, J_DF_NE_dim1
Data variables:
    Spacecraft    (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' 'A'
    J_DF_SemiQD   (Timestamp) float64 -132.5 -131.9 -131.2 ... 25.7 25.81 25.84
    QDLon         (Timestamp) float64 -22.79 -23.08 -23.38 ... -102.3 -102.3
    J_DF_NE       (Timestamp, J_DF_NE_dim1) float64 132.5 1.824 ... -5.264 25.3
    J_R           (Timestamp) float64 -0.08894 -0.08894 ... -0.04155 -0.01852
    Latitude_QD   (Timestamp) float64 -78.32 -78.3 -78.28 ... 50.96 51.02 51.09
    Longitude_QD  (Timestamp) float64 -22.79 -23.08 -23.38 ... -102.3 -102.3
    MLT           (Timestamp) float64 17.9 17.88 17.86 17.84 ... 12.6 12.6 12.6
    J_CF_SemiQD   (Timestamp) float64 -22.12 -22.27 -22.42 ... 8.053 7.782 7.614
    QDLat         (Timestamp) float64 -78.32 -78.3 -78.28 ... 50.96 51.02 51.09
    Latitude      (Timestamp) float64 -79.78 -79.72 -79.67 ... 53.79 53.85 53.91
    Longitude     (Timestamp) float64 174.7 174.8 174.9 ... -164.7 -164.7 -164.6
    J_CF_NE       (Timestamp, J_CF_NE_dim1) float64 -0.3044 22.12 ... -1.551
    MLT_QD        (Timestamp) float64 17.9 17.88 17.86 17.84 ... 12.6 12.6 12.6
Attributes:
    Sources:         ['SW_OPER_AEJALPS_2F_20150531T000000_20150531T235959_010...
    MagneticModels:  []
    RangeFilters:    []

AEJxLPS product quality¶

The AEJxLPS quality information is accessible as a separate dataset.

Avaiables Variables:

VirES Variable	Source Product Variable	Unit	Dimension	Description
`Timestamp`	`t_qual`	$-$	scalar	UTC timestamp of the quality record
`RMS_misfit`	`RMS_misfit`	$\text{nT}$	scalar	Root Mean Square error misfit between observations and model values for the oval crossing
`Confidence`	`Confidence`	$-$	scalar	Goodness of fit computed as 1 - (residual RMS / signal RMS) for the oval crossing

In [5]:

request = SwarmRequest(server_url)
request.set_collection('SW_OPER_AEJALPS_2F:Quality')
request.set_products(
    measurements=['RMS_misfit', 'Confidence'],
)

data = request.get_between(
    start_time='2015-06-01T00:00:00Z',
    end_time='2015-06-02T00:00:00Z'
).as_xarray()

print(data)

[1/1] Processing:  100%|██████████|  [ Elapsed: 00:01, Remaining: 00:00 ]
      Downloading: 100%|██████████|  [ Elapsed: 00:00, Remaining: 00:00 ] (0.037MB)

<xarray.Dataset>
Dimensions:     (Timestamp: 61)
Coordinates:
  * Timestamp   (Timestamp) datetime64[ns] 2015-06-01T00:34:39 ... 2015-06-01T23:59:42
Data variables:
    Spacecraft  (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' 'A'
    RMS_misfit  (Timestamp) float64 2.298 4.103 2.858 3.35 ... 0.4935 1.32 2.046
    Confidence  (Timestamp) float64 0.8908 0.911 0.7526 ... 0.7863 0.3651 0.9071
Attributes:
    Sources:         ['SW_OPER_AEJALPS_2F_20150531T000000_20150531T235959_010...
    MagneticModels:  []
    RangeFilters:    []

