amda-topcat use case
DESCRIPTION
AMDA-TOPCAT use case. Magnetospheric regions automatic identification V. Génot – October 2012 – V2 [email protected] Special thanks to the CDPP team, M. Taylor (TOPCAT) & K. Meziane. Science use case. Based on Jelinek et al., JGR 2012 (paper1) Uses AMDA for the analysis - PowerPoint PPT PresentationTRANSCRIPT
AMDA-TOPCAT use case
Magnetospheric regions automatic identification
V. Génot – October 2012 – [email protected]
Special thanks to the CDPP team, M. Taylor (TOPCAT) & K. Meziane
Science use case• Based on Jelinek et al., JGR 2012 (paper1)• Uses AMDA for the analysis• Uses TOPCAT for visualisations• Uses IVOA SAMP to exchange data between AMDA and TOPCAT
Goal : • Reproduce two paper1’s results in a few steps
– Identify solar wind / magnetosheah / magnetosphere– Identify bow shock and magnetopause
• Explore AMDA/TOPCAT enhanced functionalities– AMDA conditional parameters– TOPCAT weighted density maps
• Propose new research perspectives
Magnetospheric region identification in Paper1
mag
neto
sphe
re
magnetosheath
solar wind
All THEMIS data 2007/03/01-2009/10/01
With ACE data shifted to THEMIS A position
THEMIS A magnetospheric sampling over ~3 years
3dview.cesr.fr
THEMIS A orbits from 2007/03/01 to 2009/10/01
Magnetospheric regions
-- only THEMIS A
Jelinek et al., JGR 2012
AMDA – TOPCAT analysis
In both cases, the bin/contour represents the number of events
solar wind
magnetosheath
mag
neto
sphe
re
Magnetospheric regions
• rB>4-rn
• rB<10rn
Magnetosheath region
rB=4-rn
rB=10rn
= rn
rB
Condition from the plot above :
Bow shock and magnetopause identification
Jelinek et al., JGR 2012
AMDA – TOPCAT analysis
In both case, each bin represents the probability (<1) for this location to be in the magnetosheath
In TOPCAT this is automatically computed from the flag_msh values
Step by step AMDA–TOPCAT analysisMagnetospheric region identification
• define rB and rn in AMDA (create new parameters, see slide for exact definition)• time delay between ACE and THEMIS A is taken constant
• for instance : shift(param,4000) shifts ACE data from 4000s forward• here : param=BACE or nACE
• a better approach would use (see plot) : T=|XACE-XTHEMIS_A|/VSW
• a much better approach would use an iterative algorithm to compute T• for instance see http://cdpp-amda.cesr.fr/DDHTML/HELP/delay.html
• launch TOPCAT ; it automatically opens a SAMP hub• in AMDA : click the « interoperability » and open a SAMP connection• download rB and rn on 2007/03/01 – 2009/10/01 at 60s resolution (all in one file)• in AMDA : in the « Download Results » window choose « Send to TOPCAT »• the table is automatically loaded in TOPCAT• choose « density map » (2D histogram) : rB function of rn
• adjust binning and plotting range as necessary (0-8 for rn, 0-22 for rB)• do not worry about NaN values !
Step by step AMDA–TOPCAT analysisBow shock and magnetopause identification
Use of AMDA conditional parameters
• define the solar wind ram pressure pSW shifted to THEMIS A• time delay may be taken as 4000s as before• pSW=1.67e-6nACEVACE^2
• produce a time table T1 when the pSW values are in a restricted band (ex: pSW<4)• define a new (conditional) parameter : flag_msh
• flag_msh=1 if rB>4-rn and rB<10rn (see plot), else 0 (for solar wind and magnetosphere)
• download XTHA, sqrt(YTHA^2+ZTHA^2), flag_msh at 3600 s resolution (all in one file) for the above T1 time table
• the table is loaded into TOPCAT• choose « density map » (2D histogram) :
•sqrt(Y^2+Z^2) function of X weighted by flag_msh• adjust binning as necessary
Transfer via SAMP (same procedure as before)
r_n = n_i_tha/shiftT_(sw(0),4000)
r_b = bs_tha(3)/shiftT_(imf(3),4000)
Parameter definition in AMDA
p_sw = shiftT_(sw(0)*sw(1)*sw(1),4000)*1.67e-6
flag_msh = (n_i_tha/shiftT_(sw(0),4000)+bs_tha(3)/shiftT_(imf(3),4000) > 4.) & (bs_tha(3)/shiftT_(imf(3),4000) - 10.*n_i_tha/shiftT_(sw(0),4000) <0.)
flag_msh value is either 1 (THEMIS A is in the magnetosheath) or 0
3dview.cesr.fr
Time delay between ACE and THEMIS A
It is computed along the XGSE direction : T=|XACE-XTHEMIS_A|/VSW
Here the delay T is almost constant (2400) so r_b is bs_tha(3)/shiftT_(imf(3),2400)
Time delay
T=2400
T=|XACE-XTHEMIS_A|/VSW
r_b
r_b
Here the delay T varies much more, a « banded » delay could be adopted (not implemented here) with conditional parameters :
bs_tha(3)/shiftT_(imf(3),2400)
or
bs_tha(3)/shiftT_(imf(3),3200)
or
bs_tha(3)/shiftT_(imf(3),4000)
T=2400 T=3200 T=4000
Time delay
In AMDA a conditional parameter P is such that P=1 if P is true Ex: C=A*(T<3600)+B*(T>3600) is equal to either A or B depending on the value of T
T=|XACE-XTHEMIS_A|/VSW
r_b
r_b
Perspectives
•Refine analysis with smaller ram pressure domains•Extend to larger time intervals, and other S/C (all THEMIS, CLUSTER, …)•Extend to magnetosphere and solar wind region determinations•Use this procedure to deduce bow shock and magnetopause models
Tool enhancements
•TOPCAT•Bin value on mouse over•Over plot of contours and user defined lines on density maps
•AMDA•Delay procedure (continuous instead of constant or « banded »)
Using the binning TOPCAT functionality for density map :
Using the binning TOPCAT functionality for density map :
Using the binning TOPCAT functionality for density map :