Entity

Time filter

Source Type

Yanggu, South Korea

Yeom J.-M.,Korea Aerospace Research Institute | Seo Y.-K.,Korea Aerospace Research Institute | Kim D.-S.,Korea Meteorological Agency | Han K.-S.,Pukyong National University
Journal of Sensors | Year: 2016

This study mapped the solar radiation received by slopes for all of Korea, including areas that are not measured by ground station measurements, through using satellites and topographical data. When estimating insolation with satellite, we used a physical model to measure the amount of hourly based solar surface insolation. Furthermore, we also considered the effects of topography using the Global Land One-Kilometer Base Elevation (GLOBE) digital elevation model (DEM) for the actual amount of incident solar radiation according to solar geometry. The surface insolation mapping, by integrating a physical model with the Communication, Ocean, and Meteorological Satellite (COMS) Meteorological Imager (MI) image, was performed through a comparative analysis with ground-based observation data (pyranometer). Original and topographically corrected solar radiation maps were created and their characteristics analyzed. Both the original and the topographically corrected solar energy resource maps captured the temporal variations in atmospheric conditions, such as the movement of seasonal rain fronts during summer. In contrast, although the original solar radiation map had a low insolation value over mountain areas with a high rate of cloudiness, the topographically corrected solar radiation map provided a better description of the actual surface geometric characteristics. © 2016 Jong-Min Yeom et al. Source


Weissmann M.,German Aerospace Center | Harnisch F.,German Aerospace Center | Wu C.-C.,National Taiwan University | Lin P.-H.,National Taiwan University | And 6 more authors.
Monthly Weather Review | Year: 2011

A unique dataset of targeted dropsonde observations was collected during The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) in the autumn of 2008. The campaign was supplemented by an enhancement of the operational Dropsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) program. For the first time, up to four different aircraft were available for typhoon observations and over 1500 additional soundings were collected. This study investigates the influence of assimilating additional observations during the two major typhoon events of T-PARC on the typhoon track forecast by the global models of the European Centre for Medium-Range Weather Forecasts (ECMWF), the Japan Meteorological Agency (JMA), the National Centers for Environmental Prediction (NCEP), and the limited-area Weather Research and Forecasting (WRF) model. Additionally, the influence of T-PARC observations on ECMWF midlatitude forecasts is investigated. All models show an improving tendency of typhoon track forecasts, but the degree of improvement varied from about 20% to 40% in NCEPandWRFto a comparably low influence inECMWFand JMA. This is likely related to lower track forecast errors without dropsondes in the latter two models, presumably caused by a more extensive use of satellite data and four-dimensional variational data assimilation (4D-Var) of ECMWF and JMA compared to three-dimensional variational data assimilation (3D-Var) of NCEP and WRF. The different behavior of the models emphasizes that the benefit gained strongly depends on the quality of the first-guess field and the assimilation system. © 2011 American Meteorological Society. Source


Yang H.-W.,Seoul National University | Cho Y.-K.,Seoul National University | Seo G.-H.,Seoul National University | You S.H.,Korea Meteorological Agency | Seo J.-W.,Korea Meteorological Agency
Journal of Marine Systems | Year: 2014

The Yellow Sea Bottom Cold Water (YSBCW) occupies a wide region below the Yellow Sea (YS) thermocline in summer. The southern limit of the YSBCW shows pronounced interannual variability. A regional ocean model with realistic forcing was used to identify the structure of the YSBCW and to investigate the causes of its interannual variability from 1981 to 2010. Sea surface temperature (SST) in winter is strongly correlated with the southern limit of the YSBCW in summer. The correlation coefficient between the August southern limit and the February SST is - 0.884. This result suggests that cold SST is associated with the increased southern limit in the following summer. Linear regression suggests that the southern limit increases by about 55. km when the SST in February decreases by 1. °C. The southern limits are more extended to the south in August than in June in some years despite surface heating. The difference in southern limits between June and August is positively correlated with the summer southerly wind stress with a correlation coefficient of 0.529. The contribution of SST in winter on the southern limit of the YSBCW in summer is larger than the wind stress in summer. The SST in winter is mainly determined by the air temperature and wind speed in winter. The other factor affecting winter SST is the previous year's bottom water temperature. The winter SST is significantly correlated with the bottom water temperature in previous year. The southern limit of the YSBCW in the observed data in the limited area has relatively weak correlation with the winter SST and summer southerly wind stress possibly due to observation error and uncertainty of the reanalysis wind. © 2014 Elsevier B.V. Source


Kwak M.-T.,Seoul National University | Seo G.-H.,Seoul National University | Cho Y.-K.,Seoul National University | Kim B.-G.,Seoul National University | And 2 more authors.
Ocean Science Journal | Year: 2015

Satellite remotely sensed sea surface temperature (SST) was compared with in-situ SST in the seas around the Korean Peninsula from 1984 to 2013. A matchup dataset between satellite and in-situ SSTs was used. The root mean square error (RMSE) between satellite and in-situ SSTs was approximately 1°C in the offshore area and 2~3°C in the coastal area. The satellite SST exhibits a cold bias of 1°C or less in the offshore area and a warm bias of 1~3°C in the coastal area. The satellite SSTs generally agree with the in-situ data in the East/Japan Sea (EJS) better than in the South Sea and the Yellow Sea (YS). The RMSE between the two SSTs in the South Sea (SS) is 1~2°C. In-situ and satellite SST analyses respectively indicate a warming trend of 0.024°C/year and 0.011°C/year for the study period in the seas around the Korean Peninsula. The difference in the long-term trends from the two data sources is mainly due to the difference in the YS. The satellite SST showed a warm bias of 0.5~1.0°C in the early 1980’s and a cold bias of 0.5°C in the early 2010’s, which should be carefully considered in studying long-term trends with satellite SST data. © 2015, Korea Ocean Research & Development Institute (KORDI) and the Korean Society of Oceanography (KSO) and Springer Science+Business Media Dordrecht. Source

Discover hidden collaborations