• Atmosphere
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• v.28 no.2
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• pp.141-151
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• 2018

The KIAPS global model and data assimilation system were extended to assimilate brightness temperature from the Sondeur $Atmosph{\acute{e}}rique$ du Profil $d^{\prime}Humidit{\acute{e}}$ Intertropicale par $Radiom{\acute{e}}trie$ (SAPHIR) passive microwave water vapor sounder on board the Megha-Tropiques satellite. Quality control procedures were developed to assess the SAPHIR data quality for assimilating clear-sky observations over the ocean, and to characterize observation biases and errors. In the global cycle, additional assimilation of SAPHIR observation shows globally significant benefits for 1.5% reduction of the humidity root-mean-square difference (RMSD) against European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) analysis. The positive forecast impacts for the humidity and temperature in the experiment assimilating SAPHIR were predominant at later lead times between 96- and 168-hour. Even though its spatial coverage is confined to lower latitudes of $30^{\circ}S-30^{\circ}N$ and the observable variable is humidity, the assimilation of SAPHIR has a positive impact on the other variables over the mid-latitude domain. Verification showed a 3% reduction of the humidity RMSD with assimilating SAPHIR, and moreover temperature, zonal wind and surface pressure RMSDs were reduced up to 3%, 5% and 7% near the tropical and mid-latitude regions, respectively.

• Asian Journal of Atmospheric Environment
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• v.11 no.3
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• pp.184-193
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• 2017

People spend the majority of their time in indoor environments. Maintaining adequate indoor temperature and humidity is necessary to support health and improve quality of life. However, people with low incomes can be vulnerable because they may not be able to use effective cooling and heating systems in their homes. In this study, the indoor temperature and humidity in low-income residences over a year in Seoul, Korea was characterized. Indoor temperature and humidity were measured in three types of homes (12 rooftop residences, 16 basement residences, and 18 public rental apartments) occupied by low-income residents. Both differed significantly among the three types of residence, particularly during the summer and winter seasons. A regression model between indoor and outdoor temperature detected a heating threshold at $3.9^{\circ}C$ for rooftop residences, $9.9^{\circ}C$ for basement residences, and $17.1^{\circ}C$ for public rental apartments. During tropical nights and cold-wave advisory days, rooftop residences showed the most extreme indoor temperatures. This study demonstrates that people living in rooftop residences could be at risk from extreme hot and cold conditions.

• Transactions of the Korean Society of Mechanical Engineers
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• v.3 no.1
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• pp.10-17
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• 1979

The exterior ballistics of small rifles mist be analyzed for the shooter and coach who are seriously interested in attainment of maximum performance in the art of rifle marksmanship. It provides also a basic reference material for the designers of rifles having better hitting rates. The exterior ballistics are computed using a state vector analysis and presented to facilitate use by individuals according to the atmospheric conditions. The ballistics are changed by the pressure, temperature and humidity of the air.

• Journal of Biosystems Engineering
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• v.36 no.2
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• pp.122-129
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• 2011

This study was performed to develop a wireless system for measuring agricultural atmospheric factors using ubiquitous sensor network(USN). In the study, temperature, humidity and light intensity were selected and evaluated as major agricultural atmospheric factors. An USN system was designed and implemented by using Zigbex I and II (mote sensor nodes of MICA series) provided by Hanback Electronics, Korea. The system was tested in a greenhouse and an orchard. The experiment results showed that the suggested USN measuring system would be very effective on comprehensive measurement of the selected factors on the basis of time, day, spatial sequence with reasonable costs.

• Microbiology and Biotechnology Letters
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• v.49 no.3
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• pp.425-431
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• 2021

The use of big data may facilitate the recognition and interpretation of causal relationships between disease occurrence and climatic variables. Considering the immense contribution of rhinoviruses in causing respiratory infections, in this study, we examined the effects of various climatic variables on the seasonal epidemiology of rhinovirus infections in the temperate climate of Cheonan, Korea. Trends in rhinovirus detection were analyzed based on 9,010 tests performed between January 1, 2012, and December 31, 2018, at Dankook University Hospital, Cheonan, Korea. Seasonal patterns of rhinovirus detection frequency were compared with the local climatic variables for the same period. Rhinovirus infection was the highest in children under 10 years of age, and climatic variables influenced the infection rate. Temperature, wind chill temperature, humidity, and particulate matter significantly affected rhinovirus detection. Temperature and wind chill temperature were higher on days on which rhinovirus infection was detected than on which it was not. Conversely, particulate matter was lower on days on which rhinovirus was detected. Atmospheric pressure and particulate matter showed a negative relationship with rhinovirus detection, whereas temperature, wind chill temperature, and humidity showed a positive relationship. Rhinovirus infection was significantly related to climatic factors such as temperature, wind chill temperature, atmospheric pressure, humidity, and particulate matter. To the best of our knowledge, this is the first study to find a relationship between daily temperatures/wind chill temperatures and rhinovirus infection over an extended period.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.163-170
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• 2011

