• Asian Journal of Atmospheric Environment
• /
• v.12 no.2
• /
• pp.139-152
• /
• 2018

The urban model inter-comparison study (UMICS) was conducted in order to improve the performance of air quality models (AQMs) for simulating fine particulate matter ($PM_{2.5}$) in the Greater Tokyo Area of Japan. UMICS consists of three phases: the first phase focusing on elemental carbon (UMICS1), the second phase focusing on sulfate, nitrate and ammonium (UMICS2), and the third phase focusing on organic aerosol (OA) (UMICS 3). In UMICS2/3, all the participating AQMs were the Community Multiscale Air Quality modeling system (CMAQ) with different configurations, and they similarly overestimated $PM_{2.5}$ nitrate concentration and underestimated $PM_{2.5}$ OA concentration. Various sensitivity analyses on CMAQ configurations, emissions and boundary concentrations, and meteorological fields were conducted in order to seek pathways for improvement of $PM_{2.5}$ simulation. The sensitivity analyses revealed that $PM_{2.5}$ nitrate concentration was highly sensitive to emissions of ammonia ($NH_3$) and dry deposition of nitric acid ($HNO_3$) and $NH_3$, and $PM_{2.5}$ OA concentration was highly sensitive to emissions of condensable organic compounds (COC). It was found that $PM_{2.5}$ simulation was substantially improved by using modified monthly profile of $NH_3$ emissions, larger dry deposition velocities of $HNO_3$ and $NH_3$, and additionally estimated COC emissions. Moreover, variability in $PM_{2.5}$ simulation was estimated from the results of all the sensitivity analyses. The variabilities on CMAQ configurations, chemical inputs (emissions and boundary concentrations), and meteorological fields were 6.1-6.5, 9.7-10.9, and 10.3-12.3%, respectively.

• Journal of the Korean earth science society
• /
• v.36 no.6
• /
• pp.553-566
• /
• 2015

The effects of vertical resolutions and planetary boundary layer (PBL) physics schemes in a numerical simulation with a very high resolution over the metropolitan area were investigated. The numerical experiments using the Weather Research and Forecast model were conducted from 0000 UTC 25 October to 0000 UTC 26 October 2013. We verified the numerical results against with six hourly observation data from the radiosonde at Seolleung, which was located in southern part of Seoul, and forty three auto weather systems in Seoul. In the experiments of vertical resolutions in low level atmosphere with 44, 50, and 60 layers, which are set to be subdivided particularly under 2 km height. The experiment in 60 layers, which has the highest vertical resolution in this study, showed relatively a clear diurnal variation of PBL heights. Especially, the difference of PBL heights and 10-meter wind fields were mainly seen in the area of high altitude lands for the experiments of vertical resolution. In the sensitivity experiment of PBL schemes such as asymmetric convective model-version 2 (ACM2), Yonsei University (YSU), and Mellow-Yamada-Janjic (MYJ) to the temperature, all three PBL schemes revealed lower temperature than observed profile from the radiosonde in the entire period. The experiments with YSU PBL and ACM2 PBL schemes show relatively less biased in comparison with the experiment of the MYJ PBL scheme.

• International conference on construction engineering and project management
• /
• 2013.01a
• /
• pp.397-402
• /
• 2013

In super-tall building construction projects, schedule risk factors which vertically change and are not found in the low and middle-rise building construction influence duration of a project by vertical attribute; and it makes hard to estimate activity or overall duration of a construction project. However, the existing duration estimating methods, that are based on quantity and productivity assuming activities of the same work item have the same risk and duration regardless of operation space, are not able to consider the schedule risk factors which change by the altitude of operation space. Therefore, in order to advance accuracy of duration estimation of super-tall building projects, the degree of changes of these risk factors according to altitude should be analyzed and incorporated into a duration estimating method. This research proposes a simulation model using Monte Carlo method for estimating activity duration incorporating schedule risk factors by weather conditions in a super-tall building. The research process is as follows. Firstly, the schedule risk factors in super-tall building are identified through literature and expert reviews, and occurrence of non-working days at high altitude by weather condition is identified as one of the critical schedule risk factors. Secondly, a calculating method of the vertical distributions of the weather factors such as temperature and wind speed is analyzed through literature reviews. Then, a probability distribution of the weather factors is developed using the weather database of the past decade. Thirdly, a simulation model and algorithms for estimating non-working days and duration of each activity is developed using Monte-Carlo method. Finally, sensitivity analysis and a case study are carried out for the validation of the proposed model.

