• Journal of the Korean earth science society
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• v.26 no.3
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• pp.199-217
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• 2005

Using monthly total ozone data obtained from a Total Ozone Mapping Spectrometer (TOMS) onboard the Nimbus-7 and Earth Probe satellite, this study examined the trend in the total amount of global ozone during two periods: from 1979-1992 [Early period] and 1997-2002 [Latter period]. The Annual average of total ozone during the Early period was globally reduced by about 10 DU compared to the amount during the Latter, except in some areas between the equator and 20 N. Global trends of total ozone showed a decrease of -6.30 DU/decade during 1979-1992, and an increase of 0.12 DU/decade during 1997-2002. Its enhancement during the Latter period was especially noticeable in tropical areas. The EOF analyses of total ozone from this period indicated signs of temporal/spatial variability, associated with the phenomena of Quasi-Biennial Oscillation (QBO), Quasi-Triennial Oscillation (QTO), El Nino Southern Oscillation (ENSO), and volcanic eruption. Seasonal profiles of tropospheric ozone in the tropics obtained from ozonesondes, showed the spatial pattern of zonal wavenumber one. Overall, this study may be useful in analyzing possible causes in the variations of statospheric and tropospheric ozone.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.6
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• pp.650-662
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• 2011

The statistical tools such as empirical orthogonal function (EOF), and singular value decomposition (SVD) have been applied to analyze the characteristic of air pollutant over southeast Asia as well as to evaluate Zimeke's tropospheric column ozone (ZTO) determined by tropospheric residual method. In this study, we found that the EOF and SVD analyses are useful methods to extract the most significant temporal and spatial pattern from enormous amounts of satellite data. The EOF analyses with OMI $NO_2$ and OMI HCHO over southeast Asia revealed that the spatial pattern showed high correlation with fire count (r=0.8) and the EOF analysis of CO (r=0.7). This suggests that biomass burning influences a major seasonal variability on $NO_2$ and HCHO over this region. The EOF analysis of ZTO has indicated that the location of maximum ZTO was considerably shifted westward from the location of maximum of fire count and maximum month of ZTO occurred a month later than maximum month (March) of $NO_2$, HCHO and CO. For further analyses, we have performed the SVD analyses between ZTO and ozone precursor to examine their correlation and to check temporal and spatial consistency between two variables. The spatial pattern of ZTO showed latitudinal gradient that could result from latitudinal gradient of stratospheric ozone and temporal maximum of ZTO in March appears to be associated with stratospheric ozone variability that shows maximum in March. These results suggest that there are some sources of error in the tropospheric residual method associated with cloud height error, low efficiency of tropospheric ozone, and low accuracy in lower stratospheric ozone.

• Korean Journal of Ecology and Environment
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• v.42 no.4
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• pp.452-464
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• 2009

The objectives of this study were to evaluate spatial and temporal variability of water quality in 10 reservoirs and identify the key nutrients (N, P) influencing chlorophyll-a (CHL) along with analysis of empirical models and zonal patterns of total phosphorus (TP) and CHL. We analyzed total nitrogen (TN), TP, CHL, water clarity (Secchi depth, SD), and evaluated potential limiting nutrient using ambient N:P ratios and previous criteria of ambient nutrients. Water clarity and CHL varied largely depending on the seasonal monsoon and type of reservoir, but trophic state was diagnosed as eutrophy, base on mean CHL in most reservoirs. The peak of TP did not match the contents of CHL due to rapid flushing during the high run-off period. In the reservoir of DR, regression coefficient in the $P_r$ was 0.510 but was 0.159 in the $M_o$, while the TP-CHL relation in the YR increased during the monsoon compared to the premonsoon. The regression coefficient in the $P_r$ was not statistically significant but the value of $M_o$ was 0.250. TP showed similar longitudinal zonal gradients among the reservoirs of DR, YR and JR. Empirical models of TP-CHL, based on overall data, showed that CHL was determined by phosphorus($R^2=0.244$, p=0.0019). Regression analysis of CHL-SD showed a stronger linear fit ($R^2=0.638$, p<0.001) than the TP-CHL model.