AEJxPBL product¶

VirES Variable	Source Product Variable	Unit	Dimension	Description
`Timestamp`	`t_Peak`, `t_EB`, `t_PB`	$-$	scalar	UTC time of observation
`Latitude`	`Latitude_Peak`, `Latitude_EB`, `Latitude_PB`	$\text{deg}$	scalar	ITRF geocentric latitude
`Longitude`	`Longitude_Peak`, `Longitude_EB`, `Longitude_PB`	$\text{deg}$	scalar	ITRF geocentric longitude
`Latitude_QD`	`Latitude_Peak_QD`, `Latitude_EB_QD`, `Latitude_PB_QD`	$\text{deg}$	scalar	Quasi-dipole latitude
`Longitude_QD`	`Longitude_Peak_QD`, `Longitude_EB_QD`, `Longitude_PB_QD`	$\text{deg}$	scalar	Quasi-dipole longitude
`MLT_QD`	`MLT_Peak`, `MLT_EB`, `MLT_PB`	$\text{hour}$	scalar	Magnetic local time (QD)
`J_QD`	`J`	$\text{A}\ \text{km}^{-1}$	scalar	Peak eastward sheet current intensity in QD frame. Set to `NaN` for equatorial and polar boundaries.
`Flags`	`Flags`	$-$	scalar	Quality indicator (for more details of the binary flags see the product specification)
`PointType`	n/a	$-$	scalar	Point type (see the details below)

Latitude, Longitude, Latitude_QD, Longitude_QD, MLT_QD, and J_QD are set to NaN if the EJ boubdaries have not been detected (also see the Flags specification).

The multi-timestamp table structure of the source AEJxPBL products is transormed into a simple time-series. The newly introduced PointType variable determines the type of the samples. The meaning of the bit flags is as follows:

Bit No.	False (0)	True (1)	Note
bit 0 (1)	WEJ	EEJ
bit 1 (2)	Peak	Boundary
bit 2 (4)	Equatorial boundary	Polar boundary	only if bit 1 set
bit 3 (8)	Boundary pair start	Boundary pair end	only if bit 1 set

These are the possible PointType values:

Value	Hex.	Bin.	Meaning
0	0x0	0b0000	WEJ peak (minimum)
1	0x1	0b0001	EEJ peak (maximum)
2	0x2	0b0010	WEJ equatorial boundary (pair start)
3	0x3	0b0011	EEJ equatorial boundary (pair start)
6	0x6	0b0110	WEJ polar boundary (pair start)
7	0x7	0b0111	EEJ polar boundary (pair start)
10	0xA	0b1010	WEJ equatorial boundary (pair end)
11	0xB	0b1011	EEJ equatorial boundary (pair end)
14	0xE	0b1110	WEJ polar boundary (pair end)
15	0xF	0b1111	EEJ polar boundary (pair end)

Note: If the standard VirES QDLat, QDLat and MLT auxialiary variables default to the Latitude_QD, Longitude_QD, MLT_QD stored in AEBS products if they cannot be calculated from the times and locations. (Locations in the AEBS products are incomplete due to the missing Radius and they cannot be used to calucate the magnetic coordinates.)

In [6]:

request = SwarmRequest(server_url)
request.set_collection('SW_OPER_AEJAPBL_2F')
request.set_products(
    measurements=[
        'Latitude_QD', 'Longitude_QD', 'MLT_QD',
         'J_QD', 'Flags', 'PointType',
    ],
    auxiliaries=['QDLat', 'QDLon', 'MLT'],
)

data = request.get_between(
    start_time='2015-06-01T00:00:00Z',
    end_time='2015-06-02T00:00:00Z'
).as_xarray()

print(data)

[1/1] Processing:  100%|██████████|  [ Elapsed: 00:01, Remaining: 00:00 ]
      Downloading: 100%|██████████|  [ Elapsed: 00:00, Remaining: 00:00 ] (0.115MB)

<xarray.Dataset>
Dimensions:       (Timestamp: 366)
Coordinates:
  * Timestamp     (Timestamp) datetime64[ns] 2015-06-01T00:02:07.298531294 ... 2015-06-01T23:33:41.800961018
Data variables:
    Spacecraft    (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' 'A'
    Flags         (Timestamp) uint8 80 80 80 80 80 80 ... 113 113 113 113 113
    PointType     (Timestamp) uint16 7 1 11 6 0 10 2 0 ... 14 15 6 3 1 0 15 10
    QDLon         (Timestamp) float64 -52.56 -59.43 -64.89 ... -74.03 nan -76.03
    Latitude_QD   (Timestamp) float64 -73.62 -71.39 -68.96 ... -53.14 nan -50.22
    Longitude_QD  (Timestamp) float64 -52.56 -59.43 -64.89 ... -74.03 nan -76.03
    MLT           (Timestamp) float64 15.95 15.51 15.15 ... 14.05 nan 13.93
    QDLat         (Timestamp) float64 -73.62 -71.39 -68.96 ... -53.14 nan -50.22
    Latitude      (Timestamp) float64 -72.2 -69.33 -66.45 ... -51.34 nan -48.34
    Longitude     (Timestamp) float64 -176.0 -174.9 -174.2 ... -165.0 nan -164.9
    J_QD          (Timestamp) float64 nan 65.0 nan nan ... nan -20.47 nan nan
    MLT_QD        (Timestamp) float64 15.95 15.51 15.15 ... 14.05 nan 13.93
Attributes:
    Sources:         ['SW_OPER_AEJAPBL_2F_20150101T000000_20151231T235959_0101']
    MagneticModels:  []
    RangeFilters:    []

