The ShakeAlert earthquake early warning system is designed to automatically identify and characterize the initiation and rupture evolution of large earthquakes, estimate the intensity of ground shaking that will result, and deliver alerts to people and systems that may experience shaking, prior to the occurrence of shaking at their location. It is configured to issue alerts to locations within the West Coast of the United States. In 2018, ShakeAlert 2.0 went live in a regional public test in the first phase of a general public rollout. The ShakeAlert system is now providing alerts to more than 60 institutional partners in the three states of the western United States where most of the nation’s earthquake risk is concentrated: California, Oregon, and Washington. The ShakeAlert 2.0 product for public alerting is a message containing a polygon enclosing a region predicted to experience modified Mercalli intensity (MMI) threshold levels that depend on the delivery method. Wireless Emergency Alerts are delivered for M 5+ earthquakes with expected shaking of MMI≥IV⁠. For cell phone apps, the thresholds are M 4.5+ and MMI≥III⁠. A polygon format alert is the easiest description for selective rebroadcasting mechanisms (e.g., cell towers) and is a requirement for some mass notification systems such as the Federal Emergency Management Agency’s Integrated Public Alert and Warning System. ShakeAlert 2.0 was tested using historic waveform data consisting of 60 M 3.5+ and 25 M 5.0+ earthquakes, in addition to other anomalous waveforms such as calibration signals. For the historic event test, the average M 5+ false alert and missed event rates for ShakeAlert 2.0 are 8% and 16%. The M 3.5+ false alert and missed event rates are 10% and 36.7%. Real‐time performance metrics are also presented to assess how the system behaves in regions that are well‐instrumented, sparsely instrumented, and for offshore earthquakes

Andrews, Jennifer

Chung, Angela I.

de Groot, Robert

Given, Douglas D.

Guiwits, Stephen

Hartog, Renate

Henson, Ivan

Kohler, Monica D.

Smith, Deborah E.

English

Caltech Authors - Main

1 
 
Supplementary Material 
 
Title: Earthquake Early Warning ShakeAlert 2.0: Public Rollout 
 
Authors: Monica D. Kohler, Deborah E. Smith, Jennifer Andrews, Angela I. Chung, Renate 
Hartog, Ivan Henson, Douglas D. Given, Robert de Groot, Stephen Guiwits 
 
 
 
 
 
 
This is the supplementary material for Earthquake Early Warning ShakeAlert 2.0: Public Rollout. 
The supplement includes: 1) two additional figures that are referenced in the main manuscript 
(Figures S1 and S2); and 2) a detailed description of ground motion assessment tests with two 
figures that are referenced in this supplementary text (Figures S3 and S4). 
 
 
 
 
 
 
 
 
 
2 
 
 
 
Figure S1. Schematic showing ShakeAlert 2.0 algorithms EPIC and Finder, and the messaging 
architecture illustrating similarities, differences, and message-sharing among the four 
contributing regional networks based in Seattle, Pasadena, Menlo Park, and Berkeley. 
Schematic shows data flow pathways starting from incoming seismograms (bottom), to alerts 
sent to subscribers (top). Different color polygons represent different purposes of each 
algorithm and where they occur on the data flow pathway for each regional network. Light 
blue boxes: waveform processors which process incoming raw waveforms, symbolized by 
seismogram image, from the seismic stations for FinDer. Violet boxes: waveform processors 
which process incoming raw waveforms for EPIC. Gray circles: ActiveMQ message-passing 
software instances. Magenta boxes: FinDer, EPIC, and eqInfo2GM (“GM”) algorithms. Dark 
red boxes: Solution Aggregator algorithm. Green boxes: Decision Module algorithm. Red 
boxes: Heartbeat monitor. See main text for algorithm details. Large tan boxes indicate 
different groupings of tasks where the top-most layer is referred to as the ‘Alert Layer.’ Line 
segments indicate data flow where arrowhead indicates that in some cases direction is one-
way, and in others two-way. ‘Subscribers’ are the general public receiving the alerts. Note that 
alerts are sent from three out of the four regional network locations.  
 