• Journal of Astronomy and Space Sciences
• /
• v.24 no.4
• /
• pp.285-296
• /
• 2007

The Precipitable Water Vapor (PWV) from GPS with high resolution in terms of time and space might reduce the limitations of the numerical weather prediction (NWP) model for easily variable phenomena, such as precipitation and cloud. We have converted to PWV from Global Positioning System (GPS) data of Korea Astronomy and Space Science Institute (KASI) and Ministry of Maritime Affairs & Fisheries (MOMAF). First of all, we have selected the heavy rainfall case of having a predictability limitation in time and space due to small-scale motion. In order to evaluate the effect for GPS PWV, we have executed the sensitivity experiment with PWV from GPS data over Korean peninsula in the Weather Research & Forecasting 3-Dimensional Variational (WRF-3DVAR). We have also suggested the direction of further research for an improvement of the predictability of NWP model on the basis of this case.

• Atmosphere
• /
• v.21 no.4
• /
• pp.391-404
• /
• 2011

This study investigates the impact of cumulus parameterization scheme (CPS) with different horizontal grid sizes on the simulation of the local heavy rainfall case over the Korean Peninsula. The Weather Research and Forecasting (WRF)-based real-time forecast system of the Joint Center for High-impact Weather and Climate Research (JHWC) is used. Three CPSs are used for sensitivity experiments: the BMJ (Betts-Miller-Janjic), GD (Grell-Devenyi ensemble), and KF (Kain-Fritsch) CPSs. The heavy rainfall case selected in this study is characterized by low-level jet and low-level transport of warm and moist air. In 27-km simulations (DM1), simulated precipitation is overestimated in the experiment with BMJ scheme, and it is underestimated with GD scheme. The experiment with KF scheme shows well-developed precipitation cells in the southern and the central region of the Korean Peninsula, which are similar to the observations. All schemes show wet bias and cold bias in the lower troposphere. The simulated rainfall in 27-km horizontal resolution has influence on rainfall forecast in 9-km horizontal resolution, so the statements on 27-km horizontal resolution can be applied to 9-km horizontal resolution. In the sensitivity experiments of CPS for DM3 (3-km resolution), the experiment with BMJ scheme shows better heavy rainfall forecast than the other experiments. The experiments with CPS in 3-km horizontal resolution improve rainfall forecasts compared to the experiments without CPS, especially in rainfall distribution. The experiments with CPS show lower LCL(Lifted Condensation Level) than those without CPS at the maximum rainfall point, and weaker vertical velocity is simulated in the experiments with CPS compared to the experiments without CPS. It means that CPS suppresses convective instability and influences mainly convective rainfall. Consequently, heavy rainfall simulation with BMJ CPS is better than the other CPSs, and even in 3-km horizontal resolution, CPS should be applied to control convective instability. This conclusion can be generalized by conducting more experiments for a variety of cases over the Korean Peninsula.

• Atmosphere
• /
• v.23 no.3
• /
• pp.321-329
• /
• 2013

This study examines the effect of aerosols on the vertical invigoration of continental stratiform clouds, using a dataset of Atmospheric Radiation Measurement (ARM) Intensive Operational Period (IOP, March 2000) at the Southern Great Plains (SGP) site. To provide further support to our observation-based findings, the weather research and forecasting (WRF) sensitivity simulations with changing cloud condensation nuclei (CCN) concentrations have been carried out for the golden episode over SGP. First, cross correlation between observed aerosol scattering coefficient and cloud liquid water path (LWP) with a 160-minutes lag is the highest of r = 0.83 for the selected episode, which may be attributable to cloud vertical invigoration induced by an increase in aerosol loading. Modeled cloud fractions in a control run are well matched with the observation in the perspective of cloud morphology and lasting period. It is also found through a simple sensitivity with a change in CCN that aerosol invigoration (AIV) effect on stratiform cloud organization is attributable to a change in the cloud microphysics as well as dynamics such as the corresponding modification of cloud number concentrations, drop size, and latent heating rate, etc. This study suggests a possible cloud vertical invigoration even in the continental stratiform clouds due to aerosol enhancement in spite of a limited analysis based on a few observed continental cloud cases.

