This notebook demonstrates access to the data the MITx_LP_2F
, MITxTEC_2F
and PPIxFAC_2F
Swarm products 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 the products is provided [link to product documentation TBD].
The data for the whole Swarm mission is avaiable from the production VirES server API.
from viresclient import SwarmRequest
SERVER_URL = "https://vires.services/ows"
Collection | Dataset |
---|---|
SW_OPER_MITA_LP_2F |
Swarm A MIT from LP - MIT minima |
SW_OPER_MITA_LP_2F:ID |
Swarm A MIT from LP - MIT boundaries ("ID" dataset) |
SW_OPER_MITB_LP_2F |
Swarm B MIT from LP - MIT minima |
SW_OPER_MITB_LP_2F:ID |
Swarm B MIT from LP - MIT boundaries ("ID" dataset) |
SW_OPER_MITC_LP_2F |
Swarm C MIT from LP - MIT minima |
SW_OPER_MITC_LP_2F:ID |
Swarm C MIT from LP - MIT boundaries ("ID" dataset) |
SW_OPER_MITx_LP_2F
collections)¶Avaiables Variables:
VirES Variable | Source Product Variable | Unit | Dimension | Description |
---|---|---|---|---|
Counter |
Counter |
$$-$$ | vector[2] | Swarm orbit and quarter orbit counters |
Timestamp |
Timestamp |
$$-$$ | scalar | UTC time of the MIT minimum |
Latitude |
Latitude |
$$\text{deg}$$ | scalar | ITRF geocentric latitude of the MIT minimum |
Longitude |
Longitude |
$$\text{deg}$$ | scalar | ITRF geocentric longitude of the MIT minimum |
Radius |
Radius |
$$\text{m}$$ | scalar | ITRF geocentric radius of the MIT minimum |
Latitude_QD |
Latitude_QD |
$$\text{deg}$$ | scalar | Quasi-dipole latitude of the MIT minimum |
Longitude_QD |
Longitude_QD |
$$\text{deg}$$ | scalar | Quasi-dipole longitude of the MIT minimum |
MLT_QD |
MLT |
$$\text{hour}$$ | scalar | Magnetic local time (QD) of the MIT minimum |
L_value |
L_value |
$$-$$ | scalar | L-value in earth radii of the MIT minimum |
SZA |
SZA |
$$\text{deg}$$ | scalar | Solar zenith angle of the MIT minimum |
Ne |
Ne |
$$\text{cm}^{-3}$$ | scalar | LP electron density of the MIT minimum |
Te |
Te |
$$\text{K}$$ | scalar | LP electron temperature of the MIT minimum |
Depth |
Depth |
$$\text{cm}^{-3}$$ | scalar | depth of the MIT |
DR |
DR |
$$\text{%}$$ | scalar | relative change in density within the MIT |
Width |
Width |
$$\text{deg}$$ | scalar | width of the MIT calculated from QD latitudes |
dL |
dL |
$$\text{deg}$$ | scalar | width of the MIT calculated from L-values |
PW_Gradient |
PW_Gradient |
$$\log{\left(\text{cm}^{-3}\right)}\,\text{deg}^{-1}$$ | scalar | change in log electron density at the poleward wall of the MIT divided by QD latitude difference |
EW_Gradient |
EW_Gradient |
$$\log{\left(\text{cm}^{-3}\right)}\,\text{deg}^{-1}$$ | scalar | change in log electron density at the equatorward wall of the MIT divided by QD latitude difference |
Quality |
Quality |
$$-$$ | vector [8] | Characterises the detection quality of the MIT as a whole |
The Quality
vector flags contain integer values from -1 to 3 indicating the quality of the MIT as a whole.
Positive values indicate good or acceptable observation, while -1 means a likely false observation.
For all flags, a 0 value means that the information needed to derive the flag is not available.
In general, greater numbers indicate higher quality. For more details, see the product documentation.
