• 대기
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• 제21권4호
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• pp.415-427
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• 2011

In this study, the impacts of land surface conditions, land cover (LC) map and leaf area index (LAI), on the short-range weather forecast over the East-Asian region were examined using Unified Model (UM) coupled with the MOSES 2.2 (Met-Office Surface Exchange Scheme). Four types of experiments were performed at 12-km horizontal resolution with 38 vertical layers for two months, July and August 2009 through consecutive reruns of 72-hour every 12 hours, 00 and 12 UTC. The control experiment (CTRL) uses the original IGBP (International Geosphere-Biosphere Programme) LC map and old MODIS (MODerate resolution Imaging Spectroradiometer) LAI, the new LAI experiment (NLAI) uses improved monthly MODIS LAI. The new LC experiment (NLCE) uses KLC_v2 (Kongju National Univ. land cover), and the new land surface experiment (NLSE) uses KLC_v2 and new LAI. The reduced albedo and increased roughness length over southern part of China caused by the increased broadleaf fraction resulted in increase of land surface temperature (LST), air temperature, and sensible heat flux (SHF). Whereas, the LST and SHF over south-eastern part of Russia is decreased by the decreased needleleaf fraction and increased albedo. The changed wind speed induced by the LC and LAI changes also contribute the LST distribution through the change of vertical mixing and advection. The improvement of LC and LAI data clearly reduced the systematic underestimation of air temperature over South Korea. Whereas, the impacts of LC and LAI conditions on the simulation skills of precipitation are not systematic. In general, the impacts of LC changes on the short range forecast are more significant than that of LAI changes.

• 대기
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• 제20권2호
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• pp.73-89
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• 2010

An updateable model output statistics (UMOS) system for daily maximum and minimum temperature ($T_M$ and $T_m$) over South Korea based on the Canadian UMOS system were developed and validated. RDAPS (regional data assimilation and prediction system) and KWRF (Korea WRF) which have quite different physics and dynamics were used for the development of UMOS system. The 20 most frequently selected potential predictors for each season, station, and forecast projection time from the 68 potential predictors of the MOS system, were used as potential predictors of the UMOS system. The UMOS equations were developed through the weighted blending of the new and old model data, with weights chosen to emphasize the new model data while including enough old model data to ensure stable equations and a smooth transition of dependency from the old model to the new model. The UMOS equations are being updated by every 7 days. The validation results of $T_M$ and $T_m$ showed that seasonal mean bias, RMSE, and correlation coefficients for the total forecast projection times are -0.41-0.17 K, 1.80-2.46 K, and 0.80-0.97, respectively. The performance is slightly better in autumn and winter than in spring and summer. Also the performance of UMOS system are clearly dependent on location, better at the coastal region than inland area. As in the MOS system, the performance of UMOS system is degraded as the forecast day increases.

• 한국농림기상학회지
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• 제14권1호
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• pp.1-10
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• 2012

