• Journal of Korea Water Resources Association
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• v.38 no.2
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• pp.111-119
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• 2005

The climatological characteristics of the area averaged monthly precipitation over the Han- and Nakdong-river basins were investigated. The data used for this study is monthly precipitation data from 51 meteorological stations for the period of 1954 to 2002. The magnitude of area averaged precipitation in the Han-river basin was about 10% larger than that in the Nakdong-river basin. However, the variability of two monthly precipitation time series exhibited similar characteristics: April precipitation tends to decrease and August precipitation increase significantly, while there was no significant trend for the other months. There were some indications of abrupt change around the 1970's in the periodicity of precipitation and relationship with El Nino index. September precipitation showed negative correlation with NINO3 index but November precipitation, positive correlation with NINO3 index, indicating a possible connection with the global-scale phenomena.

• Water Engineering Research
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• v.2 no.2
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• pp.139-148
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• 2001

The teleconnections between El Nino/Southern Oscillation (ENSO) and droughts in Korea and the continental United States(U.S.) are investigated using cross analysis. For this purpose, monthly ENSO data and Palmer Drought Severity Index (PDSI) for Korea and for seven states in the U.S. are used. This study shows that there are significant statistical associations between ENSO indices and PDSI for Korea; however, the associations are very weak. It is found that dry conditions in Korea are positively correlated with El Nino, while wet conditions with La Nina. SOI, SSt in the Nino 4 and Ship track 6 regions among ENSO indices are more strongly correlated with PDSI than the other ENSO indices when using the original standardized data, but the SST Nino 3, SST Nino 4, and Darwin SSP exhibit abetter correlations with PDSI when using filtered data to be removed autocorrelation components of the original standardized data. The response time lag for maximum correlation between ENSO indices and PDSI appears to be affected by filtering the data. This is expecially true for Korea than for state analyzed in U.S. In addition, it is found that the PDSI in the continental U.S. is more strongly correlated wiht ENSO than in Korea. Furthermore, in analyzing the El Nino and La Nina aggregate composite data, it is found that the dry anomalies in Korea occur from the year following El Nino to about tow years after while the wet anomalies occur from La Nina year for a period of about two years.

• 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.

• Journal of Korea Water Resources Association
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• v.40 no.4
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• pp.299-311
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• 2007

Climatic abnormal phenomena involving El Nino and La Nina have been frequently reported in recent decades. The interannual climate variability represented by El Nino-Southern Oscillation (ENSO) is sometimes investigated to account for the climatic abnormal phenomena around the world. Although many hydroclimatologists have studied the impact of ENSO on regional precipitation and streamflow, however, there are still many difficulties in finding the dominant causal relationship between them. This relationship is very useful in making hydrological forecasting models for water resources management. In this study, the seasonal relationships between ENSO and hydrologic variables were investigated in Korea. As an ENSO indicator, Southern Oscillation Index (SOI) was used. Monthly precipitation, monthly mean temperature, and monthly dam inflow data were used after being transformed to the standardized normal index. Seasonal relationships between ENSO and hydrologic variables were investigated based on the exceedance probability and distribution of hydrologic variables conditioned on the ENSO episode. The results from the analysis of this study showed that the warm ENSO episode affects increases in precipitation and temperature, and the cold ENSO episode is related with decreases in precipitation and temperature in Korea. However, in some regions, the local relationships do not correspond with the general seasonal relationship.

• Journal of the Korean earth science society
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• v.28 no.1
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• pp.35-44
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• 2007

This paper investigated the relationship between El $Ni\widetilde{n}o-Southern$ Oscillation (ENSO) and Indian Ocean Dipole (IOD) mode events and the impacts of these two phenomena on the climate, temperature and precipitation, of the Korean Peninsula. Data gathered from 1954 to 2004 were used for analysis, which included NINO 3 index, IOD index, and monthly mean precipitation and temperature at eleven locations in Korea. Statistical results showed that the IOD and ENSO were significantly correlated in Spring and Fall. It was clearly shown that the distribution of the sea surface temperature in the Indian Ocean has seen the Southern and Northern Oscillation in El $Ni\widetilde{n}o$ year, and Eastern and Western in IOD year. On the other hand, in El $Ni\widetilde{n}o$ you, the mean temperature of the Korea Peninsula was lower than normal in Summer and higher in Winter and its precipitation was more than normal in both Summer and Winter. However, significant correlation was not found in IOD year. In addition, the global atmospheric circulations during the major IOD years are less influential, unlike those of El $Ni\widetilde{n}o$ events.