SW_OPER_MITx_LP_2F:ID
collections)¶Avaiables Variables:
VirES Variable | Source Product Variable | Unit | Dimension | Description |
---|---|---|---|---|
Counter |
Counter |
$$-$$ | vector[2] | Swarm orbit and quarter orbit counters |
Timestamp |
Timestamp_ID |
$$-$$ | scalar | UTC time of the observation |
Latitude |
Latitude_ID |
$$\text{deg}$$ | scalar | ITRF geocentric latitude |
Longitude |
Longitude_ID |
$$\text{deg}$$ | scalar | ITRF geocentric longitude |
Radius |
Radius_ID |
$$\text{m}$$ | scalar | ITRF geocentric radius |
Latitude_QD |
Latitude_QD_ID |
$$\text{deg}$$ | scalar | Quasi-dipole latitude |
Longitude_QD |
Longitude_QD_ID |
$$\text{deg}$$ | scalar | Quasi-dipole longitude |
MLT_QD |
MLT_ID |
$$\text{hour}$$ | scalar | Magnetic local time (QD) |
L_value |
L_value_ID |
$$-$$ | scalar | L-value in earth radii |
SZA |
SZA_ID |
$$\text{deg}$$ | scalar | Solar zenith angle |
Ne |
Ne_ID |
$$\text{cm}^{-3}$$ | scalar | LP electron density |
Te |
Te_ID |
$$\text{K}$$ | scalar | LP electron temperature |
Position_Quality |
Position_Quality_ID |
$$-$$ | scalar | detection quality of each single position |
PointType |
n/a | $$-$$ | scalar | point type derived from the source *_ID column |
Position_Quality
describes the overall quality of the corresponding boundary/position. The possible values and their meaning are 3: highest quality; 2: fair quality;
1: uncertain detection; -1: a likely false positive detection; -2: the corresponding boundary/position is not defined. For more details, see the product documentation.
These are the possible PointType
values for the MITx_LP_2F products:
Value | Hex. | Bin. | ID Column | Meaning |
---|---|---|---|---|
0 | 0x0 | 0b0000 | 1 | LP MIT equatorward edge of the equatorward wall |
1 | 0x1 | 0b0001 | 2 | LP MIT poleward edge of the equatorward wall |
2 | 0x2 | 0b0010 | 3 | LP MIT equatorward edge of poleward wall |
3 | 0x3 | 0b0011 | 4 | LP MIT poleward edge of the poleward boundary |
4 | 0x4 | 0b0100 | 5 | LP SETE equatorward bounding position |
5 | 0x5 | 0b0101 | 7 | LP SETE poleward bounding position |
6 | 0x6 | 0b0110 | 6 | LP Te peak position |
request = SwarmRequest(SERVER_URL)
# request the default dataset
request.set_collection("SW_OPER_MITA_LP_2F")
request.set_products(
measurements=SwarmRequest.PRODUCT_VARIABLES["MIT_LP"], # request all dataset variables
auxiliaries=['QDLat', 'QDLon', 'MLT'], # QD coordinates and MLT calculated by VirES
)
data = request.get_between(
start_time="2016-01-02T00:00:00Z",
end_time="2016-01-03T00:00:00Z",
asynchronous=False,
).as_xarray()
print("Requested variables", ", ".join(SwarmRequest.PRODUCT_VARIABLES["MIT_LP:ID"]))
print("Response:", data)
# request the ID dataset
request.set_collection("SW_OPER_MITA_LP_2F:ID")
request.set_products(
measurements=SwarmRequest.PRODUCT_VARIABLES["MIT_LP:ID"], # request all dataset variables
auxiliaries=['QDLat', 'QDLon', 'MLT'], # QD coordinates and MLT calculated by VirES
)
data = request.get_between(
start_time="2016-01-02T00:00:00Z",
end_time="2016-01-03T00:00:00Z",
asynchronous=False,
).as_xarray()
print("Requested variables", ", ".join(SwarmRequest.PRODUCT_VARIABLES["MIT_LP:ID"]))
print("Response:", data)
