• Atmosphere
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• v.24 no.1
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• pp.101-110
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• 2014

This study estimates and evaluates the daily January temperature from 2003 to 2012 with 30 m-resolution over South Korea, using a modified Parameter-elevation Regression on Independent Slopes Model (K-PRISM). Several factors in K-PRISM are also adjusted to 30 m grid spacing and daily time scales. The performance of K-PRISM is validated in terms of bias, root mean square error (RMSE), and correlation coefficient (Corr), and is then compared with that of inverse distance weighting (IDW) and hypsometric methods (HYPS). In estimating the temperature over Jeju island, K-PRISM has the lowest bias (-0.85) and RMSE (1.22), and the highest Corr (0.79) among the three methods. It captures the daily variation of observation, but tends to underestimate due to a high-discrepancy in mean altitudes between the observation stations and grid points of the 30 m topography. The temperature over South Korea derived from K-PRISM represents a detailed spatial pattern of the observed temperature, but generally tends to underestimate with a mean bias of -0.45. In bias terms, the estimation ability of K-PRISM differs between grid points, implying that care should be taken when dealing with poor skill area. The study results demonstrate that K-PRISM can reasonably estimate 30 m-resolution temperature over South Korea, and reflect topographically diverse signals with detailed structure features.

• Wind and Structures
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• v.19 no.5
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• pp.505-522
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• 2014

While effects of the atmospheric boundary layer flow on engineering infrastructure are more or less known, some local transient winds create difficulties for structures, traffic and human activities. Hence, further research is required to fully elucidate flow characteristics of some of those very unique local winds. In this study, important characteristics of observed vertical velocity profiles along the main wind direction for the gusty Bora wind blowing along the eastern Adriatic coast are presented. Commonly used empirical power-law and the logarithmic-law profiles are compared against unique 3-level high-frequency Bora measurements. The experimental data agree well with the power-law and logarithmic-law approximations. An interesting feature observed is a decrease in the power-law exponent and aerodynamic surface roughness length, and an increase in friction velocity with increasing Bora wind velocity. This indicates an urban-like velocity profile for smaller wind velocities and rural-like velocity profile for larger wind velocities, which is due to a stronger increase in absolute velocity at each of the heights observed as compared to the respective velocity gradient (difference in average velocity among two different heights). The trends observed are similar during both the day and night. The thermal stratification is near neutral due to a strong mechanical mixing. The differences in aerodynamic surface roughness length are negligible for different time averaging periods when using the median. For the friction velocity, the arithmetic mean proved to be independent of the time record length, while for the power-law exponent both the arithmetic mean and the median are not influenced by the time averaging period. Another issue is a large difference in aerodynamic surface roughness length when calculating using the arithmetic mean and the median. This indicates that the more robust median is a more suitable parameter to determine the aerodynamic surface roughness length than the arithmetic mean value. Variations in velocity profiles at the same site during different wind periods are interesting because, in the engineering community, it has been commonly accepted that the aerodynamic characteristics at a particular site remain the same during various wind regimes.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.3
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• pp.442-450
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• 2015

Climate temperature affects animal production. This study was conducted to evaluate whether climatic conditions affect beef carcass characteristics of Korean cattle steers. The monthly carcass characteristics of Korean cattle steers (n = 2,182,415) for 8 yr (2006 through 2013) were collected from the Korean Institute for Animal Products Quality Evaluation. Daily climate temperature (CT) and relative humidity (RH) data were collected from the Korean Meteorological Administration. Weather conditions in South Korea during summer were hot and humid, with a maximum temperature of $28.4^{\circ}C$ and a maximum RH of 91.4%. The temperature-humidity index (THI), calculated based on CT and RH, ranges from 73 to 80 during summer. Winter in South Korea was cold, with a minimum temperature of $-4.0^{\circ}C$ and a wind-chill temperature of $-6.2^{\circ}C$. Both marbling score (MS) and quality grade (QG) of Korean cattle steer carcasses were generally best (p<0.05) in autumn and worst in spring. A correlation analysis showed that MS and QG frequencies were not associated (p>0.05) with CT. Yield grade (YG) of Korean cattle steer carcasses was lowest (p<0.05) in winter (November to January) and highest in spring and summer (May to September). A correlation analysis revealed that YG frequency was strongly correlated ($r{\geq}0.71$; p<0.01) with CT and THI values. The rib eye area, a positive YG parameter, was not associated with CT. Backfat thickness (BT), a negative YG factor, was highest in winter (November and December). The BT was strongly negatively correlated ($r{\leq}-0.74$; p<0.01) with CTs. Therefore, the poor YG during winter is likely due in part to the high BT. In conclusion, YG in Korean cattle steer carcasses was worst in winter. QGs were not associated with winter or summer climatic conditions.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.293-296
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• 2008

