Development of Road Surface Temperature Prediction Model using the Unified Model output (UM-Road)

Park, Moon Soo; Joo, Seung Jin; Son, Younggon

doi:10.14191/atmos.2014.24.4.471

Cited by 6 publications

(19 citation statements)

References 7 publications

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“…Gyeonggi Bay is in the Yellow Sea in the west of the SMA and has a very irregular coastline. The Yellow Sea is an important moisture source in the case of heavy rainfall, snowfall, or heterogeneous reactions among long-rangetransporting air pollutants (Chung and Kim, 2008;Cayetano et al, 2011;Cha et al, 2011;S.-U. Park et al, 2011S.-U.…”

Section: Seoul Metropolitan Areamentioning

confidence: 99%

“…Quality check algorithms for meteorological variables and flux data have previously been developed (Aubinet et al, 2012;Chae et al, 2014;M.-S. Park et al, , 2014aKim et al, 2015). Basic quality checks for meteorological variables include missing check, physical limit check, climate range check, and spike removal .…”

Section: Urban Meteorological Observation Network System (Ums-seoul) mentioning

confidence: 99%

“…For example, the Road Weather Information System (RWIS) observed the road surface temperature and status, water depth, salinity, and conductivity and net radiation, temperature, humidity, wind speed, and wind direction on an open road in 2013, at the entrance and exit of a tunnel in 2014, and on a complex road structure with a bridge and joint cross section in 2015. These data will be used to verify and improve the road surface temperature, status, and braking distance prediction model (Yang et al, 2011;Park et al, 2014b). A mobile road weather vehicle equipped with a global positioning system and sensors in RWIS is operated to find the road sections vulnerable to road wetness and ice.…”

Section: Urban Meteorological Observation Network System (Ums-seoul) mentioning

confidence: 99%

“…The temperature is corrected according to the sea-level height of the sensor using the monthly mean lapse rate (4.8 K km −1 ) of the free atmosphere observed by a rawindsonde at the Osan Station ( Fig. 3; Park et al, 2014a). At 06:00 and 24:00 LST, the western sites show a relatively high temperature when there is no surface heating, while the eastern sites show a relatively low temperature.…”

Section: Case Study I: Spring Zonal Anticyclone Eventmentioning

confidence: 99%

“…It is well known that the urban surface material and building morphology affect meteorology in various ways including the increase in temperature, leading to the urban heat island effect (Bornstein, 1968;Oke, 1973;Landsberg, 1981;Arnfield, 2003;Kalnay and Cai, 2003;Kim and Baik, 2005;Grimmond, 2006); decrease or increase in the temporal variation of absolute humidity due to impervious surfaces and anthropogenic water use (Unger, 1999;Kuttler et al, 2007); increase in haze, cloud, and precipitation (Bornstein and Lin, 2000;Dixon and Mote, 2003;Shepherd, 2005;Carrio et al, 2010); decrease in visibility due to anthropogenic aerosols (Cheng and Tsai, 2000;Singh et al, 2008;Nichol et al, 2010); increase in the turbulent intensity and change of wind speed due to high-rise buildings (Roth, 2000;Arnfield, 2003;Grimmond et al, 2004;Barlow et al, 2011;Song et al, 2013); decrease in solar radiation due to manmade air pollutants (Peterson et al, 1978;Robaa, 2009); increase in the sensible heat flux and heat storage due to anthropogenic heat release from the urban surface; and decrease in the latent heat flux (Nunez and Oke, 1977;Christen and Vogt, 2004;Harman and Belcher, 2006;Grimmond et al, 2009;Nordbo et al, 2012;Park et al, 2014a). When the synoptic wind becomes strong, the area receiving most of the precipitation with strong upward motion moves more downwind (Bornstein and Lin, 2000;Lin et al, 2011;Han et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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High-resolution urban observation network for user-specific meteorological information service in the Seoul Metropolitan Area, South Korea

Park

Chae

et al. 2017

Atmos. Meas. Tech.

