Surface Warming Slowdown With Continued Subsurface Warming in the East Sea (Japan Sea) Over Recent Decades (2000–2014)

Abstract

The long-term surface warming trend in the East Sea (Japan Sea; ES hereafter) stalled from 2000 to 2014 (−0.05°C yr−1, surface warming slowdown), while the subsurface (100–300°m) warming trend continued (+0.03°C yr−1). To address the processes underlying these contrasting trends in surface and subsurface temperature change, the trends in sea-level anomaly, isopycnal depth, and wind pattern were analyzed using monthly mean ocean reanalysis system 4 (ORAS4) data. During this period, the strengthened northwesterly/northerly wind in the central part of ES is supposed to contribute to a negative (positive) wind stress curl to its west (east), corresponding to an anticyclonic (cyclonic) circulation in the west (east). Furthermore, the induced negative wind stress in the west appears to enhance the northward penetration of East Korean Warm Current (EKWC), the slowdown in its eastward meandering around 38° N from the Korea coast, resulting in warm water accumulation in the west with peak warm anomaly at relatively greater depth compared to peak cold anomaly in the east. Overall, these wind-driven changes in transport from west to east, wind stress curl induced horizontal divergence (convergence) and the associated upwelling (downwelling), causes surface warming to slow and subsurface warming to persist during 2000 to 2014.

Decadal intensified and slantwise Subpolar Front in the Japan/East Sea

“…The change in the SLA due to non-steric effect appears to be well following the higher (lower) SLA over the equatorial (polar) flanks of the central SPF (Figure 9C), but the decadal change due to the steric effect is relatively weak compared to h ′ and h 0 Nonsteric , and does not show a pattern that contributes to the acceleration of geostrophic current (Figure 10B). This is consistent with the results pointed out by previous studies that the non-steric effect plays a more important role in decadal, interannual and longer timescales than the steric effect (Yoon et al, 2016;Jeong et al, 2022). Moreover, the non-steric effect is affected by the volume transport from the upstream.…”

“…The differences in the SST and MSSTG between the two time periods of 1985-1994 and 2011-2020 were calculated, which could be regarded as the decadal trends from 1985 to 2020 (Figure 2). The SST warmed over the whole of the JES, except in the central region, similar to the results of Lee and Park (2019); Chen et al (2022) and Jeong et al (2022), suggesting equatorward movement of the SPF in this region. The equatorial flank of the eastern SPF warmed faster than the polar flank, implying a poleward shift.…”

“…Before 2002, there was a shift from a westerly anomaly to an easterly anomaly, and vice versa after 2002. The wind stress field in the JES is related to the large-scale East Asian Winter Monsoon (EAWM), which revealed by the sea-level pressure (SLP) in the region of Siberian High (SH) and in East Asia (Ding et al, 2014;Jeong et al, 2022). An intensity index of EAWM (hereinafter EAWM index) is defined as the sum of winter (winter is the average of December, January, and February) zonal SLP differences (110°E minus 160°E) over 20-70°N following Wu and Wang (2002).…”

Carbon cycling in the East Sea (Japan Sea): A review

“…Modelling studies and machine learning need to be coordinated with field observations and satellite remote sensing (Lee and Yoo, 2016;Restreppo et al, 2020;Li et al, 2022). For example, Jeong et al (2022) used monthly mean ocean reanalysis system 4 data to investigate the long-term surface warming trend in the EJS. estimated the turnover times of the ES MOC by using a global HYCOM reanalysis with data assimilation for a 20-yr period (1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012) in addition to the previous estimates based on chemical tracers.…”

Trends and Spatio-Temporal Variability of Summer Mean and Extreme Precipitation Events across South Korea for 1973-2022

“…On the other hand, it is necessary to understand long-term variations and trends in mean and extreme precipitation in water resource and flood risk management (Moberg et al, 2006;Ha et al, 2009;Pei et al, 2017;Kim & Ha, 2021;Wang et al, 2021;Hu et al, 2022;Ryan et al, 2022). Ensemble empirical mode decomposition (EEMD) method is employed to appropriately reflect nonlinear responses to global warming and urbanization (Yun et al, 2018;Jeong et al, 2022). Hu et al, (2022) revealed that the extreme precipitation on the Tibetan Plateau and its surrounding areas is strongly correlated with the strength of the Indian Ocean and Western Pacific warm pools through the multi-time-scale analysis.…”