• Journal of Environmental Science International
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• 제18권7호
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• pp.721-733
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• 2009

To examine the fluctuations of aerosol number concentration with different size in the boundary layer of marine area during summer season, aerosol particles were assayed in the Ieodo Ocean Research Station, which is located 419 km southwest of Marado, the southernmost island of Korea, from 24 June to 4 July, 2008. The Laser Particle Counter (LPC) was used to measure the size of aerosol particles and NCEP/NCAR reanalysis data and sounding data were used to analyze the synoptic condition. The distribution of aerosol number concentration had a large variation from bigger particles more than 3 ${\mu}m$ in diameter to smaller particles more than 1 ${\mu}m$ in diameter with wind direction during precipitation. The aerosol number concentration decreased with increasing temperature. An increase (decrease) of small size of aerosol (0.3${\sim}$0.5 ${\mu}m$ in diameter) number concentration was induced by convergence (divergence) of the wind fields. The aerosol number concentration of bigger size more than 3 ${\mu}m$ in diameter after precipitation was removed as much as 89${\sim}$94% compared with aerosol number concentration before precipitation. It is considered that the larger aerosol particles would be more efficient for scavenging at marine boundary layer. In addition, the aerosol number concentration with divergence and convergence could be related with the occurrence and mechanism of aerosol in marine boundary layer.

• Korean Journal of Remote Sensing
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• 제24권6호
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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.

• Journal of the Korean Geographical Society
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• 제49권6호
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• pp.833-848
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• 2014

The assessment of the current and future climate change-induced potential wind energy is an important issue in the planning and operations of wind farm. Here, the authors analyze spatiotemporal characteristics and variabilities of wind energy over Korean Peninsula in the near future (2006-2040) using Representative Concentration Pathway(RCP) scenarios data. In this study, National Institute of Meteorological Research (NIMR) regional climate model HadGEM3-RA based RCP 2.6 and 8.5 scenarios are analyzed. The comparison between ERA-interim and HadGEM3-RA during the period of 1981-2005 indicates that the historical simulation of HadGEM3-RA slightly overestimates (underestimates) the wind energy over the land (ocean). It also shows that interannual and intraseasonal variability of hindcast data is generally larger than those of reanalysis data. The investigation of RCP scenarios based future wind energy presents that future wind energy density will increase over the land and decrease over the ocean. The increase in the wind energy and its variability is particularly significant over the mountains and coastal areas, such as Jeju island in future global warming. More detailed analysis presents that the changes in synoptic conditions over East Asia in future decades can influence on the predicted wind energy abovementioned. It is also suggested that the uncertainty of the predicted future wind energy may increase because of the increase of interannual and intra-annual variability. In conclusion, our results can be used as a background data for devising a plan to develop and operate wind farm over the Korean Peninsula.

• Ocean and Polar Research
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• 제25권4호
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• pp.503-518
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• 2003

This study examines the relationship among temperature, wind, and sea level pressure to understand recent warming in the vicinity of the Antarctic Peninsula. To do this, the surface air temperature, NCEP/NCAR reanalysis wind data and sea level pressure data for the period of 40 years are analyzed. The 40-year surface air temperature data in the Antarctic Peninsula reveals relatively the larger warming trends for autumn and winter than other seasons. The variability of the surface air temperature in this region is compared with that of the regional atmospheric circulation. The surface air temperature is positively correlated with frequency of northwesterlies and negatively correlated with frequency of southeasterlies. This relation is more evident in the northern tip of the Antarctic Peninsula for autumn and winter. The trend analysis of wind frequency in the study area shows increasing and decreasing trends in the frequency of northwesterlies and southeasterlies, respectively, in the northwestern part of the Weddell Sea for autumn and winter. And also it is found that these winds are closely related with decreasing of sea level pressure in the southeastern region of the Antarctic Peninsula. Furthermore from the seasonal variation of sea level pressure in this area, it may be presumed that decreasing of sea level pressure in the southeastern region of the Antarctic Peninsula is related with warming in the vicinity of the Antarctic Peninsula for autumn and winter. Therefore it can be explained that recent warming in the vicinity of the Antarctic Peninsula is caused by positive feedback mechanism, that is, the process that warming in the vicinity of the Antarctic Peninsula can lead to the decrease of sea level pressure in the southeastern region of the Antarctic Peninsula and these pressure decrease in turn lead to the variation of wind direction in northwestern part of Weddell Sea, again the variation of wind direction enhances the warming in the Antarctic Peninsula.

