• Journal of Korean Society for Atmospheric Environment
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• v.31 no.2
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• pp.181-194
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• 2015

Spatial-temporal meteorological features of the Ulsan metropolitan region (UMR) were analyzed using observations and high-resolution numerical modeling. Long-term trend analysis (1970~2013) showed a significant increase of $0.033^{\circ}Cyr^{-1}$ in the 5-year moving average temperature, although detailed short-term features varied, whereas wind speed and relative humidity over the same period displayed clear decreases of $-0.007ms^{-1}$ and $-0.29%yr^{-1}$, respectively. These trends indicate the effects of regional climate change and urbanization in the UMR. Seasonal variations averaged for the most recent three years, 2011~2013, showed that temperatures in three different regions (urban/industrial, suburban, coastal areas) of the UMR had similar seasonality, but significant differences among them were observed for a certain season. Urban and industrial complex regions were characterized by relatively higher temperatures with large differences (max.: $3.6^{\circ}C$) from that in the coastal area in summer. For wind speed, strong values in the range from 3.3 to $3.9ms^{-1}$ occurred in the coastal areas, with large differences clearly shown between the three regions in September and October. Diurnal variations of temperature were characterized by pronounced differences during the daytime (in summer) or nighttime (in winter) between the three regions. Results from the WRF modeling performed for four months of 2012 showed large variations in gridaverage temperature and winds in the UMR, which displayed significant changes by season. Especially, a clear temperature rise in the urban center was identified in July ($0.6^{\circ}C$ higher than nearby urban areas), and overall, relatively weak winds were simulated over urban and inland suburban regions in all seasons.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.173-183
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• 2014

Field survey research on damages caused by volcanic activities has plenty of difficulties due to human resources, safety and costs issues. Remote sensing application using satellite image is one of very useful tools to overcome those issues. In this study, we monitored the volcanic activities of Sinabung volcano in 2010, which is located in Sumatra island, Indonesia by using Landsat 7 ETM+ satellite images acquired on 17 April, 2009 and 30 July, 2012. We found that the area of pyroclastic flow inundation after 2010 has been tripled roughly, since extracting the pyroclastic flow inundation before and after 2010 eruption from classification. The result from modeling of pyroclastic flow inundation has been compared with the extracted pyroclastic flow inundation from Landsat 7 ETM+ images. As a result, we confirmed that the length of inundation area from the modeling was calculated to 92% accurate, but the width of inundation area was somewhat imprecisely estimated in the volcanic area having the sharp slope and only calculated to 17% accurate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2569-2575
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• 2015

Network RTK generally uses a linear interpolation method by using the corrections from reference stations. This minimizes the spatial decorrelation error caused by the increase of distance between the reference station's baseline and user's baseline. However, tropospheric delay, a function of the meteorological data can cause a spatial decorrelation characteristic among reference stations within a network by local meteorological difference. A non-linear characteristic of tropospheric delay can deteriorate Network RTK performance. In this paper, the modeling of tropospheric delay irregularity is made from the data when the typhoon is occurred. By using this modeling, analyzing the effect of meteorological difference between reference stations on correction is performed. Finally, we analyze an effect of non-linear characteristics of tropospheric delay among reference stations to Network RTK user.

• Atmosphere
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• v.28 no.4
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• pp.403-414
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• 2018

Predictability of Northern Hemisphere blocking in the Korea Meteorological Administration (KMA) Global Data Assimilation and Prediction System (GDAPS) is evaluated for the period of July 2016 to May 2017. Using the operational model output, blocking is defined by a meridional gradient reversal of 500-hPa geopotential height as Tibaldi-Molteni Index. Its predictability is quantified by computing the critical success index and bias score against ERA-Interim data. It turns out that Northwest Pacific blockings, among others, are reasonably well predicted with a forecast lead time of 2~3 days. The highest prediction skill is found in spring with 3.5 lead days, whereas the lowest prediction skill is observed in autumn with 2.25 lead days. Although further analyses are needed with longer dataset, this result suggests that Northern Hemisphere blocking is not well predicted in the operational weather prediction model beyond a short-term weather prediction limit. In the spring, summer, and autumn periods, there was a tendency to overestimate the Western North Pacific blocking.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.209-217
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• 2021

Although forest fires are more often triggered by artificial causes than by natural causes, the combustion conditions that spread forest fire damage over a large area are affected by natural phenomena. Therefore, using partial least squares structural equation modeling (PLS-SEM), which can analyze the dependent and causal relationships between various factors, this study evaluated the causal relationships and relative influences between forest fire, weather, and drought, taking Gangwon Province as our sample region. The results indicated that the impact of drought on forest fires was 27 % and that of the weather was 38 %. In addition, forest fires in spring accounted for about 60 % of total forest fires. This indicatesthat along with meteorological factors, the autumn and winter droughts in the previous year affected forest fires. In assessing the risk of forest fires, if severe meteorological droughts occur in autumn and winter, the probability of forest fires may increase in the spring of the following year.

