• Title/Summary/Keyword: SST Anomaly

Search Result 48, Processing Time 0.029 seconds

Interannual variabilities of the East Asia precipitation associated with tropical and subtropical sea surface temperature (열대 및 아열대 SST에 관련된 동아시아 강우량의 경년 변동성)

  • 하경자
    • Journal of Environmental Science International
    • /
    • v.4 no.5
    • /
    • pp.413-426
    • /
    • 1995
  • The aim of the present study is to investigate the interannual variabilities of the East Asia monsoon rainfall associated with the global sea surface temperature anomaly(SSTA). For this study, the summer rainfall(from June to August) over the twenty-eight period of 1961-1988 were analyzed with being divided by nine-subregions over East Asia including Korea, China and Japan. From the analysis of the principal modes explaining the interannual variation, the interannual variabilities of summer rainfalls in South Japan and Korea are larger than those of the other subregions of the East Asia. There is a strong negative correlation between the summer rainfalls of south China and Korea. In this study, the relationship between the summer monsoon of each subregion and SSTs of the tropical NINO regions, of western Pacific warm pool, and of the subtropical ocean were investigated. The longitudinal sections of the lagged cross correlations of the summer rainfal1 anomaly in (a) Korea and (b) south China, and the monthly SSTA in the equatorial(averaged from 65 to 6N) Pacific were analyzed. The negative maximum correlation pattems of Korea's stammer rainfal1 and SSTs over the eastern Pacific is transfered to positive maximum conrlation over central Pacific region with a biennial periodicity. In South China, the significant positive correlations are found at -12 month lag over the eastern Pacific and maximum negative correlation at 16 month lag over the central Pacific with the quasi-biennial oscillation. But the correlation coefficient reverses completely to that in Korea. In order to investigate the most prevailing interannual variability of rainfall related to the favored SSTA region, the lagged cross correlations between East Asia rainfall and SSTs over the moO regions(NINO 1+2(0-105, 90W-80W), NINO 3(5N-5S, 150W-90W), NINO 4(5N-5S, 160E-l50W) and the western Pacific worm pool (5N-5S, 120E-l60E) were analyzed. Among the lagged cross-correlation cycles in NINO regions, the maximum correlations for the negative lagged months prevail in NINO 1+2 and NINO 3, and the cross correlations for the positive lagged months NINO 4. It is noteworthy that correlation between the western Pacific warm pool SSTA and the monsoon rainfall in Korea and South China have the maximum value at negative 4 month lag. The evolution of the correlation between the East Asia monsoon rainfall and SSTA is linked to the equatorial convective cluster and related to northward propagating situation, and raising the possibility that the East Asia monsoon precipitation may be more fundamentally related to the interaction of intraseasonal oscillations and the sub-regional characteristics including the surface boundary conditions and the behavior of climatological air mass.

  • PDF

Current and Future Changes in the Type of Wintertime Precipitation in South Korea (현재와 미래 우리나라 겨울철 강수형태 변화)

  • Choi, Gwang-Yong;Kwon, Won-Tae
    • Journal of the Korean Geographical Society
    • /
    • v.43 no.1
    • /
    • pp.1-19
    • /
    • 2008
  • This study intends to clarify the characteristics and causes of current changes in wintertime precipitation in Korea and to predict the future directions based on surface observational $(1973/04\sim2006/07)$ and modeled (GFDL 2.1) climate data. Analyses of surface observation data demonstrate that without changes in the total amount of precipitation, snowfall in winter (November-April) has reduced by 4.3cm/decade over the $1973\sim2007$ period. Moreover, the frequency and intensity of snowfall have decreased; the duration of snow season has shortened; and the snow-to-rain day ratio (STDR) has decreased. These patterns indicate that the type of wintertime precipitation has changed from snow to rain in recent decades. The snow-to-rain change in winter is associated with the increases of air temperature (AT) over South Korea. Analyses of synoptic charts reveal that the warming pattern is associated with the formation of a positive pressure anomaly core over northeast Asia by a hemispheric positive winter Arctic Oscillation (AO) mode. Moreover, the differentiated warming of AT versus sea surface temperature (SST) under the high pressure anomaly core reduces the air-sea temperature gradient, and subsequently it increases the atmospheric stability above oceans, which is associated with less formation of snow cloud. Comparisons of modeled data between torrent $(1981\sim2000)$ and future $(2081\sim2100)$ periods suggest that the intensified warming with larger anthropogenic greenhouse gas emission in the $21^{st}$ century will amplify the magnitude of these changes. More reduction of snow impossible days as well as more abbreviation of snow seasons is predicted in the $21^{st}$ century.