본 연구는 디지털예보(현 동네예보) 자료를 활용하여 우리나라의 산불위험예보의 정확도 향상은 물론 기상에 의한 산불위험지수를 산출하여 한반도의 산불위험예보 체계를 구축하는데 있다. 한반도 지역의 산불발생위험을 나타내는 기상지수(daily weather index, DWI)를 산출하기 위해 기상청의 5km 격자간격의 디지털예보자료를 이용하였다. DWI 분석을 위해 온도, 습도, 풍속 UV, 1시간 강우량, 12시간 강우량을 대상으로 한반도 전역에 대한 기상요소별 기후분포도를 제작하였다. 한반도의 기상에 의한 일일 DWI 산출을 위해 대형산불이 자주 발생하는 강원도 지역의 산불발생확률식 $[1+{\exp}\{-(2.494+(0.004{\times}T_{max})-(0.008{\times}EF))\}]^{-1}$을 적용하였다. 기상예보자료의 예측정확도 검증을 위해 RDAPS, 디지털예보, 실황자료 모두 2005년 12월 12일 15시 자료를 대상으로 비교 분석한 결과 76개 기상관측소에서 관측한 실황자료에 대응하는 기상요소별 디지털예보의 예측값이 RDAPS 추출 자료보다 향상된 예측결과를 보였다. 산불위험예보 정확도 검증을 위해 사용한 실황자료와 디지털예보자료의 평균오차는 평균 기온 $0.2^{\circ}C$, 실효습도 2.4%, 평균풍속 2.2m/s로 나타나 큰 변이는 없었지만, 평균풍속에서 실측값과 예측값간의 차이가 있는 것으로 나타났다. 디지털예보자료를 활용할 경우 RDAPS 자료보다 산불위험예보의 정확도가 크게 향상되는 결과를 얻을 수 있었으며, 산불위험예보의 정확도 검증을 위해 실황자료와 디지털예보자료를 적용하여 예측된 전국 233개 시 군 구의 평균 산불위험지수를 각각 추출하여 비교한 결과 $R^2$=0.854의 높은 정확도를 보였다. 산불위험도가 가장 높은 15시의 실제 76개소에서 관측한 기상자료를 적용하여 전국의 산불위험지수를 예측한 값은 70.5로 디지털예보자료를 적용하여 예측한 위험지수(70.0)와 0.5의 오차를 보여 예측력이 개선되었음을 확인할 수 있었다. 따라서 디지털예보를 적용할 경우 실황자료와의 예측력이 검증된 만큼 향후 기상에 의한 한반도의 산불발생위험지수를 보다 정확하게 계산하는데 유용하게 이용할 수 있을 것으로 기대된다.

• 한국대기환경학회지
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• 제19권5호
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• pp.595-610
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• 2003

The statistical indexes such as RMSE (Root Mean Square Error), Mean Bias error, and IOA (Index of agreement) are used to evaluate 3 Dimensional wind and temperature fields predicted by operational meteorological model RAMS (Regional Atmospheric Meteorological System) implemented in CARIS (Chemical Accident Response Information System) for the dispersion forecast of hazardous chemicals in case of the chemical accidents in Korea. The operational atmospheric model, RAMS in CARIS are designed to use GDAPS, GTS, and AWS meteorological data obtained from KMA (Korean Meteorological Administration) for the generation of 3-dimensional initial meteorological fields. The predicted meteorological variables such as wind speed, wind direction, temperature, and precipitation amount, during 19 ∼ 23, August 2002, are extracted at the nearest grid point to the meteorological monitoring sites, and validated against the observations located over the Korean peninsula. The results show that Mean bias and Root Mean Square Error are 0.9 (m/s), 1.85 (m/s) for wind speed at 10 m above the ground, respectively, and 1.45 ($^{\circ}C$), 2.82 ($^{\circ}C$) for surface temperature. Of particular interest is the distribution of forecasting error predicted by RAMS with respect to the altitude; relatively smaller error is found in the near-surface atmosphere for wind and temperature fields, while it grows larger as the altitude increases. Overall, some of the overpredictions in comparisons with the observations are detected for wind and temperature fields, whereas relatively small errors are found in the near-surface atmosphere. This discrepancies are partly attributed to the oversimplified spacing of soil, soil contents and initial temperature fields, suggesting some improvement could probably be gained if the sub-grid scale nature of moisture and temperature fields was taken into account. However, IOA values for the wind field (0.62) as well as temperature field (0.78) is greater than the 'good' value criteria (> 0.5) implied by other studies. The good value of IOA along with relatively small wind field error in the near surface atmosphere implies that, on the basis of current meteorological data for initial fields, RAMS has good potentials to be used as a operational meteorological model in predicting the urban or local scale 3-dimensional wind fields for the dispersion forecast in association with hazardous chemical releases in Korea.