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Requested variables Counter, Latitude_QD, Longitude_QD, MLT_QD, L_value, SZA, Ne, Te, Position_Quality, PointType Response: <xarray.Dataset> Dimensions: (Timestamp: 26, Quality_dim1: 8, Counter_dim1: 2) Coordinates: * Timestamp (Timestamp) datetime64[ns] 2016-01-02T01:55:43.196999936 ..... Dimensions without coordinates: Quality_dim1, Counter_dim1 Data variables: (12/22) Spacecraft (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' 'A' Latitude (Timestamp) float64 62.78 64.77 63.47 ... 57.11 60.2 55.09 SZA (Timestamp) float64 115.9 110.0 116.0 ... 115.7 107.9 115.5 DR (Timestamp) float64 22.8 61.76 22.73 ... 22.84 22.67 42.02 L_value (Timestamp) float64 4.054 6.672 4.327 ... 2.792 8.536 2.718 Ne (Timestamp) float64 6.839e+03 1.713e+04 ... 1.004e+04 ... ... Longitude_QD (Timestamp) float64 124.8 -85.74 103.9 ... -159.2 -13.53 154.7 QDLat (Timestamp) float64 59.08 66.39 60.18 ... 51.75 69.26 51.14 Counter (Timestamp, Counter_dim1) uint32 11820 2 11821 1 ... 1 11834 2 Latitude_QD (Timestamp) float64 59.08 66.39 60.18 ... 51.75 69.26 51.14 PW_Gradient (Timestamp) float64 0.1788 0.1281 0.2573 ... 0.1277 0.08771 MLT_QD (Timestamp) float64 5.114 16.5 5.387 ... 4.955 17.43 4.926 Attributes: Sources: ['SW_OPER_MITA_LP_2F_20160101T000000_20161231T235959_0103'] MagneticModels: [] RangeFilters: []
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Requested variables Counter, Latitude_QD, Longitude_QD, MLT_QD, L_value, SZA, Ne, Te, Position_Quality, PointType Response: <xarray.Dataset> Dimensions: (Timestamp: 146, Counter_dim1: 2) Coordinates: * Timestamp (Timestamp) datetime64[ns] 2016-01-02T01:55:10.19699993... Dimensions without coordinates: Counter_dim1 Data variables: (12/17) Spacecraft (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' Latitude (Timestamp) float64 64.89 64.7 63.1 ... 54.99 47.94 46.09 SZA (Timestamp) float64 116.1 116.1 115.9 ... 114.2 113.8 Position_Quality (Timestamp) int8 3 3 3 3 3 3 2 -1 3 ... 3 3 3 3 -1 2 3 3 2 L_value (Timestamp) float64 4.607 4.552 4.131 ... 2.707 2.055 1.93 Ne (Timestamp) float64 1.368e+04 1.345e+04 ... 3.418e+04 ... ... Te (Timestamp) float64 2.077e+03 2.125e+03 ... 2.01e+03 Longitude_QD (Timestamp) float64 125.1 125.0 124.8 ... 154.8 154.8 QDLat (Timestamp) float64 61.19 61.0 59.4 ... 51.04 43.8 41.87 Counter (Timestamp, Counter_dim1) uint32 11820 2 11820 ... 11834 2 Latitude_QD (Timestamp) float64 61.19 61.0 59.4 ... 51.04 43.8 41.87 MLT_QD (Timestamp) float64 5.126 5.125 5.115 ... 4.964 4.973 Attributes: Sources: ['SW_OPER_MITA_LP_2F_20160101T000000_20161231T235959_0103'] MagneticModels: [] RangeFilters: []
Collection | Dataset |
---|---|
SW_OPER_MITATEC_2F |
Swarm A MIT from GPS TEC - MIT minima |
SW_OPER_MITATEC_2F:ID |
Swarm A MIT from GPS TEC - MIT boundaries ("ID" dataset) |
SW_OPER_MITBTEC_2F |
Swarm B MIT from GPS TEC - MIT minima |
SW_OPER_MITBTEC_2F:ID |
Swarm B MIT from GPS TEC - MIT boundaries ("ID" dataset) |
SW_OPER_MITCTEC_2F |
Swarm C MIT from GPS TEC - MIT minima |
SW_OPER_MITCTEC_2F:ID |
Swarm C MIT from GPS TEC - MIT boundaries ("ID" dataset) |
SW_OPER_MITxTEC_2F
collections)¶Avaiables Variables:
VirES Variable | Source Product Variable | Unit | Dimension | Description |
---|---|---|---|---|
Counter |
Counter |
$$-$$ | vector[2] | Swarm orbit and quarter orbit counters |
Timestamp |
Timestamp |
$$-$$ | scalar | UTC time of the MIT minimum |
Latitude |
Latitude |
$$\text{deg}$$ | scalar | ITRF geocentric latitude of the MIT minimum |
