Accurate indoor localization information of the quadrotor plays an important role in many Internet of Things applications. To improve the estimation accuracy and robustness, a fix-lag extended finite impulse response smoother (FEFIRS) algorithm is proposed for fusing the inertial navigation system (INS) and ultra wide band (UWB) data tightly, which employs distance between the UWB reference nodes and a blind node measured by the INS and UWB. The FEFIRS algorithm consists of an extended unbiased finite impulse response (EFIR) filter and a fix-lag unbiased FIR (UFIR) smoother. The EFIR filter is employed to improve the robustness, and the fix-lag UFIR smoother is capable of improving the accuracy. Based on extensive test investigations employing real data, the proposed FEFIRS has a higher accuracy and robustness than the Kalman-based solutions in tightly integrated INS/UWB-based indoor quadrotor localization.

On July 4 2019, a M_w6.5 earthquake, followed 34 h later by a M_w7.1 event, struck Searles Valley, California. These events are part of a long-lived cluster of historical earthquakes along the Eastern California Shear Zone (ECSZ) which started in 1872 and are associated with temporarily elevated strain rates. We find that the M_w6.5 event initiated on a right-lateral NW striking fault and then ruptured a left-lateral fault to the surface. This event triggered right-lateral slip during the M_w7.1 earthquake. It started as a bilateral, crack-like rupture on a segment brought closer to failure by the M_w6.5 event. The rupture evolved to pulse-like as it propagated at a relatively slow velocity (2 km/s) along a segment that was unloaded by the M_w6.5 event. It stopped abruptly at the Coso volcanic area and at the Garlock Fault and brought some neighbouring faults closer to failure.

As global temperature rises, the frequency of extreme climate events, e.g., severe droughts and floods, has increased significantly and caused severe damage over the past years. To this regard, precipitation efficiency, a crucial meteorological parameter, could provide valuable insights for a better understanding of the patterns and characteristics of these extreme events. In this study, taking Guangdong province as an exemplary region, we first obtained long-term and high-resolution historical records of precipitation efficiency by integrating the observations from a dense network of Global Navigation Satellite System (GNSS) stations with precipitation data, and then characterized the extreme drought and wetness through climate indices. We found a distinct seasonal trend in precipitation efficiency in Guangdong, with annual fluctuations ranging from 10 to 25%. Notably, precipitation efficiency is higher in proximity to the Pearl River Delta Plain and gradually decreases towards the east and west. The occurrence of anomalous peaks and valleys in precipitation efficiency generally corresponds to dry and wet conditions, respectively. A total of 9 extreme wet events and 6 dry events occurred from January 2007 to May 2022, with durations from 3 to 6 months. Our results also demonstrated that both wet and dry frequencies exhibit an increasing trend with the expansion of the time scale, and the frequency of extreme events near the Pearl River Delta Plain surpasses that of other regions. Furthermore, the propagation time from meteorological anomalies to agricultural and hydrological anomalies is about 3 months. The periodic characteristics of meteorological anomalies are identified as the primary driver for other anomalous periodic patterns. Our work unveils the long-term dynamic behavior of precipitation efficiency, as well as the characteristics of extreme drought and wetness events in the regions characterized by intricate land–atmosphere interactions.