  Ground-based gravitational wave interferometers such as the Laser
Interferometer Gravitational-wave Observatory (LIGO) are susceptible to
high-magnitude teleseismic events, which can interrupt their operation in
science mode and significantly reduce the duty cycle. It can take several hours
for a detector to stabilize enough to return to its nominal state for
scientific observations. The down time can be reduced if advance warning of
impending shaking is received and the impact is suppressed in the isolation
system with the goal of maintaining stable operation even at the expense of
increased instrumental noise. Here we describe an early warning system for
modern gravitational-wave observatories. The system relies on near real-time
earthquake alerts provided by the U.S. Geological Survey (USGS) and the
National Oceanic and Atmospheric Administration (NOAA). Hypocenter and
magnitude information is generally available in 5 to 20 minutes of a
significant earthquake depending on its magnitude and location. The alerts are
used to estimate arrival times and ground velocities at the gravitational-wave
detectors. In general, 90\% of the predictions for ground-motion amplitude are
within a factor of 5 of measured values. The error in both arrival time and
ground-motion prediction introduced by using preliminary, rather than final,
hypocenter and magnitude information is minimal. By using a machine learning
algorithm, we develop a prediction model that calculates the probability that a
given earthquake will prevent a detector from taking data. Our initial results
indicate that by using detector control configuration changes, we could prevent
interruption of operation from 40-100 earthquake events in a 6-month
time-period.
