Comparative analysis of environmental standards to install a rooftop temperature monitoring station.

Urban climate influences economic activities and the health and safety of urban residents. Therefore, monitoring temperature in urban areas is important. However, owing to the lack of space for an appropriate observation site, an automatic weather station (AWS) was installed on a building rooftop. The rooftop installation can indicate temperature differences depending on the intensity of strong solar radiation and radiant heat of the building, and wind speed. Therefore, in this study, we aimed to provide observation standards for measuring rooftop temperature according to the optimal rooftop material and observation height. Specifically, an AWS was installed on the rooftop of the Gochang Standard Weather Station (GSWO), Jeollabuk-do Province, to observe the urban climate in South Korea and establish suitable weather standards. Different temperatures, optimum surface materials, and optimum heights for measuring the temperature at the rooftop of GSWO were investigated and compared over 1 year. The temperature recorded after installing a palm mat on the rooftop was more similar to that observed in the grassland. Furthermore, the installation height of the temperature sensor of 2.5-3.0 m for the palm mat and 3.5-4.0 m for concrete was found to be the optimal height for observing temperature at the rooftop.

Offshore wind resource assessment off the coast of Daejeong, Jeju Island using 30-year wind estimates.

Long-term offshore wind resource assessment was performed for the offshore site off the Daejeong coast on Jeju Island of South Korea. A jacket type offshore met mast was installed at the site to measure wind and meteorological conditions for 1 year from 1 July 2015 to 30 June 2016. The wind conditions were measured at 32.5 m, 72.5 m and 100.5 m above mean sea level (AMSL). Fundamental wind characteristics such as average wind speed, wind direction frequency, turbulence intensity and so on were analyzed utilizing 1-year wind measurements. In order to correct the limited period of 1-year measurements to long-term conditions, the Measure-Correlate-Predict (MCP) method was applied to estimate 30-year wind conditions using nearby Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) reanalysis data. Also, wind turbine classes suitable for the offshore site were determined based on extreme wind speed estimations and the measured ambient turbulence intensity. Five commercial wind turbines were chosen for estimation of the 30-year annual energy productions (AEPs) and capacity factors (CFs). As a result, it was estimated that the 30-year average wind speed was 7.86 m/s at 100.5 m AMSL. The wind turbine class II rating was estimated to be suitable for enduring extreme wind speed for a return period of 50 years. For the 30-year results, the minimum CF of 30.48% was estimated, while the maximum nearly reached 45%.