Hello. My name is Jessie Saunders. I’m a Mendenhall postdoctoral
researcher at the U.S. Geological Survey.
And today I will be sharing with you some work my co-authors and I have
done on comparing the real-time earthquake early warning alert
performance for earthquakes that have happened in California this last year.
Earthquake early warning is not earthquake prediction.
Instead, earthquake early warning aims to rapidly detect that an earthquake
is occurring and then issue alerts for earthquake shaking before the
shaking arrives at the alerted location. There are many approaches to
earthquake early warning, and today I will be talking about two of them.
The first is the ShakeAlert system. ShakeAlert is the operational
earthquake early warning system for the West Coast of the United States.
Public alerts by ShakeAlert began in California in 2019
and have now expanded to Oregon and Washington.
ShakeAlert take a source-based approach to earthquake early warning,
where ground motion observations at stations are used to rapidly estimate
earthquake source parameters like magnitude and epicenter.
These rapid source parameters are then input to ground motion models which
estimate the extents of different levels of Modified Mercalli Intensity, or MMI.
These estimated MMI distributions determine the alert regions used by
ShakeAlert for a given earthquake. Here we will be focusing mainly on the
alert regions determined using an MMI 3.5 alert threshold, which corresponds
to the early warning alerts issued via the Wireless Emergency Alert system.
The other earthquake early warning approach I will be discussing today
is PLUM, which stands for Propagation of Local Undamped Motion.
PLUM is a ground motion-based early warning algorithm originally
developed in Japan. In the PLUM approach,
observations of strong ground motions are used to forecast shaking directly
without estimating earthquake source parameters.
When PLUM detects strong ground motion models, the observed MMI
is forward-predicted out to a specified radius and assigned to
a pre-defined set of grid cells, where alerts are determined by the
grid cells predicted to have MMI above a set threshold, in our case MMI 4.
While the U.S. version of PLUM does not issue early warning alerts
to the public, it has been in internal real-time testing since 2019.
Before we examine individual earthquakes, let us first take
a bird’s-eye look of all of the earthquakes issued
early warning alerts by ShakeAlert or PLUM in 2021.
This map shows the magnitude 3 and larger earthquakes that have
occurred within the ShakeAlert reporting boundary in 2021,
colored by magnitude, where the stars indicate the
earthquakes that were issued alerts. Of the 400 or so magnitude 3 and larger
earthquakes that have occurred, 30 of these were issued early warning
alerts either by ShakeAlert, PLUM, or both.
The table shows more details about the alerted earthquakes,
organized by latitude. Earthquakes are issued public alerts
via ShakeAlert when the ShakeAlert magnitude estimate is above
magnitude 4.5, which I indicate in green in the right-most column.
The earthquakes issued PLUM alerts are indicated by purple in
the column next to that. Of these 30 earthquakes,
ShakeAlert issued public alerts for 17, and PLUM issued alerts for 23.
Many of these earthquakes are widely felt, with 13 earthquakes having
over 1,000 reports in the USGS Did You Feel It? system,
where four of these have over 10,000 reports.
The earthquakes that have larger numbers of Did You Feel It? reports
seem to depend largely on the location of the earthquake.
While the magnitude 6 Antelope Valley earthquake is the second-largest
earthquake to have occurred in California last year, and has the highest
number of Did You Feel It? reports at over 23,000, the other three earthquakes
with over 10,000 Did You Feel It? reports all have magnitudes of less
than 4.5 but are located in the San Francisco Bay Area
and in the Los Angeles metro area. Nearly all of these 30 earthquakes have
reports of significantly felt shaking, corresponding to MMI 4 and higher,
and many of these earthquakes have reports of damaging shaking,
which are indicated in the third column to the right, colored by MMI.
For the rest of this talk, I will focus on a comparison of the alert regions
by both PLUM and ShakeAlert for the five earthquakes highlighted here.
For this alert performance comparison, I will be showing what the alert regions
would look like using the real-time earthquake source characterizations
and station observations but with alert regions using the preferred
alerting strategies for each early warning approach.
These alerting strategies are chosen to maximize alert performance for
potentially damaging and significantly felt shaking targets of MMI 4 and larger
while keeping over-alerting to locations that are likely to still feel some shaking.
For ShakeAlert, our preferred alerting parameters are shown
in the green box on the left. We will be using the ShakeAlert
contour product with proposed updates to the ground motion models that
make it more consistent with ShakeMap products, so these may be a little
different than the operational alert regions that were issued
at the time of the earthquakes. We analyzed over 140 ShakeMaps
and demonstrated that an alert threshold of MMI 3.5 is optimal for alerts to
all damaging shaking targets as well as for most MMI 4 shaking
locations when ShakeAlert estimates source parameters accurately.
