Kim, Hyung Jeek;Cho, Sosul;Kim, Dongseon;Kim, Kyeong Hong;Yoo, Chan Min
Ocean and Polar Research
/
v.44
no.3
/
pp.221-233
/
2022
A sediment trap had been deployed at 1250 m depth in the Eastern Tropical Pacific (ETP) from September 2009 to July 2010, with the aim of understanding the temporal and vertical variability of particle flux. During the monitoring period, total particle flux varied from 12.4 to 101.0 mg m-2day-1, with the higher fluxes in January-March 2010. Biogenic particle flux varied in phase with the total particle flux. The increase in total particle flux during January-March 2010 was attributed to the enhanced biological production in the surface layer caused by wind-driven mixing in response to the seasonal shifts in the location of the Intertropical convergence zone. The export ratio (e-ratio) was estimated using the particulate organic carbon flux and satellite-derived net primary production data. The estimated e-ratios changed between 0.8% and 2.8% (1.4±0.6% on average). The ratio recorded in the negative phase of Pacific decadal oscillation (PDO) was similar to the previous results obtained from the ETP during the 1992/93 periods in the positive phase of PDO. This suggests that the regime shift of the PDO is not related to the carbon export ratio.
Kim, Won-Hyung;Yang, Hyo-Sun;Bu, Jun-Oh;Kang, Chang-Hee;Song, Jung-Min;Chambers, S.
Analytical Science and Technology
/
v.35
no.1
/
pp.32-40
/
2022
The concentrations of radon in the atmosphere were measured at the Gosan site of Jeju Island during 2017-2018, in order to investigate the time-series variation characteristics and the dependency of airflow transport pathways. The mean 222Rn concentration was 2,480 mBq m-3, and its monthly concentration in November was 3,262 mBq m-3, more than twice as that in July (1,459 mBq m-3). The diurnal radon concentrations increased throughout the nighttime to the maximum (2,862 mBq m-3) at around 7 a.m., then gradually decreased throughout the daytime by the minimum (1,997 mBq m-3) at around 3 p.m. The seasonal and monthly variations of CO, NO2, O3 showed a roughly similar pattern to that of radon for the same period, as high in winter and low in summer. The cluster back trajectory analysis described that about 60 % of overall airflow pathways was influenced by the airflow from China. The concentrations of radon and gaseous pollutants were relatively high as the airflow was influenced by China continent, but comparatively much lower as influenced by the northern Pacific Ocean.
Proceedings of the Korea Water Resources Association Conference
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2023.05a
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pp.178-178
/
2023
Drought and flooding have historically coexisted in Korea, occurring at different times and with varying cycles and trends. The drought indicators measured were (PDSI), (SPI), and (SPEI) in order to statistically analyze the annual or periodic drought occurrence and objectively evaluate statistical characteristics such as the periodicity, tendency, and frequency of occurrence of droughts in the Doam watershed. To compute potential evapotranspiration (PET), both Thornthwaite (Thor) and Penman-Monteith (PM) parameterizations were considered, and the differences between the two PET estimators were analyzed. Hence, SPIs 3 and SPIs 6 revealed a tendency to worsen drought in the spring and winter and a tendency to alleviate drought in the summer in the study area. The seasonal variability trend did not occur in the SPIs 12 and PDSI, as it did in the drought index over a short period. As a result of the drought trend study, the drought from winter to spring gets more severe, in addition to the duration of the drought, although the periodicity of the recurrence of the drought ranged from 3 years to 6 years at the longest, indicating that SPIs 3 showed a brief time of around 1 year. SPIs 6 and SPIs 12 had a term of 4 to 6 years, and PDSI had a period of roughly 6 years. Based on the indicators of the PDSI, SPI, and SPEI, the drought severity increases under climate change conditions with the decrease in precipitation and increased water demand as a consequence of the temperature increase. Therefore, our findings show that national and practical measures are needed for both winter and spring droughts, which happen every year, as well as large-scale and extreme droughts, which happen every six years.
Recently, Japan's Meteorological Research Institute presented the d4PDF database (Database for Policy Decision-Making for Future Climate Change, d4PDF) through large-scale climate ensemble simulations to overcome uncertainty arising from variability when the general circulation model represents extreme-scale precipitation. In this study, the change of precipitation characteristics between the historical and future climate conditions in the Yongdam-dam basin was analyzed using the d4PDF data. The result shows that annual mean precipitation and seasonal mean precipitation increased by more than 10% in future climate conditions. This study also performed an analysis on the change of the return period rainfall. The annual maximum daily rainfall was extracted for each climatic condition, and the rainfall with each return period was estimated. In this process, we represent the extreme-scale rainfall corresponding to a very long return period without any statistical model and method as the d4PDF provides rainfall data during 3,000 years for historical climate conditions and during 5,400 years for future climate conditions. The rainfall with a 50-year return period under future climate conditions exceeded the rainfall with a 100-year return period under historical climate conditions. Consequently, in future climate conditions, the magnitude of rainfall increased at the same return period and, the return period decreased at the same magnitude of rainfall. In this study, by using the d4PDF data, it was possible to analyze the change in extreme magnitude of rainfall.
