• Atmosphere
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• v.23 no.1
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• pp.39-45
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• 2013

A parameterization for the scattering of longwave radiation by ice clouds has been developed based on spectral scattering property calculations with shapes and sizes of ice crystals. For this parameterization, the size distribution data by Fu (1996) and by Michell and Arnott (1994) are used. The shapes of ice crystal considered in this study are plate, solid column, hollow column, bullet-rosette, droxtal, aggregate, and spheroid. The properties of longwave scattering by ice crystals are presented as a function of the extinction coefficient, single-scattering albedo, and asymmetry factor. The heating rate and flux by the radiative parameterization model are calculated for wide range of ice crystal sizes, shapes, and optical thickness. The results are compared with the calculated results using a six-stream discrete ordinate scattering algorithm and Chou's method. The new method (with various habits and size distributions) provides a good simulation of the scattering properties and cooling rate in optically thin clouds (optical thickness < 5). Depending on the inclusion of scattering by ice clouds, the errors in the calculation of the cooling rates are significantly different.

• Journal of Astronomy and Space Sciences
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• v.26 no.4
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• pp.643-650
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• 2009

Korea Astronomy and Space Science Institute (KASI) has been developing one mobile and one stationary SLR system since 2008 named as ARGO-M and ARGO-F, respectively. KASI finished the step of deriving the system requirements of ARGO. The requirements include definitions and scopes of various software and hardware components which are necessary for developing the ARGO-M operation system. And the requirements define function, performance, and interface requirements. The operation system consisting of ARGO-M site, ARGO-F site, and Remote Operation Center (ROC) inside KASI is designed for remote access and the automatic tracking and control system which are the main operation concept of ARGO system. To accomplish remote operation, we are considering remote access to ARGO-F and ARGO-M from ROC. The mobile-phone service allows us to access the ARGO-F remotely and to control the system in an emergency. To implement fully automatic tracking and control function in ARGO-F, we have investigated and described the requirements about the automatic aircraft detection system and the various meteorological sensors. This paper addresses the requirements of ARGO Operation System.

• KIEAE Journal
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• v.3 no.1
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• pp.5-12
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• 2003

Using the wind, we can get a thermal comfort in summer. In winter we must shut out the wind. To achieve sustainable environmental building design, especially wind data is very important. The wind direction and wind velocity of 32 cities were analyzed to suggest the wind map of Korea. The weather data which was used in this paper was from National Weather Service(19711.1~2000.12.31). The results of this study are 1) The monthly wind velocity of Seoul is 1.1m/s-3.8m/s. 2) The maximum wind velocity could be estimated from the annual average wind velocity. The regression curve is Y(The maximum wind velocity)=6.369732 X(annual average wind velocity) + 6.391668 (P< 9.66E-12). 3) The wind velocity at the inland area which is far from 25km sea side is smaller than coastal area. The distance from the sea is major index of wind velocity. 4) The monthly wind direction was compared inland area with coastal area. 5) The uniform-velocity line on the Korean map was obtained.

• Wind and Structures
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• v.31 no.4
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• pp.299-309
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• 2020

In this study, wind data such as speeds, loads and potential of Muğla which is located in the southwest of Turkey were statistically analyzed. The wind data which consists of hourly wind speed between 2010 and 2013 years, was measured at the 10-meters height in four different ground stations (Datça, Fethiye, Marmaris, Köyceğiz). These stations are operated by The Turkish State Meteorological Service (T.S.M.S). Furthermore, wind data was analyzed by using Log-Normal and Gamma distributions, since these distributions fit better than Weibull, Normal, Exponential and Logistic distributions. Root Mean Squared Error (RMSE) and the coefficients of the goodness of fit (R²) were also determined by using statistical analysis. According to the results, extreme wind speed in the research area was 33 m/s at the Datça station. The effective wind load at this speed is 0.68 kN/㎡. The highest mean power densities for Datça, Fethiye, Marmaris and Köyceğiz were found to be 46.2, 1.6, 6.5 and 2.2 W/㎡, respectively. Also, although Log-normal distribution exhibited a good performance i.e., lower AD (Anderson - Darling statistic (AD) values) values, Gamma distribution was found more suitable in the estimation of wind speed and power of the region.