Land surface Temperature (LST) is a very useful surface parameter for the wide range of applications, such as agriculture, numerical and climate modelling community. Whereas operational observation of LST is far from the needs of application community in the spatial Itemporal resolution and accuracy. So, we developed split-window type LST retrieval algorithm to estimate the LST from MTSAT-IR data. The coefficients of split-window algorithm were obtained by means of a statistical regression analysis from the radiative transfer simulations using MODTRAN 4 for wide range of atmospheric profiles, satellite zenith angle and lapse rate conditions including the surface inversions. The sensitivity analysis showed that the LST algorithm reproduces the LST with a reasonable quality. However, the LST algorithm overestimates and underestimates for the strong surface inversion and superadiabatic conditions especially for the warm temperature, respectively. And the performance of LST algorithms is superior when satellite zenith angle is small. The accuracy of the retrieved LST has been evaluated with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST data. The validation results showed that the correlation coefficients and RMSE are about 0.83${\sim}$0.98 and 1.38${\sim}$4.06, respectively. And the quality of LST is significantly better during night and winter time than during day and summer. The validation results showed that the LST retrieval algorithm could be used for the operational retrieval of LST from MTSAT-IR and COMS(Communication, Ocean and Meteorological Satellite) data with some modifications.

• Journal of Korea Water Resources Association
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• v.49 no.2
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• pp.165-175
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• 2016

In order to examine the applicability, the evaporation estimation approaches based on solar radiation are classified into 3 different model groups (Model groups A, B, and C) in this study. Each group is tested in the 6 study stations (Seoul, Daejeon, Jeonju, Busan, Mokpo, and Jeju). The model parameters of each model group are estimated and verified with measured pan evaporation data. The applicability of verified model groups are compared with results of Penman (1948) combination approach. Nash-Sutcliffe (N-S) efficiency coefficients greater than 0.663 in all study stations indicate satisfactory estimates of evaporation. On the other hand, in the model verification process, N-S efficiency coefficients greater than 0.526 in all study stations indicate also satisfactory estimates of evaporation. However, N-S efficiency coefficients in all study cases except Model groups B and C in Busan are less than those of Penman (1948) combination approach. Therefore, it is concluded in this study that the evaporation estimation approaches based on solar radiation have capability to replace Penman (1948) combination approach for the estimation of evaporation in case that some meteorological data (wind speed, relative humidity) are missing or not measured.

• Journal of the Korean Geographical Society
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• v.44 no.5
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• pp.605-623
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• 2009

This study is aimed to classify rainfall regions in Pakistan. Classification of rainfall regions is essential to understand rainfall patterns in Pakistan. Rainfall patterns have been investigated using a factor and cluster analysis technique by 10-days rainfall parameter. The data used here have been obtained from 32 specific weather stations of PMD (Pakistan Meteorological Department) for the period of January 1980 to December 2006. The results obtained from factor analysis provide three factors and these three factors accounts for 94.60% of the total variance. For a better understanding of rainfall regions, cluster analysis method has been applied. The clustering procedure is based on the Wards method algorithm. Overall, these rainfall regions have been divided into six groups. The boundary of the region is determined by the topology such as Baluchistan plateau, Indus plain, Hindu Kush and Himalaya ranges.

