Multi-Factor Intensity Estimation for Tropical Cyclones in the Western North Pacific Based on the Deviation Angle Variance Technique

In this paper, the infrared cloud images from Fengyun series geostationary satellites and the best track data from the China Meteorological Administration(CMA-BST) in 2015–2017 are used to investigate the effects of two multifactor models, generalized linear model(GLM) and long short-term memory(LSTM) model, for tropical cyclone(TC) intensity estimation based on the deviation angle variance(DAV) technique. For comparison, the typical singlefactor Sigmoid function model(SFM) with the map minimum value of DAV is also used to produce TC intensity estimation. Sensitivity experiments regarding the DAV calculation radius and different training data groups are conducted, and the estimation precision and optimum calculation radius for DAV in the western North Pacific(WNP) are analyzed. The results show that the root-mean-square-error(RMSE) of the single-factor SFM is 8.79–13.91 m s^-1 by using the individual years as test sets and the remaining two years as training sets with the optimum calculation radius of 550 km. However, after selecting and using the high-correlation multiple factors from the same test and training data, the RMSEs of GLM and LSTM models decrease to 5.93–8.68 and 4.99–7.00 m s^-1 respectively, with their own optimum calculation radii of 350 and 400 km. All the sensitivity experiments indicate that the SFM results are significantly influenced by the DAV calculation radius and characteristics of the training set data, while the results of multi-factor models appear more stable. Furthermore, the multi-factor models reduce the optimum radius within the process of DAV calculation and improve the precision of TC intensity estimation in the WNP, which can be chosen as an effective approach for TC intensity estimation in marine areas.

Maximizing ionic transport of Li1+xAlxTi2-xP3O12 electrolytes for all-solid-state lithium-ion storage:A theoretical study

The concept of all-solid-state batteries provides an efficient solution towards highly safe and long-life energy storage,while the electrolyte-related challenges impede their practical application.Li1+xAlxTi2-xP3O12(0≤x≤1)with superior Li ionic conductivity holds the promise as an ideal solidstate electrolyte.The intrinsic mechanism to reach the most optimum ionic conductivity in Al-doped Li1+xAlxTi2-xP3O12,however,is unclear to date.Herein,this work intends to provide an atomic scale study on the Li-ion transport in Li1+xAlxTi2-xP3O12electrolyte to rationalize how Al-dopant initiates interstitial Li activity and facilitate their easy mobility combining Density Functional Theory(DFT)and ab initio Molecular dynamics(AIMD)simulations.It is discovered that the interstitial Li ions introduced by Al dopants can effectively activate the neighboring occupied intrinsic Li-ions to induce a long-range mobility in the lattice and the maximum Li ionic conductivity is achieved at 0.50 Al doping concentration.The Li-ion migration paths in Li1+xAlxTi2-xP3O12have investigated as the degree of distortion of[PO4]tetrahedra and[TiO6]octahedra resulted by different Al doping concentrations.The asymmetry of the surrounding distorted[PO4]and[TiO6]polyhedrons play a critical role in reducing the migration barrier of Li ions in Li1+xAlxTi2-xP3O12.The flexible[Ti O6]polyhedrons with a capacity to accommodate the structural distortion govern the Li ionic conductivity in Li1+xAlxTi2-xP3O12.This work rationalizes the mechanism for the most optimum Li ionic conductivity in Al-doped Li Ti2P3O12electrolyte and,more importantly,paves a road for exploring novel all-solid-state lithium battery electrolytes.