가뭄재해는 다른 재해와 다르게 광범위한 공간에 걸쳐서 충분한 강우가 발생하기 전까지 오랜 기간 동안 발생되는 특성이 있다. 위성 영상은 시공간적으로 지속적인 강수량 관측을 제공할 수 있다. 본 연구는 위성 영상 기반의 강수자료를 활용하여 기상학적 가뭄 전망 모형을 개발하였다. PERSIANN_CDR, TRMM 3B42와 GPM IMERG 영상을 활용하여 강수 자료를 구축한 뒤, 표준강수지수(SPI)를 기반으로 기상학적 가뭄을 정의 하였다. 과거의 가뭄 정보와 물리적 예측 모형 기반의 가뭄 예측 결과를 결합할 수 있는 베이지안 네트워크 기반 가뭄 예측 기법을 이용하여 확률론적 가뭄 예측 결과를 생산하였으며, 가뭄 예측결과를 가뭄 전망 의사결정 모형에 적용하여 가뭄 전망 결과를 도출하였다. 가뭄 전망 정보는 가뭄 발생, 지속, 종결, 가뭄 없음의 4단계로 구분하였다. 본 연구의 가뭄 전망 결과는 ROC 분석을 통하여 물리적 예측 모형인 다중모형 앙상블(MME)을 활용한 가뭄 전망 결과와 전망 성능을 비교하였다. 그 결과, 2∼3개월 가뭄 전망에 대한 가뭄 발생 및 지속의 단계에서는 MME 모형보다 높은 전망 성능을 보여주었다.

Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.

Agricultural meteorological information is an important resource that affects farmersʼ income, food security, and agricultural conditions. Thus, such data are used in various fields that are responsible for planning, enforcing, and evaluating agricultural policies. The meteorological information obtained from automatic weather observation systems operated by rural development agencies contains missing values owing to temporary mechanical or communication deficiencies. It is known that missing values lead to reduction in the reliability and validity of the model. In this study, the hierarchical Bayesian spatio–temporal model suggests replacements for missing values because the meteorological information includes spatio–temporal correlation. The prior distribution is very important in the Bayesian approach. However, we found a problem where the spatial decay parameter was not converged through the trace plot. A suitable spatial decay parameter, estimated on the bias of root–mean–square error (RMSE), which was determined to be the difference between the predicted and observed values. The latitude, longitude, and altitude were considered as covariates. The estimated spatial decay parameters were 0.041 and 0.039, for the spatio-temporal model with latitude and longitude and for latitude, longitude, and altitude, respectively. The posterior distributions were stable after the spatial decay parameter was fixed. root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and bias were calculated for model validation. Finally, the missing values were generated using the independent Gaussian process model.

가뭄은 여러 가지 요인에 의해 복합적으로 발생하는 현상으로 자연적 원인과 인위적 원인으로 구분할 수 있다. 우리나라는 기후학적 특성상 여름철에 태평양 고기압의 발달 시기가 빠르거나 평년보다 강하면 장마 기간이 짧아져 자연적인 원인에 의해 가뭄이 발생한다. 가뭄은 발생과정과 피해 영향에 따라 기상학적, 농업적, 수문학적, 사회경제적 가뭄으로 구분할 수 있으며 직 ․ 간접적으로 다른 가뭄에 영향을 미친다. 가뭄의 종류가 기상학적 가뭄에서 농업적 가뭄 혹은 기상학적 가뭄에서 수문학적 가뭄으로 변화되는 현상을 가뭄 전이라 한다. 본 연구에서는 국내의 가뭄 전이 발생여부와 발생 패턴을 검토하기 위해 수문기상 정보를 이용하여 기상학적 가뭄에서 농업적 가뭄으로의 전이 관계를 분석하였다. 가뭄 전이 발생 현황 및 특성 분석을 위해 가뭄 발생의 유형을 5가지로 구분하였으며, 유형에 따라 가뭄 전이가 발생하지 않거나 최대 3개월까지 지체되는 것을 확인하였다. 향후 더 많은 가뭄 지표들과의 분석을 통해 가뭄 전이 관계를 일반화한다면 기상학적 가뭄 발생 시 농업적 가뭄 예측을 위한 인자로 활용할 수 있을 것으로 기대된다.

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 PM10 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.

