Single-Station Phi Using NGA-West2 Data
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1 SSHAC Level 3 Southwestern U.S. Ground Motion Characterization WS-2, October 24, 23 Berkeley, CA Single-Station Phi Using NGA-West2 Data Linda Al Atik Proponent Expert
2 Outline Background, terminology and approach Single-station phi analysis using: NGA-West2 data: Residuals from ASK4, CB4, and CY4 Taiwan data from Lin et al. (2) Observed trends versus magnitude, distance, V S3 and comparisons Path effects and regional variations
3 Residual Components δ = δb + δw es e es δ δ B e W es : Between-event (inter-event) residual for earthquake e : Within-event (intra-event) residual at station s for earthquake e 2 2 σ τ φ = + Alatik et al. (2) τ : Between-event standard deviation φ : Within-event standard deviation 3
4 Single-Station Phi: Approach Given multiple recordings of GM at an individual site, S, allows estimating the systematic site effects, δ S2S S, and removing them from the GM variability: Single-Station Phi δ S S 2 S represents the systematic deviation of the observed amplification at this site from the median amplification predicted by the model 4
5 Terminology Ergodic Partially Non-Ergodic Within-event residual, Single-station within-event residual, δ δws = δw δs2s W es es es s Within-event standard deviation, Total standard deviation, 2 2 σ = φ + τ φ Single-station within-event standard deviation, φ SS Single-station standard deviation, σ = φ + τ SS 2 2 SS Al Atik et al. (2) 5
6 Results Using ASK4 Residuals 6
7 ASK4 Data Distribution Minimum of 3 recs per station: 3,2 recs eqks -,227 stations 8 7 Region Nrecs CA,42 Taiwan,329 Japan 53 Italy 84 China 35 Magnitude Rrup (km) 7 CA Taiwan Italy Japan China
8 ASK4 Data Distribution (cont d) Frequency of Recs > 2 V S3 (m/sec) Nmin=3 8
9 Nb of Recs Used in Analysis 2 8 Nb of Recs Used Period (sec) CA Taiwan Japan Italy China 9
10 φ & φ SS versus Period Standard Deviation Period (sec) Period (sec) Phi-All Phi-All -All -All Phi-CA Phi-CA -CA -CA Phi-Taiw Phi-All -All -Taiw Phi-Taiw Phi-Jap -Taiw -Jap Phi-Jap Phi-Ita -Jap -Ita
11 φ SS versus Period.9.8 Standard Deviation Period (sec) -All -CA -Taiw -Jap -Ita
12 φ SS for Nmin = 3, 5, and Period (sec) All, CA, Nmin=3 Taiw, Ita, Nmin=3 All, CA, Nmin=5 Nmin=5 Taiw, Ita, Nmin=5 All, CA, Nmin= Nmin= 2
13 Magnitude Dependence.7 T CA Taiw Jap Ita Chi Magnitude.7 T CA Taiw Jap Ita Chi Magnitude 3
14 M-R Dependence - PGA PGA, CALIFORNIA Rrup (km) M 3 to 5 M 5 to 6 M 6 to PGA, TAIWAN Rrup (km) M 5 to 6 M 6 to 8 4
15 M-R Dependence - PGA (cont d) PGA, Japan Rrup (km) M 6 to 8 PGA, Italy Rrup (km) M 5 to 6 M 6 to 8 5
16 M-R Dependence T sec T sec, CALIFORNIA Rrup (km) M 3 to 5 M 5 to 6 M 6 to T sec, TAIWAN Rrup (km) M 5 to 6 M 6 to 8 6
17 M-R Dependence T sec (cont d) T sec, Japan Rrup (km) M 6 to T sec, Italy Rrup (km) M 5 to 6 M 6 to 8 7
18 V S3 Dependence T Chi Vs3 (m/sec) CA Taiw Jap Ita CA Taiw Jap Ita T Vs3 (m/sec) 8
19 Results Using CY4 Residuals 9
20 CY4 Data Distribution Minimum of 3 recs per station: 9,97 recs Region Nrecs CA 8,672 Japan 525 Magnitude Rrup (km) CA Japan 2
21 φ & φ SS versus Period Standard Deviation Period (sec) Period (sec) Phi-All -All Northern CA-Phi Northern CA- Phi-All -All Northern Phi-All CA-Phi Northern CA- Southern -All CA-Phi Southern CA- Southern CA-Phi Southern CA- Japan-Phi Japan 2
22 Results Using CB4 Residuals 22
23 CB4 Data Distribution Minimum of 3 recs per station: 5,284 recs Region Nrecs CA 5,25 Italy 6 China 27 Magnitude Rrup (km) CA Italy China 23
24 φ & φ SS versus Period.9.8 Standard Deviation Period (sec) Phi-All -All Phi-CA -CA 24
