Application of the WRF model to the coastal area at Ise Bay, Japan: evaluation of model output sensitivity to input data

Matsuzaki, Yuriko; Fujiki, Takashi; Kawaguchi, Koji; Inoue, Takanobu; Iwamoto, Takumu

doi:10.1080/21664250.2020.1830485

Cited by 8 publications

(2 citation statements)

References 23 publications

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“…Thus, more accurate data were not used for boundary conditions unless they could be obtained in real time. Thus, although a system that uses the output of an atmospheric simulation model as a boundary condition has since been developed for this numerical simulation model (Hafeez et al., 2021; Matsuzaki et al., 2021), this study adopted a system that creates boundary conditions based on observed values. Atmospheric forcings were created through spatial interpolation from data obtained from 12 observation stations on the land surrounding Ise Bay.…”

Section: Methodsmentioning

confidence: 99%

Perturbation of Boundary Conditions to Create Appropriate Ensembles for Regional Data Assimilation in Coastal Estuary Modeling

Matsuzaki

Inoue

2022

JGR Oceans

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Regional data assimilation is conducted for a coastal estuary using the ensemble Kalman filter, real observation data from Ise Bay, Japan, and a simulation model called the Ise Bay Simulator. The applicability and robustness of the method are then examined. We also analyze the relationship between the boundary conditions, which add perturbations and the data assimilation results of water temperature and salinity. A method of creating an ensemble by perturbing three boundary conditions (atmospheric forcing, lateral boundary conditions [open boundary conditions], and river discharge forcing) is then proposed. In situ water temperature and salinity profiles observed at fixed points are assimilated daily. The proposed assimilation method provides stable data assimilation without unnatural values for water temperature and salinity throughout the year. Further, applying a perturbation to the three boundary conditions does not lead to filter divergence, thus indicating good applicability and robustness, that is, applying a perturbation to the three boundary conditions does not degenerate the ensemble spread. According to a sensitivity experiment, perturbing the atmospheric boundary conditions of both air temperature and wind speed increases the ensemble spread of water temperature, especially near the surface layer. Wind speed has the greatest influence on the magnitude of the salinity ensemble spread, and its dominance depends on location. Perturbation of lateral boundary conditions increases the ensemble spread of water temperature and salinity at all water depths near the bay mouth, and the observations are effectively assimilated. Perturbation of river discharge forcing successfully assimilates water temperature and salinity near the estuary.

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Section: Methodsmentioning

confidence: 99%

Perturbation of Boundary Conditions to Create Appropriate Ensembles for Regional Data Assimilation in Coastal Estuary Modeling

Matsuzaki

Inoue

2022

JGR Oceans

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“…The WCA station, located by the Westchester County Airport, is situated less than 10 km from the shoreline, which may cause discrepancies in the obtained evaluation results for different locations. Coastal regions are strongly affected by atmospheric forcing [96] that may not be accurately represented by numerical models if no additional, more accurate input data (e.g., sea surface temperature) are included in calculations [97,98] or the applied resolution is not sufficient to resolve terrain complexity and small-scale weather phenomena [84,99].…”

Section: Grid Resolutionmentioning

confidence: 99%

Accuracy Assessment of WRF Model in the Context of Air Quality Modeling in Complex Terrain

Rzeszutek,

Kłosowska,

Oleniacz

2023

Sustainability

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Output data from the Weather Research and Forecasting (WRF) model are frequently used in air quality modeling for scientific, practical and regulatory purposes. Therefore, it is crucial to determine whether the accuracy of WRF predictions is suitable for application in air quality models on a local scale (<50 km) and in complex terrain. The presented research is unique because, to assess the accuracy of the WRF model, data from experimental data sets for the assessment of air quality models were used, which contained information about the actual conditions of selected meteorological parameters along the vertical profile of the atmosphere. The aim of the study was to conduct an evaluation of the WRF model using data derived from three field experiments designated to conduct air quality model evaluation studies for models such as AERMOD, ADMS or CALPUFF. Accuracy evaluation was carried out in relation to the grid resolution, station location (on-site and weather airport) and vertical profile of the atmosphere. Obtained results of the evaluation for temperature, wind speed and direction were analyzed with regard to the possibilities of application in air quality modeling systems. It was stated that the use of a grid with a resolution of 1 km generally resulted in statistically significantly lower values of errors for wind speed compared to a 4 km resolution. The outcomes of simulations for temperature and wind speed were sensitive with regard to the location. In on-site locations (complex terrain) significantly higher values of prediction errors (MB, MGE, RMSE) were obtained compared to the standard weather station locations (airport). In addition, wind speed predictions in on-site locations were generally biased (overestimated). Along the vertical profile of the atmosphere, up to the altitude of 100 m a.g.l., statistically significantly different outcomes of accuracy evaluation were achieved for wind speed and direction. Considering the above, caution should be exercised when using data from meteorological simulations in air quality modeling.

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OILPARI—A Real-Time Oil Transport Simulator for Marine Disaster Response: Its Functionary, Update, and Progress Toward the Next Generation

Matsuzaki,

Fujita

2024

Lecture Notes in Civil Engineering

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We developed a numerical simulation model called “OILPARI” to predict the transport of spilled oil on sea surfaces. Two types of OILPARI simulation systems were constructed: a stand-alone type (sa-OILPARI) improved as described herein and a web application type (net-OILPARI) developed in this study. As the ocean current and wind datasets have been improved to high-resolution datasets, sa-OILPARI must be improved to accommodate them. As another improvement, a past analysis mode is added to understand the oil transport trends according to the season and sea area and to perform calculations to reproduce past oil spill incidents. Significantly, in net-OILPARI, a client does not need to prepare any special software and can use the functionality by simply accessing a URL from a browser. The application provides an intuitive single-page graphical user interface. OILPARIs have been applied to many oil spill incidents in the past. Case studies are presented for an oil spill incident off the coast of Hachinohe, Japan, in August 2021 and a pumice stone (floating stone) transport simulation occurring in the Pacific Ocean in 2021.

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Application of the WRF model to the coastal area at Ise Bay, Japan: evaluation of model output sensitivity to input data

Cited by 8 publications

References 23 publications

Perturbation of Boundary Conditions to Create Appropriate Ensembles for Regional Data Assimilation in Coastal Estuary Modeling

Perturbation of Boundary Conditions to Create Appropriate Ensembles for Regional Data Assimilation in Coastal Estuary Modeling

Accuracy Assessment of WRF Model in the Context of Air Quality Modeling in Complex Terrain

OILPARI—A Real-Time Oil Transport Simulator for Marine Disaster Response: Its Functionary, Update, and Progress Toward the Next Generation

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