- Description
- Example
- Data Access
- Tables: Metadata, Peak Strains, and Bias Terms
- CRUST1.0 Terms
- Utilities
This is the full dataset of Plate Boundary Observatory borehole strain timeseries from Barbour and Crowell's SRL paper Dynamic Strains for Earthquake Source Characterization.
For each earthquake-station pair the data are in R's
binary format, with one
file ('bsmdata.rda') representing the timeseries of strain,
and another file ('bsmdata_nfo.rda') representing metadata associated with the timeseries. We also include a
pdf figure of the timeseries in ('fig_timeseries.pdf') for reference.
These files contain timeseries of linear strain ( in 10-9 , or nanostrain ) for each of the four gauges at a particular station, where extension is positive. This can be loaded into an R environment, for example, with:
> load('bsmdata.rda', verbose=TRUE)
Loading objects:
BThe loaded object B contains the strain data and timestamps, and
has a class and structure of:
> class(B)
[1] "hfbsm" "lin"
> str(B)
List of 3
$ srcdat : Time-Series [1:19200, 1:4] from 1 to 961: 0 0 0.0427 0.0853 0.0853 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : NULL
.. ..$ : chr [1:4] "CH0" "CH1" "CH2" "CH3"
$ Datetime: POSIXct[1:19200], format: "2010-04-04 22:41:00" "2010-04-04 22:41:00" ...
$ RelInd : num [1:19200] 20 40 60 80 100 120 140 160 180 200 ...
- attr(*, "sta4")= chr "B084"
- attr(*, "file")= chr "B084.ALL_20.l.txt"
- attr(*, "frequency")= num 20
- attr(*, "cmd")= chr "hfbsm B084 pinyon084bcs2006 2010 094 '22:41:09' 2010 094 '22:57:48' 20 "| __truncated__
- attr(*, "class")= chr [1:2] "hfbsm" "lin"Relative strains are in B[['srcdat']], which is a standard
stats::ts
object:
> class(B[['srcdat']])
[1] "mts" "ts" "matrix"See help(ts) for more information.
Missing or bad points have a value of NA:
> summary(B[['srcdat']])
CH0 CH1 CH2 CH3
Min. :-4536.606 Min. :-11318.4 Min. :-7431.4 Min. :-8133.7
1st Qu.: -3.286 1st Qu.: 503.1 1st Qu.: -742.6 1st Qu.: -834.5
Median : 49.715 Median : 578.7 Median : -691.3 Median : -783.7
Mean : 48.387 Mean : 544.7 Mean : -648.8 Mean : -737.0
3rd Qu.: 100.776 3rd Qu.: 642.3 3rd Qu.: -618.9 3rd Qu.: -721.4
Max. : 4157.278 Max. : 14841.8 Max. : 7151.3 Max. : 5753.5
NA's :233 NA's :177 NA's :219 NA's :179These files contain metadata which may be useful for reconstructing the strain data, including the command used, url of the original data, and version of python used at assembly time. This can be loaded into an R environment, for example, with:
> load('bsmdata_nfo.rda', verbose=TRUE)
Loading objects:
bThe loaded object b contains the metadata, and has a class and structure of:
> str(b)
List of 4
$ cmd : chr "hfbsm B084 pinyon084bcs2006 2010 094 '22:41:09' 2010 094 '22:57:48' 20 "| __truncated__
$ cmd.success: logi TRUE
$ results :List of 5
..$ StationNames:List of 2
.. ..$ sta4 : chr "B084"
.. ..$ sta16: chr "pinyon084bcs2006"
..$ DT :List of 2
.. ..$ from: chr "2010 094 22 41"
.. ..$ to : chr "2010 094 22 57"
..$ SamplingHz : num 20
..$ URLsrc : chr "ftp://www.ncedc.org/pub/pbo/strain/raw/bsm/pinyon084bcs2006/2010/094"
..$ files :List of 2
.. ..$ rawfi: chr "B084.ALL_20.r.txt"
.. ..$ linfi: chr "B084.ALL_20.l.txt"
$ python : chr [1:4] "CPython" "2.7.3" "('default', 'Jun 14 2013 18:17:36')" "GCC 4.2.1 (Apple Inc. build 5666) (dot 3)"
- attr(*, "class")= chr "hfbsm.nfo"The command used is in b[['cmd']], for example.
Here, for example, is the timeseries at B084 for the 2010 MW 7.2 El Mayor Cucapah earthquake showing peak strains of nearly 15 × 10-6 ( or 15 microstrain ) shown in the appropriate fig_timeseries.pdf:
We have included a sample R script plot_bsmdata.R to show how
a similar version of this figure can be reproduced.
Download the full archive through the link above, or use version control (git, Subversion, etc.) to maintain a local copy:
git clone git@github.com:abarbour/pbe-data.git
The total size of this repository is on the order of 800 Mb, so the first
fetch through git will take a considerable amount of time. The size can be minimized slightly
by replacing git clone with git clone --depth 1 in the expression above.