25 Results Using Lin et al. (2) + ASK4 Taiwan Residuals 25
26 Data Distribution: Taiwan Data Using Nmin = 3: 5,3 recs from 65 eqks at 362 stations in Taiwan Magnitude Rrup (km) Lin et al. 2 ASK4 26
27 φ & φ SS versus Period.9.8 Standard Deviation Period (sec) Phi-Taiwan -Taiwan 27
28 Comparison of Results for All Sets of Residuals Analyzed Comparison with PRP Models 28
29 φ SS vs. Period Standard Deviation Period (sec) Period (sec) Lin et al+ask4, Phi-Taiwan Lin et al+ask4, -Taiwan ASK4-CA ASK4, ASK4-CA Phi-Taiwan CB4-CA CY4-CA CB4-CA CY4-Jap ASK4, -Taiwan CY4-CA ASK4-Jap 29
30 Magnitude Dependence T. ASK4, CA CB4, CA CY4, CA Taiwan Magnitude T. ASK4, CA CB4, CA CY4, CA Taiwan Magnitude 3
31 M-R Dependence - PGA M 3 to 5 M 5 to Rrup (km) Rrup (km) ASK4, CA CB4, CA CY4, CA Taiwan M 6 to 8 ASK4, CA CB4, CA CY4, CA Taiwan Rrup (km) ASK4, CA CB4, CA CY4, CA Taiwan 3
32 M-R Dependence T sec M 3 to 5 M 5 to Rrup (km) Rrup (km) ASK4, CA CB4, CA CY4, CA Taiwan M 6 to Rrup (km) ASK4, CA CB4, CA CY4, CA Taiwan ASK4, CA CB4, CA CY4, CA Taiwan 32
33 V S3 Dependence PGA Vs3 (m/sec) ASK4, CA CB4, CA CY4, CA Taiwan.9.8 T sec Vs3 (m/sec) ASK4, CA CB4, CA CY4, CA Taiwan 33
34 PRP Models Constant R-dependent M-R dependent Rodriguez-Marek & Cotton (29) 34
35 Constant Model Period (sec) ASK4, CA PRP - Cte 35
36 M-R Dependent Model PGA Rrup (km) M 3 to 5 M 5 to 6 M 6 to 8 PRP, M4.5 PRP, M5.5 PRP, M7 T sec Rrup (km) M 3 to 5 M 5 to 6 M 6 to 8 PRP, M4.5 PRP, M5.5 PRP M7 36
37 Observations does not appear region-independent; Taiwan and Italy have lower Chen & Tsai (22) reported φ SS =.397 for Taiwan at PGA Repeated sampling of path for Taiwan? Increase in at small magnitude and short distance (M3 to 5, R < 3km) Hypocenter location errors? Radiation pattern? 37
38 Path Effects Closeness index (CI) is used as an indicator of path similarities CI i, j, k = ( R + R ) 2 i, k H i, j j, k H i,j = distance between the hypocenters of eqk i and j recorded at site s R i,k and R j,k = hypocentral distances from site k to eqk i and j. CI ranges from for co-located eqks to 2 for eqks located in opposite epicentral directions from the site 38
39 Path Effects: Approach Calculate expected CI for randomly located earthquakes Calculate the average CI of the data for each region Compare the average CI of the data to the expected CI for randomly located earthquakes 39
40 Expected CI for Randomly Located Eqks. Generate a number of randomly located earthquakes (Nhyp) in a circular area of radius R around a station 2. Calculate CI for each pair of earthquakes at the station 3. Calculate mean CI 4. Vary Nhypo and R Expected CI for randomly located earthquakes.38 4
41 Path Effects Northern CA 5 Northern CA - T..4 Northern CA - T σ Closeness index, CI δws = i, jk, ik δws 2ϕ ss jk.4.2 At CI = At CI = 2 ss Lin et al. (2) CI for randomly located earthquakes:.38 Mean CI from data:.6 Data Closeness index, CI σ = mean 2 ( ) ( ) 2 δ = Var δws δws E ( δws δws ) φ ρ( δp2p δp2p ) φ 2 = = ijk ik jk ik jk P2P ik jk 4
42 Path Effects Southern CA 4 Southern CA - T..4 Southern CA - T Closeness index, CI σ Lin et al. (2) CI for randomly located earthquakes:.38 Mean CI from data:.23 Data Closeness index, CI δws = i, jk, ik δws 2ϕ ss jk At CI = At CI = 2 ss σ = mean 2 ( ) ( ) 2 δ = Var δws δws E ( δws δws ) φ ρ( δp2p δp2p ) φ 2 = = ijk ik jk ik jk P2P ik jk 42
43 Path Effects Taiwan (ASK4+Lin et al) 25 Taiwan (ASK3+Lin et al) - T. Taiwan (ASK3+Lin et al.) - T σ Closeness index, CI δws = i, jk, ik δws 2ϕ ss jk.4.2 At CI = At CI = 2 ss Lin et al. (2) CI for randomly located earthquakes:.38 Mean CI from data:.2 Data.. Closeness index, CI σ = mean 2 ( ) ( ) 2 δ = Var δws δws E ( δws δws ) φ ρ( δp2p δp2p ) φ 2 = = ijk ik jk ik jk P2P ik jk 43