Longitude |
Longitude |
$$\text{deg}$$ | scalar | ITRF geocentric longitude of the MIT minimum |
Radius |
Radius |
$$\text{m}$$ | scalar | ITRF geocentric radius of the MIT minimum |
Latitude_QD |
Latitude_QD |
$$\text{deg}$$ | scalar | Quasi-dipole latitude of the MIT minimum |
Longitude_QD |
Longitude_QD |
$$\text{deg}$$ | scalar | Quasi-dipole longitude of the MIT minimum |
MLT_QD |
MLT |
$$\text{hour}$$ | scalar | Magnetic local time (QD) of the MIT minimum |
L_value |
L_value |
$$-$$ | scalar | L-value in earth radii of the MIT minimum |
SZA |
SZA |
$$\text{deg}$$ | scalar | Solar zenith angle of the MIT minimum |
TEC |
TEC |
$$\text{TECU}$$ | scalar | Total electron content at the MIT minimum |
Depth |
Depth |
$$\text{TECU}$$ | scalar | depth of the MIT |
DR |
DR |
$$\text{%}$$ | scalar | relative change in density within the MIT |
Width |
Width |
$$\text{deg}$$ | scalar | width of the MIT calculated from QD latitudes |
dL |
dL |
$$\text{deg}$$ | scalar | width of the MIT calculated from L-values |
PW_Gradient |
PW_Gradient |
$$\text{TECU}\,\text{deg}^{-1}$$ | scalar | change in TEC at the poleward wall of the MIT divided by QD latitude difference |
EW_Gradient |
EW_Gradient |
$$\text{TECU}\,\text{deg}^{-1}$$ | scalar | change in TEC at the equatorward wall of the MIT divided by QD latitude difference |
Quality |
Quality |
$$-$$ | vector [8] | Characterises the detection quality of the MIT as a whole |
The Quality
vector flags contain integer values from -1 to 3 indicating the quality of the MIT as a whole.
Positive values indicate good or acceptable observation, while -1 means a likely false observation.
For all flags, a 0 value means that the information needed to derive the flag is not available.
In general, greater numbers indicate higher quality. For more details, see the product documentation.
SW_OPER_MITxTEC_2F:ID
collections)¶Avaiables Variables:
VirES Variable | Source Product Variable | Unit | Dimension | Description |
---|---|---|---|---|
Counter |
Counter |
$$-$$ | vector[2] | Swarm orbit and quarter orbit counters |
Timestamp |
Timestamp_ID |
$$-$$ | scalar | UTC time of the observation |
Latitude |
Latitude_ID |
$$\text{deg}$$ | scalar | ITRF geocentric latitude |
Longitude |
Longitude_ID |
$$\text{deg}$$ | scalar | ITRF geocentric longitude |
Radius |
Radius_ID |
$$\text{m}$$ | scalar | ITRF geocentric radius |
Latitude_QD |
Latitude_QD_ID |
$$\text{deg}$$ | scalar | Quasi-dipole latitude |
Longitude_QD |
Longitude_QD_ID |
$$\text{deg}$$ | scalar | Quasi-dipole longitude |
MLT_QD |
MLT_ID |
$$\text{hour}$$ | scalar | Magnetic local time (QD) |
L_value |
L_value_ID |
$$-$$ | scalar | L-value in earth radii |
SZA |
SZA_ID |
$$\text{deg}$$ | scalar | Solar zenith angle |
TEC |
TEC_ID |
$$\text{TECU}$$ | scalar | Total electron content |
Position_Quality |
Position_Quality_ID |
$$-$$ | scalar | detection quality of each single position |
PointType |
n/a | $$-$$ | scalar | point type derived from the source *_ID column |
Position_Quality
describes the overall quality of the corresponding boundary/position. The possible values and their meaning are 3: highest quality; 2: fair quality;
1: uncertain detection; -1: a likely false positive detection; -2: the corresponding boundary/position is not defined. For more details, see the product documentation.