One can convert bsmdata.rda to comma-separated-values with rda2csv.R, on
the command line:
rda2csv.R 2010/2010.094_7.2/B084/bsmdata.rda
which writes to eqstrains.csv.gz by default. Optionally, specify an output file:
rda2csv.R 2010/2010.094_7.2/B084/bsmdata.rda my_strain_file.csv.gz
And, with convert_all, one can process every bsmdata.rda file
that exists in this directory. (This is a shell script that depends on awk
and listFiles.
convert_all | sh
This table gives information regarding the origin times, locations (latitude, longitude, and depth in km), and moment magnitudes of all the earthquakes in our search.
eqnum year mo dy hr mi sec nlat elon depkm Mw
1 2004 1 25 15 12 28.6 49.05 -127.88 12.0 5.4
2 2004 3 17 23 53 13.9 36.03 -121.35 12.0 4.7
3 2004 6 15 22 28 52.4 32.45 -117.92 12.0 5.0
4 2004 7 12 16 45 3.7 44.30 -124.71 20.0 4.9
5 2004 7 15 12 6 54.0 49.48 -127.17 18.7 5.7
and so on.
Note that this list does not indicate with BSM data is available; for this you'll want to inspect the output of listFiles
This table gives the earthquake-station pairs by four-character station ID, origin time, and hypocentral distance in kilometers:
sta4 year mo dy hr mi sec geodkm
B001 2004 1 25 15 12 29 367.79
B003 2004 1 25 15 12 29 296.98
B004 2004 1 25 15 12 29 271.42
B005 2004 1 25 15 12 29 341.16
B006 2004 1 25 15 12 29 341.36
and so on.
This table is effectively a merge of earthquakes.txt and bsm_station_times.txt, except with
the addition of an earthquake identifier, the sixteen-character station ID, and the Julian day of
the origin time:
year mo dy hr mi sec sta4 sta16 geodkm jday eqnum nlat elon depkm Mw eqid
2004 1 25 15 12 29 B001 golbeck01bwa2005 367.79 025 1 49.05 -127.88 12.0 5.4 2004.025_5.4
2004 7 12 16 45 4 B001 golbeck01bwa2005 433.24 194 4 44.30 -124.71 20.0 4.9 2004.194_4.9
2004 7 15 12 6 54 B001 golbeck01bwa2005 337.13 197 5 49.48 -127.17 18.7 5.7 2004.197_5.7
2004 7 19 8 1 52 B001 golbeck01bwa2005 344.81 201 6 49.60 -127.19 24.8 6.3 2004.201_6.3
2004 11 2 10 2 16 B001 golbeck01bwa2005 459.27 307 14 49.17 -129.13 19.0 6.6 2004.307_6.6
and so on. To find the entry for the example figure given above:
$ grep -E 'B084.*2010.094' Earthquake_BSM_pairs.txt
2010 4 4 22 41 9 B084 pinyon084bcs2006 175.83 094 112 32.31 -115.39 12.8 7.2 2010.094_7.2Note the earthquake identifier is defined as [year].[jday]_[Mw], with the terms
in the brackets representing field names in the tables.
This table gives the observed peak rms strain for each earthquake-station pair with high-frequency strain data used in the paper. The table is structured as follows:
Station Earthquake Mw D.km logE
B001 2005.323_5.3 5.3 429.53 -8.308648
B001 2008.118_5.2 5.2 435.56 -8.443865
B001 2008.238_5.1 5.1 449.24 -8.955592
B001 2008.255_5.1 5.1 446.77 -8.629519
B001 2008.255_5.2 5.2 447.31 -8.364227
and so on, with columns representing
Station, the station identifierEarthquake, the earthquake identifierMw, the moment magnitudeD.km, the hypocentral distance in kmlogE, the observed peak rms strain (log)
Here's an example (in R) showing how to load these data and run a linear mixed-effects model, while accounting for both station terms and earthquake terms:
> library(lme4)
> Obs <- read.table('ObservedStrains.txt', header=TRUE)
> lmer(logE ~ Mw + log10(D.km) + (1 | Station) + (1 | Earthquake), Obs)giving
Linear mixed model fit by REML ['lmerMod']
Formula: logE ~ Mw + log10(D.km) + (1 | Station) + (1 | Earthquake)
Data: Obs
REML criterion at convergence: -400.6526
Random effects:
Groups Name Std.Dev.
Earthquake (Intercept) 0.2798
Station (Intercept) 0.1309
Residual 0.1813
Number of obs: 1792, groups: Earthquake, 144; Station, 68
Fixed Effects:
(Intercept) Mw log10(D.km)
-9.513 1.250 -1.992The fixed effects represent the magnitude-distance scaling, and the random effects represent the station and earthquake biases.