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Abstract. To improve our knowledge of urban meteorology, including those processes applicable to high-resolution meteorological models in the Seoul Metropolitan Area (SMA), the Weather Information Service Engine (WISE) Urban Meteorological Observation System (UMS-Seoul) has been designed and installed. The UMS-Seoul incorporates 14 surface energy balance (EB) systems, 7 surface-based threedimensional (3-D) meteorological observation systems and applied meteorological (AP) observation systems, and the existing surface-based meteorological observation network. The EB system consists of a radiation balance system, sonic anemometers, infrared CO 2 /H 2 O gas analyzers, and many sensors measuring the wind speed and direction, temperature and humidity, precipitation, and air pressure. The EBproduced radiation, meteorological, and turbulence data will be used to quantify the surface EB according to land use and to improve the boundary-layer and surface processes in meteorological models. The 3-D system, composed of a wind lidar, microwave radiometer, aerosol lidar, or ceilometer, produces the cloud height, vertical profiles of backscatter by aerosols, wind speed and direction, temperature, humidity, and liquid water content. It will be used for highresolution reanalysis data based on observations and for the improvement of the boundary-layer, radiation, and microphysics processes in meteorological models. The AP system includes road weather information, mosquito activity, water quality, and agrometeorological observation instruments. The standardized metadata for networks and stations are documented and renewed periodically to provide a detailed observation environment. The UMS-Seoul data are designed to support real-time acquisition and display and automatically quality check within 10 min from observation. After the quality check, data can be distributed to relevant potential users such as researchers and policy makers. Finally, two case studies demonstrate that the observed data have a great potential to help to understand the boundary-layer structures more deeply, improve the performance of high-resolution meteorological models, and provide useful information customized based on the user demands in the SMA.

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Section: Seoul Metropolitan Areamentioning

confidence: 99%

Section: Urban Meteorological Observation Network System (Ums-seoul) mentioning

confidence: 99%

Section: Urban Meteorological Observation Network System (Ums-seoul) mentioning

confidence: 99%

Section: Case Study I: Spring Zonal Anticyclone Eventmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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High-resolution urban observation network for user-specific meteorological information service in the Seoul Metropolitan Area, South Korea

Park

Chae

et al. 2017

Atmos. Meas. Tech.

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System Dynamics Modeling for Estimating the Locations of Road Icing Using GIS

Hong

Lee²,

Kim

et al. 2021

Applied Sciences

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Road icing can cause large traffic accidents on highways because, unlike snowy roads, its location is difficult to identify and it can occur rapidly, even during rainy weather. In this study, the amount and location of road icing were modeled and simulated over time based on the system dynamics theory. The simulation is expressed on the geographic information system (GIS) and facilitates advance detection of the location and amount of road icing that occurs unexpectedly unlike previous studies. Modeling was designed to process spatial and meteorological data after combining them. The spatial data used for modeling were Hillshade, Water System, Bridge, and Road (Highway). Air temperature, cloudiness, vapor pressure, wind speed, and precipitation were used as meteorological data. The amount of road icing was estimated by scientifically designing the parameters related to its occurrence between spatial and meteorological data. Based on this, the amount of road icing by location was simulated per 1m2 using the GIS. The simulation results showed that the amount of road icing that began to increase from AM 08:00 reached its peak (an average of 213.62 g/m2) at noon and then slowly decreased. Additionally, when simulated with GIS, the sum amount of road icing between AM 12:00 and PM 13:00 was a maximum of 1707.292 (g/14 h) and a minimum of 360.082 (g/14 h) for each location. Hypothesis testing was conducted on whether road icing significantly occurs at actual points vulnerable to traffic accidents. Based on the results, the average significance level was calculated to be less than 0.05. Therefore, the alternative hypothesis that the model can estimate road icing in vulnerable areas was adopted. The verified simulation can be useful data to government agencies (e.g., road traffic authority) in their programs to prevent traffic accidents caused by road icing.

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Study on Radiative Flux of Road Resolution during Winter Based on Local Weather and Topography

Kwon

Yang

2022

Remote Sensing

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Large-scale traffic accidents caused by black ice on roads have increased rapidly; hence, there is an urgent need to prepare safety measures for their prevention. Here, we used local weather road observations and the linkage between weather prediction and a radiation flux model (LDAPS-SOLWEIG) to calculate prediction information regarding habitual shade areas, sky view factor (SVF), and downward shortwave radiative flux by road direction and lane. Using the LDAPS-SOLWEIG model system, a set of real-time weather prediction data (temperature, humidity, wind speed, and insolation at 1.5 km resolution) was applied, and 5 m resolution radiative flux prediction data, with road resolution blocked by local weather and topography, were calculated. We found that the habitual shaded area can be divided by the direction and lane of the road according to the height and shape of the terrain around the road. The downward shortwave radiation flux data from local meteorological observation data and that calculated from the LDAPS-SOLWEIG model system were compared. When road-freezing occurred on a case day, the RMSE was 20.41 W·m−2, MB was −5.04 W·m−2, and r was 0.78. The calculated information, habitual shaded area, and SVF can highlight road sections vulnerable to winter freezing and can be helpful in the special management of these areas.

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Development of Road Surface Temperature Prediction Model using the Unified Model output (UM-Road)

Cited by 6 publications

References 7 publications

High-resolution urban observation network for user-specific meteorological information service in the Seoul Metropolitan Area, South Korea

High-resolution urban observation network for user-specific meteorological information service in the Seoul Metropolitan Area, South Korea

System Dynamics Modeling for Estimating the Locations of Road Icing Using GIS

Study on Radiative Flux of Road Resolution during Winter Based on Local Weather and Topography

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