Impacts of Argo temperature in East Sea Regional Ocean Model with a 3D-Var Data Assimilation (동해 해양자료동화시스템에 대한 Argo 자료동화 민감도 분석)

  • KIM, SOYEON;JO, YOUNGSOON;KIM, YOUNG-HO;LIM, BYUNGHWAN;CHANG, PIL-HUN
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
    • /
    • v.20 no.3
    • /
    • pp.119-130
    • /
    • 2015
  • Impacts of Argo temperature assimilation on the analysis fields in the East Sea is investigated by using DAESROM, the East Sea Regional Ocean Model with a 3-dimensional variational assimilation module (Kim et al., 2009). Namely, we produced analysis fields in 2009, in which temperature profiles, sea surface temperature (SST) and sea surface height (SSH) anomaly were assimilated (Exp. AllDa) and carried out additional experiment by withdrawing Argo temperature data (Exp. NoArgo). When comparing both experimental results using assimilated temperature profiles, Root Mean Square Error (RMSE) of the Exp. AllDa is generally lower than the Exp. NoArgo. In particular, the Argo impacts are large in the subsurface layer, showing the RMSE difference of about $0.5^{\circ}C$. Based on the observations of 14 surface drifters, Argo impacts on the current and temperature fields in the surface layer are investigated. In general, surface currents along the drifter positions are improved in the Exp. AllDa, and large RMSE differences (about 2.0~6.0 cm/s) between both experiments are found in drifters which observed longer period in the southern region where Argo density was high. On the other hand, Argo impacts on the SST fields are negligible, and it is considered that SST assimilation with 1-day interval has dominant effects. Similar to the difference of surface current fields between both experiments, SSH fields also reveal significant difference in the southern East Sea, for example the southwestern Yamato Basin where anticyclonic circulation develops. The comparison of SSH fields implies that SSH assimilation does not correct the SSH difference caused by withdrawing Argo data. Thus Argo assimilation has an important role to reproduce meso-scale circulation features in the East Sea.

Climatological variability of surface particulate organic carbon (POC) and physical processes based on ocean color data in the Gulf of Mexico

  • Son, Young-Baek;Gardner, Wilford D.
    • Korean Journal of Remote Sensing
    • /
    • v.27 no.3
    • /
    • pp.235-258
    • /
    • 2011
  • The purpose of this study is to investigate climatological variations from the temporal and spatial surface particulate organic carbon (POC) estimates based on SeaWiFS spectral radiance, and to determine the physical mechanisms that affect the distribution of pac in the Gulf of Mexico. 7-year monthly mean values of surface pac concentration (Sept. 1997 - Dec. 2004) were estimated from Maximum Normalized Difference Carbon Index (MNDCI) algorithm using SeaWiFS data. Synchronous 7-year monthly mean values of remote sensing data (sea surface temperature (SST), sea surface wind (SSW), sea surface height anomaly (SSHA), precipitation rate (PR)) and recorded river discharge data were used to determine physical forcing factors. The spatial pattern of POC was related to one or more factors such as river runoff, wind-derived current, and stratification of the water column, the energetic Loop Current/Eddies, and buoyancy forcing. The observed seasonal change in the POC plume's response to wind speed in the western delta region resulted from seasonal changes in the upper ocean stratification. During late spring and summer, the low-density river water is heated rapidly at the surface by incoming solar radiation. This lowers the density of the fresh-water plume and increases the near-surface stratification of the water column. In the absence of significant wind forcing, the plume undergoes buoyant spreading and the sediment is maintained at the surface by the shallow pycnocline. However, when the wind speed increases substantially, wind-wave action increases vertical motion, reducing stratification, and the sediment were mixed downward rather than spreading laterally. Maximum particle concentrations over the outer shelf and the upper slope during lower runoff seasons were related to the Loop Current/eddies and buoyancy forcing. Inter-annual differences of POC concentration were related to ENSO cycles. During the El Nino events (1997-1998 and 2002-2004), the higher pac concentrations existed and were related to high runoffs in the eastern Gulf of Mexico, but the opposite conditions in the western Gulf of Mexico. During La Nina conditions (1999-2001), low Poe concentration was related to normal or low river discharge, and low PM/nutrient waters in the eastern Gulf of Mexico, but the opposite conditions in the western Gulf of Mexico.