AEJxPBS product¶

Avaiables Variables:

VirES Variable	Source Product Variable	Unit	Dimension	Description
`Timestamp`	`t_Peak`, `t_EB`, `t_PB`	$-$	scalar	UTC time of observation
`Latitude`	`Latitude_Peak`, `Latitude_EB`, `Latitude_PB`	$\text{deg}$	scalar	ITRF geocentric latitude
`Longitude`	`Longitude_Peak`, `Longitude_EB`, `Longitude_PB`	$\text{deg}$	scalar	ITRF geocentric longitude
`Latitude_QD`	`Latitude_Peak_QD`, `Latitude_EB_QD`, `Latitude_PB_QD`	$\text{deg}$	scalar	Quasi-dipole latitude
`Longitude_QD`	`Longitude_Peak_QD`, `Longitude_EB_QD`, `Longitude_PB_QD`	$\text{deg}$	scalar	Quasi-dipole longitude
`MLT_QD`	`MLT_Peak`, `MLT_EB`, `MLT_PB`	$\text{hour}$	scalar	Magnetic local time (QD)
`J_DF_SemiQD`	`J_DF`	$\text{A}\ \text{km}^{-1}$	scalar	Peak eastward sheet current intensity in semi-QD frame. Set to `NaN` for equatorial and polar boundaries.
`Flags`	`Flags`	$-$	scalar	Quality indicator (for more details of the binary flags see the product specification)
`PointType`	n/a	$-$	scalar	Point type (see the details below)

Latitude, Longitude, Latitude_QD, Longitude_QD, MLT_QD, and J_DF_SemiQD are set to NaN if the EJ boubdaries have not been detected (also see the Flags specification).

The multi-timestamp table structure of the source AEJxPBS products is transormed into a simple time-series. The newly introduced PointType variable determines the type of the samples. The meaning of the bit flags is as follows:

Bit No.	False (0)	True (1)	Note
bit 0 (1)	WEJ	EEJ
bit 1 (2)	Peak	Boundary
bit 2 (4)	Equatorial boundary	Polar boundary	only if bit 1 set
bit 3 (8)	Boundary pair start	Boundary pair end	only if bit 1 set

These are the possible PointType values:

Value	Hex.	Bin.	Meaning
0	0x0	0b0000	WEJ peak (minimum)
1	0x1	0b0001	EEJ peak (maximum)
2	0x2	0b0010	WEJ equatorial boundary (pair start)
3	0x3	0b0011	EEJ equatorial boundary (pair start)
6	0x6	0b0110	WEJ polar boundary (pair start)
7	0x7	0b0111	EEJ polar boundary (pair start)
10	0xA	0b1010	WEJ equatorial boundary (pair end)
11	0xB	0b1011	EEJ equatorial boundary (pair end)
14	0xE	0b1110	WEJ polar boundary (pair end)
15	0xF	0b1111	EEJ polar boundary (pair end)

Note: If the standard VirES QDLat, QDLat and MLT auxialiary variables default to the Latitude_QD, Longitude_QD, MLT_QD stored in AEBS products if they cannot be calculated from the times and locations. (Locations in the AEBS products are incomplete due to the missing Radius and they cannot be used to calucate the magnetic coordinates.)