• Atmosphere
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• v.24 no.4
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• pp.471-479
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• 2014

A road surface temperature prediction model (UM-Road) using input data of the Unified Model (UM) output and road physical properties is developed and verified with the use of the observed data at road weather information system. The UM outputs of air temperature, relative humidity, wind speed, downward shortwave radiation, net longwave radiation, precipitation and the road properties such as slope angles, albedo, thermal conductivity, heat capacity at maximum 7 depth are used. The net radiation is computed by a surface radiation energy balance, the ground heat flux at surface is estimated by a surface energy balance based on the Monin-Obukhov similarity, the ground heat transfer process is applied to predict the road surface temperature. If the observed road surface temperature exists, the simulated road surface temperature is corrected by mean bias during the last 24 hours. The developed UM-Road is verified using the observed data at road side for the period from 21 to 31 March 2013. It is found that the UM-Road simulates the diurnal trend and peak values of road surface temperature very well and the 50% (90%) of temperature difference lies within ${\pm}1.5^{\circ}C$ (${\pm}2.5^{\circ}C$) except for precipitation case.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.185-193
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• 2008

In spite of rapid development of IT-related meteorology and services, human users still ought to check the weather information manually as they did before because traditional weather information retrieval is based on pull-type and human interpretation. Furthermore, the automatic machine-driven weather information processing has been neglected for a long time although the intelligent weather information processing is expected to be very useful for personal daily life and ubiquitous computing. In this paper, we discussed a design of GRIB based ontology to enable smart weather information processing. GRIB is the general purposed and world-wildly used weather data format approved by the World Meteorological Organization. With the designed ontology and the inference system containing Jess engine, several intelligent weather applications have been implemented and tested to verify the virtue of machine-driven weather information processing.

• Atmosphere
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• v.29 no.5
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• pp.659-669
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• 2019

This study assesses the quality of the total column ozone (TCO) data from five reanalysis datasets against nine independent observation in East Asia. The assessed datasets are the ECMWF Interim reanalysis (ERAI), Monitoring Atmosphere Composition and Climate reanalysis (MACC), Copernicus Atmosphere Monitoring Service reanalysis (CAMS), the NASA Modern-Era Retrospective analysis for Research and Applications, Version2 (MERRA2), and NCEP Climate Forecast System Reanalysis (CFSR). All datasets reasonably well capture the spatial distribution, annual cycle and interannual variability of TCO in East Asia. In particular, characteristics of TCO according to the latitude difference were similar at all points with a maximum bias of less than about 4%. Among them, CAMS and CFSR show the smallest mean bias and root-mean square error across all nine ground-based observations. This result indicates that while TCO data in modern reanalyses are reasonably good, CAMS and CFSR TCO data are the best for analysing the spatio-temporal variability and change of TCO in East Asia.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.623-625
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• 2018

As the issue of particulate matter spreads, services for providing particulate matter information in real time are increasing. However, when a sensor node for collecting particulate matter is defective, a corresponding service may not be provided. To solve these problems, it is necessary to predict and deduce particulate matter. In this paper, a particulate matter prediction model is designed using artificial neural network algorithm based on past particulate matter and meteorological data to predict particulate matter. Also, the prediction results are compared by learning the input data of the model in the design stage.

• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.337-341
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• 2016

Purpose: Evaluation of atmospheric conditions for proper timing of spray application is important to prevent off-target movement of crop protection materials. Susceptible crops can be damaged downwind if proper application procedure is not followed. In our previous study, hourly data indicated unfavorable conditions, primarily between evening 18:00 hrs in the evening and 6:00 hrs next morning, during clear conditions in the hot summer months in the Mississippi delta. With the requirement of timely farm operations, sub-hourly data are required to provide better guidelines for pilots, as conditions of atmospheric stability can change rapidly. Although hourly data can be interpolated to some degree, finer resolution for data acquisition of the order of 15 min would provide pilots with more accurate recommendations to match the data recording frequency of local weather stations. Methods: In the present study, temperature and wind speed data obtained at a meteorological tower were re-sampled to calculate the atmospheric stability ratio for sub-hour and hourly recommendations. High-precision evaluation of temperature inversion periods influencing atmospheric stability was made considering strength, time of occurrence, and duration of temperature inversion. Results and Discussion: The results indicated that atmospheric stability could be determined at different time intervals providing consistent recommendations to aerial applicators, thereby avoiding temperature inversion with minimal off-target drift of the sprayed liquid.

• Journal of Astronomy and Space Sciences
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• v.32 no.1
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• pp.39-44
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• 2015

It is well known that the space radiation dose over the polar route should be carefully considered especially when the space weather shows sudden disturbances such as CME and flares. The National Meteorological Satellite Center (NMSC) and Korea Astronomy and Space Science Institute (KASI) recently established a basis for a space radiation service for the public by developing a space radiation prediction model and heliocentric potential (HCP) prediction model. The HCP value is used as a critical input value of the CARI-6 and CARI-6M programs, which estimate the aviation route dose. The CARI-6/6M is the most widely used and confidential program that is officially provided by the U.S. Federal Aviation Administration (FAA). The HCP value is given one month late in the FAA official webpage, making it difficult to obtain real-time information on the aviation route dose. In order to overcome this limitation regarding time delay, we developed a HCP prediction model based on the sunspot number variation. In this paper, we focus on the purpose and process of our HCP prediction model development. Finally, we find the highest correlation coefficient of 0.9 between the monthly sunspot number and the HCP value with an eight month time shift.