• Atmosphere
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• v.30 no.3
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• pp.277-291
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• 2020

Low-level wind shear (LLWS) events on glide path at Jeju International Airport (CJU) are evaluated using the Aircraft Meteorological Data Relay (AMDAR) and Korea Meteorological Administration Post-Processing (KMAPP) with 100 m spatial resolution. LLWS that occurs in the complex terrains such as Mt. Halla on the Jeju Island affects directly aircraft approaching to and/or departing from the CJU. For this reason, accurate prediction of LLWS events is important in the CJU. Therefore, the use of high-resolution Numerical Weather Prediction (NWP)-based forecasts is necessary to cover and resolve these small-scale LLWS events. The LLWS forecasts based on the KMAPP along the glide paths heading to the CJU is developed and evaluated using the AMDAR observation data. The KMAPP-LLWS developed in this paper successfully detected the moderate-or-greater wind shear (strong than 5 knots per 100 feet) occurred on the glide paths at CJU. In particular, this wind shear prediction system showed better performance than conventional 1-D column-based wind shear forecast.

• Spatial Information Research
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• v.18 no.4
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• pp.33-41
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• 2010

Approximately 100 permanent GPS stations are currently operational in Korea. However, only 10 sites have their own weather sensors connected directly to the GPS receiver. Thus. calculation of meteorological data through interpolation of AWS data are needed to determine precipitable water vapors at a specific GPS station without a meteorological sensor. This study analyzed the accuracy of two meteorological data interpolation methods called reverse sea level correction and kriging. As a result, the root-mean square-error of reverse sea level correction were seven times more accurate in pressure and twice more accurate in temperature than the kriging method. For the analysis of PWV accuracy, we calculated GPS PWV during the summer season in :2008 by using GPS observation data and interpolated meteorological data by reverse sea level correction. And, we compared GPS PWV s based on interpolated meteorological data with those from radiosonde observations and GPS PWV s based on onsite GPS meteorological sensor measurements. As a result, the accuracy of GPS PWV s from our interpolated meteorological data was within the required operational accuracy of 3mm.

• Atmosphere
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• v.31 no.3
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• pp.251-265
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• 2021

This study examined the impact of assimilating the bending angle (BA) obtained via the global navigation satellite system radio occultation (GNSS RO) of the three new satellites (KOMPSAT-5, FY-3C, and FY-3D) on analyses and forecasts of a numerical weather prediction model. Numerical data assimilation experiments were performed using a three-dimensional variational data assimilation system in the Korean Integrated Model (KIM) at a 25-km horizontal resolution for August 2019. Three experiments were designed to select the height and quality control thresholds using the data. A comparison of the data with an analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) integrated forecast system showed a clear positive impact of BA assimilation in the Southern Hemisphere tropospheric temperature and stratospheric wind compared with that without the assimilation of the three new satellites. The impact of new data in the upper atmosphere was compared with observations using the infrared atmospheric sounding interferometer (IASI). Overall, high volume GNSS RO data helps reduce the RMSE quantitatively in analytical and predictive fields. The analysis and forecasting performance of the upper temperature and wind were improved in the Southern and Northern Hemispheres.

• Journal of Environmental Science International
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• v.9 no.2
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• pp.109-114
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• 2000

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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.171-183
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• 2005

In order to monitor the global terrestrial carbon cycle, NASA (National Aeronautics and Space Administration) provides 8-day GPP images by use of satellite remote-sensing reflectance data from MODIS (Moderate Resolution Imaging Spectroradiometer) at l-km nadir spatial resolution since December, 1999. MODIS GPP algorithm adopts DAO (Data Assimilation Office) meteorological data to calculate daily GPP. By evaluating reliability of DAO data with respect to surface weather station data, we examined the effect of errors from DAO data on MODIS GPP estimation in the Korean Peninsula from 2001 to 2003. Our analyses showed that DAO data underestimated daily average temperature, daily minimum temperature, and daily vapor pressure deficity (VPD), but overestimated daily shortwave radiation during the study period. Each meteorological variable resulted in different spatial patterns of error distribution across the Korean Peninsula. In MODIS GPP estimation, DAO data resulted in overestimation of GPP by $25\%$ for all biome types but up to $40\%$ for forest biomes, the major biome type in the Korean Peninsula. MODIS GPP was more sensitive to errors in solar radiation and VPD than in temperatures. Our results indicate that more reliable gridded meteorological data than DAO data are necessary for satisfactory estimation of MODIS GPP in the Korean Peninsula.