Background : Recent climate change has also affected the biological season for plants. There are various studies on this, but most of them are studying horticultural crops. The purpose of this study was to investigate the timing of flowering in different regions and to predict the flowering time of Schisandra chinensis (Turcz.) Baillon. using meteorological data. Methods and Results : The flowering time and cultivation area of Schisandra chinensis were searched and surveyed by the Internet data and Annual research report of the RDA. Accumulated temperature and Growing degree day at 0℃, 5℃, 10℃ or more and Cumulative hours of sunshine at 0℃ or more to the cultivation area and flowering period of irradiated Schisandra chinensis were calculated from meteorological data of KMA (Korea. Meteorological Administration) and calculated using Excel, respectively. statistical analysis was performed using Excel. The data collected were 15 research reports and 20 internet surveys, but it was difficult to use statistical significance due to the high coefficient of variation. The 5-year Suwon data and the 3-year data of Jinan were used in the study report data relatively close to the meteorological stations. Conclusion : Results of statistical analysis. The flowering time of Schisandra chinensis is the time when Accumulated temperature of 0℃ or more [Σ (daily average temperature > 0℃)] becomes 650℃ and the Growing degree day of 0℃ or more { Σ [ (day maximum temperature + day minimum temperature) / 2 > 0℃ ] } was 670℃. The coefficient of variation was 6.5% and 6.2%, respectively.

최근 국지성 집중호우 및 돌발홍수와 같은 급격한 기상변화로 인한 기상재해의 발생빈도가 증가함에 따라 고해상도의 기상레이더 강우자료를 사 용한 수공학 분야의 연구가 활발하게 진행되고 있다. 기상레이더는 넓은 지역에 걸쳐 실시간으로 강우현상 감시가 가능하며 지상우량계로는 파악 이 불가능한 미계측유역을 통과하는 강우장의 이동 및 변동성 파악이 가능한 장점이 있지만 대기 중 존재하는 수상체로부터 반사되는 반사도를 사 용하여 강우량을 산정하므로 시공간적 오차가 존재한다. 본 연구에서는 이러한 문제점을 해결하기 위하여 다변량 Copula 함수를 활용하여 레이더 강우에 존재하는 시공간적 오차를 규명하고 레이더 강우앙상블 생산기법을 개발하였다. 개발된 모형으로부터 생산된 레이더 강우앙상블은 통계적 효율기준 분석결과 우수한 모형성능을 확인하였으며 추가적으로 극치호우 및 강우시계열 패턴 분석결과 지상강우의 특성을 효과적으로 재현하는 것을 확인하였다.

최근 기후변화로 인하여 발생하는 기상재해 및 위험기상 현상의 대비를 위하여 조밀한 시공간적 해상도를 갖는 레이더 강우가 활용되고 있지만 널리 사용되는 Marshall-Palmer의 Z-R 관계식으로 추정된 레이더 강우는 과소추정의 문제점이 있다. 본 연구는 이러한 문제점을 해결하기 위하여 분위회귀 분석기법을 통한 레이더 강우자료 편의보정 기법과 Copula 함수를 연계한 강우자료 확충기법을 개발하였다. 본 연구에서 개발된 모형을 통하여 편의가 보정된 시계열 레이더 강우자료 효율을 통계적으로 분석한 결과 우수한 모형성능을 확인하였으며 Copula 기법을 이용하여 지상강 우 및 레이더 강우자료를 확충한 결과 기존의 강우특성을 현실적으로 재현하는 것을 확인하였다. Copula 기법을 통한 강우자료 확충기법은 레이 더 강우의 오차분포를 평가하는데 유용하게 활용될 것으로 판단된다.

The correlation between meteorological data collected at the optical wide-field patrol network (OWL-Net) Station No. 1 and the seeing of satellite optical observation data was analyzed. Meteorological data and satellite optical observation data from June 2014 to November 2015 were analyzed. The analyzed meteorological data were the outdoor air temperature, relative humidity, wind speed, and cloud index data, and the analyzed satellite optical observation data were the seeing full-width at half-maximum (FWHM) data. The annual meteorological pattern for Mongolia was analyzed by collecting meteorological data over four seasons, with data collection beginning after the installation and initial set-up of the OWL-Net Station No. 1 in Mongolia. A comparison of the meteorological data and the seeing of the satellite optical observation data showed that the seeing degrades as the wind strength increases and as the cloud cover decreases. This finding is explained by the bias effect, which is caused by the fact that the number of images taken on the less cloudy days was relatively small. The seeing FWHM showed no clear correlation with either temperature or relative humidity.

