On 20 January 2017, the fresh snow cover which is more than 20 cm, accompaning with lightning occurred over Yeongdong coastal region for the first 3-hour of the heavy snowfall event. This study analyzed sounding observations in the heavy snow period which were including the measurements of wind profiler, radiometer and rawinsonde. The features examined from the vertical wind and temperature data at the two adjacent stations, Bukgangneung and Gangneung-Wonju National University, are summarized as follows: 1) The strong (30-40 kts) north-east winds were observed in the level from 2 to 6 km. The Strong atmospheric instability was found from 4 to 6 km, in which the lapse rate of temperature was about $-18^{\circ}C\;km^{-1}$. These features indicate that the deep convective cloud develops up to the height of 6 km in the heavy snowfall period, which is shown in the satellite infrared images. 2) The cooling was observed in the level below 1 km. At this time, the surface air temperature at Bukgangneung station decreased by $4^{\circ}C$. The narrow cooling zone estimated from AWS and buoy data was located in east-west direction. These are the features observed in the cold front of extratropical cyclone. The distributions of radar echo and lightning also show the same shape in east-west direction. Therefore, the results indicate that the Yeongdong thundersnow event was the combined precipitation system of deep convective cloud and cold frontal precipitation.
Journal of the Korean Association of Geographic Information Studies
/
v.9
no.3
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pp.82-92
/
2006
As beaches throughout Korea have suffered great losses of sand due to artificial developments and meteorological phenomena, particularly typhoons, it is necessary to monitor beaches that are prone to erosion continuously, establish and enforce a comprehensive plan to attack coastal erosion with the object of the long-term management. However, debates and temporary measures, not based on accurate coastal zone surveys and analyses, have been established up to now. Therefore, with Haeundae sand beach as a case study, we proposed methods to collect accurate spatial data of the coastline and the sand beach through GPS survey. And we detected and analyzed topographic changes resulting from Typhoon Nabi quantitatively and qualitatively, by using GIS technique. Results showed a mean elevation of 1.95 m, a total area of 53,441 $m^2$, and a total volume of 104,639 $m^3$ after Typhoon Nabi. Mean elevation rose 0.06 m between the pre- and the post-typhoon surveys by a protective shore wall. However, strong winds and north-northeast surges brought by the typhoon caused erosion of the area and the volume, by 3,096 $m^2$ and 2,320 $m^3$. Accurate spatial databases of coastal zones based on integrated GPS GIS techniques and quantitative and qualitative analyses of topographical changes will help Korea develop systematic and effective countermeasures against coastal erosion.
Ocean-air observation using an Automatic Weather Station (AWS) and Conductivity Temperature Depth (CTD) was conducted in the Mid-Yellow Sea off Korea during 8-10 July 2002. A water mass lower than 17$^{\circ}C$ around the Taean peninsula and a tidal front between 36$^{\circ}$20'N and 36$^{\circ}$30'N were observed. The horizontal distribution of air temperature was similar to that of sea surface temperature (SST). Hourly observation around Dukjuk island showed the cold and saline southwesterly and the warm and fresh northeasterly in phase with tidal current. Sea fogs two times formed at 2300 LST 8-0130 LST 9, and 0300-0600 LST 9 July 2002 during the observation period, respectively. During the initial stage of fogs, winds became northeasterly at the speed of 2-4m/s$^{-1}$, and air temperature dropped to 18$^{\circ}C$, as the North Pacific High weakened. The satellite image indicated that sea fogs formed over warm water in the western Yellow Sea and moved eastward toward the observation site, which could be called a steam fog. The fogs dissipated when wind speed and air temperature increased.
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.
