This work presents a sensitive refractive index sensor based on the dual resonance of an excessively tilted long period fiber grating (Ex-TLPFG). The Ex-TLPFG is tuned to couple the guided core mode with only the polarization-degenerate cladding mode LP, which consists of TE/TM and HE vector modes. It is found that the p-polarized LP1,lp mode exhibits a higher sensitivity than that of the s-polarized LP1,ls mode. An optimized sensitivity as high as 12182.9  nm/RIU is achieved for the p-polarized LP1,2p mode at the low refractive index region by tuning the initial resonance condition. The sensing performance is also evaluated through the power measurement method for a single resonance band. It is demonstrated that the improved sensitivity in this work for diameter-reduced Ex-TLPFG is much higher than that for the conventional LPFG based devices, which makes this sensing platform very attractive for a variety of index sensing applications.

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The overall purpose of this paper is to post-evaluate the predictability of Hurricane Florence using the Advanced Research Weather Research Forecast (WRF) (ARW) version of a mesoscale model. This was performed over the period from 0000 UTC 13 September 2018 through 0000 UTC 18 September 2018. The WRF ARW core resolution used here was the 27-km grid spacing chosen to in order to balance finer resolution against in house processing time and storage. The large-scale analysis showed that a change in the Northern Hemisphere flow regime, especially the flow in the western part of the Northern Hemisphere may have contributed partly to the reduced forward speed of the tropical cyclone. In order to measure the predictability of a system, we will use different convective and boundary layer schemes initialized from the same conditions. The results demonstrated that the sign of the local IRE tendency was similar to that of the Northern Hemisphere Integrated Enstrophy. The results also showed that when the boundary layer, convective, and cloud microphysical schemes of the model were varied, the areal coverage of heavy precipitation of Florence was under-forecast by approximately 10% or more, and the heaviest amounts were under-forecast by an average of about 20%.