• Atmosphere
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• v.26 no.1
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• pp.59-72
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• 2016

The comparison of prediction errors in geopotential height, temperature, and precipitation forecasts is made quantitatively to evaluate medium-range forecast skills between Global Seasonal Forecasting System version 5 (GloSea5) and Unified Model (UM) in operation by Korea Meteorological Administration during 2014. In addition, the performances in prediction of sea surface temperature anomaly in NINO3.4 region, Madden and Julian Oscillation (MJO) index, and tropical storms in western north Pacific are evaluated. The result of evaluations appears that the forecast skill of UM with lower values of root-mean square error is generally superior to GloSea5 during forecast periods (0 to 12 days). The forecast error tends to increase rapidly in GloSea5 during the first half of the forecast period, and then it shows down so that the skill difference between UM and GloSea5 becomes negligible as the forecast time increases. Precipitation forecast of GloSea5 is not as bad as expected and the skill is comparable to that of UM during 10-day forecasts. Especially, in predictions of sea surface temperature in NINO3.4 region, MJO index, and tropical storms in western Pacific, GloSea5 shows similar or better performance than UM. Throughout comparison of forecast skills for main meteorological elements and weather extremes during medium-range, the effects of initial and model errors in atmosphere-ocean coupled model are verified and it is suggested that GloSea5 is useful system for not only seasonal forecasts but also short- and medium-range forecasts.

• Journal of the Korean earth science society
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• v.28 no.3
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• pp.343-356
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• 2007

This paper explored the characteristics of the interannual sea surface temperature (SST) variability in the equatorial Pacific by analyzing the simulated data from a newly coupled general circulation model (CGCM). The CGCM simulates well the realistic ENSO variability as well as the mean climatologies including SST, seasonal cycle, precipitation, and subsurface structures. It is argued that the zonal gradient of SST in the equatorial Pacific is responsible for the over-energetic SST variability near the equatorial western boundary in the model. This variability could also be related to the strong westward propagation of SST anomalies which resulted from the enhanced the zonal advection feedback. The simple two-strip model supports this by sensitivity tests. Analysis of the relationship between zonal mean thermocline depth and NINO3 SST index suggested that the ENSO variability is controlled by the recharge-discharge oscillator of the model. The lead-lag regression result reveals that heat buildup process in the western equatorial Pacific associated with the increase of the barrier layer thickness (BLT) is a precedent condition for El $Ni\widetilde{n}o$ to develop.

• Atmosphere
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• v.27 no.3
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• pp.261-276
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• 2017

The main objectives of this study are to introduce Global Seasonal forecasting system version5 (GloSea5) of KMA and to evaluate the performance of ensemble prediction of system. KMA has performed an operational seasonal forecast system which is a joint system between KMA and UK Met office since 2014. GloSea5 is a fully coupled global climate model which consists of atmosphere (UM), ocean (NEMO), land surface (JULES) and sea ice (CICE) components through the coupler OASIS. The model resolution, used in GloSea5, is N216L85 (~60 km in mid-latitudes) in the atmosphere and ORCA0.25L75 ($0.25^{\circ}$ on a tri-polar grid) in the ocean. In this research, we evaluate the performance of this system using by RMSE, Correlation and MSSS for ensemble mean values. The forecast (FCST) and hindcast (HCST) are separately verified, and the operational data of GloSea5 are used from 2014 to 2015. The performance skills are similar to the past study. For example, the RMSE of h500 is increased from 22.30 gpm of 1 week forecast to 53.82 gpm of 7 week forecast but there is a similar error about 50~53 gpm after 3 week forecast. The Nino Index of SST shows a great correlation (higher than 0.9) up to 7 week forecast in Nino 3.4 area. It can be concluded that GloSea5 has a great performance for seasonal prediction.

• Journal of the Korean earth science society
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• v.35 no.4
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• pp.249-258
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• 2014

Despite the greenhouse gases like carbon dioxide have steadily increased in atmosphere, the overall trend of the global average surface air temperature has stalled during the last decade (2002-present). This phenomenon is often called hiatus or warming pause, which is challenging the prevailing view that anthropogenic forcing causes warming environment. Our study characterized the hiatus by analyzing the HadGEM2-AO (95 yrs) simulation data based on RCP8.5 scenario. The PC2 time series from the EOF of the zonal mean vertical ocean temperature has been defined as the index that represents the warming pause. The relationship between the hiatus, ENSO and the changes in climate system are identified by utilizing the newly defined PC2. Since the La Nina index (defined as the negative of NINO3 index) leads PC2 by about 11 months, it may be possible that the La Nina causes the warming to be interrupted. We also show that the cooling of the climate system closed tied to the heat penetration into the deep ocean, indicating the weakening the warming rate is due to the oceanic heat uptake. Finally, the global warming hiatus is characterized by the anomalous warming in Arctic region as well as the intensification of the trade wind in the equatorial Pacific.

• Ocean and Polar Research
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• v.43 no.1
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• pp.15-30
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• 2021

In this study, using 16 ORA-IP (Ocean Reanalysis Intercomparison Project) data, we investigated spatial and temporal changes of net surface heat flux in the East Asian seas and presented a new ensemble net surface heat flux index. The ensemble net surface heat flux index is produced considering the data distribution and the standard deviation of each ORA-IP. From the correlation analysis with air temperature averaged over the Korean Peninsula, ensemble net heat flux around the Korea Strait shows the highest correlation (0.731) with a 3 month time lag. For the correlation study regarding precipitation over the Korean Peninsula, it also shows significant correlation especially in winter and spring seasons. Similar results are also found in comparison with climate indices (AO, PDO, and NINO3.4), but ensemble net surface heat flux data in winter season reveals the strongest correlation patterns especially with winter temperature and spring precipitation.