• Korean Journal of Remote Sensing
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• 제37권5_2호
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• pp.1295-1305
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• 2021

Satellite-derived ocean color products are required to effectively monitor clear open ocean and coastal water regions for various research fields. For this purpose, accurate correction of atmospheric effect is essential. Currently, the Geostationary Ocean Color Imager (GOCI)-II ground segment uses the reanalysis of meteorological fields such as European Centre for Medium-Range Weather Forecasts (ECMWF) or National Centers for Environmental Prediction (NCEP) to correct gas absorption by water vapor and ozone. In this process, uncertainties may occur due to the low spatiotemporal resolution of the meteorological data. In this study, we develop water vapor absorption correction model for the GK-2 combined GOCI-II atmospheric correction using Advanced Meteorological Imager (AMI) total precipitable water (TPW) information through radiative transfer model simulations. Also, we investigate the impact of the developed model on GOCI products. Overall, the errors with and without water vapor absorption correction in the top-of-atmosphere (TOA) reflectance at 620 nm and 680 nm are only 1.3% and 0.27%, indicating that there is no significant effect by the water vapor absorption model. However, the GK-2A combined water vapor absorption model has the large impacts at the 709 nm channel, as revealing error of 6 to 15% depending on the solar zenith angle and the TPW. We also found more significant impacts of the GK-2 combined water vapor absorption model on Rayleigh-corrected reflectance at all GOCI-II spectral bands. The errors generated from the TOA reflectance is greatly amplified, showing a large error of 1.46~4.98, 7.53~19.53, 0.25~0.64, 14.74~40.5, 8.2~18.56, 5.7~11.9% for from 620 nm to 865 nm, repectively, depending on the SZA. This study emphasizes the water vapor correction model can affect the accuracy and stability of ocean color products, and implies that the accuracy of GOCI-II ocean color products can be improved through fusion with GK-2A/AMI.

• Atmosphere
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• 제28권2호
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• pp.211-222
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• 2018

Cloud droplet activation process is well described by $K{\ddot{o}}hler$ theory and several parameterizations based on $K{\ddot{o}}hler$ theory are used in a wide range of models to represent this process. Here, we test the two different method of calculating the solute effect in the $K{\ddot{o}}hler$ equation, i.e., osmotic coefficient method (OSM) and ${\kappa}-K{\ddot{o}}hler$ method (KK). To do that, each method is implemented in the cloud droplet activation parameterization module of WRF-CHEM (Weather Research and Forecasting model coupled with Chemistry) model. It is assumed that aerosols are composed of five major components (i.e., sulfate, organic matter, black carbon, mineral dust, and sea salt). Both methods calculate similar representative hygroscopicity parameter values of 0.2~0.3 over the land, and 0.6~0.7 over the ocean, which are close to estimated values in previous studies. Simulated precipitation, and meteorological variables (i.e., specific heat and temperature) show good agreement with reanalysis. Spatial patterns of precipitation and liquid water path from model results and satellite data show similarity in general, but on regional scale spatial patterns and intensity show some discrepancy. However, meteorological variables, precipitation, and liquid water path do not show significant differences between OSM and KK simulations. So we suggest that the relatively simple KK method can be a good alternative to the OSM method that requires various information of density, molecular weight and dissociation number of each individual species in calculating the solute effect.

