The 6 February 2023 $Mw$ 7.8 Pazarcık and subsequent $Mw$ 7.5 Elbistan earthquakes generated strong ground shaking that resulted in catastrophic human and economic loss across south‐central Türkiye and northwest Syria. The rapid characterization of the earthquakes, including their location, size, fault geometries, and slip kinematics, is critical to estimate the impact of significant seismic events. The U.S. Geological Survey National Earthquake Information Center (NEIC) provides real‐time monitoring of earthquakes globally, including rapid source characterization and impact estimates. Here, we describe the seismic characterization products generated and made available by the NEIC over the two weeks following the start of the earthquake sequence in southeast Türkiye, their evolution, and how they inform our understanding of regional seismotectonics and hazards. The kinematics of rupture for the two earthquakes was complex, involving multiple fault segments. Therefore, incorporating observations from rupture mapping was critical for characterizing these events. Dense local datasets facilitated robust source characterization and impact assessment once these observations were obtained and converted to NEIC product input formats. We discuss how we may improve the timeliness of NEIC products for rapid assessment of future seismic hazards, particularly in the case of complex ruptures.

Following the catastrophic 6 February 2023 Mw 7.8 and Mw 7.6 Kahramanmaraş earthquakes in the East Anatolian Fault Zone (EAFZ; southeast Türkiye), numerous aftershocks occurred along the major branches of this left‐lateral shear zone. The spatio‐temporal distribution of the earthquakes implied the stress‐triggering effects of co‐seismic ruptures on closely connected fault segments over large distances. On the 20 February 2023 two earthquakes with Mw 6.4 and Mw 5.2 struck Hatay (Türkiye) located near the Samandağ‐Antakya segment of the EAFZ. To understand the rupture evolution of these earthquakes, we first re‐located the aftershock sequence that occurred over a 3‐month period in the Hatay‐Syria region. A normal faulting mechanism with a significant amount of left‐lateral strike‐slip component at a shallow focal depth of 12 km was estimated for the 2023 Mw 6.4 earthquake from the inversion of seismological data. Our slip models describe a relatively simple and unilateral rupture propagation along about 36 km‐long active segments of the EAFZ. The co‐seismic horizontal displacements inferred from the Global Navigation Satellite System data are compatible with the oblique slip kinematics. Furthermore, we suggest that this earthquake did not produce notable tsunami waves on the adjacent coasts since the rupture plane did not extend to the seafloor of the Eastern Mediterranean with substantial amount of vertical displacement. We reckon that a future large earthquake (Mw ≥ 7.0) in the Hatay‐Syria region where increased stress was transferred to the fault segments of the EAFZ and the Dead Sea Fault Zone (DSFZ) after the 2023 earthquakes will be a probable source of tsunami at the coastal plains of the Eastern Mediterranean Sea region.

An earthquake doublet (Mw 7.8 and Mw 7.6) occurred on the East Anatolian Fault Zone (EAFZ) on February 6th, 2023. The events produced significant ground motions and caused major impacts to life and infrastructure throughout SE Türkiye and NW Syria. Here we show the results of earthquake relocations of the first 11 days of aftershocks and rupture models for both events inferred from the kinematic inversion of HR-GNSS and strong motion data considering a multi-fault, 3D geometry. We find that the first event nucleated on a previously unmapped fault before transitioning to the East Anatolian Fault (EAF) rupturing for ~ 350 km and that the second event ruptured the Sürgü fault for ~ 160 km. Maximum rupture speeds were estimated to be 3.2 km/s for the Mw 7.8 event. For the Mw 7.6 earthquake, we find super-shear rupture at 4.8 km/s westward but sub-shear eastward rupture at 2.8 km/s. Peak slip for both events were as large as ~8m and ~6m, respectively.

The multipath effect in GNSS has become a robust data source thanks to GNSS Interferometric Reflectometry (GNSS-IR), which provides environment-related features by considering the interference pattern of direct and reflected signals recorded simultaneously on the antenna phase center (APC) of the GNSS receiver. When analyzing the fluctuation of the signal strength, known as signal-to-noise ratio (SNR), SNR metrics such as frequency, amplitude, and phase can be estimated. Frequency is directly related to the reflector height, which can be converted into snow-depth. However, traditional GNSS-IR approaches have limitations in retrieving environmental features, as they generally focus on a selected satellite track or use all available tracks together for a common satellite elevation angle, which can result in missing appropriate satellite elevation angle ranges for station-based retrievals, especially for non-planar surfaces. To address this issue, we proposed an approach that searches for the proper satellite elevation angle range for each satellite track to improve snow-depth retrievals. We analyzed a 31-day GNSS data from a CORS station (KARB) located in Istanbul, Turkey, including a 3-day heavy snowstorm, to prove the performance of the proposed method. The results of the proposed algorithm were compared with the traditional GNSS-IR method results and in-situ snow-depth measurements. The initial results indicate a 10.70% increase in the correlation for snow-depth estimation compared to the traditional approach using L2 SNR data. Moreover, when the results were assessed based on MAD threshold values, increasements of 4.93% and 13.84% were obtained in the correlations for L1 SNR and L2 SNR, respectively.