These are the possible PointType
values for the MITxTEC_2F products:
Value | Hex. | Bin. | ID Column | Meaning |
---|---|---|---|---|
0 | 0x0 | 0b0000 | 1 | TEC MIT equatorward edge of the equatorward wall |
1 | 0x1 | 0b0001 | 2 | TEC MIT poleward edge of the equatorward wall |
2 | 0x2 | 0b0010 | 3 | TEC MIT equatorward edge of poleward wall |
3 | 0x3 | 0b0011 | 4 | TEC MIT poleward edge of the poleward boundary |
request = SwarmRequest(SERVER_URL)
# request the default dataset
request.set_collection("SW_OPER_MITATEC_2F")
request.set_products(
measurements=SwarmRequest.PRODUCT_VARIABLES["MIT_TEC"], # request all dataset variables
auxiliaries=['QDLat', 'QDLon', 'MLT'], # QD coordinates and MLT calculated by VirES
)
data = request.get_between(
start_time="2016-01-02T00:00:00Z",
end_time="2016-01-03T00:00:00Z",
asynchronous=False,
).as_xarray()
print("Requested variables", ", ".join(SwarmRequest.PRODUCT_VARIABLES["MIT_TEC:ID"]))
print("Response:", data)
# request the ID dataset
request.set_collection("SW_OPER_MITATEC_2F:ID")
request.set_products(
measurements=SwarmRequest.PRODUCT_VARIABLES["MIT_TEC:ID"], # request all dataset variables
auxiliaries=['QDLat', 'QDLon', 'MLT'], # QD coordinates and MLT calculated by VirES
)
data = request.get_between(
start_time="2016-01-02T00:00:00Z",
end_time="2016-01-03T00:00:00Z",
asynchronous=False,
).as_xarray()
print("Requested variables", ", ".join(SwarmRequest.PRODUCT_VARIABLES["MIT_TEC:ID"]))
print("Response:", data)
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Requested variables Counter, Latitude_QD, Longitude_QD, MLT_QD, L_value, SZA, TEC, Position_Quality, PointType Response: <xarray.Dataset> Dimensions: (Timestamp: 15, Quality_dim1: 8, Counter_dim1: 2) Coordinates: * Timestamp (Timestamp) datetime64[ns] 2016-01-02T06:24:35 ... 2016-01-... Dimensions without coordinates: Quality_dim1, Counter_dim1 Data variables: (12/21) Spacecraft (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' 'A' Latitude (Timestamp) float64 71.06 70.22 69.19 ... 63.61 60.73 63.39 SZA (Timestamp) float64 111.8 111.5 111.2 ... 116.4 108.1 116.4 DR (Timestamp) float64 87.17 82.74 69.45 ... 84.17 81.56 77.3 L_value (Timestamp) float64 7.023 6.087 5.634 ... 3.827 8.94 4.142 Depth (Timestamp) float64 0.4311 0.5704 1.165 ... 0.7037 0.7399 ... ... Longitude_QD (Timestamp) float64 -126.6 -143.7 -162.4 ... -13.46 154.4 QDLat (Timestamp) float64 67.03 65.1 64.11 ... 58.07 69.76 59.4 Counter (Timestamp, Counter_dim1) uint32 11823 1 11824 1 ... 1 11834 2 Latitude_QD (Timestamp) float64 67.03 65.1 64.11 ... 58.07 69.76 59.4 PW_Gradient (Timestamp) float64 0.09949 0.1164 0.1653 ... 0.3494 0.2213 MLT_QD (Timestamp) float64 17.2 17.72 18.07 ... 4.656 17.44 4.871 Attributes: Sources: ['SW_OPER_MITATEC_2F_20160101T000000_20161231T235959_0103'] MagneticModels: [] RangeFilters: []