In [7]:

equest = SwarmRequest(server_url)
request.set_collection('SW_OPER_AEJAPBS_2F')
request.set_products(
    measurements=[
        'Latitude_QD', 'Longitude_QD', 'MLT_QD',
         'J_DF_SemiQD', 'Flags', 'PointType',
    ],
    auxiliaries=['QDLat', 'QDLon', 'MLT'],
)

data = request.get_between(
    start_time='2015-06-01T00:00:00Z',
    end_time='2015-06-02T00:00:00Z'
).as_xarray()

print(data)

[1/1] Processing:  100%|██████████|  [ Elapsed: 00:01, Remaining: 00:00 ]
      Downloading: 100%|██████████|  [ Elapsed: 00:00, Remaining: 00:00 ] (0.115MB)

<xarray.Dataset>
Dimensions:       (Timestamp: 364)
Coordinates:
  * Timestamp     (Timestamp) datetime64[ns] 2015-06-01T00:01:32 ... 2015-06-01T23:34:07
Data variables:
    Spacecraft    (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' 'A'
    J_DF_SemiQD   (Timestamp) float64 nan nan 96.41 nan ... nan nan -7.49 nan
    Flags         (Timestamp) uint8 96 96 96 96 32 32 32 ... 72 72 72 72 72 72
    PointType     (Timestamp) uint16 10 7 1 11 3 1 15 2 0 ... 0 14 7 1 11 6 0 10
    QDLon         (Timestamp) float64 -45.97 -45.97 -58.46 ... -73.9 -76.97
    Latitude_QD   (Timestamp) float64 -75.57 -75.57 -72.24 ... -54.38 -49.98
    Longitude_QD  (Timestamp) float64 -45.97 -45.97 -58.46 ... -73.9 -76.97
    MLT           (Timestamp) float64 16.38 16.38 15.57 ... 14.37 14.05 13.87
    QDLat         (Timestamp) float64 -75.57 -75.57 -72.24 ... -54.38 -49.98
    Latitude      (Timestamp) float64 -74.35 -74.35 -69.9 ... -52.45 -47.95
    Longitude     (Timestamp) float64 -179.0 -179.0 -176.6 ... -166.0 -165.7
    MLT_QD        (Timestamp) float64 16.38 16.38 15.57 ... 14.37 14.05 13.87
Attributes:
    Sources:         ['SW_OPER_AEJAPBS_2F_20150101T000000_20151231T235959_0101']
    MagneticModels:  []
    RangeFilters:    []

AEJxPBS product - Ground magnetic disturbance¶

The AEJxPBS ground magnetic disturbance is avaialble as a separate dataset.

Avaiables Variables:

VirES Variable	Source Product Variable	Unit	Dimension	Description
`Timestamp`	n/a	$-$	scalar	UTC timestamp ⃰
`Latitude`	`Latitude_B`	$\text{deg}$	scalar	Geodetic latitude ⃰ ⃰
`Longitude`	`Longitude_B`	$\text{deg}$	scalar	Geodetic longitude ⃰ ⃰
`B_NE`	`B`	$\text{nT}$	vector [2]	Peak value of the horizontal ground magnetic disturbance in the geodetic NE frame ⃰ ⃰

⃰ The ground magnetic disturbance timestamp is not present in the original product. It is assigned from the corresponding peak and therefore it may not excatly express the time of the disturbance event.

⃰ ⃰ Due to the missing elevation the geodetic coordinates cannot be reliably converted to ITRF geocentric ones.

In [8]:

SwarmRequest.COLLECTIONS['AEJ_PBS:GroundMagneticDisturbance'] = [
    'SW_OPER_AEJ{}PBS_2F:GroundMagneticDisturbance'.format(x) for x in 'ABC'
]

SwarmRequest.PRODUCT_VARIABLES['AEJ_PBS:GroundMagneticDisturbance'] = ['B']

request = SwarmRequest(server_url)
request.set_collection('SW_OPER_AEJAPBS_2F:GroundMagneticDisturbance')
request.set_products(
    measurements=['B'],
)

data = request.get_between(
    start_time='2015-06-01T00:00:00Z',
    end_time='2015-06-02T00:00:00Z'
).as_xarray()

print(data)

[1/1] Processing:  100%|██████████|  [ Elapsed: 00:01, Remaining: 00:00 ]
      Downloading: 100%|██████████|  [ Elapsed: 00:00, Remaining: 00:00 ] (0.037MB)