Kim, Hyo Jeong;Kim, Da Bin;Jeong, Ok Jin;Moon, Yun Seob
Journal of the Korean earth science society
/
v.42
no.3
/
pp.264-277
/
2021
This study analyzed the relationship between the total precipitable water vapor in the atmosphere and the moving speed of recent typhoons. This study used ground observation data of air temperature, precipitation, and wind speed from the Korea Meteorological Administration (KMA) as well as total rainfall data and Red-Green-Blue (RGB) composite images from the U.S. Meteorological and Satellite Research Institute and the KMA's Cheollian Satellite 2A (GEO-KOMPSAT-2A). Using the typhoon location and moving speed data provided by the KMA, we compared the moving speeds of typhoon Bavi, Maysak, and Haishen from 2020, typhoon Tapah from 2019, and typhoon Kong-rey from 2018 with the average typhoon speed by latitude. Tapah and Kong-rey moved at average speed with changing latitude, while Bavi and Maysak showed a significant decrease in moving speed between approximately 25°N and 30°N. This is because a water vapor band in the atmosphere in front of these two typhoons induced frontogenesis and prevented their movement. In other words, when the water vapor band generated by the low-level jet causes frontogenesis in front of the moving typhoon, the high pressure area located between the site of frontogenesis and the typhoon develops further, inducing as a blocking effect. Together with the tropical night phenomenon, this slows the typhoon. Bavi and Maysak were accompanied by copious atmospheric water vapor; consequently, a water vapor band along the low-level jet induced frontogenesis. Then, the downdraft of the high pressure between the frontogenesis and the typhoon caused the tropical night phenomenon. Finally, strong winds and heavy rains occurred in succession once the typhoon landed.
Park, Jinku;Kim, Dae-Won;Jo, Young-Heon;Kim, Deoksu
Korean Journal of Remote Sensing
/
v.34
no.2_1
/
pp.213-225
/
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.
Occurrences of sandstorms in the deserts and loess of Mongolia and northern China and associated dustfall episodes in the Korean Peninsula were monitored during the period January through December, 2005. False colour images were made by directly receiving the NOAA Advanced Very High Resolution Radiometer (AVHRR) data, and the distribution and transport of sandstorms were analyzed. The ground concentrations for PM10, PM2.5 and visibility of the dustfall episodes (PM10 concentration over $190{\mu}g\;m^{-3}$) were analyzed at Cheongwon, located midway in South Korea, and in the leeward direction of the place of origin of the sandstorms. Variations in the concentrations of $O_3,\;NO_2$, CO and $SO_2$ were also compared with dust concentrations in the dustfall episodes. Fewer occurrences of strong sandstorms in the place of origin were observed in 2005, due largely to the accumulation of snow and mild fluctuations of high and low pressure systems in the place of origin, thereby accounting for a low frequency of dustfall episodes in Korea, compared with those during the period 1997-2005. A total of 7 dustfall episodes were monitored in Korea in 2005 that lasted 11 days. In summer, sandstorms occurred less frequently in the source region in 2005 due to high humidity and milder winds, thereby causing no dustfall episodes in Korea. In case the sandstorms occurring at the place of source head directly to Korea without passing through large cities and industrial areas of China, the PM2.5 concentrations were measured at 20% or lower than the PM10 concentrations. However, when the sandstorms headed to Korea via the industrial areas of eastern China, where they pick up anthropogenic air pollutants, the PM2.5 concentrations were at least 25% higher of the PM10 concentrations. On the other hand, over 5 cases were observed and analyzed in 2005 where the PM10 concentrations of sand dust originating from the deserts were measured at $190{\mu}g\;m^{-3}$ or lower, falling short of the level of a dustfall episode.
Atmospheric Motion Vector (AMV) from satellite images have shown Slow Speed Bias (SSB) in comparison with rawinsonde. The causes of SSB are originated from tracking, selection, and height assignment error, which is known to be the leading error. However, recent works have shown that height assignment error cannot be fully explained the cause of SSB. This paper attempts a new approach to examine the possibility of SSB reduction of COMS AMV by using a new target tracking algorithm. Tracking error can be caused by averaging of various wind patterns within a target and changing of cloud shape in searching process over time. To overcome this problem, Gaussian Mixture Model (GMM) has been adopted to extract the coldest cluster as target since the shape of such target is less subject to transformation. Then, an image filtering scheme is applied to weigh more on the selected coldest pixels than the other, which makes it easy to track the target. When AMV derived from our algorithm with sum of squared distance method and current COMS are compared with rawindsonde, our products show noticeable improvement over COMS products in mean wind speed by an increase of $2.7ms^{-1}$ and SSB reduction by 29%. However, the statistics regarding the bias show negative impact for mid/low level with our algorithm, and the number of vectors are reduced by 40% relative to COMS. Therefore, further study is required to improve accuracy for mid/low level winds and increase the number of AMV vectors.