Proceedings of the Korea Water Resources Association Conference
/
2022.05a
/
pp.329-329
/
2022
Accurate characterization of terrestrial precipitation variation from high spatial resolution satellite sensors is beneficial for urban hydrology and microscale agriculture modeling, as well as natural disasters (e.g., urban flooding) early warning. However, the widely-used top-down approach for precipitation retrieval from microwave satellites is limited in several hydrological and agricultural applications due to their coarse spatial resolution. In this research, we aim to apply a novel bottom-up method, the parameterized SM2RAIN, where precipitation can be estimated from soil moisture signals based on an inversion of water balance model, to generate high spatial resolution terrestrial precipitation estimates at 0.01º grid (roughly 1-km) from the C-band SAR Sentinel-1. This product was then tested against a common reanalysis-based precipitation data and a domestic rain gauge network from the Korean Meteorological Administration (KMA) over central South Korea, since a clear difference between climatic types (coasts and mainlands) and land covers (croplands and mixed forests) was reported in this area. The results showed that seasonal precipitation variability strongly affected the SM2RAIN performances, and the product derived from separated parameters (rainy and non-rainy seasons) outperformed that estimated considering the entire year. In addition, the product retrieved over the mainland mixed forest region showed slightly superior performance compared to that over the coastal cropland region, suggesting that the 6-day time resolution of S1 data is suitable for capturing the stable precipitation pattern in mainland mixed forests rather than the highly variable precipitation pattern in coastal croplands. Future studies suggest comparing this product to the traditional top-down products, as well as evaluating their integration for enhancing high spatial resolution precipitation over entire South Korea.
NA Jung-Yul;HAN Snag-Kyu;SEO Jang-Won;NOH Yi-Gn;KANG In-Sik
Korean Journal of Fisheries and Aquatic Sciences
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v.30
no.2
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pp.188-202
/
1997
The seasonal variability of the sea surface winds over the last Sea of Korea (Japan Sea) is investigated by means of empirical orthogonal function (EOF) analysis. The combined representation of fields of three climatic variables by empirical orthogonal functions is discussed. The eigenvectors are derived from daily sea level pressure, wind speed and 10-day mean sea surface temperature (SST) during 15 years $(1978\~1992)$. The spatial patterns of the mean pressure are characterized by the high pressure in the western part and the low pressure in the eastern part. The spatial distribution of the standard deviation (SD) of pressure are characterized by max SD of 6.6 mb near the Vladivostok, and minima along the coast of the Japan. In Vladivostok, the maxima of SD of SST and south-north wind (WV) were also occurred. The representation of fields of individual meteorological variables by EOF shows that the first mode of the west-east wind (WU) explain over $47.3\%$ of the variance and the second mode of WU represents $30\%$. Especially, the first mode of the WV explain $70.9\%$ of the variance and their time series coefficients show 1-cpy, 0.5-cpy frequency spectrum. The spatial distribution of the first mode eigenvectors of SST are characterized by maximum near Vladivostok. The combined representation of fields of several variables (pressure, wind, SST) reveals that the first mode magnitudes of the variance of the combined eigenvectors (WU-PR) are increased. By means of this result, the 1-year peak and the 6-months peak are remarkable. In the three combined patterns (wind, pressure, SST), the second mode of the eigenvector (wind) is affected by the SST. Their time coefficients of the first mode show noticeable 1-year peak. The spectral analysis of the second mode shows broad seasonal signal with the period of 4-months and a significant peak of variability at 3-month period.
In this paper, the performance improvement for the new KMA's Climate Prediction System (GloSea6), which has been built and tested in 2021, is presented by assessing the bias distribution of basic variables from 24 years of GloSea6 hindcasts. Along with the upgrade from GloSea5 to GloSea6, the performance of GloSea6 can be regarded as notable in many respects: improvements in (i) negative bias of geopotential height over the tropical and mid-latitude troposphere and over polar stratosphere in boreal summer; (ii) cold bias of tropospheric temperature; (iii) underestimation of mid-latitude jets; (iv) dry bias in the lower troposphere; (v) cold tongue bias in the equatorial SST and the warm bias of Southern Ocean, suggesting the potential of improvements to the major climate variability in GloSea6. The warm surface temperature in the northern hemisphere continent in summer is eliminated by using CDF-matched soil-moisture initials. However, the cold bias in high latitude snow-covered area in winter still needs to be improved in the future. The intensification of the westerly winds of the summer Asian monsoon and the weakening of the northwest Pacific high, which are considered to be major errors in the GloSea system, had not been significantly improved. However, both the use of increased number of ensembles and the initial conditions at the closest initial dates reveals possibility to improve these biases. It is also noted that the effect of ensemble expansion mainly contributes to the improvement of annual variability over high latitudes and polar regions.