• 한국물환경학회지
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• 제30권6호
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• pp.673-682
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• 2014

A watershed model was constructed using Hydrological Simulation Program Fortran to predict the water temperature at major tributaries of Nakdong River basin, Korea. Water temperature is one of the most fundamental indices used to determine the nature of an aquatic environment. Most processes of an aquatic environment such as saturation level of dissolved oxygen, the decay rate of organic matter, the growth rate of phytoplankton and zooplankton are affected by temperature. The heat flux to major reservoirs and tributaries was analyzed to simulate water temperature accurately using HSPF model. The annual mean heat flux of solar radiation was estimated to $150{\sim}165W/m^2$, longwave radiation to $-48{\sim}-113W/m^2$, evaporative heat loss to $-39{\sim}-115W/m^2$, sensible heat flux to $-13{\sim}-22W/m^2$, precipitation heat flux to $2{\sim}4W/m^2$, bed heat flux to $-24{\sim}22W/m^2$ respectively. The model was calibrated at major reservoir and tributaries for a three-year period (2008 to 2010). The deviation values (Dv) of water temperature ranged from -6.0 to 3.7%, Nash-Sutcliffe efficiency(NSE) of 0.88 to 0.95, root mean square error(RMSE) of $1.7{\sim}2.8^{\circ}C$. The operational water temperature forecasting results presented in this study were in good agreement with measured data and had a similar accuracy with model calibration results.

• 한국태양에너지학회 논문집
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• 제29권2호
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• pp.31-38
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• 2009

This study was conducted to forecast inner water temperature strata change by extracting deep water from a dam. For the methodology, the scope wherein the balance between the volume of low-temperature water intake through the virtual water intake opening as installed within the stored water area and the volume of water intake from the surrounding area is not destroyed was calculated through the CFD simulation technique using the computational fluid dynamics(CFD) interpretation method. This study suggested a supplementary method(diffuser) to avoid destroying the water temperature strata, and the effect was reviewed. In case of intake of the same volume, when the velocity of flow of water intake is reduced by increasing the pipe diameter, the destruction of water temperature strata can be minimized. When the area(height) where the intake of water is possible is low, a diffuser for interrupting the vertical direction inflow should be installed to secure favorable water intake conditions in case of water intake on the upper part. This study showed that there was no problem if the intake-enabled, low-temperature area was secured approximately 10m from the bottom when the scope that does not destroy the water temperature strata in case of water intake was forecast using the regression formula.

• 대한전기학회논문지:전력기술부문A
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• 제53권6호
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• pp.358-363
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• 2004

Due to the weather sensitivity of the power load, it is difficult to forecast accurately the peak power load of summer season. We improve the accuracy of the load forecasting considering weather condition. We introduced the sensitivity of temperature and proposed an improved forecasting algorithm. The proposed algorithm shows that the error of the load forecasting is 1.5%.

• 한국해양학회지:바다
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• 제20권1호
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• pp.1-15
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• 2015

한반도 주변을 연구해역으로 하는 지역 해양순환예측시스템을 이용하여 관측기반의 분석 자료인 Operational Sea Surface Temperature and Sea Ice Analysis(OSTIA) 해수면 온도 자료의 동화를 통한 초기장 개선효과가 황해, 동중국해 그리고 동해의 해수면온도 예측결과에 미치는 영향을 조사하였다. 이를 위해서, 본 연구에서는 3차원 최적내삽법을 적용한 실험(Exp. DA)과 적용하지 않은 실험(Exp. NoDA)을 수행하여 각각의 실험결과를 관측자료와 비교 분석하였다. 2011년 9월 OSTIA 해수면 온도 자료와의 비교결과, Exp. NoDA는 24, 48, 72 예측시간에서 약 $1.5^{\circ}C$의 비교적 높은 Root Mean Square Error(RMSE)를 보였으나, Exp. DA에서는 모든 예측시간에서 $0.8^{\circ}C$ 이하의 상대적으로 낮은 RMSE가 나타났다. 특히, 초기 24시간 예측결과에서 RMSE는 $0.57^{\circ}C$를 보여 Exp. NoDA에 비해 예측성능이 크게 향상된 결과를 보였다. 해역별로는 황해와 동해에서 자료동화 적용 시, 60% 이상의 높은 RMSE 감소율이 나타났다. 기상청 8개 지점 연안 계류부이의 표층수온 자료를 이용하여 자료동화 효과를 계절적으로 살펴본 결과, 전반적으로 여름철을 제외한 모든 계절에서 자료동화 적용 후 70% 이상의 높은 RMSE 감소율을 보여 한반도 연안 표층수온의 단기 예측성이 향상됨을 확인하였다. 또한, 해수면 온도 자료의 동화로 인한 해양상층부의 수온구조 변화를 살펴보기 위해 동해를 대표해역으로 하여 Argo 수온 프로파일 자료와 실험결과를 비교하였다. 특히 연직 혼합이 강한 겨울철 해양 상층부(<100 m) 경우 Exp. DA의 RMSE가 Exp. NoDA에 비해 약 $1.5^{\circ}C$ 감소한 결과를 보여 해수면 온도의 자료동화 효과가 해양상층부의 수온 예측성 향상에 기여함을 확인하였다. 하지만, 겨울철 혼합층 아래에서는 Argo 관측 대비 수온 오차가 오히려 증가한 해역도 존재하여 해수면 온도 자료동화의 한계성도 나타났다.

