2013년 태풍에 대한 수치모델들의 강도 예측성 평가

김지선(Ji-Seon Kim),이우정(Woojeong Lee),강기룡(KiRyong Kang),변건영(Kun-Young Byun),김지영(Jiyoung Kim),윤원태(Won-Tae Yun) 한국기상학회 2014 대기 Vol.24 No.3

An assessment of typhoon intensity predictability of numerical models was conducted to develop the typhoon intensity forecast guidance comparing with the RSMC-Tokyo best track data. Root mean square error, box plot analysis and time series of wind speed comparison were performed to evaluate the each model error level. One of noticeable fact is that all models have a trend of error increase as typhoon becomes stronger and the Global Forecast System showed the best performance among the models. In the detailed analysis in two typhoon cases [Danas (1324) and Haiyan (1330)], GFS showed good performance in maximum ind speed and intensity trend in the best track, however it could not simulate well the rapid intensity increasing period. On the other hand, ECMWF and Hurricane-WRF overestimated the typhoon intensity but simulated track trend well.

이동속도와 방향을 고려한 수치모델의 태풍진로 예측성 평가

신현진(Hyeonjin Shin),이우정(WooJeong Lee),강기룡(KiRyong Kang),변건영(Kun-Young Byun),윤원태(Won-Tae Yun) 한국기상학회 2014 대기 Vol.24 No.4

Evaluation of predictability of numerical models for tropical cyclone track was performed using along-and cross-track component. The along-and cross-track bias were useful indicators that show the numerical models predictability associated with cause of errors. Since forecast errors, standard deviation and consistency index of along-track component were greater than those of cross-track component, there was some rooms for improvement in along-track component. There was an overall slow bias. The most accurate model was JGSM for 24-hour forecast and ECMWF for 48~96-hour forecast in direct position error, along-track error and cross-track error. ECMWF and GFS had a high variability for 24-hour forecast. The results of predictability by track type showed that most significant errors of tropical cyclone track forecast were caused by the failure to estimate the recurvature phenomenon.

태풍 진로예측을 위한 다중모델 선택 컨센서스 기법 개발

전상희(Sanghee Jun),이우정(Woojeong Lee),강기룡(KiRyong Kang),윤원태(Won-Tae Yun) 한국기상학회 2015 대기 Vol.25 No.2

A Selected Multi-model CONsensus (SMCON) technique was developed and verified for the tropical cyclone track forecast in the western North Pacific. The SMCON forecasts were produced by averaging numerical model forecasts showing low 70% latest 6 h prediction errors among 21 models. In the homogeneous comparison for 54 tropical cyclones in 2013 and 2014, the SMCON improvement rate was higher than the other forecasts such as the Non-Selected Multi-model CONsensus (NSMCON) and other numerical models (i.e., GDAPS, GEPS, GFS, HWRF, ECMWF, ECMWF_H, ECMWF_EPS, JGSM, TEPS). However, the SMCON showed lower or similar improvement rate than a few forecasts including ECMWF_EPS forecasts at 96 h in 2013 and at 72 h in 2014 and the TEPS forecast at 120 h in 2013. Mean track errors of the SMCON for two year were smaller than the NSMCON and these differences were 0.4, 1.2, 5.9, 12.9, 8.2 km at 24-, 48-, 72-, 96-, 120-h respectively. The SMCON error distributions showed smaller central tendency than the NSMCON’s except 72-, 96-h forecasts in 2013. Similarly, the density for smaller track errors of the SMCON was higher than the NSMCON’s except at 72-, 96-h forecast in 2013 in the kernel density estimation analysis. In addition, the NSMCON has lager range of errors above the third quantile and larger standard deviation than the SMCON’s at 72-, 96-h forecasts in 2013. Also, the SMCON showed smaller bias than ECMWF_H for the cross track bias. Thus, we concluded that the SMCON could provide more reliable information on the tropical cyclone track forecast by reflecting the real-time performance of the numerical models.

북서태평양 태풍 강도 예측 컨센서스 기법

오유정(Youjung Oh),문일주(Il-Ju Moon),이우정(Woojeong Lee) 한국기상학회 2018 대기 Vol.28 No.3

In this study, a new consensus technique for predicting tropical cyclone (TC) intensity in the western North Pacific was developed. The most important feature of the present consensus model is to select and combine the guidance numerical models with the best performance in the previous years based on various evaluation criteria and averaging methods. Specifically, the performance of the guidance models was evaluated using both the mean absolute error and the correlation coefficient for each forecast lead time, and the number of the numerical models used for the consensus model was not fixed. In averaging multiple models, both simple and weighted methods are used. These approaches are important because that the performance of the available guidance models differs according to forecast lead time and is changing every year. In particular, this study develops both a multi-consensus model (M-CON), which constructs the best consensus models with the lowest error for each forecast lead time, and a single best consensus model (S-CON) having the lowest 72-hour cumulative mean error, through on training process. The evaluation results of the selected consensus models for the training and forecast periods reveal that the M-CON and S-CON outperform the individual best-performance guidance models. In particular, the M-CON showed the best overall performance, having advantages in the early stages of prediction. This study finally suggests that forecaster needs to use the latest evaluation results of the guidance models every year rather than rely on the well-known accuracy of models for a long time to reduce prediction error.

Compact Optical Autocorrelator with 0.1-Meter Scanning Range Using a Rotating Pair of Mirrors

장재형(Jaehyung Jang),이승후(Seunghoo Lee),이우정(Woojeong Lee),임현우(Hyeonwoo Lim),이주형(Joohyung Lee) Korean Society for Precision Engineering 2021 한국정밀공학회지 Vol.38 No.5

We present a rotating pair of mirrors based optical autocorrelator which is capable of providing a 0.1 m scanning range. The rotating mirror-pair technique enables rapid data update-rate, compactness, and simpler data post-processing compared to that of conventional linear motion-based optical autocorrelators. We optimized the geometrical design of the mirror-pair configuration by using off-the-shelf mirrors and conducted a simulation to calculate the expected capability of the scanning range. By exploiting a He-Ne laser as a light source, we validated the performance of the autocorrelator in its provision of a 100 mm scanning range and 0.2 Hz data update-rate, which was limited by the adopted commercial data sampling device, and not limited by the proposed principle. The developed autocorrelator is expected to be adopted for various applications that require sub-cm<SUP>-1</SUP> spectroscopic resolution.

북서태평양 태풍 강도 가이던스 모델 성능평가

오유정(You-Jung Oh),문일주(Il-Ju Moon),김성훈(Sung-Hun Kim),이우정(Woojeong Lee),강기룡(KiRyong Kang) 한국기상학회 2016 대기 Vol.26 No.1

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.