 
 
 
3 
 
 
 
 
 
 
Figure S2. ShakeAlert 2.0 development, testing, and production environments and workflows. 
Different color boxes represent the different purposes of each processor. From top to bottom, 
Gray: processors where algorithms are developed or modified. Light blue: source code 
repository. Tan: environment where code is built, compiled where relevant, and linked to 
libraries. Olive green: repository containing binary and configuration files associated with 
code. Brown: processors that are part of the testing environment in-situ at the four contributing 
regional network operations locations in Pasadena (PAS), Berkeley (BK), Menlo Park (MP), 
and Seattle (SE). Dark green squares: pairs of Alert Production processors in-situ at three out 
of the four contributing regional network locations. Salmon squares: Pairs of Pre-alert 
Production processors in-situ at each network location. Light green pentagons: Pairs of 
processors in-situ at three out of the four network locations responsible for disseminating alerts 
to general public. Curved lines: feedback loop between code and code test results. Solid lines: 
one-way data-passing between processors. Dashed lines: communication feedback loop 
between code developers and results of tests performed on code. Tan oval defines processors 
and tasks that are formal components of ShakeAlert; the Development Environment is, by 
contrast, under the control of the developers. 
 
 
 
4 
 
Description of additional ground motion validation tests 
Validation of GMPE/GMICE implementation in eqInfo2GM 
 The validation of GMPE/GMICE implementation is tested by assessing their use by the 
algorithm eqInfo2GM (Thakoor et al., 2019). Eqinfo2GM is used to translate earthquake source 
parameters to ground motion estimates and contains some critical differences with respect to the 
ShakeMap software. This analysis is carried out to validate the GMPE and GMICE 
implementations in eqInfoGM, and to understand the effect of deviations from ShakeMap 
methodology; these include different treatment of source-site differences, and the effect of voiding 
source terms that cannot be determined (see Thakoor et al. [2019] for further details). 
 The eqInfo2GM messages are generated for the source parameters from the ShakeAlert 2.0 
DM alerts. This includes both contour messages and gridded map messages. ShakeMaps are then 
also generated using similar latitude/longitude ranges and GMPE/GMICE settings, but no 
observed station data are used. Next, a point-by-point comparison is generated for the historic 
events, comparing the ShakeMaps to eqInfo2GM maps at the lower resolution of the latter. Plots 
are generated to compare SI (Shaking Intensity), PGA, and PGV for different regions, including 
southern California, northern California, Pacific Northwest, and “Unknown” which corresponds 
to different GMPE/GMICE selections. The comparisons between ShakeMaps and eqInfo2GM are 
assessed from the union of the two grids, looking at all earthquakes in the test suite, for grid points 
with MMI II or greater. The average SI MMI difference between all points on the two grids 
corresponding to eqInfo2GM and ShakeMap ranges from -0.32 to 0.68, with a peak near 0.05. Fig. 
S3a shows the average SI MMI differences for each earthquake in the test suite. Each point in the 
histogram is an average over all points for every pair of eqInfo2GM-ShakeMap grids produced for 
that earthquake’s first alert and its updates. The Variance Reduction (VR) for the SI differences 
ranges from 91% to 99.7%, where 100% is a perfect fit (Fig. S3b). Note that VR is defined from 
Thakoor et al. (2019) as  
  𝑉𝑅 =  [1 −
∑ 𝑚𝑖𝑠𝑓𝑖𝑡2
∑ 𝑜𝑏𝑠𝑒𝑟𝑣𝑎𝑡𝑖𝑜𝑛2
] ∗ 100  (1) 
 