• Atmosphere
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• v.24 no.2
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• pp.131-140
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• 2014

The "Barents Oscillation (BO)", first designated by Paul Skeie (2000), is an anomalous recurring atmospheric circulation pattern of high relevance for the climate of the Nordic Seas and Siberia, which is defined as the second Emperical Orthogonal Function (EOF) of monthly winter sea level pressure (SLP) anomalies, where the leading EOF is the Arctic Oscillation (AO). BO, however, did not attracted much interest. In recent two decades, variability of BO tends to increase. In this study, we analyzed the spatio-temporal structures of Atmospheric internal modes such as Arctic Oscillation (AO) and Barents Oscillation (BO) and examined how these are related with Arctic warming in recent decade. We identified various aspects of BO, not dealt in Skeie (2000), such as upper-level circulation and surface characteristics for extended period including recent decade and examined link with other surface variables such as sea-ice and sea surface temperature. From the results, it was shown that the BO showed more regionally confined spatial pattern compared to AO and has intensified during recent decade. The regional dipolelar structure centered at Barents sea and Siberia was revealed in both sea-level pressure and 500 hPa geopotential height. Also, BO showed a stronger link (correlation) with sea-ice and sea surface temperature especially over Barents-Kara seas suggesting it is playing an important role for recent Arctic amplification. BO also showed high correlation with Ural Blocking Index (UBI), which measures seasonal activity of Ural blocking. Since Ural blocking is known as a major component of Eurasian winter monsoon and can be linked to extreme weathers, we suggest deeper understanding of BO can provide a missing link between recent Arctic amplification and increase in extreme weathers in midlatitude in recent decades.

• Korean Journal of Environment and Ecology
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• v.29 no.1
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• pp.29-45
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• 2015

Water chemistry and fish community, based on fish compositions and ecological characteristics(trophic/tolerance guilds and condition factor), were compared in Gucheon Reservoir($G_cR$) and Yeoncho Reservoir($Y_cR$). Chemical parameters of water quality such as BOD, COD, nutrient(N, P) and suspended solids indicated that water quality was better in the $Y_cR$ than $G_cR$, and the temporal variability in seasonal and interannual patterns were greater in the $Y_cR$. The greater variability was mainly attributed to intense dilutions of reservoir water by Asian monsoon rain during July-August. Fish guild analysis indicated that species diversity was higher in the $G_cR$ than the $Y_cR$, and that the proportion of tolerant and omnivore species were greater in the $Y_cR$. Regression analysis of body weight-total length showed that the regression coefficient(b value) was lower in the $G_cR$(2.15 ~ 2.40) than the $Y_cR$(2.59 ~ 3.14). Condition factor(K) of fish against the total length showed negative slope of Zacco temminckii, Carassius auratus, Pseudorasbora parva and Rhinogobius brunneus population in the $G_cR$, and a positive slope of Carassius auratus and Rhinogobius brunneus population in $Y_cR$. Overall, our data suggest that the growth of the fish populations, based on the length-weight relations and condition factor, reflected the trophic regime of nutrients and organic matter.

• Atmosphere
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• v.28 no.4
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• pp.509-520
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• 2018

The performance of the newly designed Pusan National University Coupled General Circulation Model (PNU CGCM) Ensemble Forecast System which produce 40 ensemble members for 12-month lead prediction is evaluated and analyzed in terms of boreal winter temperature over South Korea (S. Korea). The influence of ensemble size on prediction skill is examined with 40 ensemble members and the result shows that spreads of predictability are larger when the size of ensemble member is smaller. Moreover, it is suggested that more than 20 ensemble members are required for better prediction of statistically significant inter-annual variability of wintertime temperature over S. Korea. As for the ensemble average (ENS), it shows superior forecast skill compared to each ensemble member and has significant temporal correlation with Automated Surface Observing System (ASOS) temperature at 99% confidence level. In addition to forecast skill for inter-annual variability of wintertime temperature over S. Korea, winter climatology around East Asia and synoptic characteristics of warm (above normal) and cold (below normal) winters are reasonably captured by PNU CGCM. For the categorical forecast with $3{\times}3$ contingency table, the deterministic forecast generally shows better performance than probabilistic forecast except for warm winter (hit rate of probabilistic forecast: 71%). It is also found that, in case of concentrated distribution of 40 ensemble members to one category out of the three, the probabilistic forecast tends to have relatively high predictability. Meanwhile, in the case when the ensemble members distribute evenly throughout the categories, the predictability becomes lower in the probabilistic forecast.

• Ocean Science Journal
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• v.43 no.4
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• pp.195-208
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• 2008

This paper evaluates whether a thermodynamic ocean-carbon model can be used to predict the monthly mean global fields of the surface-water partial pressure of $CO_2$ ($pCO_{2SEA}$) from sea surface salinity (SSS), temperature (SST), and/or nitrate ($NO_3$) concentration using previously published regional total inorganic carbon ($C_T$) and total alkalinity ($A_T$) algorithms. The obtained $pCO_{2SEA}$ values and their amplitudes of seasonal variability are in good agreement with multi-year observations undertaken at the sites of the Bermuda Atlantic Timeseries Study (BATS) ($31^{\circ}50'N$, $60^{\circ}10'W$) and the Hawaiian Ocean Time-series (HOT) ($22^{\circ}45'N$, $158^{\circ}00'W$). By contrast, the empirical models predicted $C_T$ less accurately at the Kyodo western North Pacific Ocean Time-series (KNOT) site ($44^{\circ}N$, $155^{\circ}E$) than at the BATS and HOT sites, resulting in greater uncertainties in $pCO_{2SEA}$ predictions. Our analysis indicates that the previously published empirical $C_T$ and $A_T$ models provide reasonable predictions of seasonal variations in surface-water $pCO_{2SEA}$ within the (sub) tropical oceans based on changes in SSS and SST; however, in high-latitude oceans where ocean biology affects $C_T$ to a significant degree, improved $C_T$ algorithms are required to capture the full biological effect on $C_T$ with greater accuracy and in turn improve the accuracy of predictions of $pCO_{2SEA}$.