Statistical Method and Deep Learning Model for Sea Surface Temperature Prediction (수온 데이터 예측 연구를 위한 통계적 방법과 딥러닝 모델 적용 연구)

  • Moon-Won Cho;Heung-Bae Choi;Myeong-Soo Han;Eun-Song Jung;Tae-Soon Kang
    • Journal of the Korean Society of Marine Environment & Safety
    • /
    • v.29 no.6
    • /
    • pp.543-551
    • /
    • 2023
  • As climate change continues to prompt an increasing demand for advancements in disaster and safety management technologies to address abnormal high water temperatures, typhoons, floods, and droughts, sea surface temperature has emerged as a pivotal factor for swiftly assessing the impacts of summer harmful algal blooms in the seas surrounding Korean Peninsula and the formation and dissipation of cold water along the East Coast of Korea. Therefore, this study sought to gauge predictive performance by leveraging statistical methods and deep learning algorithms to harness sea surface temperature data effectively for marine anomaly research. The sea surface temperature data employed in the predictions spans from 2018 to 2022 and originates from the Heuksando Tidal Observatory. Both traditional statistical ARIMA methods and advanced deep learning models, including long short-term memory (LSTM) and gated recurrent unit (GRU), were employed. Furthermore, prediction performance was evaluated using the attention LSTM technique. The technique integrated an attention mechanism into the sequence-to-sequence (s2s), further augmenting the performance of LSTM. The results showed that the attention LSTM model outperformed the other models, signifying its superior predictive performance. Additionally, fine-tuning hyperparameters can improve sea surface temperature performance.

A Study on the Characteristics of Tropical Cyclone Passage Frequency over the Western North Pacific using Empirical Orthogonal Function (경험적 직교함수를 이용한 북서태평양 열대저기압의 이동빈도 특성에 관한 연구)

  • Choi, Ki-Seon;Kang, Ki-Ryong;Kim, Do-Woo;Hwang, Ho-Seong;Lee, Sang-Ryong
    • Journal of the Korean earth science society
    • /
    • v.30 no.6
    • /
    • pp.721-733
    • /
    • 2009
  • A pattern of tropical cyclone (TC) movement in the western North Pacific area was studied using the empirical orthogonal function (EOF) and the best track data from 1951 to 2007. The independent variable used in this study was defined as the frequency of tropical cyclone passage in 5 by 5 degree grid. The $1^{st}$, $2^{nd}$ and $3^{rd}$ modes were the east-west, north-south and diagonal variation patterns. Based on the time series of each component, the signs of first and second mode changed in 1997 and 1991, respectively, which seems to be related to the fact that the passage frequency was higher in the South China Sea for 20 years before 1990s, and recent 20 years in the East Asian area. When the eigen vectors were negative values in the first and second modes and TC moves into the western North Pacific, TC was formed mainly at the east side relatively compared to the case of the positive eigen vectors. The first mode seems to relate to the pressure pattern at the south of Lake Baikal, the second mode the variation pattern around $30^{\circ}N$, and the third mode the pressure pattern around Japan. The first mode was also closely related to the ENSO and negatively related to the $Ni\tilde{n}o$-3.4 index in the correlation analysis with SST anomalies.