originally based on Dreger and Woods (2002).  
 The eqInfo2GM algorithm performs similarly to ShakeMap in southern California and 
northern California, and good matches are observed between eqInfo2GM and ShakeMap for the 
historic test suite comparison. Looking at the comparison between ShakeAlert 2.0 and ShakeAlert 
1.0 (our baseline), approximately 64% of the comparisons have an SI VR of 99% or better, and 
83% of the comparisons have an SI VR of 98% or better. With eqInfo2GM there are larger 
variations for Pacific Northwest events in the historic test suite comparison. This is more 
noticeable for the PGA and PGV VR statistics than SI VR statistics because SI is based on the 
logarithm of PGA and PGV values. Slight differences in the way in which vs30 data are used by 
eqInfo2GM and ShakeMap calculations explain most of the discrepancies; the extent of the vs30 
map used by eqInfo2GM is smaller and has to be extrapolated into uncovered areas such as 
Canada. Examining the average SI difference for all regions, this test result comparison suggests 
average SI errors of up to ~0.5 MMI units. The maximum SI difference, which looks at the 
differences point by point (and includes small length-scale variability), is on average 1.0 MMI unit 
(where the average is computed over all the point-by-point differences, individually for each 
earthquake’s first alert and its updates), and as large as 2.5 MMI units (Fig. S3c). Larger maximum 
differences tend to occur for larger magnitudes, which may be due to how the source-receiver 
distance is computed, first noted by Thakoor et al. (2019). For M>5, Shakemap computes a 
5 
 
 
Figure S3. Histograms showing: (a) the average shaking intensity (SI) MMI differences between 
eqInfo2GM and ShakeMaps, (b) the range of variance reductions for the different SIs, and (c) 
the range of maximum SI MMI differences between eqInfo2GM and ShakeMaps. The values 
in (a), (b), and (c) are computed for each earthquake’s first alert and its updates. 
 
6 
 
‘median distance’ (the distance that produces the median ground motions of all the possible fault 
orientations that pass through the hypocenter; Worden and Wald, 2016) that addresses the 
deficiency of using an epicentral distance for an extended rupture. In contrast, eqInfo2GM always 
uses epicentral distance unless a FinDer fault is available, which is rare in the test examples as 
early alerts usually do not incorporate the FinDer fault when the point-source estimate of 
magnitude is below 6.0. Where a line source is available, eqInfo2GM uses the Joyner-Boore 
distance where relevant for the GMPE.  
 The ShakeMaps produced for the historic test suite only use the point-source information, 
regardless of magnitude. Since eqInfo2GM uses the finite-fault source for M 6+ earthquakes, some 
differences can arise between the ShakeMap and the eqInfo2GM map message output for the larger 
events in the historic test suite. In contrast, for the large finite-fault scenario earthquakes discussed 
next, the ShakeMaps are calculated using finite-fault information; hence, these are a better test of 
the finite-fault capabilities of eqInfo2GM. In general, eqInfo2GM matches better in southern and 
northern California. There is greater variation in the near-source regions for the Pacific Northwest 
(note 0.2° resolution for eqInfo2GM and a finer 0.05° resolution for the ShakeMaps, the latter are 
downsampled during comparison). 
 We also tested eqInfo2GM against ShakeMaps for three large-magnitude finite-fault scenario 
events: an M 7.3 Hayward fault scenario, an M 7.9 Southern San Andreas fault scenario, and an 
M 9.34 Cascadia scenario (Fig. S4) (see Data and Resources for details on scenario data sources). 
Note that these comparisons show how well eqInfo2GM can generate a ShakeMap-like product 
from source parameters, but not how well the ShakeAlert system will predict the source parameters 
for this type of event or the timeliness of the alerts. For this test, we first regenerated the scenario 
event ShakeMaps with expanded boundaries to better compare with eqInfo2GM output. We then 
translated finite-fault information (already produced by the scenario datasets) to FinDer-style 
XML messages by reducing fault plane descriptions from the scenario to line-source descriptions 
by taking the upper or lower edge, as this is the limit of the capability of eqInfo2GM input. Next, 
we generated eqInfo2GM map messages using the FinDer-style XML messages as input, to 
generate map output. Last we compared the (independently produced) ShakeMap and eqInfo2GM 
ground motion estimates. Figs. S4a,d,g show the differences in shaking intensity (in MMI units) 
between the ShakeMap ground intensity estimates (Figs. S4b,e,h), and the eqInfo2GM ground 
intensity estimates (Figs. S4c,f,i) for the three scenario earthquakes. The Hayward fault M 7.3 
scenario earthquake has a good SI VR of 99.6%, and the Southern San Andreas M 7.9 scenario 
earthquake also has a good SI VR of 99.2%. To model the M 9.34 Cascadia scenario, we used two 
different FinDer line sources, one with shallow slip (5 km) and one with deep slip (26 to 35 km). 
The shallow slip scenario generated an SI VR of 94.8% and the deep slip scenario generated an SI 
VR of 96.3%.  
 
