• Ocean and Polar Research
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• v.38 no.2
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• pp.89-102
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• 2016

In this study, we evaluated the model performance with respect to Sea Surface Temperature (SST) and Net Heat Flux (NHF) by considering the characteristics of seasonal temperature variation and contributing factors and by analyzing heat budget terms in the Northwestern Pacific and East Asian Marginal Seas ($110^{\circ}E-160^{\circ}E$, $15^{\circ}N-60^{\circ}N$) using the HadGEM2-AO historical run. Annual mean SST of the HadGEM2-AO is about $0.065^{\circ}C$ higher than observations (EN3_v2a) from 1950 to 2000. Since 1960, the model has simulated well the long-term variation of SST and the increasing rate of SST in the model ($0.014^{\circ}C/year$) is comparable with observations ($0.013^{\circ}C/year$). Heat loss from the ocean to the atmosphere was simulated slightly higher in the HadGEM2-AO than that in the reanalysis data on the East Asian Marginal Seas and the Kuroshio region. We investigated the causes of temperature variation by calculating the heat budget equation in the two representative regions. In the central part of the Kuroshio axis ($125^{\circ}E-130^{\circ}E$, $25^{\circ}N-30^{\circ}N$: Region A), both heat loss in the upper mixed layer by surface heat flux and vertical heat advection mainly cause the decrease of heat storage in autumn and winter. Release of latent heat flux through the heat convergence brought about by the Kuroshio contributes to the large surface net heat flux. Positive heat storage rate is mainly determined by horizontal heat advection from March to April and surface net heat flux from May to July. In the central part of the subtropical gyre ($155^{\circ}E-160^{\circ}E$, $22^{\circ}N-27^{\circ}N$: Region B), unlike Region A, vertical heat advection predominantly causes the decrease of heat storage in autumn and winter. In spring and summer, surface heat flux contributes to the increase of heat storage in Region B and the period is two times longer than the period for Region A. In this season, shoaling of the mixed layer depth plays an important role in the increase of SST.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.143-154
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• 2012

As demand of water resources and attentions to changes in climate (e.g., due to ENSO) increase, long/short term prediction of precipitation is getting necessary in water planning. This research evaluated the ability of MM5 to predict precipitation in the Tampa Bay region over 23 year period from 1986 to 2008. Additionally MM5 results were statistically bias-corrected using observation data at 33 stations over the study area using CDF-mapping approach and evaluated comparing to raw results for each ENSO phase (i.e., El Ni$\tilde{n}$o and La Ni$\tilde{n}$a). The bias-corrected model results accurately reproduced the monthly mean point precipitation values. Areal average daily/monthly precipitation predictions estimated using block-kriging algorithm showed fairly high accuracy with mean error of daily precipitation, 0.8 mm and mean error of monthly precipitation, 7.1 mm. The results evaluated according to ENSO phase showed that the accuracy in model output varies with the seasons and ENSO phases. Reasons for low predictions skills and alternatives for simulation improvement are discussed. A comprehensive evaluation including sensitivity to physics schemes, boundary conditions reanalysis products and updating land use maps is suggested to enhance model performance. We believe that the outcome of this research guides to a better implementation of regional climate modeling tools in water management at regional/seasonal scale.

• Journal of Environmental Impact Assessment
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• v.19 no.2
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• pp.169-177
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• 2010

One of the most obvious climatic manifestations of urbanization in Korea is a trend towards higher air temperature. The trends of long-term annual temperature generally well describe the warming of urban areas. The increase of air temperature in urban area has been observed to the present since the meteorological observations in Korea began. The objective of this study is to explore the actual increase and the regional long-term trends of air temperature attributed to urbanization in the Korean Peninsula. Therefore, temperatures of the selected urban areas were compared with that of the surrounding rural areas, with the results varying by the application of the estimates of each region. The second objective is to separate the long-term trend of surface air temperature of global warming from urbanization and to find the actual temperature increase from urbanization in Korean peninsula. For the data analysis, daily air temperatures observed by the Korea Meteorological Administration (KMA) during between from 1961 and 2005 were used at five rural sites and cities. The re-analyzed surface air temperatures by the National Centers for Environmental Prediction (NCEP) was also carried out to compare the result from the observed air temperature in the Korean climate domain. In this study, the urban areas in Korea showed high increase rate of air temperature with $0.4^{\circ}C$ per decade during past 50 year period, while rural sites as Chupungryung with the $0.2^{\circ}C$ decadal increase rate. The analyses reflect that the urban area shows the high rate of temperature increase with $1.39^{\circ}C$ of regression value at the urban area, Seoul, and $0.43^{\circ}C$ at the rural site, Chupungnyeong during the period of 30 years. The temperature increas due to the urbanization only showed the increase range between $0.44^{\circ}C$ and $0.86^{\circ}C$, and the observed decrease in diurnal temperature range at five urban areas during the 30 years period.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.37-46
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• 2012