• Journal of Korea Water Resources Association
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• v.37 no.9
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• pp.737-744
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• 2004

In this study, to evaluate the effect of forest vegetation on the long-term water balance in a watershed, semi-distributed and physically based parameter model, SWAT was applied to the Bocheong watershed, and the variation of hydrological components such as evapotranspiration, surface flow, lateral flow, base flow, and total runoff was investigated with coniferous and deciduous forests, respectively. First, SWAT model was modified to simulate the actual plant growth pattern of coniferous trees which have the uniform value of leaf area index all the seasons of the year. The modified model was applied to the watershed that is assumed to have only one land cover in the whole watershed, and the variation of the water balance components was investigated for each land cover. It was found that coniferous forest affected the increase in evapotranspiration and decrease in runoff more than deciduous forest. However, the age and the density of stand, the location, and soil characteristics and meteorological conditions including the tree species should be also considered to examine the effect more quantitatively and to reduce the uncertainties in simulated output from the hydrological model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.626-628
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• 2018

In this paper, we compare the performances of SVM (Support Vector Machine) and ANN (Artificial Neural Network) machine learning models for predicting solar energy by using meteorological data. Two machine learning models were built by using fifteen kinds of weather data such as long and short wave radiation average, precipitation and temperature. Then the RBF (Radial Basis Function) parameters in the SVM model and the number of hidden layers/nodes and the regularization parameter in the ANN model were found by experimental studies. MAPE (Mean Absolute Percentage Error) and MAE (Mean Absolute Error) were considered as metrics for evaluating the performances of the SVM and ANN models. Sjoem Simulation results showed that the SVM model achieved the performances of MAPE=21.11 and MAE=2281417.65, and the ANN model did the performances of MAPE=19.54 and MAE=2155345.10776.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.721-727
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• 2002

Precipitation evapotranspiration and runoff are three key parameters of regional water balance. Problems exist in the traditional methods for calculating such factors , such as explaining of the geographic rationality of spatial interpolating methods and lacking of enough observation stations in many important area for bad natural conditions. With the development of modern spatial info-techniques, new efficient shifts arose for traditional studies. Guided by theories on energy flow and materials exchange within Soil-Atmosphere-Plant Continuant (SPAC), retrieval models of key hydrological parameters were established in the Yellow River basin using CMS-5 and FengYun-2 meteorological satellite data. Precipitation and evapotranspiration were then estimated: (1) Estimating tile amount of solar energy that is absorbed by the ground with surface reflectivity, which is measured in the visible wavelength band (VIS): (2) Assessing the partitioning of the absorbed energy between sensible and latent heat with the surface temperature, which was measured in the thermal infrared band (TIR), the latent heat representing the evapotranspiration of water; (3) Clouds are identified and cloud top levels are classified using both VIS and TIR data. Hereafter precipitation will be calculated pixel by pixel with retrieval model. Daily results are first obtained, which are then processed to decade, monthly and yearly products. Precipitation model has been has been and tested with ground truth data; meanwhile, the evapotranspiration result has been verified with Large Aperture Scintillometry (LAS) presented by Wageningen University of the Netherlands. Further studies may concentrate on the application of models, i.e., establish a hydrological model of the Yellow river basin to make the accurate estimation of river volume and even monitor the whole hydrological progress.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.119-124
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• 2007

The few observed data related snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. Remote sensing technology is very effective to observe a wide area. Although many researchers have used remote sensing for snow observation, there were a few discussions on the characteristics of spatial and temporal variation. Snow cover maps were derived from NOAA AVHRR images for the winter seasons from 1997 to 2006. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation stations. Model parameters (Snow Cover Area: SCA, snow depth, Snow cover Depletion Curve: SDC) building for 5 major watersheds in South Korea. Especially SDC is important parameter of snowmelt model.