Long-term Predictability for El Nino/La Nina using PNU/CME CGCM (PNU/CME CGCM을 이용한 엘니뇨/라니냐 장기 예측성 연구)

  • Jeong, Hye-In;Ahn, Joong-Bae
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
    • /
    • v.12 no.3
    • /
    • pp.170-177
    • /
    • 2007
  • In this study, the long-term predictability of El Nino and La Nina events of Pusan National University Coupled General Circulation Model(PNU/CME CGCM) developed from a Research and Development Grant funded by Korea Meteorology Administration(KMA) was examined in terms of the correlation coefficients of the sea surface temperature between the model and observation and skill scores at the tropical Pacific. For the purpose, long-term global climate was hindcasted using PNU/CME CGCM for 12 months starting from April, July, October and January(APR RUN, JUL RUN, OCT RUN and JAN RUN, respectively) of each and every years between 1979 and 2004. Each 12-month hindcast consisted of 5 ensemble members. Relatively high correlation was maintained throughout the 12-month lead hindcasts at the equatorial Pacific for the four RUNs starting at different months. It is found that the predictability of our CGCM in forecasting equatorial SST anomalies is more pronounced within 6-month of lead time, in particular. For the assessment of model capability in predicting El Nino and La Nina, various skill scores such as Hit rates and False Alarm rate are calculated. According to the results, PNU/CME CGCM has a good predictability in forecasting warm and cold events, in spite of relatively poor capability in predicting normal state of equatorial Pacific. The predictability of our CGCM was also compared with those of other CGCMs participating DEMETER project. The comparative analysis also illustrated that our CGCM has reasonable long-term predictability comparable to the DEMETER participating CGCMs. As a conclusion, PNU/CME CGCM can predict El Nino and La Nina events at least 12 months ahead in terms of NIino 3.4 SST anomaly, showing much better predictability within 6-month of leading time.

Determining Spatial and Temporal Variations of Surface Particulate Organic Carbon (POC) using in situ Measurements and Remote Sensing Data in the Northeastern Gulf of Mexico during El $Ni\tilde{n}o$ and La $Ni\tilde{n}a$ (현장관측 및 원격탐사 자료를 이용한 북동 멕시코 만에서 El $Ni\tilde{n}o$와 La $Ni\tilde{n}a$ 기간 동안 표층 입자성 유기탄소의 시/공간적 변화 연구)

  • Son, Young-Baek;Gardner, Wilford D.
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
    • /
    • v.15 no.2
    • /
    • pp.51-61
    • /
    • 2010
  • Surface particulate organic carbon (POC) concentration was measured in the Northeastern Gulf of Mexico on 9 cruises from November 1997 to August 2000 to investigate the seasonal and spatial variability related to synchronous remote sensing data (Sea-viewing Wide Field-of-view Sensor (SeaWiFS), sea surface temperature (SST), sea surface height anomaly (SSHA), and sea surface wind (SSW)) and recorded river discharge data. Surface POC concentrations have higher values (>100 $mg/m^3$) on the inner shelf and near the Mississippi Delta, and decrease across the shelf and slope. The inter-annual variations of surface POC concentrations are relatively higher during 1997 and 1998 (El Nino) than during 1999 and 2000 (La Nina) in the study area. This phenomenon is directly related to the output of Mississippi River and other major rivers, which associated with global climate change such as ENSO events. Although highest river runoff into the northern Gulf of Mexico Coast occurs in early spring and lowest flow in late summer and fall, wide-range POC plumes are observed during the summer cruises and lower concentrations and narrow dispersion of POC during the spring and fall cruises. During the summer seasons, the river discharge remarkably decreases compared to the spring, but increasing temperature causes strong stratification of the water column and increasing buoyancy in near-surface waters. Low-density plumes containing higher POC concentrations extend out over the shelf and slope with spatial patterns and controlled by the Loop Current and eddies, which dominate offshore circulation. Although river discharge is normal or abnormal during the spring and fall seasons, increasing wind stress and decreasing temperature cause vertical mixing, with higher surface POC concentrations confined to the inner shelf.