Atmosphere Mitigation in Precise Point Positioning Ambiguity Resolution for Earthquake Early Warning in the Western U.S.

Thursday, 18 December 2014
Jianghui Geng, University of California San Diego, La Jolla, CA, United States, Yehuda Bock, UCSD/IGPP 0225, La Jolla, CA, United States and Yuval Reuveni, IGPP/SIO/UCSD, La Jolla, CA, United States
Earthquake early warning (EEW) is a time-critical system and typically relies on seismic instruments in the area around the source to detect P waves (or S waves) and rapidly issue alerts. Thanks to the rapid development of real-time Global Navigation Satellite Systems (GNSS), a good number of sensors have been deployed in seismic zones, such as the western U.S. where over 600 GPS stations are collecting 1-Hz high-rate data along the Cascadia subduction zone, San Francisco Bay area, San Andreas fault, etc. GNSS sensors complement the seismic sensors by recording the static offsets while seismic data provide highly-precise higher frequency motions. An optimal combination of GNSS and accelerometer data (seismogeodesy) has advantages compared to GNSS-only or seismic-only methods and provides seismic velocity and displacement waveforms that are precise enough to detect P wave arrivals, in particular in the near source region. Robust real-time GNSS and seismogeodetic analysis is challenging because it requires a period of initialization and continuous phase ambiguity resolution. One of the limiting factors is unmodeled atmospheric effects, both of tropospheric and ionospheric origin. One mitigation approach is to introduce atmospheric corrections into precise point positioning with ambiguity resolution (PPP-AR) of clients/stations within the monitored regions. NOAA generates hourly predictions of zenith troposphere delays at an accuracy of a few centimeters, and 15-minute slant ionospheric delays of a few TECU (Total Electron Content Unit) accuracy from both geodetic and meteorological data collected at hundreds of stations across the U.S. The Scripps Orbit and Permanent Array Center (SOPAC) is experimenting with a regional ionosphere grid using a few hundred stations in southern California, and the International GNSS Service (IGS) routinely estimates a Global Ionosphere Map using over 100 GNSS stations. With these troposphere and ionosphere data as additional observations, we can shorten the initialization period and improve the ambiguity resolution efficiency of PPP-AR. We demonstrate this with data collected by a cluster of Real-Time Earthquake Analysis for Disaster mItigation (READI) network stations in southern California operated by UNAVCO/PBO and SOPAC.