• Atmosphere
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• 제29권3호
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• pp.295-309
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• 2019

Due to frequent occurrence of abnormal weather, the need to improve the accuracy of subseasonal prediction has increased. Here we analyze the performance of weekly predictions out to 6 weeks by GloSea5 climate model. The performance in circulation field from January 1991 to December 2010 is first analyzed at each grid point using the 500-hPa geopotential height. The anomaly correlation coefficient and mean-square skill score, calculated each week against the ECWMF ERA-Interim reanalysis data, illustrate better prediction skills regionally in the tropics and over the ocean and seasonally during winter. Secondly, we evaluate the predictability of 7 major teleconnection patterns in the Northern Hemisphere: North Atlantic Oscillation (NAO), East Atlantic (EA), East Atlantic/Western Russia (EAWR), Scandinavia (SCAND), Polar/Eurasia (PE), West Pacific (WP), Pacific-North American (PNA). Skillful predictability of the patterns turns out to be approximately 1~2 weeks. During summer, the EAWR and SCAND, which exhibit a wave pattern propagating over Eurasia, show a considerably lower skill than the other 5 patterns, while in winter, the WP and PNA, occurring in the Pacific region, maintain the skill up to 2 weeks. To account for the model's bias in reproducing the teleconnection patterns, we measure the similarity between the teleconnection patterns obtained in each lead time. In January, the model's teleconnection pattern remains similar until lead time 3, while a sharp decrease of similarity can be seen from lead time 2 in July.

• Journal of the Korean earth science society
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• 제24권6호
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• pp.558-567
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• 2003

The regional dependency of cloud-radiative forcing at the top of atmosphere is studied using ERBE (Earth Radiation Budget Experiment), ISCCP (International Satellite Cloud Climatology Project) and NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data for 60 months from January 1985 to December 1989 over tropical ocean. In the interannual time scale, the dependency of cloud-radiative forcing on the sea surface temperature over the equatorial eastern Pacific ocean is about 7.4Wm$^{-2}$K$^{-1}$ for longwave radiation and about -4.4Wm$^{-2}$K$^{-1}$ for shortwave radiation, respectively. This shows that the net cloud-radiative forcing due to the increase of sea surface temperature over the equatorial eastern Pacific ocean heats the atmosphere. But the dependency is reversed over tropical oceans with -3.4Wm$^{-2}$K$^{-1}$ for longwave and 1.9WmWm$^{-2}$K$^{-1}$ for shortwave radiation, indicating that the net cloud-radiative forcing cools the atmosphere over tropical oceans. In raw data including seasonal cycle, the dependency of cloud-radiative forcing over the equatorial eastern Pacific ocean is very similar to that in interannual time scale in both the magnitude and the sign. But the dependency of cloud-radiative forcing on the sea surface temperature over tropical oceans is about 0.2Wm$^{-2}$K$^{-1}$ for longwave and 2.7Wm$^{-2}$K$^{-1}$ for shortwave radiation, respectively. These results represent that the role of seasonal cycle on the cloud radiative forcing is gradually more important than role of interannual time scale as the ocean area is broadening from the tropical central Pacific to the tropical ocean.

• Journal of the Korean earth science society
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• 제40권6호
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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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• 제34권2_1호
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• pp.213-225
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• 2018

In order to access the accuracy of the gridded daily Advanced Scatterometer (hereafter DASCAT) ocean surface wind data in the surrounding of Korea, the DASCAT was compared with the wind data from buoys. In addition, the reanalysis data for wind at 10 m provided by European Centre for Medium-Range Weather Forecasts (ECMWF, hereafter ECMWF), National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR, hereafter NCEP), Modern Era Retrospective-analysis for Research and Applications-2 (MERRA-2, hereafter MERRA) were compared and analyzed. As a result, the RMSE of DASCAT for the actual wind speed is about 3 m/s. The zonal components of wind of buoys and the DASCAT have strong correlation more than 0.8 and the meridional components of wind them have lower correlation than that of zonal wind and are the lowest in the Yellow Sea (r=0.7). When the actual wind speed is below 10 m/s, the EMCWF has the highest accuracy, followed by DASCAT, MERRA, and NCEP. However, under the wind speed more than 10 m/s, DASCAT shows the highest accuracy. In the nature of error according to the wind direction, when the zonal wind is strong, all dataset has the error of more than $70^{\circ}$ on the average. On the other hand, the RMSE of wind direction was recorded $50^{\circ}$ under the strong meridional winds. ECMWF shows the highest accuracy in these results. The RMSE of the wind speed according to the wind direction varied depending on the actual wind direction. Especially, MERRA has the highest RMSE under the westerly and southerly wind condition, while the NCEP has the highest RMSE under the easterly and northerly wind condition.