Sensitivity of the WRF Regional Meteorological Model to Input Datasets and Surface Parameters for the Kanto Plain on Fine Summer Days

Akimoto, Yuko

doi:10.4157/grj.83.324

Cited by 8 publications

(7 citation statements)

References 11 publications

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“…Besides these sets of default data, in Japan, land use data from the Geospatial Information Authority of Japan can be used as land use data, and meso objective analysis data (MANAL: Meso-Scale Analysis) from the Japanese Meteorological Agency can be used as weather data. Akimoto et al (2010) [19] showed that by using land use data from the Geospatial Information Authority of Japan instead of data from the USGS, calculation results that more closely match observed values can be obtained in Japan. Therefore, in this study, as weather data and landform data, the WRF default data, that is, FNL and USGS data, were used; and as land use data, based on Akimoto et al (2010) [19], urban area land use subdivided mesh data for 2009 from the Geospatial Information Authority of Japan was used.…”

Section: Data Collectionmentioning

confidence: 79%

“…(1) There are 27 categories of land use in the WRF; however, the above-mentioned urban area land use subdivided mesh data has 11 categories, and its method of classifying land use is different to that of the WRF. Therefore, with reference to Akimoto et al (2010) [19], the land use categories in the urban area land use subdivided mesh were made to correspond to the unique categories of the WRF, as shown in Table 1. Further, in Scenario 1, which does not divide buildings into low-rise buildings and high-rise buildings, both types of buildings were classified as "Low Intensity Residential".…”

Section: Data Processingmentioning

confidence: 99%

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Method for Evaluating the Influence of Obstruction of Sea Breeze by Clusters of High-Rise Buildings on the Urban Heat Island Effect

Sashiyama¹,

Yamamoto²

2014

JEP

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This study aims to propose a method for quantitatively evaluating the influence which the obstruction of sea breezes by clusters of high-rise buildings has on the urban heat island effect using a weather simulation model and Geographic Information Systems (GIS). Specifically, a method of evaluating the influence of the obstruction of sea breeze by high-rise buildings on the urban heat island effect was proposed. In the method, two scenarios that imagine urban forms which differ with regard to whether or not they contain high-rise buildings are created and weather simulation is conducted, and the results of the simulations are comparatively analyzed focusing on temperature and wind speed. Evaluation was conducted in two stages, and Shiodome of Minato City in the Tokyo Metropolis was selected as the region for evaluation. In two stages of evaluation, a rise in temperature of approximately 0.3 K and a reduction in wind speed of approximately 1 m/s were observed in a region approximately five to ten kilometers square downwind of high-rise buildings in the period 6 PM to 9 PM, and a higher temperature caused by the obstruction of sea breeze by high-rise buildings was identified. The fact that such a higher temperature was confirmed in the time period from 6 PM onwards, in which the temperature decreases, reveals that obstruction of sea breeze by high-rise buildings dulls the decrease in temperature which occurs from evening onwards, and influences nighttime urban heat island formation.

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Section: Data Collectionmentioning

confidence: 79%

Section: Data Processingmentioning

confidence: 99%

Method for Evaluating the Influence of Obstruction of Sea Breeze by Clusters of High-Rise Buildings on the Urban Heat Island Effect

Sashiyama¹,

Yamamoto²

2014

JEP

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“…When using meteorological models, it is useful to make sensitivity studies of model parameters to evaluate and understand the model accuracy and characteristics. Previous studies have investigated meteorological model sensitivity using different dataset input methods (Tatsumi et al, 2008;Akimoto and Kusaka, 2010;Zhang et al, 2012). In addition, numerical simulations have been applied over complex terrain in order to evaluate the ability of meteorological models (Jiménez and Dudhia, 2013;Zhang et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Strong Local Wind in Northwestern Hokkaido, Japan

