• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.27 no.5
• /
• pp.565-574
• /
• 2009

The water vapor weighted vertically mean temperature(Tm) models, which were developed by the consideration of seasonal characteristics over the Korea, was used in the retrieval of precipitable water vapor (PWV) from GPS data which were observed at four GPS permanent stations. Since the weighted mean temperature relates to the water vapor pressure and temperature profile at a site, the accuracy of water vapor information which were estimated from GPS tropospheric wet delay is proportional to the accuracy of the weighted mean temperature. The adaption of Korean seasonal weighted mean temperature model, as an alternative to other formulae which are suggested from other nation, provides an improvement in the accuracy of the GPS PWV estimation. Therefore, it can be concluded that the seasonally appropriate weighted mean temperature model, which is used to convert actual zenith wet delay (ZWD) to the PWV, can be more reduced the relative biases of PWV estimated from GPS signal delays in the troposphere than other annual model, so that it would be useful for GPS PWV estimation with high accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.30 no.6_2
• /
• pp.615-622
• /
• 2012

Since the accuracy of precipitable/integrated water vapor estimates from GNSS measurements is proportional to the accuracy of water vapor Weighted Mean Temperature Model (WMTM), the WMTM is a significant formulation in the retrieval of precipitable water vapor from zenith wet delay of GNSS signal. The purpose of this paper is to develop available the WMTM to apply for GNSS meteorology in the region of Algeria, by using the Algerian radiosonde network in the World Meteorological Organization (WMO). It can be concluded that the available GNSS precipitable water vapor which is retrieved by the developed Algerian Weighted Mean Temperature Equation (AWMTE) can be useful technique for sensing of water vapor in the Algeria, after Algerian Continuously Operating Reference System (CORS) will be constructed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.1
• /
• pp.53-62
• /
• 2015

The water vapor including latent heat is the important component in an atmospheric circulation and in a monitoring of the Earth's climate changes, as well as in the weather forecast improvement. In this study, to establish the Algerian weighted mean temperature model, a linear regression method had been developed under 5 radiosonde observations for a total 24,694 profiles from 2004 to 2013. An weighted mean temperature is a key parameter in the processing of PWV from GNSS tropospheric delays. The result from the study has expected to provide an useful model to demonstrate the realization and utility of using the ground-based GNSS meteorology technique that will bring improvements in weather forecasting, climate monitoring in Algeria.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.52 no.5
• /
• pp.511-518
• /
• 2019

Evaluating the habitat suitability of potential aquaculture sites for cultured species is critical to the sustainable use of tidal flats. This study evaluated the habitat suitability index (HSI) of 12 sites in a tidal flat aquaculture farm at Geunso Bay, Taean, in June 2016. The parameters used to model the suitability index were Growth (water temperature, chlorophyll ${\alpha}$, hydrodynamics), Survival (sediment-sand, mean size, air exposure), and Environment (DO, salinity). The HSI was calculated using weighted and No weighted geometric means. The results showed high habitat suitability at the bay's entrance (HIS; No weighted, 0.60-0.70; weighted, 0.60). Hydrodynamics, air exposure, sediment-sand and mean size are thought to have a significant impact on habitat selection by Manila clams Ruditapes philippinarum. This study explored the optimum habitat for Manila clams by calculating the HSI, providing basic data for tidal flat management.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.4
• /
• pp.233-242
• /
• 2019

ZHD (Zenith Hydrostatic Delay) model is important parameter in estimating of GNSS (Global Navigation Satellite System) PWV (Precipitable Water Vapor) along with weighted mean temperature. The ZWD (Zenith Wet Delay) is tend to accumulate the ZHD error, so that biases from ZHD will be affected on the precision of GNSS PWV. In this paper, we compared the accuracy of GNSS PWV with radiosonde PWV using three ZHD models, such as Saastamoinen, Hopfield, and Black. Also, we adopted the KWMT (Korean Weighted Mean Temperature) model and the mean temperature which was observed by radiosonde on the retrieval processing of GNSS PWV. To this end, GNSS observation data during one year were processed to produce PWVs from a total of 5 GNSS permanent stations in Korea, and the GNSS PWVs were compared with radiosonde PWVs for the evaluating of biases. The PWV biases using mean temperature estimated by the KWMT model are smaller than radiosonde mean temperature. Also, we could confirm the result that the Saastamoinen ZHD which is most used in the GNSS meteorology is not valid in South Korea, because it cannot be exclude the possibility of biases by latitude or height of GNSS station.