• Journal of the Korean earth science society
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• v.24 no.5
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• pp.440-448
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• 2003

We have performed 3-D geomagnetic induction Modeling considering with anomalous conductive structures to interpret the conductive anomaly proposed by previous studies on the Korean Peninsula. The results of modeling coincide well with the observed induction arrow. we confirm the fact that Imjin River Belt and Ogcheon Belt presumed in the model are reasonable. In the western-middle area of the peninsula (YIN, ICHN) the induction arrows seem to reflect the existence for the Imjin River Belt and the induction arrows in western-south area (HNS, CHY, DZN, MWN) is likely to reflect the effect of the Ogcheon Belt. The difference arrows, calculated by subtracting the sea effect from observed induction arrow in the western area of the peninsula at the period of 60-minutes, show little difference with the observed induction arrows. Especially, the difference arrows in YIN, ICHN also show a similar pattern to those at the periods longer than 10-minutes. These results strongly suggest that the Imjin River Belt and the Ogcheon Belt extend down to the deep part of the crust in spite of the limitation of our model.

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.181-191
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• 2020

In order to produce accurate initial condition of soil moisture for global Numerical Weather Prediction (NWP), spin-up experiment is carried out using Noah Land Surface Model (LSM). The model is run repeatedly through 10 years, under the atmospheric forcing condition of 2008-2017 until climatological land surface state is achieved. Spin-up time for the equilibrium condition of soil moisture exhibited large variability across Koppen-Geiger climate classification zone and soil layer. Top soil layer took the longgest time to equilibrate in polar region. From the second layer to the fourth layer, arid region equilibrated slower (7 years) than other regions. This result means that LSM reached to equilibrium condition within 10 year loop. Also, spin-up time indicated inverse correlation with near surface temperature and precipitation amount. Initialized from the equilibrium state, LSM was spun up to obtain land surface state in 2018. After 6 months from restarted run, LSM simulates soil moisture, skin temperature and evaportranspiration being similar land surface state in 2018. Based on the results, proposed LSM spin-up system could be used to produce proper initial soil moisture condition despite updates of physics or ancillaries for LSM coupled with NWP.

• Atmosphere
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• v.32 no.3
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• pp.179-189
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• 2022

The purpose of this study is to build and evaluate a high-resolution (50 m) KMAPP (Korea Meteorological Administration Post Processing) reflecting building data. KMAPP uses LDAPS (Local Data Assimilation and Prediction System) data to detail ground wind speed through surface roughness and elevation corrections. During the detailing process, we improved the vegetation roughness data to reflect the impact of city buildings. AWS (Automatic Weather Station) data from a total of 48 locations in the metropolitan area including Seoul in 2019 were used as the observation data used for verification. Sensitivity analysis was conducted by dividing the experiment according to the method of improving the vegetation roughness length. KMAPP has been shown to improve the tendency of LDAPS to over simulate surface wind speeds. Compared to LDAPS, Root Mean Square Error (RMSE) is improved by approximately 23% and Mean Bias Error (MBE) by about 47%. However, there is an error in the roughness length around the Han River or the coastline. Accordingly, the surface roughness length was improved in KMAPP and the building information was reflected. In the sensitivity experiment of improved KMAPP, RMSE was further improved to 6% and MBE to 3%. This study shows that high-resolution KMAPP reflecting building information can improve wind speed accuracy in urban areas.

• Atmosphere
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• v.34 no.4
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• pp.445-462
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• 2024

This study analyzes and compares the results of airborne snowfall enhancement experiments conducted on November 25 and 28, 2019, as part of the International Joint Cloud Observation and Weather Control Experiment (IJCO-WCE) 2019 campaign. The objective was to assess the effects of experimental interventions on cloud precipitation patterns. To address the challenges in verifying artificial snowfall enhancement, this study proposes an innovative approach, utilizing a post-experiment zigzag flight path for in-situ observations. This approach allowed for detailed comparisons between affected and unaffected cloud regions. Precipitation was observed in the target area on the leeward side on November 25, whereas no precipitation was recorded during the November 28 experiment. We concluded that airborne snowfall enhancement is more effective when the lower atmosphere is unstable at the rear of a trough, as confirmed by changes in the distribution of precipitation particles in the clouds and on the ground. Two identical flight experiments were conducted using the KMA/NIMS atmospheric research aircraft, allowing detailed observations. Data collected from onboard cloud observation instruments and six ground stations facilitated detailed analyses of changes in the concentration and size distribution of cloud particles (e.g., supercooled droplets, ice crystals, and snow particles). The method of comparing particle sizes between clouds affected and unaffected by the experiments is used to verify the effectiveness of artificial snowfall enhancement techniques. This methodology could be widely adopted in future studies to improve our understanding of weather modification strategies.

• Journal of the Korean earth science society
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• v.42 no.4
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• pp.390-400
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• 2021

Ocean biogeochemistry plays a crucial role in sustaining the marine ecosystem and global carbon cycle. To investigate the oceanic biogeochemical responses to iron parameters in the tropical Pacific, we conducted sensitivity experiments using the Nucleus for European Modelling of the Ocean-Tracers of Ocean Phytoplankton with Allometric Zooplankton (NEMO-TOPAZ) model. Compared to observations, the NEMO-TOPAZ model overestimated the concentrations of chlorophyll and dissolved iron (DFe). The sensitivity tests showed that with increasing (+50%) iron scavenging rates, chlorophyll concentrations in the tropical Pacific were reduced by approximately 16%. The bias in DFe also decreased by approximately 7%; however, the sea surface temperature was not affected. As such, these results can facilitate the development of the model tuning strategy to improve ocean biogeochemical performance using the NEMO-TOPAZ model.