Park, GwangSeob;Kim, Hyun-Cheol;Lee, Taehee;Son, Young Baek
Korean Journal of Remote Sensing
/
v.34
no.6_2
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pp.1299-1310
/
2018
In this study, we analyzed distribution and movement trends using in-situ observations and particle tracking methods to understand the movement of the drift ice in the Arctic Ocean. The in-situ movement data of the drift ice in the Arctic Ocean used ITP (Ice-Tethered Profiler) provided by NOAA (National Oceanic and Atmospheric Administration) from 2009 to 2018, which was analyzed with the location and speed for each year. Particle tracking simulates the movement of the drift ice using daily current and wind data provided by HYCOM (Hybrid Coordinate Ocean Model) and ECMWF (European Centre for Medium-Range Weather Forecasts, 2009-2017). In order to simulate the movement of the drift ice throughout the Arctic Ocean, ITP data, a field observation data, were used as input to calculate the relationship between the current and wind and follow up the Lagrangian particle tracking. Particle tracking simulations were conducted with two experiments taking into account the effects of current and the combined effects of current and wind, most of which were reproduced in the same way as in-situ observations, given the effects of currents and winds. The movement of the drift ice in the Arctic Ocean was reproduced using a wind-imposed equation, which analyzed the movement of the drift ice in a particular year. In 2010, the Arctic Ocean Index (AOI) was a negative year, with particles clearly moving along the Beaufort Gyre, resulting in relatively large movements in Beaufort Sea. On the other hand, in 2017 AOI was a positive year, with most particles not affected by Gyre, resulting in relatively low speed and distance. Around the pole, the speed of the drift ice is lower in 2017 than 2010. From seasonal characteristics in 2010 and 2017, the movement of the drift ice increase in winter 2010 (0.22 m/s) and decrease to spring 2010 (0.16 m/s). In the case of 2017, the movement is increased in summer (0.22 m/s) and decreased to spring time (0.13 m/s). As a result, the particle tracking method will be appropriate to understand long-term drift ice movement trends by linking them with satellite data in place of limited field observations.
Lee, Hee-Jin;Nam, Won-Ho;Yoon, Dong-Hyun;Mark, D. Svoboda;Brian, D. Wardlow
Journal of Korea Water Resources Association
/
v.54
no.8
/
pp.577-587
/
2021
Drought is generally considered to be a natural disaster caused by accumulated water shortages over a long period of time, taking months or years and slowly occurring. However, climate change has led to rapid changes in weather and environmental factors that directly affect agriculture, and extreme weather conditions have led to an increase in the frequency of rapidly developing droughts within weeks to months. This phenomenon is defined as 'Flash Drought', which is caused by an increase in surface temperature over a relatively short period of time and abnormally low and rapidly decreasing soil moisture. The detection and analysis of flash drought is essential because it has a significant impact on agriculture and natural ecosystems, and its impacts are associated with agricultural drought impacts. In South Korea, there is no clear definition of flash drought, so the purpose of this study is to identify and analyze its characteristics. In this study, flash drought detection condition was presented based on the satellite-derived drought index Evaporative Stress Index (ESI) from 2014 to 2018. ESI is used as an early warning indicator for rapidly-occurring flash drought a short period of time due to its similar relationship with reduced soil moisture content, lack of precipitation, increased evaporative demand due to low humidity, high temperature, and strong winds. The flash droughts were analyzed using hydrometeorological characteristics by comparing Standardized Precipitation Index (SPI), soil moisture, maximum temperature, relative humidity, wind speed, and precipitation. The correlation was analyzed based on the 8 weeks prior to the occurrence of the flash drought, and in most cases, a high correlation of 0.8(-0.8) or higher(lower) was expressed for ESI and SPI, soil moisture, and maximum temperature.
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