This table gives bias terms (the random effects in the example above) from the linear mixed-effects models given in the paper. The table is structured as follows:
LME Effect Term Bias Std.error
Station Station B928 -0.419 0.0671
Station Station B012 -0.371 0.0651
Station Station B927 -0.364 0.0671
Station Station B035 -0.363 0.0337
Station Station B926 -0.338 0.0693
and so on, with columns representing
LME, the type of lme regression done ('Station', 'Earthquake', or 'Station.and.Earthquake')Effect, the random effect group ('Station', or 'Earthquake') ★Term, the identifier within the random effect group (i.e., the station name or earthquake ID)Bias, the fixed mean bias estimateStd.error, the standard error associated withBias, from the conditional covariance matrix
Below is a list demonstrating the meaning of the LME field with
the equivalent expression to run a linear mixed-effects model in R (with
the lme4 package):
Value of LME |
Equivalent expression in R |
|---|---|
| 'Station' | `lmer(logE ~ Mw + log10(D.km) + (1 |
| 'Earthquake' | `lmer(logE ~ Mw + log10(D.km) + (1 |
| 'Station.and.Earthquake' | `lmer(logE ~ Mw + log10(D.km) + (1 |
★ Note that the Effect terms are the same as in other tables, so 'Station' ⟺ 'sta4' and 'Earthquake' ⟺ 'eqid'. ↩
CRUST1.0 Codes
The crustal rock-type classification codes for the BSMs are in BSM_C1_Codes.txt; this table is structured as follows:
Station C1.code.sta
B001 L1
B003 T-
B004 T-
B005 L1
B006 L1
B007 L1
B009 L1
B010 L1
and so on, with column C1.code representing the CRUST 1.0
The classification codes for the earthquakes are in EQS_C1_Codes.txt, which is structured similarly:
Earthquake C1.code.eq Oceanic.crust
2004.025_5.4 A1 TRUE
2004.197_5.7 A1 TRUE
2004.201_6.3 A1 TRUE
2004.307_5.0 A0 TRUE
2004.307_5.1 A0 TRUE
2004.307_5.2 A1 TRUE
2004.307_6.6 A0 TRUE
2004.357_5.1 A0 TRUE
and so on, except for an additional column (Oceanic.crust) representing
whether or not C1.code represents oceanic crust (TRUE == oceanic).
Here is a reference table giving the description of each value possible for
C1.code:
C1.code |
Description adapted from CRUST1.0 database |
|---|---|
| A0 | oceans 3 Myr and younger |
| A1 | normal oceanic |
| B- | melt affected oceanic crust and oceanic plateaus |
| C- | continental shelf |
| D- | platform |
| E- | slow thin platform |
| F- | Archean (Antarctica) |
| G1 | early Archean |
| G2 | late Archean |
| H1 | early/mid Proterozoic |
| H2 | early/mid Proterozoic (Antarctica, slow) |
| I1 | late Proterozoic |
| I2 | slow late Proterozoic |
| J- | island arc |
| K- | forearc |
| L1 | continental arc |
| L2 | slow continental arc |
| M- | extended crust |
| N- | fast extended crust (Antarctica) |
| O- | orogen (Antarctica), thick upper crust, thin lower crust |
| P- | orogen, thick upper crust, very thin lower crust |
| Q- | orogen, thick upper crust, fast middle crust |
| R1 | orogen, slow lower crust (Andes) |
| R2 | slow orogen (Himalaya) |
| S- | continental slope-margin transition |
| T- | margin-continent/shield transition |
| U- | slow margin/shield (Antarctica) |
| V1 | inactive ridge, Alpha Ridge |
| V2 | thinned continental crust, Red Sea |
| W- | oceanic plateau with continental crust |
| X- | rift |
| Y1 | Caspian depression |
| Y2 | intermediate continental/oceanic crust, Black Sea |
| Y3 | Caspian Sea oceanic |
| Z1 | Phanerozoic |
| Z2 | fast Phanerozoic (E. Australia, S. Africa, N. Siberia) |
To include these classifications into the strain regression★, the equivalent expression in R would be
lmer(logE ~ Mw + log10(D.km) + Oceanic.crust + (1 | C1.code.sta), Obs)
★ Note that these classification tables will need to be merged with the observation table ↩
A bash shell script that can be used to list files by the earthquake and station identifiers. This includes both the raw data and metadata files:
$ listFiles | head -5
eqid sta4 type rdafile
2005.323_5.3 B001 raw 2005/2005.323_5.3/B001/bsmdata.rda
2005.323_5.3 B004 raw 2005/2005.323_5.3/B004/bsmdata.rda
2005.323_5.3 B005 raw 2005/2005.323_5.3/B005/bsmdata.rda
2005.323_5.3 B006 raw 2005/2005.323_5.3/B006/bsmdata.rda$ listFiles | tail -5
2014.072_5.5 B040 nfo 2014/2014.072_5.5/B040/bsmdata_nfo.rda
2014.072_5.5 B045 nfo 2014/2014.072_5.5/B045/bsmdata_nfo.rda
2014.072_5.5 B933 nfo 2014/2014.072_5.5/B933/bsmdata_nfo.rda
2014.072_5.5 B934 nfo 2014/2014.072_5.5/B934/bsmdata_nfo.rda
2014.072_5.5 B935 nfo 2014/2014.072_5.5/B935/bsmdata_nfo.rda