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Requested variables Counter, Latitude_QD, Longitude_QD, MLT_QD, L_value, SZA, TEC, Position_Quality, PointType Response: <xarray.Dataset> Dimensions: (Timestamp: 60, Counter_dim1: 2) Coordinates: * Timestamp (Timestamp) datetime64[ns] 2016-01-02T06:21:52 ... 2016... Dimensions without coordinates: Counter_dim1 Data variables: (12/16) Spacecraft (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' Latitude (Timestamp) float64 60.65 63.15 77.01 ... 54.81 51.03 SZA (Timestamp) float64 108.6 109.4 113.3 ... 115.3 114.7 Position_Quality (Timestamp) int8 1 3 -1 -1 2 3 -1 -1 ... 3 -1 -1 -1 3 3 -1 L_value (Timestamp) float64 3.368 3.895 13.32 ... 9.49 2.87 2.371 MLT (Timestamp) float64 17.37 17.35 16.97 ... 4.928 4.949 ... ... PointType (Timestamp) uint8 0 1 2 3 0 1 2 3 0 ... 0 0 1 2 3 3 2 1 0 Longitude_QD (Timestamp) float64 -123.3 -123.8 -130.5 ... 154.7 154.8 QDLat (Timestamp) float64 55.69 58.39 73.53 ... 70.16 50.86 47.0 Counter (Timestamp, Counter_dim1) uint32 11823 1 11823 ... 11834 2 Latitude_QD (Timestamp) float64 55.69 58.39 73.53 ... 70.16 50.86 47.0 MLT_QD (Timestamp) float64 17.37 17.35 16.97 ... 4.928 4.949 Attributes: Sources: ['SW_OPER_MITATEC_2F_20160101T000000_20161231T235959_0103'] MagneticModels: [] RangeFilters: []
Collection | Dataset |
---|---|
SW_OPER_PPIAFAC_2F |
Swarm A PPI and SSFAC boundaries |
SW_OPER_PPIAFAC_2F:ID |
Swarm A edges of the SSFAC boundaries ("ID" dataset) |
SW_OPER_PPIBFAC_2F |
Swarm B PPI and SSFAC boundaries |
SW_OPER_PPIBFAC_2F:ID |
Swarm B edges of the SSFAC boundaries ("ID" dataset) |
SW_OPER_PPICFAC_2F |
Swarm C PPI and SSFAC boundaries |
SW_OPER_PPICFAC_2F:ID |
Swarm C edges of the SSFAC boundaries ("ID" dataset) |
SW_OPER_PPIxFAC_2F
collections)¶Avaiables Variables:
VirES Variable | Source Product Variable | Unit | Dimension | Description |
---|---|---|---|---|
Counter |
Counter |
$$-$$ | vector[2] | Swarm orbit and quarter orbit counters |
Timestamp |
Timestamp |
$$-$$ | scalar | UTC time of the SSFAC boundary |
Latitude |
Latitude |
$$\text{deg}$$ | scalar | ITRF geocentric latitude of the SSFAC boundary |
Longitude |
Longitude |
$$\text{deg}$$ | scalar | ITRF geocentric longitude of the SSFAC boundary |
Radius |
Radius |
$$\text{m}$$ | scalar | ITRF geocentric radius of the SSFAC boundary |
Latitude_QD |
Latitude_QD |
$$\text{deg}$$ | scalar | Quasi-dipole latitude of the SSFAC boundary |
Longitude_QD |
Longitude_QD |
$$\text{deg}$$ | scalar | Quasi-dipole longitude of the SSFAC boundary |
MLT_QD |
MLT |
$$\text{hour}$$ | scalar | Magnetic local time (QD) of the SSFAC boundary |
L_value |
L_value |
$$-$$ | scalar | L-value in earth radii of the SSFAC boundary |
SZA |
SZA |
$$\text{deg}$$ | scalar | Solar zenith angle of the SSFAC boundary |
Sigma |
Sigma |
$$-$$ | scalar | Standard deviation of the linear fit of S at the boundary |
PPI |
PPI |
$$\text{R_E}$$ | scalar | midnight plasmapause index |
dL |
dL |
$$\text{deg}$$ | scalar | boundary width in Earth radii |
Quality |
Quality |
$$-$$ | vector [7] | Quality indicators of SSFAC boundary detection |
The Quality
vector flags contain integer values from -1 to 3 indicating the quality of the MIT as a whole.
