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

WRF simulations were conducted for Ise Bay, Japan for January and July 2016 to evaluate sensitivity of model input and output above sea surface to the replacement of three default input datasets with region-specific input datasets. For atmospheric input data, a final analysis created by the National...

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Bibliographic Details
Published inCoastal engineering journal Vol. 63; no. 1; pp. 17 - 31
Main Authors Matsuzaki, Yoshitaka, Fujiki, Takashi, Kawaguchi, Koji, Inoue, Tetsunori, Iwamoto, Takumu
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis 02.01.2021
Taylor & Francis Inc
Subjects
above sea surface
Accuracy
Analysis
Atmospheric data
Coastal zone
Data
Datasets
Geological surveys
Ise Bay
Land use
Model accuracy
Sea surface
Sea surface temperature
Sensitivity analysis
Simulation
Surveying
temperature
Topography
Wind speed
WRF
Japan
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Summary:WRF simulations were conducted for Ise Bay, Japan for January and July 2016 to evaluate sensitivity of model input and output above sea surface to the replacement of three default input datasets with region-specific input datasets. For atmospheric input data, a final analysis created by the National Centers for Environmental Prediction (NCEP-FNL) was replaced with a mesoscale analysis created by the Japan Meteorological Agency (JMA). Topography and land use dataset released by the US Geological Survey were replaced with dataset released by the GeoSpatial Information authority of Japan. For sea surface temperature (SST) data, NCEP-FNL was replaced with an analysis created by JMA. Of the three region-specific datasets, replacement of atmospheric data results in the largest improvements in the accuracy of simulated wind speeds in January and July and of temperature in July 2016. Improvements in model output accuracy over sea surface can be seen near the coastline by replacing topography and land use data. Replacement of SST data results in the largest improvements in simulated temperature accuracy in January 2016. Replacing all three default input datasets results in the largest improvement, and expands on results from previous studies that focused on the effects of replacing only one input data.
ISSN:2166-4250
1793-6292
DOI:10.1080/21664250.2020.1830485