• Journal of Astronomy and Space Sciences
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• v.29 no.3
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• pp.295-303
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• 2012

In this study, we compared the precipitable water vapor (PWV) data derived from the radiosonde observation data at Sokcho Observatory and the PWV data at Sokcho Global Positioning System (GPS) Observatory provided by Korea Astronomy and Space Science Institute, for the years of 2006, 2008, 2010, and analyzed the radiosonde seasonal, diurnal bias according to radiosonde sensor types. In the scatter diagram of the daytime and nighttime radiosonde PWV data and the GPS PWV data, dry bias was found in the daytime radiosonde observation as known in the previous study. Overall, the tendency that the wet bias of the radiosonde PWV increased as the GPS PWV decreased and the dry bias of the radiosonde PWV increased as the GPS PWV increased. The quantitative analysis of the bias and error of the radiosonde PWV data showed that the mean bias decreased in the nighttime except for 2006 winter, and in comparison for summer, RS92-SGP sensor showed the highest quality.

• Journal of Astronomy and Space Sciences
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• v.27 no.4
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• pp.367-375
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• 2010

In this study, we compared the precipitable water vapor (PWV) data derived from the radiosonde observation data at Sokcho Observatory and the PWV data at Sokcho Global Positioning System (GPS) Observatory provided by Korea Astronomy and Space Science Institute, from 0000 UTC, June 1, 2007 to 1200 UTC, May 31, 2009, and analyzed the radiosonde bias between the day and the night. In the scatter diagram of the daytime and nighttime radiosonde PWV data and the GPS PWV data, dry bias was found in the daytime radiosonde observation as known in the previous study. In addition, for all the rainfall events, the tendency that the wet bias of the radiosonde PWV increased as the GPS PWV decreased and the dry bias of the radiosonde PWV increased as the GPS PWV increased was significantly less distinctive in nighttime than in daytime. The quantitative analysis of the bias and error of the radiosonde PWV data showed that the mean bias decreased in the second year, regardless of nighttime or daytime rainfall, and the non-rainfall root mean square error (RMSE) was similar to that of the previous studies, while the rainfall RMSE was larger to a certain extent.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.491-495
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• 1999

We compared the satellite observed temperature with the radiosonde observed temperature in the Korean Peninsula. The radiosonde observed data were obtained from four upper air observation stations in the Korean Peninsula from 1981 to 1998, and that was compared with the satellite observed data of the channel-2 and channel-4 of microwave sounding unit(MSU) on board NOAA series of polar-orbiting satellites. The radiosonde data were reconstructed into monthly radiosonde T$_{b}$ using MSU weighting function. The monthly climatology shows radiosonde T$_{b2}$ is higher than MSU T$_{b2}$ in summer. The correlation between MSU T$_{b2}$ and radiosonde T$_{b2}$ is 0.72-0.76 and 0.73-0.81 between MSU T$_{b4}$ and radiosonde T$_{b4}$.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.15 no.4
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• pp.94-99
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• 2007

The purpose of this study is analysis of aircraft turbulence of mid Korea using VWS from Osan radiosonde data and comparison with the PIREPs reporting the aircraft turbulence during $1990{\sim}1999$. The results of this study summarized that the frequence of aircraft events is more higher in winter time and in lower level(near the surface) of the atmosphere from VWS analysis using radiosonde data. And comparison with PIREPs data shows that relatively high skill score(44%) using the VWS method. It appears that the operational forecast skill score of aircraft turbulence is much higher using VWS than empirical method, due to the upgrade of the discrimination criteria of the aircraft turbulence.

• Korean Journal of Remote Sensing
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• v.16 no.1
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• pp.47-54
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• 2000

We compared the satellite observed temperature with the radiosonde observed temperature in the Korean Peninsula. The radiosonde observed data were obtained from four upper air observation stations in the Korean Peninsula from 1981 to 1998, and were compared with the satellite observed data of the channel-2 and channel-4 of microwave sounding unit(MSU) on board NOAA series of polar-orbiting satellites. The radiosonde data were reconstructed from radiosonde T$_b$ using MSU weighting function. The monthly climatology shows radiosonde T$_{b2}$ is higher than MSU T$_{b2}$ in summer. The correlation between MSU T$_{b2}$ and radiosonde T$_{b2}$ is 0.72-0.76 and 0.73-0.81 between MSU T$_{b4}$ and radiosonde T$_{b4}$. The T$_{b2}$ show a positive trend and the T$_{b4}$ has a negative trend during the 18 years.