We tested the effects of endogenous attention and reorienting on the performance of detection task. In the classic detection paradigm of Posner and Cohen (1980), performance on target detection is measured, where target appears either on the same or difference spatial location of cue stimulus after brief period of SOA (stimulus onset asynchrony). In this study, we induced exogenous attention by manipulating predictability of cue for target, and also induced reorientation by inserting additional (reorienting) cue between initial cue and target. Experiment 1 had three conditions of reorienting speed: Early, middle, and late. Facilitation and IOR (inhibition of return) occurred in different forms depending on SOA and reorienting speed, but we were not able to discover interpretable pattern in the results. However, reanalysis of early reorienting condition revealed that facilitation and IOR occurred in a crossed manner where short SOA found facilitation and long SOA did IOR, the typical results of simple detection task. Experiment 2 collected additional data to replicate the results in early reorienting condition of experiment 1. The results obtained that facilitation occurred with short SOA and IOR with long SOA. These results contrast with those of Wright and Richard (2000) where they reported elimination of IOR when cue had predictability of target locations. These results suggest that additional cue (here, orienting cue), which rapidly appears before extinction of IOR by prior cue, brings about double IOR. The present research demonstrates that even when attention is allocated to certain location via endogenous mechanism, rapidly repeating cues in certain location maximizes IOR that offsets the effects of endogenous attention to the same location.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.535-549
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• 2008

Vicarious calibration for the satellite sensor relies on simulated TOA (Top-of-Atmosphere) radiances over various targets. In this study, TOA visible radiance was calculated over ocean targets which are located in five different regions over the Indian and Pacific ocean, and its possible use for the satellite sensor calibration was examined. TOA radiances are simulated with the 6S radiative transfer model for the comparison with MODIS/Terra and SeaWiFS measurements. Geometric angles and sensor characteristics of the reference satellites were taken into account for the simulation. AOT (Aerosol Optical Thickness) from MODIS/Terra, pigment concentrations from Sea WiFS, and ozone amount from OMI measurements were used as inputs to the model. Other atmospheric input parameters such as surface wind and total column water vapor were taken from NCEP/NCAR reanalysis data. The 5-day averaged radiances over all targets show that the percent differences between simulated and observed radiances are within about ${\pm}5%$ in year 2005, indicating that the calculated radiances are in good agreement with satellite measurements. It has also been shown that the algorithm can produce the SeaWiFS radiances within about ${\pm}5%$ uncertainty range. It has been suggested that the algorithm can be used as a tool for calibrating the VIS bands within about 5% uncertainty range.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.1
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• pp.79-91
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• 2019

Long-term trends and recent variations of upwelling index (UI), which affects significantly ecosystem in southwestern part of the East Sea, were investigated. The UI was calculated with the NCEP/NCAR reanalysis data from January 1948 to September 2018. The mean UI has positive value that causes upwelling in April to August with a peak in July. The long-term reducing trend of UI was in statistically significant in June and July, and the sum of UI in May, June and July also showed same result. Through the atmospheric pressure analysis around the Korean peninsula, it was found that the trend of the UI was the influence of the pressure change trend in the northwestern region ($35-50^{\circ}N$, $114-129^{\circ}E$) of the southwestern part of the East Sea. Investigating UI in recent 7 years from 2012 to 2018, it was revealed that the UI was bigger than 3 times of standard deviation in July 2013. This was result from the sea level pressure difference became larger in the southwestern part of the East Sea than normal year due to the lowered air pressure in the northeastern region of China and the strengthened high air pressure of western peripheral of the North Pacific High. On the other hand, the UI in July 2018 was negative when the impact of the North Pacific High and the low air pressure in the northeastern China was weak. Due to the decreasing trend of UI and its large year-to-year variation in southwestern part of the East Sea, continuous monitoring is necessary to know the influence of coastal upwelling on the ecosystem.

• Atmosphere
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• v.30 no.4
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• pp.377-390
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• 2020

Not only emissions, but also atmospheric circulation is a key factor that affects local particulate matters (PM) concentrations in Korea through ventilation effects and transboundary transports. As part of the atmospheric circulation, air stagnation especially adversely affects local air quality due to weak ventilation. This study investigates the large-scale circulation related to air stagnation over Korea during winter and projects the climate change impacts on atmospheric patterns, using observed PM data, reanalysis and regional climate projections from HadGEM3-RA with Modified Korea Particulate matter Index. Results show that the stagnation affects the PM concentration, accompanied by pressure ridge at upper troposphere and weaken zonal pressure gradient at lower troposphere. Downscaling using HadGEM3-RA is found to yield Added-Value in the simulated low tropospheric winds. For projection of future stagnation, SSP5-8.5 and SSP1-2.6 (high and low emission) scenarios are used here. It has been found that the stagnation condition occurs more frequently by 11% under SSP5-8.5 and by 5% under SSP1-2.6 than in present-day climate and is most affected by changes in surface wind speed. The increase in the stagnation conditions is related to anticyclonic circulation anomaly at upper troposphere and weaken meridional pressure gradient at lower troposphere. Considering that the present East Asian winter monsoon is mainly affected by change in zonal pressure gradient, it is worth paying attention to this change in the meridional gradient. Our results suggest that future warming condition increase the frequency of air stagnation over Korea during winter with response of atmospheric circulation and its nonlinearity.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.584-598
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• 2019