<xarray.Dataset>
Dimensions:     (Timestamp: 121)
Coordinates:
  * Timestamp   (Timestamp) datetime64[ns] 2015-06-01T00:02:46 ... 2015-06-01T23:32:53
Data variables:
    Spacecraft  (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' 'A'
    Longitude   (Timestamp) float64 165.7 -144.9 -163.9 ... 34.37 -166.3 178.3
    Latitude    (Timestamp) float64 -82.66 85.2 79.07 ... -72.74 -52.89 -80.83
Attributes:
    Sources:         ['SW_OPER_AEJAPBS_2F_20150101T000000_20151231T235959_0101']
    MagneticModels:  []
    RangeFilters:    []

AOBxFAC product¶

Avaiables Variables:

Variable	Unit	Dimension	Description
`Timestamp`	$-$	scalar	UTC time of observation
`Latitude`	$\text{deg}$	scalar	ITRF geocentric latitude
`Longitude`	$\text{deg}$	scalar	ITRF geocentric longitude
`Latitude_QD`	$\text{deg}$	scalar	Quasi-dipole latitude
`Longitude_QD`	$\text{deg}$	scalar	Quasi-dipole longitude
`MLT_QD`	$\text{hour}$	scalar	Magnetic local time (QD)
`Boundary_Flag`	$-$	scalar	Indicator for equatorward (1) or poleward (2) boundary
`Pair_Indicator`	$-$	scalar	Quality indicator (for more details of the binary flags see the product specification)
`Quality`	$-$	vector [2]	Quality indicator of equatorward/poleward boundary (Pa, Sigma)

Note: If the standard VirES QDLat, QDLat and MLT auxialiary variables default to the Latitude_QD, Longitude_QD, MLT_QD stored in AEBS products if they cannot be calculated from the times and locations. (Locations in the AEBS products are incomplete due to the missing Radius and they cannot be used to calucate the magnetic coordinates.)

In [9]:

request = SwarmRequest(server_url)
request.set_collection('SW_OPER_AOBAFAC_2F')
request.set_products(  
    measurements=[
        'Latitude_QD', 'Longitude_QD', 'MLT_QD',
        'Quality', 'Pair_Indicator',
    ],
    auxiliaries=['QDLat', 'QDLon', 'MLT'],
)

data = request.get_between(
    start_time='2015-06-01T00:00:00Z',
    end_time='2015-06-02T00:00:00Z'
).as_xarray()

print(data)

[1/1] Processing:  100%|██████████|  [ Elapsed: 00:01, Remaining: 00:00 ]
      Downloading: 100%|██████████|  [ Elapsed: 00:00, Remaining: 00:00 ] (0.115MB)

<xarray.Dataset>
Dimensions:         (Quality_dim1: 2, Timestamp: 102)
Coordinates:
  * Timestamp       (Timestamp) datetime64[ns] 2015-06-01T00:02:10.500000 ... 2015-06-01T23:26:29.500000
Dimensions without coordinates: Quality_dim1
Data variables:
    Spacecraft      (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A'
    Pair_Indicator  (Timestamp) int8 1 -1 1 -1 1 -1 1 -1 ... -1 0 1 -1 1 -1 0 0
    QDLon           (Timestamp) float64 -53.06 -59.62 -115.8 ... 23.12 -38.02
    Latitude_QD     (Timestamp) float64 -73.47 -71.3 70.39 ... -77.08 -74.39
    Longitude_QD    (Timestamp) float64 -53.11 -59.66 -115.8 ... 23.11 -38.06
    MLT             (Timestamp) float64 15.92 15.49 12.34 ... 1.213 20.36 16.35
    Quality         (Timestamp, Quality_dim1) float64 4.012 0.1697 ... 0.2392
    QDLat           (Timestamp) float64 -73.46 -71.29 70.4 ... -77.08 -74.39
    Latitude        (Timestamp) float64 -72.0 -69.22 72.77 ... -87.26 -75.78
    Longitude       (Timestamp) float64 -175.9 -174.9 -168.6 ... 95.84 -170.6
    Radius          (Timestamp) float64 6.839e+06 6.839e+06 ... 6.839e+06
    MLT_QD          (Timestamp) float64 15.92 15.49 12.34 ... 1.21 20.36 16.34
Attributes:
    Sources:         ['SW_OPER_AOBAFAC_2F_20150101T000000_20151231T235959_0102']
    MagneticModels:  []
    RangeFilters:    []