Interannual SST variability in the Japan/East Sea and relationship with environmental variables

Park, Sunghyea; Chu, Peter C.

doi:10.1007/s10872-006-0038-6

Cited by 23 publications

(15 citation statements)

References 42 publications

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“…To analyze the temporal variability in the warming trends, we calculated the multi-year moving trends in the SST by applying a 20-year-wide temporal domain for the estimation of linear trends, for all spatial grids. The 20-year period was determined by considering relatively high interannual variability of SSTs in the EJS at dominant frequency amounting to 7 years according to the previous study [41]. Figure 6a shows the time series of the spatial distribution for the 20-year-long moving trends in the SST variations, during the observation period from 1982 to 2018.…”

Section: Moving Trends In the Sstmentioning

confidence: 99%

Change in the Recent Warming Trend of Sea Surface Temperature in the East Sea (Sea of Japan) over Decades (1982–2018)

Lee

Park

2019

Remote Sensing

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Long-term trends of sea surface temperature (SST) of the East Sea (Sea of Japan, EJS) were estimated by using 37-year-long satellite data, for the observation period from 1982 to 2018. Overall, the SST tended to increase with time, for all analyzed regions. However, the warming trend was steeper in the earlier decades since the 1980s and slowed down during the recent two decades. Based on the analysis of the occurrence of events with extreme SST (high in the summertime and low in the wintertime), a shift toward the more frequent occurrence of events with extremely high SST and the less frequent occurrence of events with extremely low SST has been observed. This supports the observations of the consistent warming of the EJS. However, seasonal trends revealed continuous SST warming in the summertime, but frequent extreme SST cooling in the wintertime, in recent decades. The observed reduction in the warming rates occurred more frequently in specific regions of the EJS, where the occurrence frequency of events with extremely low SST was unusually high in the recent decade. The recent tendency toward the SST cooling was distinctively connected with variations in the Arctic Oscillation index. This suggests that changes in the Arctic Ocean environment likely affect the recently observed SST changes in the EJS, as one of the marginal seas in the mid-latitude region far from the polar region.

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Section: Moving Trends In the Sstmentioning

confidence: 99%

Change in the Recent Warming Trend of Sea Surface Temperature in the East Sea (Sea of Japan) over Decades (1982–2018)

Lee

Park

2019

Remote Sensing

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“…Meanwhile, the wintertime SST variability in the EJS is associated with the Arctic Oscillation (hereafter, AO) (Park and Chu, 2006;Lee and Park, 2019). The AO is the most dominant mode of wintertime atmospheric circulation characterized by a meridional seesaw-like pattern in the sea level pressure (SLP) between the Arctic and the mid-latitude Northern Hemisphere along with a quasi-zonally symmetric structure (Thompson and Wallace, 1998).…”

Section: Introductionmentioning

confidence: 99%

Wintertime sea surface temperature variability modulated by Arctic Oscillation in the northwestern part of the East/Japan Sea and its relationship with marine heatwaves

et al. 2023

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The northwestern part of the East/Japan Sea (EJS) is a region with large sea surface temperature (SST) variability and is known as a hotspot of marine heatwaves (MHW) stress for marine environments that peaked in boreal winter (January-February-March). This could have profound impacts on the marine ecosystems over the EJS. Here, we used a set of high-resolution satellite and reanalysis products to systematically analyze the spatiotemporal SST variations and examine their linkage to a large-scale mode of climate variability, such as the Arctic Oscillation (AO). The results show that AO-related wind forcing modulates the SST variability over the EJS via the oceanic dynamic adjustment processes. In particular, the abnormally warm SSTs in the northwestern part of the EJS are driven by the anomalous anticyclonic eddy-like circulation and Ekman downwelling during a positive AO phase. This physical linkage between a positive AO and the abnormally warm SST could be conducive to MHW occurrences in the EJS as in the extremely positive AO event during the winter of 2020. These results have implications that the MHW occurrences in the EJS could be amplified by natural climate variability along with long-term SST warming.

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“…The residual method is often used for studies of El-Niño in the tropical Pacific as well as studies on the connectivity of the marginal sea to the ENSO and other climate indices (e.g., White et al 1985;Lie and Endoh, 1991;Wang et al 1999;Park and Chu, 2006;Capotondi et al 2006). Most likely, low-pass filtering is seldom used for computing the interannual anomaly due to short data length in time.…”

Section: Computation Of Interannual Anomaliesmentioning

confidence: 99%

“…For instance, temporal variations in regional climate and oceanography have been investigated in the Yellow Sea, the East China Sea, and the East Sea for connectivity to global climate changes such as the El-Niño and the Southern Oscillation (ENSO) in the tropical Pacific (Wang et al 1999;Chang et al 2000;Wang et al 2000;Park and Oh, 2000;Hong et al 2001;Wu and Wang, 2002;Gordon and Giuiliv, 2004;Hu and Wang, 2004;Park and Chu, 2006;Yoon and Yeh, 2009). Climate change studies basically require long serial records from continuous observations over many years.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction of regular time series from bi-monthly temperature data in the Yellow Sea and the northwestern East China Sea

Lie¹,

Lee²

2010

Ocean Sci. J.

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Reconstruction of evenly-spaced, regular time series from routine survey serial data was investigated for precise analysis of spatio-temporal variations in a temperate sea at mid-latitudes where the seasonality dominates the interannual variability. Considering that the annual range of sea surface temperature in the Yellow Sea and the northwestern East China Sea can be as large as 15-20 o C, temperature data collected bimonthly in these temperate seas were used for the assessment of reconstruction methodology. The cubic spline interpolation with a sampling interval of 0.5 months reconstructed the regular time series closest to the in-situ measurements among various interpolation schemes. Also, two computation methods for the interannual anomaly were compared; the residual method that the long-term monthly means are subtracted from the monthly serial data and the filtering method that high-frequency variations are removed using a low-pass filter. In that the highfrequency variations in frequencies greater than 1 cycle per year are comparable in magnitude to the interannual variation, the residual method proves inadequate in the temperate sea. Highfrequency noises can be effectively removed through the use of a proper low-pass filter with bell-shaped weights.

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Interannual SST variability in the Japan/East Sea and relationship with environmental variables

Cited by 23 publications

References 42 publications

Change in the Recent Warming Trend of Sea Surface Temperature in the East Sea (Sea of Japan) over Decades (1982–2018)

Change in the Recent Warming Trend of Sea Surface Temperature in the East Sea (Sea of Japan) over Decades (1982–2018)

Wintertime sea surface temperature variability modulated by Arctic Oscillation in the northwestern part of the East/Japan Sea and its relationship with marine heatwaves

Reconstruction of regular time series from bi-monthly temperature data in the Yellow Sea and the northwestern East China Sea

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