44 Path Effects Taiwan 25 2 All Data Taiwan - T. M3to5, R 4 to km M3to5, R > km Closeness index, CI Mean CI from all data =.2 Mean CI from data with M<5 and R 4 to km =.995 Mean CI from data with M<5 and R > km =.3 44
45 Epistemic Uncertainty of φ SS 45
46 Epistemic Uncertainty of φ SS (cont d) 7 California, PGA, Nmin= 4 California, PGA, Nmin= z-score SS,S log( SS,S ) Logormal Distribution: Mean =.52, Median =.5, std dev =.22 (Ln) 46
47 Can the radiation pattern explain the high φ SS for CA M3 to 5 and R < 3 km? NGA-West2 flatfile: Rfn.Hyp and Rfp.Hyp: S-wave radiation coefficients to approximate finite fault radiation pattern of the hypocenter for the FN and FP components. Only available for eqks that have finite fault models Used sqrt(rfn.hyp^2+ Rfp.Hyp^2) Doug Douglas: Provided effective radiation coefficient for CA data with M3 to 5 and Rrup < 3km Calculated using Green s functions for a central coast D model Effective radiation coefficient is ratio of max amplitude at the station relative to the maximum amplitude over a ring at the distance of the station from the epicenter 47
48 Radiation Pattern CA Data - PGA 3 2 IntraSS Residual Effective Radiation Coefficient M3to5, Rto5 M3to5, R5to3 Log. (M3to5, Rto5) Log. (M3to5, R5to3) 2.5 IntraSS Residual Avg. S-wave Radiation Coefficient M5to6 M6to8 Log. (M5to6) Log. (M6to8) 48
49 Radiation Pattern CA Data PGA (cont d) Radiation Coefficient M 3 to 5, R to 5 M 3 to 5, R 5 to 3 M 5 to 6 M 6 to Rrup (km) M 3 to 5 M 5 to 6 M 6 to 8 49
50 Radiation Pattern CA Data T sec IntraSS Residual IntraSS Residual Effective Radiation Coefficient M3to5, Rto5 M3to5, R5to3 Log. (M3to5, Rto5) Log. (M3to5, R5to3) Avg. S-wave Radiation Coefficient M5to6 M6to8 Log. (M5to6) Log. (M6to8) 5
51 Radiation Pattern CA Data T sec (cont d) Radiation Coefficient M 3 to 5, R to 5 M 3 to 5, R 5 to 3 M 5 to 6 M 6 to Rrup (km) M 3 to 5 M 5 to 6 M 6 to 8 5
52 Summary might not be region-independent as previously observed (still work in progress) Reason for increase in for M3 to 5 and at short distance Study site-to-site term and evaluate φ S2S Build models!!! 52
53 References Abrahamson, N.A., W.J. Silva, & R. Kamai (24). Update of the AS8 groundmotion prediction equations based on the NGA-West2 data set. Earthquake Spectra, in press. Al Atik, L., N. Abrahamson, J. J. Bommer, F. Scherbaum, F. Cotton, & N. Kuehn (2). The variability of ground-motion prediction models and its components, Seismol. Res. Let., 8, Campbell, K.W. & Y. Bozorgnia (24). NGA-West2 Campbell-Bozorgnia ground motion model for the horizontal components of PGA, PGV, and 5%-damped elastic pseudo-acceleration response spectra for periods ranging from. to sec. Earthquake Spectra, in press. Chen Y-H., and C-C. P. Tsai (22). A new method for estimation of the attenuation relationship with variance components, Bull. Seism. Soc. Am., 92, Chiou, B.S.J & R.R. Youngs (24). Update of the Chiou and Youngs NGA ground motion model for average horizontal component of peak ground motion and response spectra, Earthquake Spectra, in press. Lin, P.-S., B. Chiou, N. Abrahamson, M. Walling, C.-T. Lee, & C.-T. Cheng (2). Repeatable Source, Site, and Path Effects on the Standard Deviation for Empirical Ground-Motion Prediction Models, Bull. Seismol. Soc. Am., Vol., No. 5, Rodriguez-Marek, A. & F. Cotton (2). Final report: Single-station sigma project prepared for PEGASOS Refinement Project, EXT-TB
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