• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.36.3-37
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• 2009

This is an attempt to improve a formula to predict variations of geomagnetic storm indices (Dst) from solar wind parameters. A formula which is most widely accepted was given by Burton et al. (1975) over 30 years ago. Their formula is: dDst*/dt = Q(t) - Dst*(t)/$\tau$, where Q(t) is the Dst injection rate given by the convolution of dawn-to-dusk electric field generated by southward solar wind magnetic field and some response function. However, they did not clearly specify the response function. As a result, misunderstanding seems to be prevailing that the injection rate is proportional to the dawn-to-dusk electric field. In this study we tried to determine the response function by examining 12 intense geomagnetic storms with minimum Dst < -200 nT for which solar wind data are available. The method is as follows. First we assume the form of response function that is specified by several time constants, so that we can calculate the injection rate Q1(t) from the solar wind data. On the other hand, Burton et al. expression provide the observed injection rate Q2(t) = dDst*/dt + Dst*(t)/$\tau$. Thus, it is possible to determine the time constants of response function by a least-squares method to minimize the difference between Q1(t) and Q2(t). We have found this simple method successful enough to reproduce the observed Dst variations from the corresponding solar wind data. The present result provides a scheme to predict the development of Dst 30 minutes to 1 hour in advance by using the real time solar wind data from the ACE spacecraft.

• Atmosphere
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• v.29 no.5
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• pp.567-583
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• 2019

In this study, the high-resolution numerical simulations considering detailed anthropogenic heat, albedo, emission and roughness length are analyzed by using single layer Urban Canopy Model (UCM) in Weather Research Forecast (WRF). For this, improved urban parameter data for Seoul Metropolitan Area (SMA) was collected from global data. And then the parameters were applied to WRF-UCM model after it was processed into 2-dimensional topographical data. The 6 experiments were simulated by using the model with each parameter and verified against observation from Automated Weather Station (AWS) and flux tower for the temperature and sensible heat flux. The data for sensible heat flux of flux towers on Jungnang and Bucheon, the temperature of AWS on Jungnang, Gangnam, Bucheon and Neonggok were used as verification data. In the case of summer, the improvement of simulation by using detailed anthropogenic heat was higher than the other experiments in sensible flux simulation. The results of winter case show improved in all simulations using each advanced parameters in temperature and sensible heat flux simulation. Improvement of urban parameters in this study are possible to reflect the heat characteristics of urban area. Especially, detailed application of anthropogenic heat contributed to the enhancement of predicted value for sensible heat flux and temperature.

• Korean Journal Plant Pathology
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• v.14 no.4
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• pp.331-338
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• 1998

To develop the model for prediction of potato late blight progress, the relationship between severity index of potato late blight transformed by the logit and Gompit transformation function and cumulative severity value (CSV) processing weather data during growing period in Taegwallyeong alpine area, 1975 to 1992 were examined. When logistic model and Gompertz model were compared by determining goodness of fit for progressive degree of late blight using CSV as independent variable, the coefficients of determination were higher as 0.742 in the logistic model than 0.680 in the Gompertz model. Parameters in logistic model were composed of progressive rate and initial value of logistic model. Initial value was calculated in -3.664. The progressive rate of potato late blight was 0.137 in cv. Superior, 0.136 in cv. Irish Cobbler, and 0.070 in cv. Jopung without fungicide sprays. According to in crease of the number of spray times the progressive rate was lowered, was 0.020 in cv. Superior under the conventional program of fungicide sprays, 10 times sprays during cropping season. Equation of progressive rate, b1=0.0088 ACSV-0.033 (R2=0.976), was written by examining the relationship between the parameters of progressive rate of late blight and the average CSV (ACSV) quantifing weather information. By estimating parameters of logistic function, model able to describe the late blight progress of potato, cv. Superior was formulated in Y=4/(1+39.0·exp((0.0088 ACSV-0.033)·CSV).

• Journal of Environmental Science International
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• v.31 no.6
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• pp.515-524
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• 2022

This study investigated characteristics of meteorological parameters and ionic components of PM_2.5 during Asian dust events on November 28 and 30, 2018 at Busan, Korea. The seasonal occurrence frequencies of Asian dust during 1960~2019 (60 years) were 81.7% in spring, 12.2% in winter, and 6.1% in autumn. Recently, autumn Asian dust occurrence in Busan has shown an increasing trend. The result of AWS (automatic weather station), surface weather chart, and backward trajectory analyses showed that the first Asian dust of Nov. 28, 2018, in Busan came with rapid speed through inner China and Bohai Bay from Mongolia. The second Asian dust of Nov. 30, 2018, in Busan seems to have resulted from advection and deposition of proximal residual materials. These results indicated that understanding the characteristics of meteorological parameters and ionic components of PM_2.5 during Asian dust events could provide insights into establishing a control strategy for urban air quality.