• Atmosphere
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• v.19 no.2
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• pp.213-226
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• 2009

In order to investigate the characteristics of Changma over the Korean peninsula, KEOP-2007 IOP (Intensive Observing Period) was conducted from 15 June 2007 to 15 July 2007. KEOP-2007 IOP is high spatial and temporal radiosonde observations (RAOB) which consisted of three special stations (Munsan, Haenam, and Ieodo) from National Institute of Meteorological Research, five operational stations (Sokcho, Baengnyeongdo, Pohang, Heuksando, and Gosan) from Korea Meteorological Administration (KMA), and two operational stations (Osan and Gwangju) from Korean Air Force (KAF) using four different types of radiosonde sensors. The error statistics of the sensor of radiosonde were investigated using quality control check. The minimum and maximum error frequency appears at the sensor of RS92-SGP and RS1524L respectively. The error frequency of DFM-06 tends to increase below 200 hPa but RS80-15L and RS1524L show vice versa. Especially, the error frequency of RS1524L tends to increase rapidly over 200 hPa. Systematic biases of radiosonde show warm biases in case of temperature and dry biases in case of relative humidity compared with ECMWF (European Center for Medium-Range Weather Forecast) analysis data and precipitable water vapor from GPS. The maximum and minimum values of systematic bias appear at the sensor of DFM-06 and RS92-SGP in case of temperature and RS80-15L and DFM-06 in case of relative humidity. The systematic warm and dry biases at all sensors tend to increase during daytime than nighttime because air temperature around sensor increases from the solar heating during daytime. Systematic biases of radiosonde are affected by the sensor type and the height of the sun but random errors are more correlated with the moisture conditions at each observation station.

• Journal of Astronomy and Space Sciences
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• v.27 no.3
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• pp.213-220
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• 2010

As an observation instrument of the longest record of tropospheric water vapor, radiosonde data provide upper-air pressure (geopotential height), temperature, humidity and wind. However, the data have some well-known elements related to inaccuracy. In this article, radiosonde precipitable water vapor (PWV) at Sokcho observatory was compared with global positioning system (GPS) PWV during each summertime of year 2007 and 2008 and the biases were calculated. As a result, the mean bias showed negative values regardless of the rainfall occurrence. In addition, on the basis of GPS PWV, the maximum root mean square error (RMSE) was 5.67 mm over the radiosonde PWV.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.263-274
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• 2016

In this study, we compared the Precipitable Water Vapor (PWV) data derived from the radiosonde observation at Sokcho observatory and the PWV data at Sokcho Global Navigation Satellite System (GNSS) observatory provided by Korea Astronomy and Space Science Institute, for the summer of 2007~2014, and analyzed the radiosonde diurnal and rainfall-dependent bias according to radiosonde sensor types. In the scatter diagram of the daytime and nighttime radiosonde PWV data and GNSS PWV data, dry bias was found in the daytime radiosonde observation as known in the previous study and dry bias of RSG-20A sensor was larger than other sensors. Overall, the tendency that the wet bias of the radiosonde PWV increased as GNSS PWV decreased and the dry bias of the radiosonde PWV increased as GNSS PWV increased. The quantitative analysis of the bias and error of the radiosonde PWV data showed that the mean bias decreased in the nighttime except for 2007, 2008 summer. In comparison for summer according to the presence or absence of rainfall, RS92-SGP sensor showed the highest quality.

• 한국항공운항학회:학술대회논문집
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• 2007.12a
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• pp.18-20
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• 2007

• Journal of Korea Water Resources Association
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• v.39 no.8 s.169
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• pp.717-726
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• 2006

In this study, we developed a rainfall forecasting model using data from radiosonde and rain gauge network and neural networks. The primary hypothesis is that if we can consider the moving direction of the rain generating weather system in forecasting rainfall, we can get more accurate results. We assume that the moving direction of the rain generating weather system is same as the wind direction at 700mb which is measured at radiosonde networks. Neural networks are consisted of 8 different modules according to 8 different wind directions. The model was verified using 350 AWS data and Pohang radiosonde data. Correlation coefficient is improved from 0.41 to 0.73 and skill score is 0.35. Statistical performance measures of the Quantitative Precipitation Forecast (QPF) model show improved output compared to that of rainfall forecasting model using only AWS data.