SuperDARN operations
Pasha Ponomarenko
Outline
• Operational principles
• Antenna design and coverage
• Pulse sequence and ACF
• Data processing and presentation
Just to remind: The Main Objective• Mapping 2D ionospheric plasma circulation at
high latitudes
Operation principles
• Resolving 2D ionospheric plasma velocities in range-azimuth (horizontal) domain– Azimuth: multi-beam pattern– Range: pulsed mode (time delay)– Line-of-sight Velocity: Doppler shift– Velocity vector:
• receiving echoes from the same areas by different radars (i.e. from different directions)
• fitting to a velocity model
phase shift
0
Phased array: Azimuthal scan
• SuperDARN:– main array: 16 log-periodic
antennae
– interferometer: 4 log-periodic antennae
– resolution: ~3.5 deg
– coverage (16 beams): ~54 deg
Field of view (FoV)
• Each radar consecutively scans through 16 directions (“beams”) every 1or 2 minutes.
• Along each beam the returned echoes are sampled at 45-km steps forming 70-75 “range gates” (max. range~3500 km)
• Total FoV consists of ~1200 range-beam cells
Pulse sequence & complex ACF
• For each range gate a complex autocorrelation function (ACF) is calculated
• Radar emits a sequence of 7 or 8 pulses
FITACF
Experimental ACFSuperDARN software: FITACF
ptab[mppul] short mppul Pulse table.ltab[2][mplgs] short 2,mplgs Lag table.pwr0[nrng] float nrng Lag zero power.slist[0-nrng] short 0-nrng List of stored ranges.nlag[0-nrng] short 0-nrng Number of points in the fit.qflg[0-nrng] char 0-nrng Quality of fit flag for ACF.gflg[0-nrng] char 0-nrng Ground scatter flag for ACF.p_l[0-nrng] float 0-nrng Power from lambda fit of ACF.p_l_e[0-nrng] float 0-nrng Power error from lambda fit of ACF.p_s[0-nrng] float 0-nrng Power from sigma fit of ACF..p_s_e[0-nrng] float 0-nrng Powr error from sigma fit of ACF.v[0-nrng] float 0-nrng Velocity from ACF.v_e[0-nrng] float 0-nrng Velocity error from ACF.w_l[0-nrng] float 0-nrng Spectral width from lambda fit of ACF.w_l_e[0-nrng] float 0-nrng Spectral width error from lambda fit of ACF.w_s[0-nrng] float 0-nrng Spectral width from sigma fit of ACF.w_s_e[0-nrng] float 0-nrng Spectral width error from sigma fit of ACF.sd_l[0-nrng] float 0-nrng Standard deviation of sigma fit.sd_s[0-nrng] float 0-nrng Standard deviation of lambda fit.sd_phi[0-nrng] float 0-nrng Standard deviation of phase fit of ACF.x_qflg[0-nrng] char 0-nrng Quality of fit flag for XCF.x_gflg[0-nrng] char 0-nrng Ground scatter flag for XCF.x_p_l[0-nrng] float 0-nrng Power from lambda fit of XCF.x_p_l_e[0-nrng] float 0-nrng Power error from lambda fit of XCF.x_p_s[0-nrng] float 0-nrng Power from sigma fit of XCF.x_p_s_e[0-nrng] float 0-nrng Power error from sigma fit of XCF.x_v[0-nrng] float 0-nrng Velocity from XCF.x_v_e[0-nrng] float 0-nrng Velocity error from XCF.x_w_l[0-nrng] float 0-nrng Spectral width from lambda fit of XCF.x_w_l_e[0-nrng] float 0-nrng Spectral width error from lambda fit of XCF.x_w_s[0-nrng] float 0-nrng Spectral width from sigma fit of XCF.x_w_s_e[0-nrng] float 0-nrng Spectral width error from sigma fit of XCF.phi0[0-nrng] float 0-nrng Phase determination at lag zero of the ACF.phi0_e[0-nrng] float 0-nrng Phase determination error at lag zero of the ACF.elv[0-nrng] float 0-nrng Angle of arrival estimate.elv_low[0-nrng] float 0-nrng Lowest estimate of angle of arrival.elv_high[0-nrng] float 0-nrng Highest estimat of angle of arrival.x_sd_l[0-nrng] float 0-nrng Standard deviation of lambda fit of XCF.x_sd_s[0-nrng] float 0-nrng Standard deviation of sigma fit of XCF.x_sd_phi[0-nrng] float 0-nrng Standard deviation of phase fit of XCF.
Main estimated parameters
• Signal-to-noise ratio (“power”) [dB] – maximum ACF power
• Spectral width [m/s] – ACF power decay time
• Line-of-sight velocity (“velocity”) [m/s] – ACF phase slope
ACF power
ACF phase
Velocity vector measurements
• Overlapping FoVs provide line-of-sight measuremets from two different directions at the same location
• They are combined into a 2D velocity vector
Plasma circulation (“convection”) maps
• Velocity vectors from different radars are combined into a plasma circulation map
• Electric field distribution is calculated from velocities based on ExB assumption
Plotting data: range-time maps
Plotting data: fan plots
Attention: Software availability!
• SuperDARN “starter’s kit” that contains ready-to-use IDL routines which have been tested on Chapman:– reading fitted data from the standard radar output files into
IDL variables
– range-time plotting
– plotting “fan” diagrams (maps, coordinate systems etc)
• PDF files describing SuperDARN data formats/variables/parameters
Top Related