• Atmosphere
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• v.34 no.2
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• pp.83-95
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• 2024

Atmospheric rivers (ARs) are closely related to local precipitation which can be both beneficial and destructive. Although several studies have evaluated their predictability, there is a lack of studies on East Asian ARs. This study evaluates the prediction skill of East Asian ARs in the Korean Integrated Model (KIM) for 2020~2022 summer. The spatial distribution of AR frequency in KIM is qualitatively similar to the observation but overestimated. In particular, the model errors greatly increase along the boundary of the western North Pacific subtropical high as the forecast lead time increases. When the prediction skills are quantitatively verified by computing the Anomaly Correlation Coefficient and Mean Square Skill Score, the useful prediction skill of daily AR around the Korean Peninsula is found up to 5 days. Such prediction limit is primarily set by the wind field errors with a minor contribution of moisture distribution errors. This result suggests that the improved prediction of atmospheric circulation field can improve the prediction of East Asian summer ARs and the associated precipitation.

• Journal of the Korean earth science society
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• v.36 no.2
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• pp.158-170
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• 2015

This study evaluates the wind speed forecast near the surface layer using the Weather Research Forecasting with Large Eddy Simulation (WRF-LES) model in order to compare the planetary boundary layer (PBL) parameterization with the LES model in terms of different spatial resolution. A numerical simulation is conducted with 1-km and 333-m horizontal resolution over the Gangwon Province including complex mountains and coastal region. The numerical experiments with 1-km and 333-m horizontal resolution employ PBL parameterization and LES, respectively. The wind speed forecast in mountainous region shows a better forecast performance in 333-m experiment than in 1-km, while wind speed in coastal region is similar to the observation in 1-km spatial resolution experiment. Therefore, LES experiment, which directly simulates the turbulence process near the surface layer, contributes to more accurate forecast of surface wind speed in mountainous regions.

• Atmosphere
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• v.26 no.1
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• pp.1-18
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• 2016

Eleven Tropical Cyclone (TC) intensity guidance models in the western North Pacific have been validated over 2008~2014 based on various analysis methods according to the lead time of forecast, year, month, intensity, rapid intensity change, track, and geographical area with an additional focus on TCs that influenced the Korean peninsula. From the evaluation using mean absolute error and correlation coefficients for maximum wind speed forecasts up to 72 h, we found that the Hurricane Weather Research and Forecasting model (HWRF) outperforms all others overall although the Global Forecast System (GFS), the Typhoon Ensemble Prediction System of Japan Meteorological Agency (TEPS), and the Korean version of Weather and Weather Research and Forecasting model (KWRF) also shows a good performance in some lead times of forecast. In particular, HWRF shows the highest performance in predicting the intensity of strong TCs above Category 3, which may be attributed to its highest spatial resolution (~3 km). The Navy Operational Global Prediction Model (NOGAPS) and GFS were the most improved model during 2008~2014. For initial intensity error, two Japanese models, Japan Meteorological Agency Global Spectral Model (JGSM) and TEPS, had the smallest error. In track forecast, the European Centre for Medium-Range Weather Forecasts (ECMWF) and recent GFS model outperformed others. The present results has significant implications for providing basic information for operational forecasters as well as developing ensemble or consensus prediction systems.

• Atmosphere
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• v.32 no.2
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• pp.149-162
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• 2022

This study investigated the prediction skill of the Asian dust seasonal forecasting model (GloSea5-ADAM) on the Asian dust and meteorological variables related to the dust generation for the period of 1991~2016. Additionally, we evaluated the prediction skill of those variables depending on the combination of the initial dates in the sub-seasonal scale for the dust source region affecting South Korea. The Asian dust and meteorological variables (10 m wind speed, 1.5 m relative humidity, and 1.5 m air temperature) from GloSea5-ADAM were compared to that from Synoptic observation and European Centre for medium range weather forecasts reanalysis v5, respectively, based on Mean Bias Error (MBE), Root Mean Square Error (RMSE), and Anomaly Correlation Coefficient (ACC) as evaluation criteria. In general, the Asian dust and meteorological variables in the source region showed high ACC in the prediction scale within one month. For all variables, the use of the initial dates closest to the prediction month led to the best performances based on MBE, RMSE, and ACC, and the performances could be improved by adjusting the number of ensembles considering the combination of the initial date. ACC was as high as 0.4 in Spring when using the closest two initial dates. In particular, the GloSea5-ADAM shows the best performance of Asian dust generation with an ACC of 0.60 in the occurrence frequency of Asian dust in March when using the closest initial dates for initial conditions.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2004.11a
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• pp.193-194
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• 2004

• Journal of the Korean earth science society
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• v.43 no.3
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• pp.367-385
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• 2022

This study evaluates the temperature and precipitation results in East Asia simulated from the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) developed by the UK Met Office. The HadGEM3-RA is conducted in the Coordinated Regional climate Downscaling Experiment-East Asia (CORDEX-EA) Phase II domain for 15 year (2000-2014). The spatial distribution of rainbands produced from the HadGEM3-RA by the summer monsoon is in good agreement with the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of water resources (APRODITE) data over the East Asia. But, precipitation amount is overestimated in Southeast Asia and underestimated over the Korean Peninsula. In particular, the simulated summer rainfall and APRODITE data show the least correlation coefficient and the maximum value of root mean square error in South Korea. Prediction of temperature in Southeast Asia shows underestimation with a maximum error during winter season, while it appears the largest underestimation in South Korea during spring season. In order to evaluate local predictability, the time series of temperature and precipitation compared to the ASOS data of the Seoul Meteorological Station is similar to the spatial average verification results in which the summer precipitation and winter temperature underestimate. Especially, the underestimation of the rainfall increases when the amounts of precipitation increase in summer. The winter temperature tends to underestimate at low temperature, while it overestimates at high temperature. The results of the extreme climate index comparison show that heat wave is overestimated and heavy rainfall is underestimated. The HadGEM3-RA simulated with a horizontal resolution of 25 km shows limitations in the prediction of mesoscale convective system and topographic precipitation. This study indicates that improvement of initial data, horizontal resolution, and physical process are necessary to improve predictability of regional climate model.

