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Atmosphere 2018, 9(5), 164; https://doi.org/10.3390/atmos9050164

Development of an Urban High-Resolution Air Temperature Forecast System for Local Weather Information Services Based on Statistical Downscaling

1
Research Center for Atmospheric Environment, Hankuk University of Foreign Studies, Yongin-si, Gyeonggi-do 17035, Korea
2
Atmospheric Program, School of Earth and Environmental Sciences, Seoul National University, Seoul 08826, Korea
*
Author to whom correspondence should be addressed.
Received: 30 November 2017 / Revised: 11 February 2018 / Accepted: 12 February 2018 / Published: 26 April 2018
(This article belongs to the Special Issue Atmospheric Effects on Humans—EMS 2017 Session)
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Abstract

The Korean peninsula has complex and diverse weather phenomena, and the Korea Meteorological Administration has been working on various numerical models to produce better forecasting data. The Unified Model Local Data Assimilation and Prediction System is a limited-area working model with a horizontal resolution of 1.5 km for estimating local-scale weather forecasts on the Korean peninsula. However, in order to numerically predict the detailed temperature characteristics of the urban space, in which surface characteristics change rapidly in a small spatial area, a city temperature prediction model with higher resolution spatial decomposition capabilities is required. As an alternative to this, a building-scale temperature model was developed, and a 25 m air temperature resolution was determined for the Seoul area. The spatial information was processed using statistical methods, such as linear regression models and machine learning. By comparing the accuracy of the estimated air temperatures with observational data during the summer, the machine learning was improved. In addition, horizontal and vertical characteristics of the urban space were better represented, and the air temperature was better resolved spatially. Air temperature information can be used to manage the response to heat-waves and tropical nights in administrative districts of urban areas. View Full-Text
Keywords: heat-wave; statistical downscaling; weather information service; building-scale air temperature; heat-exposure map heat-wave; statistical downscaling; weather information service; building-scale air temperature; heat-exposure map
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Yi, C.; Shin, Y.; Roh, J.-W. Development of an Urban High-Resolution Air Temperature Forecast System for Local Weather Information Services Based on Statistical Downscaling. Atmosphere 2018, 9, 164.

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