• The Korean Journal of Community Living Science
• /
• v.26 no.1
• /
• pp.115-126
• /
• 2015

The study investigates the clothes-wearing behaviors of female college students based on differences in indoor heating systems and cold sensitivity. The respondents included a total of 281 female college students living in South Korea and China. Data were analyzed through an ANOVA and, a paired t-test based on SPSS 21.0. Korean students were less dependent on winter clothing than Chinese students for the whole body parts except for the trunk. Korean students were more likely to feel coldness more but wore less clothing. Korean students' clothes-wearing behaviors with respect to coldness depended on the indoor heating system. Korean students tended to buy warmer clothing, although they preferred not to wear undergarments and tended to wear and to wear less winter clothing. Chinese students showed more active clothes-wearing behaviors to keep their feet warm. Finally, groups divided by indoor heating systems and cold sensitivity showed different clothes-wearing behaviors in comparison to those groups based only on indoor heating systems. Even in similar weather conditions, clothes-wearing behaviors for cold adaptation depended on the indoor heating systems and cold sensitivity. The results suggest that this perspective should be taken into consideration when evaluating clothes-wearing behaviors of certain groups or individuals.

• Water Engineering Research
• /
• v.6 no.2
• /
• pp.73-89
• /
• 2005

Two kinds of high resolution GCMs with the same spatial resolutions but with different schemes run by domestic and foreign agencies are used to clarify the usefulness and sensitivity of GCM for water resources applications for Korea. One is AMIP-II (Atmospheric Model Intercomparison Project-II) type GCM simulation results done by ECMWF (European Centre for Medium-Range Weather Forecasts) and the other one is AMIP-I type GCM simulation results done by METRI (Korean Meteorological Research Institute). Observed mean areal precipitation, temperature, and discharge values on 7 major river basins were used for target variables. Monte Carlo simulation was used to establish the significance of the estimator values. Sensitivity analyses were done in accordance with the proposed ways. Through the various tests, discrimination condition is sensitive for the distribution of the data. Window size is sensitive for the data variation and the area of the basins. Discrimination abilities of each nodal value affects on the correct association. In addition to theses sensitivity analyses results, we also noticed some characteristics of each GCM. For Korean water resources, monthly and small window setting analyses are recommended using GCMs.

• Journal of Korea Society of Industrial Information Systems
• /
• v.27 no.6
• /
• pp.77-93
• /
• 2022

In this study, we present an algorithm that analyzes the risk by reflecting regional characteristics for factors affected by direct and indirect damage from heavy-snow. Factors affected by heavy-snow damage by 29 regions are selected as influencing variables, and the concept of sensitivity is derived through the relationship with the amount of damage. A snow damage risk prediction model was developed using a machine learning (XGBoost) algorithm by setting weather conditions (snow cover, humidity, temperature) and sensitivity as independent variables, and setting the risk derived according to changes in the independent variables as dependent variables.

• Atmosphere
• /
• v.26 no.1
• /
• pp.111-126
• /
• 2016

In the numerical weather model, surface properties can be defined by various parameters such as terrain height, landuse, surface albedo, soil moisture, surface emissivity, roughness length and so on. And these parameters need to be improved in the Seoul metropolitan area that established high-rise and complex buildings by urbanization at a recent time. The surface roughness length map is developed from digital elevation model (DEM) and it is implemented to the high-resolution numerical weather (WISE-WRF) model. Simulated results from WISE-WRF model are analyzed the relationship between meteorological variables to changes in the surface roughness length. Friction speed and wind speed are improved with various surface roughness in urban, these variables affected to temperature and relative humidity and hence the surface roughness length will affect to the precipitation and Planetary Boundary Layer (PBL) height. When surface variables by the WISE-WRF model are validated with Automatic Weather System (AWS) observations, NEW experiment is able to simulate more accurate than ORG experiment in temperature and wind speed. Especially, wind speed is overestimated over $2.5m\;s^{-1}$ on some AWS stations in Seoul and surrounding area but it improved with positive correlation and Root Mean Square Error (RMSE) below $2.5m\;s^{-1}$ in whole area. There are close relationship between surface roughness length and wind speed, and the change of surface variables lead to the change of location and duration of precipitation. As a result, the accuracy of WISE-WRF model is improved with the new surface roughness length retrieved from DEM, and its surface roughness length is important role in the high-resolution WISE-WRF model. By the way, the result in this study need various validation from retrieved the surface roughness length to numerical weather model simulations with observation data.