• 한국환경과학회지
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• 제26권12호
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• pp.1307-1319
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• 2017

In this study, we investigated the impact of different initial data on atmospheric modeling results using the Weather Research and Forecast (WRF) model. Four WRF simulations were conducted with different initialization in March 2015, which showed the highest monthly mean $PM_{10}$ concentration in the recent ten years (2006-2015). The results of WRF simulations using NCEP-FNL and ERA-Interim were compared with observed surface temperature and wind speed data, and the difference of grid nudging effect on WRF simulation between the two data were also analyzed. The FNL simulation showed better accuracy in the simulated temperature and wind speed than the Interim simulation, and the difference was clear in the coastal area. The grid nudging effect on the Interim simulation was larger than that of the FNL simulation. Despite of the higher spatial resolution of ERA-Interim data compared to NCEP-FNL data, the Interim simulation showed slightly worse accuracy than those of the FNL simulation. It was due to uncertainties associated with the Sea Surface Temperature (SST) field in the ERA-Interim data. The results from the Interim simulation with different SST data showed significantly improved accuracy than the standard Interim simulation. It means that the SST field in the ERA-Interim data need to be optimized for the better WRF simulation. In conclusion, although the WRF simulation with ERA-Interim data does not show reasonable accuracy compared to those with NCEP-FNL data, it would be able to be Improved by optimizing the SST variable.

• 한국대기환경학회지
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• 제28권1호
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• pp.1-11
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• 2012

A case study was conducted for a severe wintertime dust event that occurred on December 29, 2007 in Korea. Three different dust emission schemes, namely, those of Marticorena and Bergametti (1995), Lu and Shao (1999), and Shao (2004) (hereinafter, referred to MB, LS, and S04 schemes, respectively) were implemented in Weather Research Forecast with Chemistry (WRF/Chem) to assess their performance in simulating wintertime Asian dust events. WRF/Chem simulation reproduces dust emission over Mongolia on December 27 and 28, 2007 and the onset timing of the dust event in Korea well. There is, however, a huge difference among the estimated dust emission amounts for the three schemes; the dust concentration derived by MB scheme is 6 times larger than that from LS scheme. The three schemes overestimate dust concentrations when comparing to observed surface-level $PM_{10}$ mass concentrations in Ganghwa, Seoul, and Yeongwol. This discrepancy is thought to be mainly due to the overestimated model winds and the surface condition such as snow cover fraction, which did not adequately represent the real conditions. Considering frozen soil effect on dust emission, the model results are comparable with observation data: it is important to consider frozen soil in simulating wintertime dust events.

• 한국환경과학회지
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• 제23권6호
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• pp.1121-1130
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• 2014

This study aims to find the perception and utilization of the citizen about the dryness watch warning (DWW) among special weather reports. For this we have made up a descriptive questionnaire including the perception, utilization of special weather reports. Using the SPSS 17.0 program, descriptive statistics, t-test, ANOVA and Scheffe test were used to analyze the collected data. The results are as follows; The perception of DWW is measured by 4 point Likert scale and the average is $15.97{\pm}3.70$ (percentile=57.0). This value shows that the awareness level is not that high and according to the occupation, college students show the lowest awareness and housewives show the highest awareness. According to the age, the teens and twenties show the lowest awareness and fifties and sixties show the highest awareness. Although the perception of the teens and college students are rather poor, there were many positive answers that it is necessary to establish the advanced disaster prevention plan according to the questionnaire about the utilization of DWW. Therefore, if we come up with an effective plan to improve the perception than we can expect a large-effect in terms of fire and forest fire prevention. The perception of DWW can be improved by providing weather information and weather related education program on TV or internet which have the high level of preference. Also, it is necessary to provide online and offline program of advertising education and disaster management education through the weather forecast bureau which is the host organization of delivering weather information.

• 대한지리학회지
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• 제28권2호
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• pp.112-122
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• 1993

장마는 일반적으로 6월 21-26일에 시작되는데 1961년부터 1990년까지의 일강수자료와 동부아시아의 일기도를 분석하여 장마와 늦장마 시작일의 분포를 보면 El Ni${\~{n}}$o해에는 늦어지고 La Nina현상이 나타나는 해에는 일찍 시작되는 경향이 있어서, 장마 및 늦장마 시작일과 태평양의 해수면은 도(SST) 및 북반구 500mb 고도값과의 관계를 분석하여 장마와 늦장마의 시작시기를 예측할 수 있는 모델을 구축하고자 하였다. 장마 시작일은 중태평양의 5월 평균 SST, 북부 허스슨만의 3월 평균 500mb 고도값과 유의한 상관관계를 보인다. 8월 18일경에 중서부 지방에서부터 시작되는 늦장마의 시작일은 호주 서안에 면한 인도양의 5월 평균 SST, 그리고 적도 남부 중태평양의 5월 평균 SST, 시베리아 북서부의 7월 평균 500MB 고도값과 유의한 상관관계를 나타내므로 polynomial regression을 사용하여 장마와 늦장마 시작일의 최적 예측모델을 구축하였다. 이 모델은 장마 시작일의 경우 비교적 정확하게 예측 할 수 있으나 (residual=${\pm}$5.0) 늦장마의 경우에는 평균오차가 3.3일이고 최대오차가 10일에 달하므로 보다 정확한 예측모델을 구축하기 위한 지속적인 연구가 필요하다.

• 에너지공학
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• 제27권4호
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• pp.103-110
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• 2018

본 논문에서는 Mean Absolute Percentage Error (이하 MAPE)와 Symmetric Mean Absolute Percentage (이하 sMAPE)의 새로운 접근법을 이용한 시계열 예측 모델의 평가 방법을 소개한다. MAPE, sMAPE에는 다음과 같은 문제점이 있다. 데이터 집합에서 관측 값이 0일 경우 평가할 수 없고, 관측 값이 0에 매우 가깝다면 과도한 평가 값을 측정한다. 관측 값과 예측 값 간에 동일한 오차를 가지더라도 다른 값으로 평가하는 문제도 가지고 있다. 동일한 오류 값이 과대 예측되었는지 아니면 과소 예측되었는지에 따라 다른 평가 값을 측정하거나 관측 값의 부호와 예측 값의 부호가 서로 다르면 그 오차는 평가 값에 반영되지 않는다. 이러한 문제는 Maximum Mean Absolute Percentage Error (이하 mMAPE)에 의해 해결하였다. 우리는 MAPE 평가 방법의 분모에서 관측 값을 사용하는 대신 최대 절대 값을 사용했다. 최대 절대 값이 1보다 작으면 분모를 제거하여 0 값이 정의되지 않은 문제와 미세한 값일 경우 과대 측정되는 문제를 해결하였다. Beijing PM2.5의 온도 데이터와 시뮬레이션 데이터를 통해 mMAPE와 다른 평가 방법들의 결과 값을 비교하였으며, 위의 문제들을 해결할 수 있음을 검증하였다.