In this study, the effects of air-sea interactions on precipitation over the Seoul-Gyeonggi region of the Korean Peninsula from 28 to 30 August 2018, were analyzed using a Regional atmosphere-ocean Coupled Model (RCM). In the RCM, a WRF (Weather Research Forecasts) was used as the atmosphere model whereas ROMS (Regional Oceanic Modeling System) was used as the ocean model. In a Regional Single atmosphere Model (RSM), only the WRF model was used. In addition, the sea surface temperature data of ECMWF Reanalysis Interim was used as low boundary data. Compared with the observational data, the RCM considering the effect of air-sea interaction represented that the spatial correlations were 0.6 and 0.84, respectively, for the precipitation and the Yellow Sea surface temperature in the Seoul-Gyeonggi area, which was higher than the RSM. whereas the mean bias error (MBE) was -2.32 and -0.62, respectively, which was lower than the RSM. The air-sea interaction effect, analyzed by equivalent potential temperature, SST, dynamic convergence fields, induced the change of SST in the Yellow Sea. In addition, the changed SST caused the difference in thermal instability and kinematic convergence in the lower atmosphere. The thermal instability and convergence over the Seoul-Gyeonggi region induced upward motion, and consequently, the precipitation in the RCM was similar to the spatial distribution of the observed data compared to the precipitation in the RSM. Although various case studies and climatic analyses are needed to clearly understand the effects of complex air-sea interaction, this study results provide evidence for the importance of the air-sea interaction in predicting precipitation in the Seoul-Gyeonggi region.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.763-774
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• 2020

Wind data forecasted from the numerical weather prediction (NWP) model is generally used as the first-guess of the target tracking process to obtain the atmospheric motion vectors(AMVs) because it increases tracking accuracy and reduce computational time. However, there is a contradiction that the NWP model used as the first-guess is used again as the reference in the AMVs verification process. To overcome this problem, model-independent first guesses are required. In this study, we propose the AMVs derivation from Lucas and Kanade optical flow method and then using it as the first guess. To retrieve AMVs, Himawari-8/AHI geostationary satellite level-1B data were used at 00, 06, 12, and 18 UTC from August 19 to September 5, 2015. To evaluate the impact of applying the optical flow method on the AMV derivation, cross-validation has been conducted in three ways as follows. (1) Without the first-guess, (2) NWP (KMA/UM) forecasted wind as the first-guess, and (3) Optical flow method based wind as the first-guess. As the results of verification using ECMWF ERA-Interim reanalysis data, the highest precision (RMSVD: 5.296-5.804 ms^-1) was obtained using optical flow based winds as the first-guess. In addition, the computation speed for AMVs derivation was the slowest without the first-guess test, but the other two had similar performance. Thus, applying the optical flow method in the target tracking process of AMVs algorithm, this study showed that the optical flow method is very effective as a first guess for model-independent AMVs derivation.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.19 no.3
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• pp.169-179
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• 2014

Monthly mean surface heat fluxes in the southeastern Yellow Sea are calculated using directly observed airsea variables from an ocean buoy station including short- and longwave radiations, and COARE 3.0 bulk flux algorithm. The calculated monthly mean heat fluxes are then compared with previous estimates of climatological monthly mean surface heat fluxes near the buoy location. Sea surface receives heat through net shortwave radiation ($Q_i$) and loses heat as net longwave radiation ($Q_b$), sensible heat flux ($Q_h$), and latent heat flux ($Q_e$). $Q_e$ is the largest contribution to the total heat loss of about 51 %, and $Q_b$ and $Q_h$ account for 34% and 15% of the total heat loss, respectively. Net heat flux ($Q_n$) shows maximum in May ($191.4W/m^2$) when $Q_i$ shows its annual maximum, and minimum in December ($-264.9W/m^2$) when the heat loss terms show their annual minimum values. Annual mean $Q_n$ is estimated to be $1.9W/m^2$, which is negligibly small considering instrument errors (maximum of ${\pm}19.7W/m^2$). In the previous estimates, summertime incoming radiations ($Q_i$) are underestimated by about $10{\sim}40W/m^2$, and wintertime heat losses due to $Q_e$ and $Q_h$ are overestimated by about $50W/m^2$ and $30{\sim}70W/m^2$, respectively. Consequently, as compared to $Q_n$ from the present study, the amount of net heat gain during the period of net oceanic heat gain between April and August is underestimated, while the ocean's net heat loss in winter is overestimated in other studies. The difference in $Q_n$ is as large as $70{\sim}130W/m^2$ in December and January. Analysis of long-term reanalysis product (MERRA) indicates that the difference in the monthly mean heat fluxes between the present and previous studies is not due to the temporal variability of fluxes but due to inaccurate data used for the calculation of the heat fluxes. This study suggests that caution should be exercised in using the climatological monthly mean surface heat fluxes documented previously for various research and numerical modeling purposes.