We investigate the amount of potential electricity energy generated by wind power in Busan metropolitan area, using the mesoscale meteorological model WRF (Weather Research & Forecasting), combined with small wind power generators. The WRF modeling has successfully simulated meteorological characteristics over the urban areas, and showed statistical significant to predict the amount of wind energy generation. The highest amount of wind power energy has been predicted at the coastal area, followed by at riverbank and upland, depending on predicted spatial distributions of wind speed. The electricity energy prediction method in this study is expected to be used for plans of wind farm constructions or the power supplies.

To estimate the benefit of high-resolution meteorological data for building energy estimation, a building energy analysis has been conducted over Busan metropolitan areas. The heating and cooling load has been calculated at seven observational sites by using temperature, wind and relative humidity data provided by WRF model combined with the inner building data produced by American Society of Heating Refrigeration and Air-conditioning Engineers (ASHRAE). The building energy shows differences 2-3% in winter and 10-30% in summer depending on locations. This result implicates that high spatiotemporal resolution of meteorological model data is significantly important for building energy analysis.

Recent climate change has led to fluctuations in agricultural production, and as a result national food supply has become an important strategic factor in economic policy. As such, in this study, panel data was collected to analyze the effects of seven meteorological elements and using the Lagrange multipliers method, the fixed-effects model for the production of five types of food crop and the seven meteorological elements were analyzed. Results showed that the key factors effecting increases in production of rice grains were average temperature, average relative humidity and average ground surface temperature, while wheat and barley were found to have positive correlations with average temperature and average humidity. The implications of this study are as follow. First, it was confirmed that the meteorological elements have profound effects on the production of food crops. Second, when compared to existing studies, the study was not limited to one food crop but encompassed all five types, and went beyond other studies that were limited to temperature and rainfall to include various meterological elements.

본 연구의 목적은 기록된 관측가뭄자료를 이용하여 수문기상 기반의 국내 가뭄판단기준을 제시하는데 있다. 과거 1991년에서 2009년까지 기록된 가뭄사례를 수집한 후, 관측기상정보와 LSM(Land Surface Model)으로부터 생산된 수문정보를 이용하여 백분위 해석을 수행하였다. 기간별 가뭄판단기준을 도출하기 위해 객관적 가뭄평가 기법인 ROC(Relative Operating Characteristics) 분석을 이용하였다. 국내 가뭄기준은 대표적으로 강수 및 유출이 지속기간 3개월에 평년대비 35% 이하, 토양수분이 지속기간 2개월의 35% 이하 그리고 증발산량이 지속기간 3개월에 65% 이상으로 나타났다. 가뭄판단기준의 적용성 평가를 위해 SPI(3)와의 ROC 분석을 수행한 결과 SPI(3)에 비해 적용성이 높은 것으로 나타났다. 또한 가뭄판단기준에 대한 지역별 분석을 수행한 결과 공간적으로 가뭄상황을 적절히 반영하는 것을 확인하였다.

The air quality data is important for understanding and analyzing a surrounding influence. In that light, it is positively necessary for a propriety assessment to determine a location of the air quality monitoring sites. In this study, the climate analysis about temperature and wind, using the meteorological data in the Pohang, is conducted to do that. In the next stage, we distinguished the wind by east-west or north-south component, which has less correlation than temperature, analyzed and divided the wind sector. As the result, the wind circumstance of the Pohang is divided into major 5 wind sector; that is the urban area, the northeast coastal area, the east ocean and the west mountainous area. We think that an analysis on detailed wind sector by utilizing the numerical simulation is needed.

