An extended three-dimensional variational data assimilation (3DVAR) method based on the Weather Research and Forecasting Model (WRF) is developed to assimilate satellite-derived humidity from sea fog at its initial stage over the Yellow Sea. The sea fog properties, including its horizontal distribution and thickness, are retrieved empirically from the infrared and visible cloud imageries of the Multifunctional Transport Satellite (MTSAT). Assuming a relative humidity of 100% in fog, the MTSAT-derived humidity is assimilated by the extended 3DVAR assimilation method. Two sea fog cases, one spread widely over the Yellow Sea and the other spread narrowly along the coast, are first studied in detail with a suite of experiments. For the widespread-fog case, the assimilation of MTSAT-derived information significantly improves the forecast of the sea fog area, increasing the probability of detection and equitable threat scores by about 20% and 15%, respectively. The improvement is attributed to a more realistic representation of the marine boundary layer (MBL) and better descriptions of moisture and temperature profiles. For the narrowly spread coastal case, the model completely fails to reproduce the sea fog event without the assimilation of MTSAT-derived humidity. The extended 3DVAR assimilation method is then applied to 10 more sea fog cases to further evaluate its effect on the model simulations. The results reveal that the assimilation of MTSAT-derived humidity not only improves sea fog forecasts but also provides better moisture and temperature structure information in the MBL.

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We have synthesized a new layered oxychalcogenide La2O2Bi3AgS6. From synchrotron X-ray diffraction and Rietveld refinement, the crystal structure of La2O2Bi3AgS6 was refined using a model of the P4/nmm space group with a = 4.0644(1) Å and c = 19.412(1) Å, which is similar to the related compound LaOBiPbS3, while the interlayer bonds (M2-S1 bonds) are apparently shorter in La2O2Bi3AgS6. The tunneling electron microscopy (TEM) image confirmed the lattice constant derived from Rietveld refinement (c ~ 20 Å). The electrical resistivity and Seebeck coefficient suggested that the electronic states of La2O2Bi3AgS6 are more metallic than those of LaOBiS2 and LaOBiPbS3. The insertion of a rock-salt-type chalcogenide into the van der Waals gap of BiS2-based layered compounds, such as LaOBiS2, will be a useful strategy for designing new layered functional materials in the layered chalcogenide family.

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The 2016–18 NOAA Hazardous Weather Testbed (HWT) Spring Forecasting Experiments (SFE) featured the Community Leveraged Unified Ensemble (CLUE), a coordinated convection-allowing model (CAM) ensemble framework designed to provide empirical guidance for development of operational CAM systems. The 2017 CLUE included 81 members that all used 3-km horizontal grid spacing over the CONUS, enabling direct comparison of forecasts generated using different dynamical cores, physics schemes, and initialization procedures. This study uses forecasts from several of the 2017 CLUE members and one operational model to evaluate and compare CAM representation and next-day prediction of thunderstorms. The analysis utilizes existing techniques and novel, object-based techniques that distill important information about modeled and observed storms from many cases. The National Severe Storms Laboratory Multi-Radar Multi-Sensor product suite is used to verify model forecasts and climatologies of observed variables. Unobserved model fields are also examined to further illuminate important intermodel differences in storms and near-storm environments. No single model performed better than the others in all respects. However, there were many systematic intermodel and intercore differences in specific forecast metrics and model fields. Some of these differences can be confidently attributed to particular differences in model design. Model intercomparison studies similar to the one presented here are important to better understand the impacts of model and ensemble configurations on storm forecasts and to help optimize future operational CAM systems.

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The effect of adding minor elements, such as Ti, Mg, Zr, Ca or Hf, on the size of oxide particles was investigated in Ni-based ODS alloy, Ni-0.5 mass%Al-1 mass%Y 2 O 3 . Among these elements, Hf is the most effective at refining the oxide particles, particularly at a concentration of 0.8 mass% Hf, as verified by TEM observation and hardness measurement. X-ray diffraction measurements indicate that the formation of Y 2 Hf 2 O 7 is responsible for the refinement of oxide particles. The Hf is also effective for a commercial superalloy of PM1000.