• 대기
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• 제25권1호
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• pp.67-83
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• 2015

Predicting the location and intensity of precipitation still remains a main issue in numerical weather prediction (NWP). Resolution is a very important component of precipitation forecasts in NWP. Compared with a lower resolution model, a higher resolution model can predict small scale (i.e., storm scale) precipitation and depict convection structures more precisely. In addition, an ensemble technique can be used to improve the precipitation forecast because it can estimate uncertainties associated with forecasts. Therefore, NWP using both a higher resolution model and ensemble technique is expected to represent inherent uncertainties of convective scale motion better and lead to improved forecasts. In this study, the limited area ensemble prediction system for the convective-scale (i.e., high resolution) operational Unified Model (UM) in Korea Meteorological Administration (KMA) was developed and evaluated for the ensemble forecasts during August 2012. The model domain covers the limited area over the Korean Peninsula. The high resolution limited area ensemble prediction system developed showed good skill in predicting precipitation, wind, and temperature at the surface as well as meteorological variables at 500 and 850 hPa. To investigate which combination of horizontal resolution and ensemble member is most skillful, the system was run with three different horizontal resolutions (1.5, 2, and 3 km) and ensemble members (8, 12, and 16), and the forecasts from the experiments were evaluated. To assess the quantitative precipitation forecast (QPF) skill of the system, the precipitation forecasts for two heavy rainfall cases during the study period were analyzed using the Fractions Skill Score (FSS) and Probability Matching (PM) method. The PM method was effective in representing the intensity of precipitation and the FSS was effective in verifying the precipitation forecast for the high resolution limited area ensemble prediction system in KMA.

• 대기
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• 제28권2호
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• pp.187-200
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• 2018

The heavy snowfall phenomenon with thunder and lightning occurred in Yeongdong coastal region on 20 January 2017. Amount of snow on that day was a maximum of 47 cm and was concentrated in a short time (2 hours) at the Yeongdong coastal area. The mechanism of thundersnow was investigated to describe in detail using observational data and numerical simulation (Weather Research and Forecast, WRF) applied lightning option. The results show that a convective cloud occurred at the Yeongdong coastal area. The east wind flow was generated and the pressure gradient force was maximized by the rapidly developed cyclone. The cold and dry air in the upper atmosphere has descended (so called tropopause folding) atmospheric lower layer at precipitation peak time (1200 LST). In addition, latent heat in the lower atmosphere layer and warm sea surface temperature caused thermal instability. The convective cloud caused by the strong thermal instability was developed up to 6 km at that time. And the backdoor cold front was determined by the change characteristics of meteorological elements and shear line in the east sea. Instability indexes such as Total totals Index (TT) and Lightning Potential Index (LPI) are also confirmed as one of good predictability indicates for the explosive precipitation of convective rainfall.