• Journal of the Korean Solar Energy Society
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• v.29 no.5
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• pp.81-87
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• 2009

Computer simulation of buildings and solar energy systems is being used increasingly in energy assessments and design.. Building designers often now predict the performance of buildings simulation programmes that require hourly weather data. However, not all weather stations provide hourly data. Climate prediction models such as HadCM3 also provide the daily average dry bulb temperature as well as the maximum and minimum. Hourly temperature values are available for building thermal simulations that accounts for future changes to climate. In order to make full use of these predicted future weather data in building simulation programmes, algorithms for downscaling daily values to hourly values are required. This paper describes a more accurate method for generating hourly temperature values in the South Korea that uses all three temperature parameters from climate model. All methods were evaluated for accuracy and stability in terms of coefficient of determination and cumulative error. They were compared with hourly data collected in Seoul and Ulsan, South Korea.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.40.4-40.4
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• 2019

Interplanetary coronal mass ejections (ICMEs) are regarded as one of the most powerful sources of space weather disturbances observed near the Earth orbit (1 AU). In this study, we aim at investigating the relation between these disturbances and the physical properties of an ICME. Toward this end, we used an spheromak-type ICME and performed a series of three-dimensional magnetohydrodynamic (MHD) simulations with different sets of ICME parameters. The ICME is injected into the background solar wind generated from near-Sun data and interplanetary scintillation (IPS) data via an MHD-IPS tomography method. We will compare simulation results to in situ observations near the Earth and discuss how the physical properties of an ICME affect the space weather disturbances at 1 AU.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.573-581
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• 2020

Using CCTV images and weather parameters, a method for estimating PM (Particulate Matter) index was proposed, and an experiment was conducted. For CCTV images, we proposed a method of estimating the PM index by applying a deep learning technique based on a CNN (Convolutional Neural Network) with ROI(Region Of Interest) image including a specific spot and an full area image. In addition, after combining the predicted result values by deep learning with the two weather parameters of humidity and wind speed, a post-processing experiment was also conducted to calculate the modified PM index using the learned regression model. As a result of the experiment, the estimated value of the PM index from the CCTV image was R2(R-Squared) 0.58~0.89, and the result of learning the ROI image and the full area image with the measuring device was the best. The result of post-processing using weather parameters did not always show improvement in accuracy in all cases in the experimental area.

• Solar Energy
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• v.18 no.3
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• pp.31-39
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• 1998

Selection of a right weather data set has been considered as one of important factors for a successful building energy audit process. A set of 30 year raw weather data base for six major cities has been developed to provide the weather data file for building energy audit and retrofit analysis in Korea. The program named as KWDP(KIER Weather Data Processor) uses the DB to produce a right data set for a specific building energy performance simulation program like DOE2.1E. A program called WMAKE has been developed to generate the right set of input parameters for DOE2.1E weather utility program. The set of the programs could provide the right weather data for specific building energy audit and retrofit analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1090-1098
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• 2018

Many short range weather radars with the low elevation search capability are needed for analysis and prediction of unusual weather changes or rainfall phenomena which occurs regionally. However, due to the characteristics of low elevation electromagnetic wave beam, it is highly probable that the received weather signals of these radars are seriously contaminated by the ground clutter. Therefore, the filter removing low Doppler frequency band is generally used to mitigate this problem. However, the phase noise in a radar system may limit the removal of the strong clutter and this may cause serious problems in estimating weather parameters because of the remaining clutter. Therefore, in this paper, the characteristics of phase noise in a radar system are investigated and the effects of the system phase noise are analyzed in the improvement of signal to clutter ratio for the strong clutter environment such as a short and low-elevated weather radar.

• Journal of Astronomy and Space Sciences
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• v.31 no.2
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• pp.149-157
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• 2014

As the prediction of geomagnetic storms is becoming an important and practical problem, conditions in the Earth's magnetosphere have been studied rigorously in terms of those in the interplanetary space. Another approach to space weather forecast is to deal with it as a probabilistic geomagnetic storm forecasting problem. In this study, we carry out detailed statistical analysis of solar wind parameters and geomagnetic indices examining the dependence of the distribution on the solar cycle and annual variations. Our main findings are as follows: (1) The distribution of parameters obtained via the superimposed epoch method follows the Gaussian distribution. (2) When solar activity is at its maximum the mean value of the distribution is shifted to the direction indicating the intense environment. Furthermore, the width of the distribution becomes wider at its maximum than at its minimum so that more extreme case can be expected. (3) The distribution of some certain heliospheric parameters is less sensitive to the phase of the solar cycle and annual variations. (4) The distribution of the eastward component of the interplanetary electric field BV and the solar wind driving function BV2, however, appears to be all dependent on the solar maximum/minimum, the descending/ascending phases of the solar cycle and the equinoxes/solstices. (5) The distribution of the AE index and the Dst index shares statistical features closely with BV and $BV^2$ compared with other heliospheric parameters. In this sense, BV and $BV^2$ are more robust proxies of the geomagnetic storm. We conclude by pointing out that our results allow us to step forward in providing the occurrence probability of geomagnetic storms for space weather and physical modeling.