ABSTRACT

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.

抽象的

在2016年1月和2016年7月对日本伊势湾进行了WRF模拟，以评估模型输入和输出在海面之上对将三个默认输入数据集替换为特定于区域的输入数据集的敏感性。对于大气输入数据，由日本国家环境预测中心（NCEP-FNL）创建的最终分析被日本气象厅（JMA）创建的中尺度分析代替。美国地质调查局发布的地形和土地使用数据集被日本地理空间信息管理局发布的数据集所取代。对于海表温度（SST）数据，NCEP-FNL被JMA创建的分析所代替。在三个特定于区域的数据集中，替换大气数据将最大程度地提高模拟风速（分别在1月和7月和2016年7月）的准确性。通过替换地形和土地利用数据，可以在海岸线附近看到海面的模型输出精度的提高。替换SST数据将在2016年1月带来最大的模拟温度精度改进。替换所有三个默认输入数据集将带来最大的改进，并且扩展了以前研究的结果，这些研究仅关注替换一个输入数据的效果。