Validation of ShakeAlert ground motion map accuracy 
 The assessment of full ShakeAlert ground motion accuracy involves comparisons of 
eqInfo2GM map predictions with USGS-NEIC Shakemaps which include station observations. 
This comparison is a better measure of how ShakeAlert 2.0 will perform compared to observed 
ground motions, whereas the previous comparison tested how well eqInfo2GM replicates 
Shakemap’s ground motion prediction equations (i.e. source information without station data). 
This work is discussed in Thakoor et al. (2019) and is summarized here, but these types of tests 
are an ongoing part of ShakeAlert. Thakoor et al. (2019) implemented the comparison of 
eqInfo2GM output to NEIC Shakemaps for regions with MMI ≥ II. In their study, they found that 
7 
 
Figure S4. Ground motion test assessment for three scenario earthquakes, and comparison 
between ShakeMap and eqInfo2GM output. (a) Hayward fault scenario comparison between 
ShakeMap and eqInfo2GM showing difference in shaking intensity in MMI units. (b) 
Hayward fault scenario ShakeMap. (c) Hayward fault scenario eqInfo2GM output. (d) San 
Andreas fault scenario comparison between ShakeMap and eqInfo2GM showing difference 
in shaking intensity in MMI units. (e) San Andreas fault scenario ShakeMap. (f) San Andreas 
fault scenario eqInfo2GM output. (g) Cascadia scenario comparison between ShakeMap and 
eqInfo2GM showing difference in shaking intensity in MMI units. (h) Cascadia scenario 
ShakeMap. (i) Cascadia scenario eqInfo2GM output. In all three cases, the differences 
between ShakeMap and eqInfo2GM output are very small, illustrating the effectiveness of 
eqInfo2GM estimates. 
 
 
8 
 
97% of the maps had an SI VR > 50%, 76% of the maps had an SI VR > 80%, and 46% of the 
maps had an SI VR > 90%. In terms of SI difference, 14% of the maps had a mean SI difference 
within 0.25 MMI units and 62% of the maps have a mean SI difference within 1.00 MMI units. 
For the August 24, 2014 M 6.0 South Napa earthquake, they had a VR of 99.5% when comparing 
output to Shakemaps (with same source and no station observations) vs. a VR of 62% when 
comparing output to ShakeMaps (with earthquake catalog source parameters and with station 
observations). 
 
References 
Dreger, D., and B. Woods (2002). Regional distance seismic moment tensors of nuclear 
explosions, Tectonophysics, 356, 1-3, 139-156. 
Thakoor, K., J. Andrews, E. Hauksson and T. H. Heaton (2019). From earthquake source 
parameters to ground motion warnings near you: the ShakeAlert earthquake information to 
ground motion (eqInfo2GM) method, Seis. Res. Lett., 90(3), 1243-1257, 
doi:10.1785/0220180245. 
Worden, C. B. and D. J. Wald (2016). ShakeMap Manual Online: technical manual, user’s guide, 
and software guide, U. S. Geological Survey, doi:10.5066/F7D21VPQ. 
 
 
 
 
 
 
 


Earthquake Early Warning ShakeAlert 2.0: Public Rollout

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Earthquake Early Warning ShakeAlert 2.0: Public Rollout

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