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The development of high-precision, long-term, hourly-scale precipitation data is essential for understanding extreme precipitation events. Reanalysis systems are particularly promising for this type of research due to their long-term observations and wide spatial coverage. This study aims to construct a more robust precipitation dataset by integrating three widely-used reanalysis precipitation estimates: Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA2), Climate Forecast System Reanalysis (CFSR), and European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5). A novel integration method based on the generalized three-cornered hat (TCH) approach is employed to quantify uncertainties in these products. To enhance accuracy, the high-density daily precipitation data from the Asian Precipitation-Highly-Resolved Observation Data Integration Towards Evaluation (APHRODITE) dataset is used for correction. Results show that the TCH method effectively identifies seasonal and spatial uncertainties across the products. The TCH-weighted product (TW), calculated using signal-to-noise ratio weighting, outperforms the original reanalysis datasets across various watersheds and seasons. After correction with APHRODITE data, the enhanced integrated product (ATW) significantly improves accuracy, making it more suitable for extreme precipitation event analysis. Quantile mapping was applied to assess the ability of TW and ATW to represent extreme precipitation. Both products showed improved accuracy in regional average precipitation, with ATW demonstrating superior improvement. This integration method provides a robust approach for refining reanalysis precipitation datasets, contributing to more reliable hydrological and climate studies. [ABSTRACT FROM AUTHOR]

Existing research in the shipbuilding field tends to focus on isolated single aspects of Industry 4.0 (I4.0) without a full picture. To address this gap, this paper seeks to offer a thorough and in-depth examination of the concepts and technologies necessary to integrate I4.0 into the design, construction, maintenance, and other stages throughout the entire life cycle of a ship. This paper will firstly examine the recent developments and identify the gaps in I4.0 application within shipbuilding. By conducting a systematic literature review on 68 publications through an appropriate review methodology, we synthesize the current state of I4.0 research in the shipbuilding industry, propose a framework for the application of I4.0 in shipbuilding to analyze the progression and research agenda of I4.0 in the shipbuilding sector, and discuss its implications. The Shipbuilding 4.0 framework proposed comprises five main components: concepts, value chain, smart factory, smart manufacturing, infrastructure, and technologies. The proposed framework aims to enhance the understanding of both academics and practitioners regarding the specific needs of the shipbuilding industry and the role I4.0 can and should play in its advancement. [ABSTRACT FROM AUTHOR]

Coupling the Weather Research and Forecasting (WRF) model with wind farm parameterization can be effective in examining the performance of large-scale wind farms. However, the current scheme is not suitable for floating wind turbines. In this study, a new scheme is developed for floating wind farm parameterization (FWFP) in the WRF model. The impacts of the side columns of a semi-submersible floating wind turbine on waves are first parameterized in the spectral wave model (SWAN) where the key idea is to consider both inertial and drag forces on side columns. A machine learning model is trained using results from idealized high-resolution SWAN simulations and then implemented in the WRF to form the FWFP. The difference between our new scheme and the original scheme in a realistic case is investigated using a coupled atmosphere–wave model. The results show that the original scheme has a lower power output in most of the grids with an average of 12 % compared to the FWFP scheme. The upstream wind speed is increased slightly compared to the original scheme (<0.4 m s -1), while the downstream wind speed is decreased but by a much larger magnitude (<1.8 m s -1). The distribution of the difference in turbulent kinetic energy (TKE) corresponds well to that of the wind speed, and the TKE budget reveals that the difference in TKE in the rotor region between the two schemes is mainly due to vertical wind shear. This demonstrates that the FWFP is necessary for both predicting the wind power and evaluating the impact of floating wind farms on the surrounding environment. [ABSTRACT FROM AUTHOR]