• Journal of Korean Society for Atmospheric Environment
• /
• v.32 no.5
• /
• pp.513-525
• /
• 2016

To propose an effective ensemble methods in predicting $PM_{10}$ concentration, six experiments were designed by different ensemble average methods (e.g., non-weighted, single weighted, and cluster weighted methods). The single weighted method was calculated the weighted value using both multiple regression analysis and singular value decomposition and the cluster weighted method was estimated the weighted value based on temperature, relative humidity, and wind component using multiple regression analysis. The effects of ensemble average methods were significantly better in weighted average than non-weight. The results of ensemble experiments using weighted average methods were distinguished according to methods calculating the weighted value. The single weighted average method using multiple regression analysis showed the highest accuracy for hourly $PM_{10}$ concentration, and the cluster weighted average method based on relative humidity showed the highest accuracy for daily mean $PM_{10}$ concentration. However, the result of ensemble spread analysis showed better reliability in the single weighted average method than the cluster weighted average method based on relative humidity. Thus, the single weighted average method was the most effective method in this study case.

• Journal of Korean Institute of Industrial Engineers
• /
• v.7 no.1
• /
• pp.21-31
• /
• 1981

This paper develops a short term forecasting model for household electric power consumption in Seoul, which can be used for the effective planning and control of utility management. The model developed is based on exponentially weighted moving average model and incorporates monthly average temperature as an exogeneous factor so as to enhance its forecasting accuracy. The model is empirically compared with the Winters' three parameter model which is widely used in practice and the Box-Jenkins model known to be one of the most accurate short term forecasting techniques. The result indicates that the developed hybrid exponential model is better in terms of accuracy measured by average forecast error, mean squared error, and autocorrelated error.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.1
• /
• pp.33-39
• /
• 2018

As the retrieval accuracy of PWV estimates from GPS measurements is proportional to the accuracy of water vapor WMT, the WMT model is a significant formulation in the conversion of PWV from the GPS ZWD. The purpose of this study is to develop a MWMT model for the retrieval of highly accurate GPS PWV using the radiosonde measurements from six upper-air observing stations in the region of Korea. The values of 1-hr PWV estimated at four GPS stations during one year are used to evaluate the validity of the MWMT model. It is compared to the PWV obtained from radiosonde data that are located in the vicinity of GPS stations. Intercomparison of radiosonde PWVs and GPS PWVs derived using different WMT models is performed to assess the quality of our MWMT model for Korea. The result in this study indicates that the MWMT model is an effective model to retrieve the enhanced accurate GPS PWV, compared to other GPS PWV derived by Korean annual or global WMT models.

• Atmosphere
• /
• v.28 no.3
• /
• pp.247-261
• /
• 2018

The objective of this paper is to compare probabilistic temperature forecasts from different regional and global ensemble prediction systems over PyeongChang area. A statistical post-processing method is used to take into account combination and calibration of forecasts from different numerical prediction systems, laying greater weight on ensemble model that exhibits the best performance. Observations for temperature were obtained from the 30 stations in PyeongChang and three different ensemble forecasts derived from the European Centre for Medium-Range Weather Forecasts, Ensemble Prediction System for Global and Limited Area Ensemble Prediction System that were obtained between 1 May 2014 and 18 March 2017. Prior to applying to the post-processing methods, reliability analysis was conducted to identify the statistical consistency of ensemble forecasts and corresponding observations. Then, ensemble model output statistics and bias-corrected methods were applied to each raw ensemble model and then proposed weighted combination of ensembles. The results showed that the proposed methods provide improved performances than raw ensemble mean. In particular, multi-model forecast based on ensemble model output statistics was superior to the bias-corrected forecast in terms of deterministic prediction.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.2 no.4
• /
• pp.175-182
• /
• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.