Generalization of PhaseNet in Shandong and its application to the Changqing M4.1 earthquake sequence

Waveforms of seismic events,extracted from January 2019 to December 2021 were used to construct a test dataset to investigate the generalizability of PhaseNet in the Shandong region.The results show that errors in the picking of seismic phases(P-and Swaves)had a broadly normal distribution,mainly concentrated in the ranges of−0.4–0.3 s and−0.4–0.8 s,respectively.These results were compared with those published in the original PhaseNet article and were found to be approximately 0.2–0.4 s larger.PhaseNet had a strong generalizability for P-and S-wave picking for epicentral distances of less than 120 km and 110 km,respectively.However,the phase recall rate decreased rapidly when these distances were exceeded.Furthermore,the generalizability of PhaseNet was essentially unaffected by magnitude.The M4.1 earthquake sequence in Changqing,Shandong province,China,that occurred on February 18,2020,was adopted as a case study.PhaseNet detected more than twice the number of earthquakes in the manually obtained catalog.This further verified that PhaseNet has strong generalizability in the Shandong region,and a high-precision earthquake catalog was constructed.According to these precise positioning results,two earthquake sequences occurred in the study area,and the southern cluster may have been triggered by the northern cluster.The focal mechanism solution,regional stress field,and the location results of the northern earthquake sequence indicated that the seismic force of the earthquake was consistent with the regional stress field.

A variational successive corrections approach for the sea ice concentration analysis

The sea ice concentration observation from satellite remote sensing includes the spatial multi-scale information.However,traditional data assimilation methods cannot better extract the valuable information due to the complicated variability of the sea ice concentration in the marginal ice zone.A successive corrections analysis using variational optimization method,called spatial multi-scale recursive filter(SMRF),has been designed in this paper to extract multi-scale information resolved by sea ice observations.It is a combination of successive correction methods(SCM)and minimization algorithms,in which various observational scales,from longer to shorter wavelengths,can be extracted successively.As a variational objective analysis scheme,it gains the advantage over the conventional approaches that analyze all scales resolved by observations at one time,and also,the specification of parameters is more convenient.Results of single-observation experiment demonstrate that the SMRF scheme possesses a good ability in propagating observational signals.Further,it shows a superior performance in extracting multi-scale information in a two-dimensional sea ice concentration(SIC)experiment with the real observations from Special Sensor Microwave/Imager SIC(SSMI).

Effects of a two-equation turbulence model on the simulation of the internal lee waves

In order to understand the wave-turbulence interaction under non-hydrostatic conditions to prepare future ad-vanced very-high-resolution ocean reanalysis data,an𝜎-coordinate ocean model-namely,the Marine Environ-ment Research and Forecasting(MERF)model-with an idealized supercritical slope topography is applied to conduct a series of high-resolution numerical experiments with and without the non-hydrostatic approximation.The popular Mellor-Yamada two-equation turbulence model(MY2.5)is enclosed in MERF to validate its effect on small-scale internal lee waves.Instantaneous results show that the internal lee-wave processes are relaxed through employment of the MY2.5 scheme,whether or not in the non-hydrostatic model.Time averaged results suggest the influences of the vertical mixing parameterization scheme on the numerical results are more dominant than the non-hydrostatic/hydrostatic selection for the large-scale dynamic process.Besides,diagnostic analyses of the energy budget show that the spread of internal lee waves at the slope is dramatically suppressed by the vertical turbulent mixing,indicating more tidal energy is able to be converted into the irreversible mixing when the two-equation turbulence model is employed.

Confinement synthesis of bimetallic MOF-derived defect-rich nanofiber electrocatalysts for rechargeable Zn-air battery

Zn-air batteries with high energy density and safety have acquired enormous attention,while the practical application is hindered by the sluggish kinetics of the oxygen evolution reaction(OER)and the oxygen reduction reaction(ORR).In this work,a threedimensional(3D)defect-rich bifunctional electrocatalyst(CoFe/N CNFs)comprising irregular hollow CoFe nanospheres in Ndoped carbon nanofibers is presented,which is fabricated from CoFe ZIFs-derived(ZIF:zeolitic-imidazolate framework)polymer nanofibers precursor.The CoFe ZIFs with tunable particle size and composition are constructed using a confined synthesis strategy.Moreover,the Kirkendall diffusion process is available for forming the irregular hollow CoFe nanospheres,and the decomposition of polyvinylpyrrolidone(PVP)results in forming the defective carbon nanofibers,which provide more efficient active sites and enhance the electrocatalytic properties toward both OER and ORR.The optimized CoFe/N CNFs exhibit superior bifunctional activities,outperforming that of the benchmark Pt/C+RuO_(2) catalyst.As a result,the CoFe/N CNFs as an air-cathode endow the rechargeable Zn-air battery with an excellent power density of 149 mW·cm^(−2),energy density of 875 Wh·kg^(−1),and cycling stability.This work provides a new strategy to develop bifunctional electrocatalysts with desired nanostructure and regulated performance toward energy applications.