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The Weather Research and Forecasting (WRF) model was used to simulate Typhoon Rumbia in this paper. The sensitivity experiments were conducted with 16 different parameterization combination schemes, including four microphysics (WSM6, WSM5, Lin, and Thompson), two boundary layers (YSU and MYJ), and two cumulus convection (Kain–Fritsch and Grell–Freitas) schemes. The impacts of 16 parameterization combination schemes and the data assimilation (DA) of Global Navigation Satellite System (GNSS) water vapor were evaluated by the simulation accuracy of typhoon track and intensity. The results show that the typhoon track and intensity are significantly influenced by parameterization schemes of cumulus and boundary layers rather than microphysics. The averaged track error of Lin_KF_Y is 104.73 km in the entire 72-h simulation period. The track errors of all the other combination schemes are higher than Lin_KF_Y. During the entire 72-h, the averaged intensity error of Thompson_GF_M is 1.36 hPa. It is the lowest among all the combination schemes. As for data assimilation, the simulation accuracy of typhoon tracks can be significantly improved by adding the GNSS water vapor. Thompson_GF_M-DA combination scheme has the lowest average track error of 45.05 km in the initial 24 h. The Lin_KF_Y-DA combination scheme exhibits an average track error of 32.17 km on the second day, 28.03 km on the third day, and 35.33 km during 72-h. The study shows that the combination of parameterization schemes and the GNSS water vapor data assimilation significantly improve the initial conditions and the accuracy of typhoon predictions. The study results contribute to the selection of appropriate combinations of physical parameterization schemes for the WRF-ARW model in the mid-latitude region of the western Pacific coast. [ABSTRACT FROM AUTHOR]

In response to the nonlinear fitting difficulty of the traditional weighted average temperature (Tm) modeling, this paper proposed four machine learning (ML)-based Tm models. Based on the seven radiosondes in the Yangtze River Delta region from 2014 to 2019, four forecasting ML-based Tm models were constructed using Light Gradient Boosting Machine (LightGBM), Support Vector Machine (SVM), Random Forest (RF), and Classification and Regression Tree (CART) algorithms. The surface temperature (Ts), water vapor pressure (Es), and atmospheric pressure (Ps) were identified as crucial influencing factors after analyzing their correlations to the Tm. The ML-based Tm models were trained using seven radiosondes from 2014 to 2018. Then, the mean bias and root mean square error (RMSE) of the 2019 dataset were used to evaluate the accuracy of the ML-based Tm models. Experimental results show that the overall accuracy of the LightGBM-based Tm model is superior to the SVM, CART, and RF-based Tm models under different temporal variations. The mean RMSE of the daily LightGBM-based Tm model is reduced by 0.07 K, 0.04 K, and 0.13 K compared to the other three ML-based models, respectively. The mean RMSE of the monthly LightGBM-based Tm model is reduced by 0.09 K, 0.04 K, and 0.11 K, respectively. The mean RMSE of the quarterly LightGBM-based Tm model is reduced by 0.09 K, 0.04 K, and 0.11 K, respectively. The mean bias of the LightGBM-based Tm model is also smaller than that of the other ML-based Tm models. Therefore, the LightGBM-based Tm model can provide more accurate Tm and is more suitable for obtaining GNSS precipitable water vapor in the Yangtze River Delta region. [ABSTRACT FROM AUTHOR]

The development of high-quality GaN-based heterojunctions breaks through the limitation of lattice mismatch, which is of particular importance for promoting their optoelectronic applications. Herein, we report the incommensurate heteroepitaxial growth of single-crystal cesium lead iodine (CsPbI3) nanoplatelets on a c-GaN/sapphire substrate with a uniform rectangular shape and composition distribution via one-step chemical vapor deposition. The formed CsPbI3/GaN heterojunction presents a type-II band alignment with the valence and conduction band offsets of 2.12 ± 0.15 eV and 0.60 ± 0.15 eV, respectively. Compared with CsPbI3 grown on a mica substrate, the CsPbI3/GaN heterojunction exhibits remarkable photoluminescence quenching and a shorter exciton lifetime, which arises from the enhanced carrier separation and extraction efficiencies induced by the band-offset effect. Thanks to the complementarity between the band gaps of CsPbI3 and GaN, the optical absorption of the formed heterojunction is expanded from the visible light to ultraviolet. These findings suggest the large potential of the CsPbI3/GaN heterojunction for the development of high-performance integrated photovoltaic and optoelectronic devices. [ABSTRACT FROM AUTHOR]

Monolayer transition metal dichalcogenide (TMD) alloys with tunable band gaps exhibit huge potential in nanoelectronics, optoelectronics, and photonics. The scalable production of uniform atomically thin TMD alloys is a key step for the realization of their device applications but remains a large challenge so far. Here, we report oxygen-assisted chemical vapor deposition (CVD) of uniform atomically thin MoS2(1–x)Se2x semiconductor alloys via a vertical Mo-precursor supply strategy. The growth scheme leads to the formation of highly crystalline MoS2(1–x)Se2x monolayer films within a short growth time of 8 min, which benefits from a stable and homogeneous Mo-precursor feeding environment and the synergic effect of NaBr and oxygen carrier on the growth. The high-resolution spectral characterizations and density functional theory calculations demonstrate that the chemical composition of the as-grown MoS2(1–x)Se2x monolayers can be continuously tuned from x = 0 to 1, leading to the corresponding band gap being gradually changed from 1.81 to 1.55 eV. This work provides an efficient strategy to obtain large-area uniform MoS2(1–x)Se2x monolayer alloys with tunable compositions and optical properties, which is essential for driving their applications in various functional optoelectronic devices, especially for high-performance flexible photodetectors. [ABSTRACT FROM AUTHOR]