융설 모형을 이용하여 융설 기간 동안의 하천유출량을 모의하기 위해서는 융설 관련 매개변수의 정립이 반드시 필요하다. 우리나라의 경우 관측 자료의 부족으로 인하여 적설분포면적, 적설심, 적설분포면적 감소곡선과 같은 융설 관련 매개변수의 추출이 불가능하였다. 본 연구에서는 1997년부터 2003년까지의 겨울철(11월-4월) NOAA/AVHRR 위성영상을 이용하여 한반도의 적설분포도를 추출하고 기상청의 69개소 유인지상기상관측소의 기상자료 중 최심적설심 자료

In this study, climate analysis and wind sector division were conducted for a propriety assessment to determine the location of air quality monitoring sites in the Busan metropolitan area. The results based on the meteorological data(2000～2004) indicated hat air temperature is strongly correlated between 9 atmospheric monitoring sites, while wind speed and direction are not. This is because wind is strongly affected by the surrounding terrain and the obstacles such as building and tree. In the next stage, we performed cluster analysis to divide wind sector over the Busan metropolitan area. The cluster analysis showed that the Busan metropolitan area is divided into 6 wind sectors. However 1 downtown and 2 suburbs an area covering significantly broad region in Busan are not divided into independent sectors, because of the absence of atmospheric monitoring site. As such, the Busan metropolitan area is finally divided into 9 sectors.

The purpose of this research is development of radar data assimilation observed at Jindo S-band radar. The accurate observational data assimilation system is one of the important factors to meteorological numerical prediction of the region scale. Diagnostic analysis system LAPS(Local Analysis and Prediction System) developed by US FSL(Forecast Systems Laboratory) is adopted assimilation system of the Honam district forecasting system. The LAPS system was adjusted in calculation environment in the Honam district. And the improvement in the predictability by the application of the LAPS system was confirmed by the experiment applied to Honam district local severe rain case of generating 22 July 2003. The results are as follows: 1) Precipitation amounts of Gwangju is strong associated with the strong in lower level from analysis of aerological data. This indicated the circulation field especially, 850 hPa layer, acts important role to precipitation in Homan area. 2) Wind in coastal area tends to be stronger than inland area and radar data show the strong wind in conversions zone around front. 3) Radar data assimilation make the precipitation area be extended and maximum amount of precipitation be smaller. 4) In respect to contribution rate of different height wind field on precipitation variation, radar data assimilation of upper level is smaller than that of lower level.

The importance of atmospheric conditions for the assessment of an air pollution situation has been demonstrated by their influence on the various compartments of an air pollution system, comprising all stages from emission to effects. Especially, air pollutants dispersion phenomenon are very sensitive according to wind data. But the discussions of how to apply representative meteorological data in air pollution dispersion model are not frequent in Korean environmental assessment processes. In this study, we investigated the difference of air pollutants dispersion phenomenon using U.S EPA ISCLT3 model according to applying the different meteorological data observed at two points for Seongseo industrial complex of Daegu. Two points are the spot site of Seongseo industrial complex and Daegu meteorological observatory. The winds speed of the spot site were smaller than those of Daegu meteorological observatory. In the winter season, the differences came to about 64% for the period(1 February 2001～31 January 2002). Wind directions were also fairly different at two points. The air pollutants dispersion phenomenon estimated from our numerical experiments were also fairly different owing to the meteorological conditions at two points.

This study was carried out for reading the change of local meteorological environment according to dam construction of Nakdong-river using meteorological data analysis, and modeling. The meteorological data analysised are mean temperature, foggy day, precipittion day and sunshine time. As the result of analyzing meteorological data of before and after the construction of dam in Andong and Hapchon, some discrepancy were observed by month because the lakes have different effect on the region as wind field. The common phenomenons that are revealed after dam construction are increase of foggy day and decrease of sunshine time.

The purpose of the present study is to develope the estimation scheme for sensible heat flux by semi-empirical approach using routine meteorological data such as solar radiation and air temperature. To compare observed sensible heat flux with estimated sensible heat flux, the sensible heat fluxes were measured by three dimensional sonic anemometer-thermometer. The field observation was performed during 1 year from December 1, 1995 to November 30, 1996 on a rice paddy field in Chunchon basin. The heat fluxes were measured at a heights of 5m and mean meteorological variables were obtained at two levels, 2.5m(or 1.5m) and 10m. Since condition of rice paddy field such as, wetness of the field, roughness length, vary widely, we devided annual data to 5 periods. Comparing with two sensible heat fluxes, the results showed that the correlation coefficients were more than 0.86. Thus, we can conclude that the estimation method of sensible heat fluxes using routine meteorological data is practical and reliable enough.