- Ground-motion model is:
- Uses data from 21 TriNet stations with known V
_{s,30}values. 190 ≤ V_{s,30}≤ 958m∕s. Uses two approaches for site term S_{i}. In first method (denoted ‘empirically-corrected amplitudes’, emp - amp) uses empirical site amplification factors from previous study of TriNet stations (for PGA uses site factor for PSA at 0.3s because correction for PGA is unavailable). In second method [denoted ‘Boore-Joyner-Fumal (BJF)-corrected amplitudes’, BJF] uses amplification factors based on V_{s,30}from Boore et al. (1997) to correct observations to reference (arbitrarily selected) V_{s,30}= 760m∕s. - Uses only data with amplitudes > 0.01%g (100 times greater than resolution of data, 0.0001%g).
- States that developed relations not intended for engineering applications due to lack of data from large events and from short distances. Equations developed for investigation of variability issues for which database limitations are not crucial.
- Many records from Landers mainshock and aftershocks.
- Uses standard linear regression since facilitates comparisons using regressions of different types of datasets, including single-station datasets.
- Notes possible complications to functional form due to effects such as magnitude-dependent shape are not important due to small source size of most events.
- Truncates data at 300km to get dataset that is well distributed in distance-amplitude space.
- Notes that small differences between σs when no site correction is applied and when site correction is applied could be due to complex site response in Los Angeles basin.
- Fits trend-lines to residuals versus distance for each station and finds slope not significantly different from zero at most stations except for Osito Audit (OSI) (lying in mountains outside the geographical area defined by other stations), which has a significant positive trend.
- Finds empirical-amplification factors give better estimate of average site response (average residuals per
station closer to zero) than V
_{s,30}-based factors at short periods but the reverse for long periods. Notes V_{s,30}gives more stable site-response estimates, with residuals for individual stations less than factor of 1.6 for most stations. - Finds standard deviations of station residuals not unusually large at sites with large mean residual, indicating that average site response estimates could be improved.
- Plots standard deviation of station residuals using V
_{s,30}-based factors and the average of these weighted by number of observations per station. Compares with standard deviation from entire databank. Finds that generally standard deviations of station residuals slightly lower (about 10%) than for entire databank. - Examines standard deviations of residuals averaged over 0.5-unit magnitude bins and finds no apparent trend for M3.5 to M7.0 but notes lack of large magnitude data.
- Restricts data by magnitude range (e.g. 4 ≤M ≤ 6) and/or distance (e.g. ≤ 80km) and find no reduction in standard deviation.
- Finds no reduction in standard deviation using one component rather than both.
- Performs separate analysis of residuals for Landers events (10 stations having ≥ 20 observations) recorded at > 100km. Notes that due to similarity of source and path effects for a station this should represent a minimum in single-station σ. Finds σ of 0.18 ± 0.06.