Positive values indicate good or acceptable observation, while -1 means a likely false observation.
For all flags, a 0 value means that the information needed to derive the flag is not available.
In general, greater numbers indicate higher quality. For more details, see the product documentation.
SW_OPER_PPIxFAC_2F:ID
collections)¶Avaiables Variables:
VirES Variable | Source Product Variable | Unit | Dimension | Description |
---|---|---|---|---|
Counter |
Counter |
$$-$$ | vector[2] | Swarm orbit and quarter orbit counters |
Timestamp |
Timestamp_ID |
$$-$$ | scalar | UTC time of the observation |
Latitude |
Latitude_ID |
$$\text{deg}$$ | scalar | ITRF geocentric latitude |
Longitude |
Longitude_ID |
$$\text{deg}$$ | scalar | ITRF geocentric longitude |
Radius |
Radius_ID |
$$\text{m}$$ | scalar | ITRF geocentric radius |
Latitude_QD |
Latitude_QD_ID |
$$\text{deg}$$ | scalar | Quasi-dipole latitude |
Longitude_QD |
Longitude_QD_ID |
$$\text{deg}$$ | scalar | Quasi-dipole longitude |
MLT_QD |
MLT_ID |
$$\text{hour}$$ | scalar | Magnetic local time (QD) |
L_value |
L_value_ID |
$$-$$ | scalar | L-value in earth radii |
SZA |
SZA_ID |
$$\text{deg}$$ | scalar | Solar zenith angle |
Position_Quality |
Position_Quality_ID |
$$-$$ | scalar | detection quality of each single position |
PointType |
n/a | $$-$$ | scalar | point type derived from the source *_ID column |
Position_Quality
describes the overall quality of the corresponding boundary/position. The possible values and their meaning are 3: highest quality; 2: fair quality;
1: uncertain detection; -1: a likely false positive detection; -2: the corresponding boundary/position is not defined. For more details, see the product documentation.
These are the possible PointType
values for the PPIxFAC_2F products:
Value | Hex. | Bin. | ID Column | |
---|---|---|---|---|
0 | 0x0 | 0b0000 | 1 | equatorward edge of SSFAC boundary |
1 | 0x1 | 0b0001 | 2 | poleward edge of SSFAC boundary |
request = SwarmRequest(SERVER_URL)
# request the default dataset
request.set_collection("SW_OPER_PPIAFAC_2F")
request.set_products(
measurements=SwarmRequest.PRODUCT_VARIABLES["PPI_FAC"], # request all dataset variables
auxiliaries=['QDLat', 'QDLon', 'MLT'], # QD coordinates and MLT calculated by VirES
)
data = request.get_between(
start_time="2016-01-02T00:00:00Z",
end_time="2016-01-03T00:00:00Z",
asynchronous=False,
).as_xarray()
print("Requested variables", ", ".join(SwarmRequest.PRODUCT_VARIABLES["PPI_FAC:ID"]))
print("Response:", data)
# request the ID dataset
request.set_collection("SW_OPER_PPIAFAC_2F:ID")
request.set_products(
measurements=SwarmRequest.PRODUCT_VARIABLES["PPI_FAC:ID"], # request all dataset variables
auxiliaries=['QDLat', 'QDLon', 'MLT'], # QD coordinates and MLT calculated by VirES
)
data = request.get_between(
start_time="2016-01-02T00:00:00Z",