In this paper, we analyzed the phase change of 5-triangular trihedral comer reflectors by using X-band Ground-Based Synthetic Aperture Radar (GB-SAR) system. Each reflector was set as a stationary target at a different distance from the system. We obtained total 123 full-polarization images during 40 hours continuously at 20 minute interval. Results of SAR interferometric analysis showed phase changes of maximum 2 radians and followed similar pattern with atmospheric data. Through a GB-SAR phase formula that includes refractive index in the air, we performed regression analysis for refractive index as a function of atmospheric humidity, temperature and pressure. As a result, refractive index of air in X-band showed relatively high coefficient of determination with humidity and temperature (0.72 and 0.76 on average, respectively) but not so with pressure (0.34). The refractive index of air in X -band changed by 3.14\;{\times}\;10^{-5}$ during the measuring time with a humidity range of 50% ~ 90% and a temperature range of $-1^{\circ}C$ ~ $9^{\circ}C$. We expect that a total expression of refractive index of air including humidity, temperature and pressure can be calculated when more extensive data would be collected at various atmospheric conditions.

• Journal of Environmental Health Sciences
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• v.47 no.6
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• pp.548-557
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• 2021

Background: Due to the emergence of new diseases such as COVID-19, an increasing number of people are struggling with stress and depression. Interest is growing in forest-based recreation for physical and mental relief. Objectives: A prediction model equation using meteorological factors and data was developed to predict the quantities of medicinal substances generated in forests (monoterpenes) in real-time. Methods: The concentration of phytoncide and meteorological factors in the forests near Chuncheon in South Korea were measured for nearly two years. Meteorological factors affecting the observation data were acquired through a multiple regression analysis. A model equation was developed by applying a linear regression equation with the main factors. Results: The linear regression analysis revealed a high explanatory power for the coefficients of determination of temperature and humidity in the coniferous forest (R²=0.7028 and R²=0.5859). With a temperature increase of 1℃, the phytoncide concentration increased by 31.7 ng/Sm³. A humidity increase of 1% led to an increase in the coniferous forest by 21.9 ng/Sm³. In the deciduous forest, the coefficients of determination of temperature and humidity had approximately 60% explanatory power (R²=0.6611 and R²=0.5893). A temperature increase of 1℃ led to an increase of approximately 9.6 ng/Sm³, and 1% humidity resulted in a change of approximately 6.9 ng/Sm³. A prediction model equation was suggested based on such meteorological factors and related equations that showed a 30% error with statistical verification. Conclusions: Follow-up research is required to reduce the prediction error. In addition, phytoncide data for each region can be acquired by applying actual regional phytoncide data and the prediction technique proposed in this study.

• Asian Journal of Atmospheric Environment
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• v.12 no.3
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• pp.244-254
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• 2018

Ulaanbaatar, the capital of Mongolia, is subject to high levels of atmospheric pollution during winter, which severely threatens the health of the population. By analyzing surface meteorological data, ground-based LIDAR data, and radiosonde data collected from 2008 to 2016, we studied seasonal variations in particulate matter (PM) concentration, visibility, relative humidity, temperature inversion layer thickness, and temperature inversion intensity. PM concentrations started to exceed the 24-h average standard ($50{\mu}g/m^3$) in mid-October and peaked from December to January. Visibility showed a significant negative correlation with PM concentration. Relative humidity was within the range of 60-80% when there were high PM concentrations. Both temperature inversion layer thickness and intensity reached maxima in January and showed similar seasonal variations with respect to PM concentration. The monthly average temperature inversion intensity showed a strong positive correlation with the monthly average $PM_{2.5}$ concentration. Furthermore, the temperature inversion layer thickness exceeded 500 m in midwinter and overlaid the weak mixed layer during daytime. Radiative cooling enhanced by the basin-like terrain led to a stable urban atmosphere, which strengthened particulate air pollution.

• ETRI Journal
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• v.38 no.6
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• pp.1172-1178
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• 2016

The atmospheric meteorology parameters of the earth, such as temperature, pressure, and humidity, strongly influence the propagation of signals in Global Navigation Satellite Systems (GNSSs). The propagation delays associated with GNSS signals can be modeled and explained based on the atmospheric temperature, pressure, and humidity, as well as the locations of the satellites and receivers. In this paper, we propose an optimized and simplified low cost GNSS base weather station that can be used to provide a global estimate of the integrated water vapor value. Our algorithm can be used to measure the zenith tropospheric delay based on the measured propagation delays in the received signals. We also present the results of the data measurements performed at our station located in the Tlemcen region of Algeria.

• The Journal of Internal Korean Medicine
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• v.30 no.1
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• pp.200-211
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• 2009

There are many reports about correlations between meteorological elements and stroke. In Oriental medicine, it is recognized that the weather affects the human body and diseases, but there are few studies about the correlation between meteorological elements and pattern identification of stroke. 105 stroke patients classified into fire-heat pattern or dampress-phlegm pattern were registered during the study period. We took the measurement of each meteorological element (atmospheric pressure, temperature, humidity, wind speed) according to pattern identification and analyzed pattern identification into two groups according to mean of each meteorological element during the study period. Mean temperature was higher with the heat-fire pattern than with the dampness-phlegm pattern. Heat-fire pattern also had higher frequency when temperature was higher than mean temperature. There was no correlation between atmospheric pressure, relative humidity, or wind speed and pattern identification.