Here is an example of these optimization comparisons for the 1989
magnitude 6.9 Loma Prieta earthquake. These maps show the ShakeMap of the
earthquake colored by alert quality relative to a set target shaking threshold,
where the alert region in each map uses different alert thresholds.
The bar plots show alert quality totals for these alert thresholds
in terms of area on the top and population on the bottom.
An optimal alert strategy is one that minimizes the amount of missed
alerts in red and reduces the amount of over-alerting in yellow,
where our preferred MMI 3.5 alert threshold for the ShakeAlert contour
product is highlighted by the green box in sub-plot C.
And here are our preferred PLUM alert parameters.
We used a cost-benefit analysis of the earthquakes in the ShakeAlert testing
data set to determine optimal PLUM prediction radii and alert
thresholds given the constraint that alert regions will be based on
the grid used in the ShakeAlert grid product.
The max here show an example of these comparisons using three PLUM
prediction radii for the 2019 magnitude 7.1 Ridgecrest earthquake, where the
ShakeMap is colored by alert quality and expected warning time
for each strategy. Similar to the ShakeAlert alert
strategy optimization shown in the previous slide, an optimal PLUM alert
strategy is one that minimizes the amount of missed alerts in red and late
alerts in black while also reducing the amount of over-alerting in yellow.
We found that a 60-kilometer prediction radius and an MMI 4 alert
threshold are the preferred PLUM alerting parameters
for the shaking targets we are considering in this analysis.
For the alert performance comparisons, I will be showing maps like this,
which compare ShakeAlert and PLUM alert regions against the
observed shaking intensity distributions from ShakeMap and Did You Feel It?.
These are a bit complicated, so let’s walk through them a bit.
In the background, I have plotted the ShakeMap from the earthquake as the
contour map and intensity observations from Did You Feel It? reports in the
squares, where I have highlighted the locations and reports of
MMI 4-plus shaking in dark blue. The triangles are the real-time seismic
station locations, the star is the epicenter, and the concentric circles
show the approximate extent of the S wave at 10-second intervals.
For ShakeAlert, I show the ShakeAlert alert parameters by the octagons
colored by the alert threshold MMI. Our preferred MMI 3.5 alert contour
is outlined in black, but I also show the other ShakeAlert contours
used for public alerts outlined in gray.
The green circle shows the extent of the S wave at the time the first alert
was issued by ShakeAlert. This represents the approximate
minimum size of the initial late alert zone where locations outside
of the circle may get some warning while locations
inside the circle will not get a timely alert.
For PLUM, the PLUM alert region perimeter is highlighted in pink,
and the purple circle shows the estimated initial late alert zone.
Combining them all together gives us this map.
The magnitude 5.3 Calipatria earthquake near the Salton Sea
shown here is a nice example of good alert performance behavior
by both ShakeAlert and PLUM.
Both approaches issue alerts at approximately the same time, and both
have alert regions that encompass the locations that experience target shaking.
Another example of good alert performance for both ShakeAlert
and PLUM is the magnitude 6.2 Petrolia
earthquake sequence that occurred last month.
This event is complicated, as Kathryn Materna will discuss
in her talk later in this session. Analysis of this event is still ongoing,
but recent results suggest that there were two earthquakes,
the magnitude 5.7 foreshock offshore, followed by the magnitude 6.2
main shock 11 seconds later. During this earthquake sequence,
both ShakeAlert and PLUM issued alerts with the detection of the
foreshock, where these alerts were issued several seconds
before the S wave from the main shock reached the surface.
For ShakeAlert, there was some epicenter mislocation,
and the magnitude estimate did not get above magnitude 5.6.
However, the MMI 3.5 alert contour is able to compensate for these errors
in most locations that experience MMI 4-plus shaking by the
main shock are issued an alert by ShakeAlert.
For PLUM, PLUM’s first alert was issued at about 2 seconds after
ShakeAlert’s first alert once detection thresholds were exceeded by the
foreshock’s S wave arrival at enough onshore stations.
PLUM’s alert region for this sequence is able to encompass all onshore
locations of MMI 4-plus shaking from the magnitude 6.2 main shock.
Alongside reducing missed alerts, the additional alerts by PLUM
would have provided timely warning to these locations.
Next, let’s take a look at the magnitude 6 Antelope Valley earthquake.