This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R2) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R2 was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R2 was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R2 of 0.69 and RMSE of 2.88%.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.26
no.1
/
pp.11-36
/
2021
The solar annual (Sa) and semiannual (Ssa) tides account for much of the non-uniform annual and seasonal variability observed in sea levels. These non-equilibrium tides depend on atmospheric variations, forced by changes in the Sun's distance and declination, as well as on hydrographic conditions. Here we employ tidal harmonic analyses to calculate Sa and Ssa harmonic constants for 21 Korean coastal tidal stations (TS), operated by the Korea Hydrographic and Oceanographic Agency. We used 19 year-long (1999 to 2017) 1 hr-interval sea level records from each site, and used two conventional harmonic analysis (HA) programs (Task2K and UTide). The stability of Sa harmonic constants was estimated with respect to starting date and record length of the data, and we examined the spatial distribution of the calculated Sa and Ssa harmonic constants. HA was performed on Incheon TS (ITS) records using 369-day subsets; the first start date was January 1, 1999, the subsequent data subset starting 24 hours later, and so on up until the final start date was December 27, 2017. Variations in the Sa constants produced by the two HA packages had similar magnitudes and start date sensitivity. Results from the two HA packages had a large difference in phase lag (about 78°) but relatively small amplitude (<1 cm) difference. The phase lag difference occurred in large part since Task2K excludes the perihelion astronomical variable. Sensitivity of the ITS Sa constants to data record length (i.e., 1, 2, 3, 5, 9, and 19 years) was also tested to determine the data length needed to yield stable Sa results. HA results revealed that 5 to 9 year sea level records could estimate Sa harmonic constants with relatively small error, while the best results are produced using 19 year-long records. As noted earlier, Sa amplitudes vary with regional hydrographic and atmospheric conditions. Sa amplitudes at the twenty one TS ranged from 15.0 to 18.6 cm, 10.7 to 17.5 cm, and 10.5 to 13.0 cm, along the west coast, south coast including Jejudo, and east coast including Ulleungdo, respectively. Except at Ulleungdo, it was found that the Ssa constituent contributes to produce asymmetric seasonal sea level variation and it delays (hastens) the highest (lowest) sea levels. Comparisons between monthly mean, air-pressure adjusted, and steric sea level variations revealed that year-to-year and asymmetric seasonal variations in sea levels were largely produced by steric sea level variation and inverted barometer effect.
Kim, Kuh;Kim, Yun-Bae;Park, Jong-Jin;Nam, Sung-Hyun;Park, Kyung-Ae;Chang, Kyung-Il
Ocean Science Journal
/
v.40
no.1
/
pp.25-44
/
2005
Long-term, continuous, and real-time ocean monitoring has been undertaken in order to evaluate various oceanographic phenomena and processes in the East/Japan Sea. Recent technical advances combined with our concerted efforts have allowed us to establish a real-time monitoring system and to accumulate considerable knowledge on what has been taking place in water properties, current systems, and circulation in the East Sea. We have obtained information on volume transport across the Korea Strait through cable voltage measurements and continuous temperature and salinity profile data from ARGO floats placed throughout entire East Sea since 1997. These ARGO float data have been utilized to estimate deep current, inertial kinetic energy, and changes in water mass, especially in the northern East Sea. We have also developed the East Sea Real-time Ocean Buoy (ESROB) in coastal regions and made continual improvements till it has evolved into the most up-to-date and effective monitoring system as a result of remarkable technical progress in data communication systems. Atmospheric and oceanic measurements by ESROB have contributed to the recognition of coastal wind variability, current fluctuations, and internal waves near and off the eastern coast of Korea. Long-tenn current meter moorings have been in operation since 1996 between Ulleungdo and Dokdo to monitor the interbasin deep water exchanges between the Japanese and Ulleung Basins. In addition, remotely sensed satellite data could facilitate the investigation of atmospheric and oceanic surface conditions such as sea surface temperature (SST), sea surface height, near-surface winds, oceanic color, surface roughness, and so on. These satellite data revealed surface frontal structures with a fairly good spatial resolution, seasonal cycle of SST, atmospheric wind forcing, geostrophic current anomalies, and biogeochemical processes associated with physical forcing and processes. Since the East Sea has been recognized as a natural laboratory for global oceanic changes and a clue to abrupt climate change, we aim at constructing a 4-D continuous real-time monitoring system, over a decade at least, using the most advanced techniques to understand a variety of oceanic processes in the East Sea.
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