end_time="2016-01-03T00:00:00Z",
asynchronous=False,
).as_xarray()
print("Requested variables", ", ".join(SwarmRequest.PRODUCT_VARIABLES["PPI_FAC:ID"]))
print("Response:", data)
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Requested variables Counter, Latitude_QD, Longitude_QD, MLT_QD, L_value, SZA, Position_Quality, PointType Response: <xarray.Dataset> Dimensions: (Timestamp: 25, Quality_dim1: 7, Counter_dim1: 2) Coordinates: * Timestamp (Timestamp) datetime64[ns] 2016-01-02T00:05:50.500000 ... 2... Dimensions without coordinates: Quality_dim1, Counter_dim1 Data variables: (12/17) Spacecraft (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' 'A' Latitude (Timestamp) float64 54.2 69.51 37.46 ... 54.51 64.04 68.72 SZA (Timestamp) float64 106.6 116.4 99.95 ... 105.9 116.5 116.7 L_value (Timestamp) float64 5.059 5.873 1.929 ... 4.518 3.976 5.507 MLT (Timestamp) float64 17.21 4.956 16.88 ... 18.07 4.848 4.823 Quality (Timestamp, Quality_dim1) int8 3 3 -1 0 -1 1 ... -1 -1 0 1 1 3 ... ... Longitude_QD (Timestamp) float64 -25.57 146.9 -53.39 ... 19.23 177.1 154.1 PPI (Timestamp) float64 5.022 5.931 1.881 ... 4.526 4.04 5.571 QDLat (Timestamp) float64 63.36 65.41 43.44 ... 61.67 59.61 64.55 Counter (Timestamp, Counter_dim1) uint32 11819 1 11819 2 ... 2 11834 2 Latitude_QD (Timestamp) float64 63.36 65.41 43.44 ... 61.67 59.61 64.55 MLT_QD (Timestamp) float64 17.21 4.956 16.88 ... 18.07 4.848 4.823 Attributes: Sources: ['SW_OPER_PPIAFAC_2F_20160101T000000_20161231T235959_0103'] MagneticModels: [] RangeFilters: []
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Requested variables Counter, Latitude_QD, Longitude_QD, MLT_QD, L_value, SZA, Position_Quality, PointType Response: <xarray.Dataset> Dimensions: (Timestamp: 50, Counter_dim1: 2) Coordinates: * Timestamp (Timestamp) datetime64[ns] 2016-01-02T00:05:07.500000 .... Dimensions without coordinates: Counter_dim1 Data variables: (12/15) Spacecraft (Timestamp) object 'A' 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A' Latitude (Timestamp) float64 51.45 54.97 72.12 ... 72.41 67.63 SZA (Timestamp) float64 105.6 106.9 116.5 ... 116.8 116.7 Position_Quality (Timestamp) int8 2 2 2 2 2 2 2 2 2 2 ... 2 1 1 2 2 3 3 2 2 L_value (Timestamp) float64 4.253 5.328 7.181 ... 7.279 5.113 MLT (Timestamp) float64 17.2 17.21 4.941 ... 4.902 4.781 4.834 ... ... PointType (Timestamp) uint8 0 1 1 0 0 1 1 0 1 ... 1 1 0 0 1 1 0 1 0 Longitude_QD (Timestamp) float64 -25.52 -25.58 146.9 ... 153.7 154.2 QDLat (Timestamp) float64 60.72 64.09 67.89 ... 68.05 63.51 Counter (Timestamp, Counter_dim1) uint32 11819 1 11819 ... 11834 2 Latitude_QD (Timestamp) float64 60.72 64.09 67.89 ... 68.05 63.51 MLT_QD (Timestamp) float64 17.2 17.21 4.941 ... 4.902 4.781 4.834 Attributes: Sources: ['SW_OPER_PPIAFAC_2F_20160101T000000_20161231T235959_0103'] MagneticModels: [] RangeFilters: []