• Atmosphere
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• v.31 no.1
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• pp.85-100
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• 2021

The necessity of accurate high-resolution meteorological forecasts becomes increasing in socio-economical applications and disaster risk management. The Korea Meteorological Administration Post-Processing (KMAPP) system has been operated to provide high-resolution meteorological forecasts of 100 m over the South Korea region. This study evaluates and improves the KMAPP performance in simulating wind speeds over complex terrain areas using the ICE-POP 2018 field campaign measurements. The mountainous measurements give a unique opportunity to evaluate the operational wind speed forecasts over the complex terrain area. The one-month wintertime forecasts revealed that the operational Local Data Assimilation and Prediction System (LDAPS) has systematic errors over the complex mountainous area, especially in deep valley areas, due to the orographic smoothing effect. The KMAPP reproduced the orographic height variation over the complex terrain area but failed to reduce the wind speed forecast errors of the LDAPS model. It even showed unreasonable values (~0.1 m s-1) for deep valley sites due to topographic overcorrection. The model's static parameters have been revised and applied to the KMAPP-Wind system, developed newly in this study, to represent the local topographic characteristics better over the region. Besides, sensitivity tests were conducted to investigate the effects of the model's physical correction methods. The KMAPP-Wind system showed better performance in predicting near-surface wind speed during the ICE-POP period than the original KMAPP version, reducing the forecast error by 21.2%. It suggests that a realistic representation of the topographic parameters is a prerequisite for the physical downscaling of near-ground wind speed over complex terrain areas.

• Atmosphere
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• v.27 no.2
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• pp.133-150
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• 2017

This study evaluates CMIP5 model performance on rainy season evolution in the East Asian summer monsoon. Historical (1986~2005) simulation is analyzed using ensemble mean of CMIP5 19 models. Simulated rainfall amount is underestimated than the observed and onset and termination of rainy season are earlier in the simulation. Compared with evolution timing, duration of the rainy season is uncertain with large model spread. This area-averaged analysis results mix relative differences among the models. All model show similarity in the underestimated rainfall, but there are quite large difference in dynamic and thermodynamic processes. The model difference is shown in horizontal distribution analysis. BEST and WORST group is selected based on skill score. BEST shows better performance in northward movement of the rain band, summer monsoon domain. Especially, meridional gradient of equivalent potential temperature and low-level circulation for evolving frontal system is quite well captured in BEST. According to RCP8.5, CMIP5 projects earlier onset, delayed termination and longer duration of the rainy season with increasing rainfall amount at the end of 21st century. BEST and WORST shows similar projection for the rainy season evolution timing, meanwhile there are large discrepancy in thermodynamic structure. BEST and WORST in future projection are different in moisture flux, vertical structure of equivalent potential temperature and the subsequent unstable changes in the conditional instability.

• Journal of the Korean Solar Energy Society
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• v.39 no.3
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• pp.81-89
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• 2019

Long-term solar irradiance data are required for reliable performance evaluation and feasibility analysis of solar photovoltaic systems. However, measurement data of the global horizontal irradiance (GHI) are only available for major cities in Korea. Neither the direct normal irradiance (DNI) nor the diffuse horizontal irradiance (DHI) are available, which are also needed to calculate the irradiance on the tilted surface of PV array. It is a simple approach to take advantage of the decomposition model that extracts DNI and DHI from GHI. In this study, we investigate variations of solar PV power estimation due to the choice of decomposition model. The GHI data from Korea Meteorological Administration (KMA) were used and different sets of typical meteorological year (TMY) data using some well-known decomposition models were generated. Then, power outputs with the different TMY data were calculated, and a variation of 3.7% was estimated due to the choice of decomposition model.

• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.9-17
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• 2013

Hourly horizontal global solar radiation has been used as one of significant parameters in a weather file for building energy simulations, which determines the quality of building thermal performance. However, as about twenty two weather stations in Korea have actually measured the horizontal global sola radiation, the weather files collected in other stations requires solar data simulation from the other meteorological parameters. Thus, finding the reliable complicated method that can be used in various weather conditions in Korea is critically important. In this paper, three solar simulation models were selected and evaluated through the reliability test with the simulated hourly horizontal global solar radiation against the actually measured solar data to find the most suitable model for the south east area of Korea. Three selected simulation models were CRM, ZHM, and MRM. The first two models are regression type models using site-fitted coefficients which are derived from the correlation between measured solar data and local meteorological parameters from the previous years, and the last model is a mechanistic type model using the meteorological data to calculate conditions of atmospheric constituents that cause absorption and scattering of the extraterrestrial radiation on the way to the surface on the Earth. The evaluation results show that ZHM is the most reliable model in this area, yet a complicated hybrid simulation methods applying the advantages of each simulation method with the monthly-based weather data is needed.