Kasai¹,

Kimura

Shiomi

et al. 2018

チリガクロンシュウ

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A strong local wind has been observed in Rumoi, northwestern Hokkaido, Japan. In order to investigate the wind around Rumoi, an analysis was performed using 30-year AMeDAS wind observations and numerical experiments with the Weather Research and Forecasting (WRF) model. Observation results show that there is a frequent strong wind in Rumoi in comparison with other areas around Rumoi. In relation to seasonal changes in wind direction, more than 50% of the wind in summer blows from ESE, but westerly winds are frequent in winter. To clarify the mechanisms involved in producing a strong local wind in winter, we compared two events using observations and numerical experiments. One case involves a strong local wind with a speed of approximately 12 m/s in Rumoi and a weak wind of less than 5 m/s in the surrounding areas; the prevailing wind direction is ESE (03:00 on January 28, 2003). The other case is that of a strong wind over 10 m/s blowing over the entire study area (on the afternoon of March 8, 2005), with a westerly prevailing wind. The experimental results show a relatively good correspondence with those of the observation. A cross-section view demonstrates the existence of a mountain wave when the strong local wind is observed in Rumoi. The wind then passes through the valleyshaped topography, and wind speeds are accelerated in the vicinity of Rumoi, which suggests the existence of a gap wind. Additionally, a sensitivity experiment is performed by changing the land surface model without considering snow, and the wind speed over land is seen to be reduced by 2 m/s, with very little change in the wind direction.

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“…The climate in an urban area is primarily influenced by synoptic conditions. At the same time, the local climate is also strongly affected by intrinsic aspects of the target region, e.g., land use [e.g., Fujibe , ; Akimoto and Kusaka , ; Aoyagi et al , ], sea surface temperature (SST) surrounding the area [e.g., Oda and Kanda , ; Takahashi et al , ], and topography [e.g., Ishizaki and Takayabu , ; Takane and Kusaka , ]. It is necessary to express these aspects adequately in the model for accurate estimation of surface air temperature (SAT) in urban areas.…”

Section: Introductionmentioning

confidence: 99%

“…Akimoto and Kusaka [] investigated the impact of differences in the boundary data used on model simulations of SAT in the Tokyo metropolitan area. The inputs were atmospheric data from the outer model, SST data, land use data, topography, and ground surface parameters.…”

Section: Introductionmentioning

confidence: 99%

Impact of high‐resolution sea surface temperature and urban data on estimations of surface air temperature in a regional climate

et al. 2016

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We investigated the impact of using high‐resolution sea surface temperature (SST) data and a sophisticated urban model on the simulation of surface air temperature (SAT) in the Nagoya metropolitan area using a regional climate model. The spatially detailed structure of SST, expressed in high‐resolution SST data, had relatively little impact on SAT. On the other hand, the difference in areal mean value of SST strongly affected SAT across a wide range of land surfaces. When a spatially inhomogeneous distribution was used for the urban fraction and anthropogenic heat, and appropriate physical properties for building materials were given according to the specific urban categories, we achieved significant improvements in both the diurnal range of SAT and its daily mean. Based on a comparison with an additional sensitivity experiment for building albedo, the sophistication of urban fraction and thermal parameters related to building materials had a comparable impact on SAT as presumable building albedo in the daytime, while they indicated a larger impact on the nighttime SAT. We conclude that (1) the areal mean SST is critical rather than its resolution for the climatological average of SAT over the land; (2) the simultaneous refinement of the urban fraction and building material parameters, as well as an appropriate building albedo setting, greatly improves the representation of SAT; and (3) the refinement of areal mean SST and the urban data have the same degree of importance for a better representation of the SAT.

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Sensitivity of the WRF Regional Meteorological Model to Input Datasets and Surface Parameters for the Kanto Plain on Fine Summer Days

Cited by 8 publications

References 11 publications

Method for Evaluating the Influence of Obstruction of Sea Breeze by Clusters of High-Rise Buildings on the Urban Heat Island Effect

Method for Evaluating the Influence of Obstruction of Sea Breeze by Clusters of High-Rise Buildings on the Urban Heat Island Effect

Analysis of the Strong Local Wind in Northwestern Hokkaido, Japan

Impact of high‐resolution sea surface temperature and urban data on estimations of surface air temperature in a regional climate

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