• Atmosphere
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• v.17 no.4
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• pp.435-453
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• 2007

KEOP (Korea Enhanced Observing Period)-2004 intensive summer observation was carried out from 20 June to 5 July 2004 over the Southwestern part of the Korean peninsula. In this study, the effects of KEOP-2004 intensive observation data on the simulation of precipitation system are investigated using KLAPS (Korea Local Analysis and Prediction System) and PSU/NCAR MM5. Three precipitation cases during the intensive observation are selected for detailed analysis. In addition to the control experiments using the traditional data for its initial and boundary conditions, two sensitivity experiments using KEOP data with and without Jindo radar are performed. Although it is hard to find a clear and consistent improvement in the verification score (threat score), it is found that the KEOP data play a role in improving the position and intensity of the simulated precipitation system. The experiments started at 00 and 12 UTC show more positive effect than those of 06 and 18 UTC. The effect of Jindo radar is dependent on the case. It plays a significant role in the heavy rain cases related to a mesoscale low over Changma front and the landing of a Typhoon. KEOP data produce more strong difference in the 06/18 UTC experiments than in 00/12 UTC, but give more positive effects in 00/12 UTC experiments. One of the possible explanations for this is that : KEOP data could properly correct the atmosphere around them when there are certain amounts of data, while gives excessive effect to the atmospheric field when there are few data. CRA analysis supports this reasoning. According to the CRA (Contiguous Rain Area) analysis, KEOP data in 00/12 UTC experiments improve only the surrounding area, resulting in essentially same precipitation system so the effects remain only in each convective cell rather than the system itself. On the other hand, KEOP data modify the precipitation system itself in 06/18 UTC experiments. Therefore the effects become amplified with time integration.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.135-139
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• 1999

Wind velocity is one of the primary variables for describing atmospheric state from GMS-5. And its accurate depiction is essential for operational weather forecasting and for initialization of NWP(Numerical Weather Prediction) models. The aim of this research is to incorporate imagery from other available spectral channels and examine the error characteristics of winds derived from these images. Multi spectral imagery from GMS-5 was used for this purpose and applied to Korean region with together BoM(Bureau of Meteorology). The derivation of wind velocity estimates from low and high resolution visible, split window infrared, and water vapor images, resulted in improvements in the amount and quality of wind data available for forecasting.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.1
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• pp.47-54
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• 2015

Recently, rapid urbanization and industrialization had increased the air pollution in major cities by increasing the fuel consumption. Air pollution models have been widely used for air quality management in many countries. Also, a lot of related studies have been conducted using air dispersion models. In this study, The meteorological preprocessing program was developed to convert the korea meteorological data to the U.S. meteorological data and to expand the usability of air dispersion models of U.S. EPA. In addition, the usability evaluation was carried out through a case study. In the results of the evaluation of the program, this program was accurately convert the Korea meteorological data to the U.S. meteorological data, and the prediction was carried out without a error in air quality modeling. Therefore, the program showed a high utilization as meteorological data pre-processing tool.

• New & Renewable Energy
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• v.8 no.2
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• pp.14-23
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• 2012

The TMY (Typical Meteorological Year) for the solar energy study is generated using observation data with 22 solar sites from KMA (Korea Meteorological Administration) during 11 years (2000-2010). The meteorological data for calculation the TMY are used solar radiation, temperature, dew point temperature, wind speed and humidity data. And the TMY is calculated to apply the FS (Finkelstein and Schafer) statistics and RMSE (Root Mean Squared Error) methods. FS statistics performed with each point and each variable and then selected top five candidate TMM months with statistical analysis and normalization. Finally TMY is generated to select the highest TMM score with evaluation the average errors for the 22 whole points. The TMY data is represented average state and long time variations with 22 sites and meteorological data. When TMY validated with the 11-year daily solar radiation data, the correlation coefficient was about 0.40 and the highest value is 0.57 in April and the lowest value is 0.23 in May. Mean monthly solar radiation of TMY is 411.72 MJ which is 4 MJ higher than original data. Average correlation coefficient is 0.71, the lowest correlation is 0.43 in May and the highest correlation is 0.90 in January. Accumulated annual solar radiation by TMY have higher value in south coast and southwestern region and have relatively low in middle regions. And also, differences between TMY and 11-year mean of is distributed lower 100 MJ in Kyeongbuk, higher 200 MJ in Jeju and higher 125 MJ in Jeonbuk and Jeonnam, respectively.

• Journal of Environmental Science International
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• v.29 no.10
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• pp.981-988
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• 2020

This study presents meteorological data integrity to improve environmental quality assessment in Yongdam catchment. The study examines both extreme ranges of meteorological data measurements and data reliability which include maximum and minimum temperature, relative humidity, dew point temperature, radiation, heat flux. There were some outliers and missing data from the measurements. In addition, the latent heat flux and sensible heat flux data were not reasonable and evapotranspiration data did not match at some points. The accuracy and consistency of data stored in a database for the study were secured from the data integrity. Users need to take caution when using meteorological data from the Yongdam catchment in the preparation of water resources planning, environmental impact assessment, and natural hazards analysis.