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Wang, Bowen

Publications and source records attributed to Wang, Bowen.

An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)

Abstract. Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to the low resolution of global climate models (GCMs). Yet the climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality and high-resolution predictions. Here, we present an ensemble of dynamically downscaled simulations over the western US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs. This dataset is titled the Western US Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography. (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven by locally intensified atmospheric updrafts tied to sharper, more realistic gradients in topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western US climate.

Rahimi, Stefan (ORCID:0000000331884462)↗

Corrigendum to “Transport of intensity equation: A tutorial” Optics and Lasers in Engineering, Volume 135 (2020) 106187

In this Corrigendum, we correct misprints in equations and figures of the article titled “Transport of intensity equation: a tutorial” Optics and Lasers in Engineering, 135, 106187, 2020.1 These misprints were caused by unanticipated issues in email communication between the authors and the editorial team during the proofreading stage. The authors would like to apologize for any inconvenience caused.

36 MATERIALS SCIENCE↗

Transport of intensity equation: a tutorial

When it comes to “phase measurement” or “quantitative phase imaging”, many people will automatically connect them with “laser” and “interferometry”. Indeed, conventional quantitative phase imaging and phase measurement techniques generally rely on the superposition of two beams with a high degree of coherence: complex interferometric configurations, stringent requirements on the environmental stabilities, and associated laser speckle noise severely limit their applications in optical imaging and microscopy. On a different note, as one of the most well-known phase retrieval approaches, the transport of intensity equation (TIE) provides a new non-interferometric way to access quantitative phase information through intensity only measurement. Despite the insufficiency for interferometry, TIE is applicable under partially coherent illuminations (like the Köhler’s illumination in a conventional microscope), permitting optimum spatial resolution, higher signal-to-noise ratio, and better image quality. In this tutorial, we give an overview of the basic principle, research fields, and representative applications of TIE, focus particularly on optical imaging, metrology, and microscopy. The purpose of this tutorial is twofold. It should serve as a self-contained introduction to TIE for readers with little or no knowledge of TIE. On the other hand, it attempts to give an overview of recent developments in this field. These results highlight a new era in which strict coherence and interferometry are no longer prerequisites for quantitative phase imaging and diffraction tomography, paving the way toward new generation label-free three-dimensional microscopy, with applications in all branches of biomedicine.

42 ENGINEERING↗

Emission Control from Transition Metal Dichalcogenide Monolayers by Aggregation-Induced Molecular Rotors

Organic–inorganic (O–I) heterostructures, consisting of atomically thin inorganic semiconductors and organic molecules, present synergistic and enhanced optoelectronic properties with a high tunability. Here, we develop a class of air-stable vertical O–I heterostructures comprising a monolayer of transition-metal dichalcogenides (TMDs), including WS 2 , WSe 2 , and MoSe 2 , on top of tetraphenylethylene (TPE) core-based aggregation-induced emission (AIE) molecular rotors. The created O–I heterostructures yields a photoluminescence (PL) enhancement of up to ~950%, ~500%, and ~330% in the top monolayer WS 2 , MoSe 2 , and WSe 2 as compared to PL in their pristine monolayers, respectively. The strong PL enhancement is mainly attributed to the efficient photogenerated carrier process in the AIE luminogens (courtesy of their restricted intermolecular motions in the solid state) and the charge-transfer process in the created type I O–I heterostructures. Moreover, we observe an improvement in photovoltaic properties of the TMDs in the heterostructures including the quasi-Fermi level splitting, minority carrier lifetime, and light absorption. Overall, this work presents an inspiring example of combining stable, highly luminescent AIE-based molecules, with rich photochemistry and versatile applications, with atomically thin inorganic semiconductors for multifunctional and efficient optoelectronic devices.

14 SOLAR ENERGY↗