• Journal of Fisheries and Marine Sciences Education
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• v.12 no.2
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• pp.152-163
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• 2000

Floating resin pellets including plastics were surveyed from 7 coastal beaches near Young-il Bay during summer and winter season on 1998 ~ 2000 year. Plastic fabrication materials in the survey were founded with 6 items using the following; resin pellets, plastic debris, styrofoams, cigar filters, wood pieces and charcoals. The results deduced in the areas are as follows: 1. The seasonal variability of the all debris is revealed that summer season were remarkably larger than those of winter. This is deduced it is attributed to meteorological effects, e.g, the seasonal wind strength, current vectors and resorts of crowded people for beach enjoy. And the distribution of plastic debris is Pohang Songdo $12.9ea/m^2$, Pohang Bookbu $8.8ea/m^2$, Togoo $4.9ea/m^2$, Chilpo $3.2ea/m^2$, Hwajin $1.4ea/m^2$, Wolpo and Guryongpo $0.8ea/m^2$ respectively. 2. Compared with each beaches, Songdo beach, northern part beach of Pohang city and Togoo beach have higher densities than those of the others. Especially, the highest densities of all debris were discovered in the Songdo beach of Pohang city. 3. The change of density over the whole year was similarly distributed in quantities and fabrication materials. 4. These surveys were founded that the most parts of plastic debris materials were made up with PE and PP.

• Atmosphere
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• v.25 no.2
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• pp.323-337
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• 2015

This study explores the 6-month lead prediction skill of several climate indices that influence on East Asian climate in the GloSea5 hindcast experiment. Such indices include Nino3.4, Indian Ocean Diploe (IOD), Arctic Oscillation (AO), various summer and winter Asian monsoon indices. The model's prediction skill of these indices is evaluated by computing the anomaly correlation coefficient (ACC) and mean squared skill score (MSSS) for ensemble mean values over the period of 1996~2009. In general, climate indices that have low seasonal variability are predicted well. For example, in terms of ACC, Nino3.4 index is predicted well at least 6 months in advance. The IOD index is also well predicted in late summer and autumn. This contrasts with the prediction skill of AO index which shows essentially no skill beyond a few months except in February and August. Both summer and winter Asian monsoon indices are also poorly predicted. An exception is the Western North Pacific Monsoon (WNPM) index that exhibits a prediction skill up to 4- to 6-month lead time. However, when MSSS is considered, most climate indices, except Nino3.4 index, show a negligible prediction skill, indicating that conditional bias is significant in the model. These results are only weakly sensitive to the number of ensemble members.

• Atmosphere
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• v.28 no.1
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• pp.85-97
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• 2018

This study evaluates the performance of the Weather Research and Forecasting (WRF) model in reproducing the present-day (1981~2005) precipitation over Far East Asia and South Korea. The WRF model is configured with 25-km horizontal resolution within the context of the COordinated Regional climate Downscaling Experiment (CORDEX) - East Asia Phase 2. The initial and lateral boundary forcing for the WRF simulation are derived from European Centre for Medium-Range Weather Forecast Interim reanalysis. According to our results, WRF model shows a reasonable performance to reproduce the features of precipitation, such as seasonal climatology, annual and inter-annual variabilities, seasonal march of monsoon rainfall and extreme precipitation. In spite of such model's ability to simulate major features of precipitation, systematic biases are found in the downscaled simulation in some sub-regions and seasons. In particular, the WRF model systematically tends to overestimate (underestimate) precipitation over Far East Asia (South Korea), and relatively large biases are evident during the summer season. In terms of inter-annual variability, WRF shows an overall smaller (larger) standard deviation in the Far East Asia (South Korea) compared to observation. In addition, WRF overestimates the frequency and amount of weak precipitation, but underestimates those of heavy precipitation. Also, the number of wet days, the precipitation intensity above the 95 percentile, and consecutive wet days (consecutive dry days) are overestimated (underestimated) over eastern (western) part of South Korea. The results of this study can be used as reference data when providing information about projections of fine-scale climate change over East Asia.