This was the second-largest earthquake to occur in the ShakeAlert reporting
boundary this year, and it unfortunately caused some problems for ShakeAlert.
The sparse station coverage, as well as triggers from a small foreshock on the
closest stations caused ShakeAlert to severely mislocate the epicenter
of the main shock over 70 kilometers to the southeast, which led to
magnitude underestimation. This mislocation then prevented
triggers from later stations from being properly associated with this event,
which caused ShakeAlert to create split events, including a magnitude 4.8
event near Stockton to the southwest. Because of these large source estimation
errors, neither of the ShakeAlert events that created public alerts have MMI 3.5
alert contours that include the areas that experienced significant shaking.
For PLUM, the ground motions from the small foreshock did not exceed
detection thresholds, so PLUM issued an alert for the magnitude 6
main shock about 10 seconds faster than ShakeAlert.
Due to the sparse station coverage, the first stations to detect strong
shaking weren’t immediate neighbors of each other.
So PLUM also had multiple detections for this earthquake.
However, unlike source-based early warning algorithms,
multiple PLUM detections for the same event do not affect
the PLUM alert region. This is because PLUM alert regions,
by definition, surround the stations observed to have
strong ground motions. So multiple PLUM event detections
would not cause source estimation errors that would impact alert regions.
Now let’s take a look at the magnitude 4.7 Truckee earthquake.
Sparse station spacing also caused ShakeAlert to mislocate the earthquake,
however for this events, ShakeAlert’s initial magnitude estimate was too high
at magnitude 6, and this magnitude overestimate was used in the
first alert issued to the public. While the preferred MMI 3.5 alert
threshold would have kept alerts to locations that still felt shaking,
the operational MMI 2.5 alert region used to issue public alerts sent alerts all
the way to the San Francisco Bay Area, which did not feel the earthquake.
PLUM detected the earthquake about 10 seconds faster than ShakeAlert.
But the sparse station spacing still prevented PLUM alerts from being
timely in the locations of target shaking. And while PLUM alerts will have
[inaudible] at over-alerting surrounding the locations that experienced target
shaking, over-alerting is limited to the extent of the 60-kilometer PLUM
prediction radius. So large-scale over- alerting is not possible in PLUM.
Finally, let’s go back to the Mendocino area and examine the alert performance
for the offshore magnitude 5.1 Petrolia earthquake that occurred last July.
This earthquake was a deeper event with 31-kilometer source depth.
So ShakeAlert likely detected the earthquake before the S waves reached
the surface, which is why you don’t see a green late alert zone on the map.
However, ShakeAlert underestimated the magnitude for this event,
preventing a public alert from being issued.
PLUM detected and issued and alert for this earthquake, and despite
PLUM detecting the event much later than ShakeAlert once the S waves
reached the surface, a PLUM alert would likely have been timely for
the locations that experienced target shaking.
Offshore and edge-of-network earthquakes can be problematic
for ShakeAlert source characterization due to the one-sided station azimuthal
coverage. For events like the one here, PLUM would help confirm that
significant shaking is occurring onshore and that an alert is needed.
In summary, we discussed the real-time alerting behavior of ShakeAlert and
PLUM for earthquakes in 2021. For ShakeAlert, the MMI 3.5 contour
product using proposed updates to the ground motion models used
in the alerting process yields improved alert performance for significant
shaking targets compared to other operational contour products.
For PLUM, once significant shaking is detected, PLUM alerts areas that
surround the stations with observed significant ground motions.
For most earthquakes, PLUM and ShakeAlert have comparable alert
performance, where first alert times are usually within one or two seconds
of each other, and the alert region coverage is similar,
like for the magnitude 5.3 Calipatria earthquake.
However, for cases where ShakeAlert has large errors in its source estimations,
these source errors contribute to errors in the alert region.
For cases where the ShakeAlert epicenter is off by a large distance,
and/or if the ShakeAlert magnitude is significantly underestimated,
the errors in the resulting alert contours may prevent locations
that experience target shaking from being alerted.
Because PLUM alerts surround the stations with significant shaking,
PLUM alerts are not affected by source estimation errors, so it can
help provide a backup to source-based alerts when there are problems.
We also observed that there were no negative impacts to the alert
performance due to PLUM, such as extreme over-alerting.
PLUM is a simple and robust approach to earthquake early warning,
and I hope this presentation demonstrated how integrating PLUM
into ShakeAlert in the future could improve early warning performance
in the United States as it has already done for early warning in Japan.
Thank you very much for listening to my talk.