Contrasting Air-Sea Coupling Processes of Conventional and Unconventional
Oceanic Eddies in the East China Sea during Winter
Tangxuan Song1, Shengyi Qian1, Haibo Hu1, #, Xiaoming Zhai2, Xiu-Qun Yang1,
Weixuan Chen3, 4
1CMA Key Laboratory for Climate Prediction Studies, School of Atmospheric Sciences, Nanjing University, Nanjing, China
2Centre for Ocean and Atmospheric Sciences, School of Environmental Sciences, University of East Anglia, Norwich, Norfolk, England
3Fujian Climate Center, Fuzhou, China
4Fujian Key Laboratory of Severe Weather, Fuzhou, China
#Corresponding author: Haibo Hu (huhaibo@nju.edu.cn)
Key Points:
1.		The 3D structures and features of conventional and unconventional oceanic eddies in the Kuroshio front zone during winter are compared.
2.		The conventional and unconventional eddies exhibit opposite coupling relationship between SST and air-sea heat flux.
3.		Discrepancies in vertical responses of various atmospheric physical quantity fields to the two types of eddies are revealed.
Abstract
Both conventional (cold cyclonic and warm anticyclonic) and unconventional (warm cyclonic and cold anticyclonic) oceanic eddies are frequently observed near the Kuroshio axis in the East China Sea, as identified from daily oceanic reanalysis datasets during winter months since 1993. These four types of eddies exhibit remarkably different temporal evolution 
structures. Each eddy type demonstrates significantly varying intensities in multiple oceanic and atmospheric physical quantities, including sea surface temperature (SST) anomalies, vorticity fields, and heat flux exchanges. In particular, the air-sea coupling relationships presented by the correlations between SST and air-sea turbulent heat flux over the conventional and unconventional eddies exhibit opposite characteristics, which are likely to contribute to longer (shorter) lifespans of conventional (unconventional) eddies. In addition, the difference in air-sea heat flux anomalies associated with four eddy types determines the corresponding responses of the lower and middle atmosphere over the oceanic eddies, including the 3D air temperature, horizontal wind, vertical velocity at various pressure levels and the atmospheric boundary layer height.

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characteristics and spatial

patterns, along with contrasting 3D thermal and dynamic

Key words: Kuroshio front; conventional/unconventional oceanic eddies; air-sea interaction; East China Sea.
Plain Language Summary
The detailed air-sea coupling processes for the conventional cold-cyclonic-, conventional warm-anticyclonic-, unconventional warm-cyclonic-, and unconventional cold-anticyclonic- eddies within the oceanic front zone remain unclear. Utilizing oceanic reanalysis data, the diverse types of oceanic eddies within the Kuroshio front zone in the ECS during winter since 1993 are detected. Composite results reveal the three-dimensional structure of temperature, current and vorticity for each eddy type as well as their spatial frequency distribution. Furthermore, contrasting air-sea interactions between conventional and unconventional eddies are found to critically influence sea surface temperature (SST) anomaly persistence and have potential impacts on their lifespans. The corresponding responses of the lower and middle atmosphere including the three-dimensional air temperature, horizontal wind, vertical velocity at different pressure levels, and the atmospheric boundary layer height are demonstrated to be primarily driven by the distinct sea surface turbulent heat fluxes anomalies related to four eddy types. This study may be helpful to the understanding of detailed processes of air-sea interactions and supports improvements in the mid- to long-term numerical forecasting capabilities at middle latitudes.
1		Introduction
The Kuroshio is the northward branch of the North Equatorial Current in the Pacific Ocean, usually originated from the eastern Philippines, and is one of the strongest warm currents in the world. Based on its geographical location, it can be divided into the Kuroshio in the East China Sea (KECS) and the Kuroshio Extension (KE) flowing out of the East China Sea (ECS) into the Pacific Ocean. The KECS front mainly flows through the outer continental shelf of the ECS, formed by the convergence of warm saltwater from the Kuroshio and cold freshwater from the ECS continental shelf (Qiu et al., 1990, 2010; Tseng et al., 2000; Zhang et al., 2001; Furey et al., 2005). The most significant sea surface temperature (SST) gradient of Kuroshio front appears in cold seasons (Kelly et al., 2010; Bai et al., 2019), accompanied by frequent occurrences of mesoscale oceanic eddies. Previous studies have highlighted the significant impact of the KECS front on the weather and climate of East Asia during winter (Taguchi et al., 2009; Xu et al., 2015; Bai et al., 2023; Shi et al., 2021).
According to the rotation direction (cyclonic and anticyclonic), thermal properties (cold and warm) and dynamic formation mechanisms, oceanic eddies within the KECS front zone can be classified. Ding et al. (2018) classified these eddies based on their dynamic formation mechanisms: the eddies generated because of the horizontal shear of currents exhibit a shorter lifespan and tend to be cyclonic (anticyclonic) on the cold (warm) side of the Kuroshio. The other type of eddies, which are formed due to the shedding wave-like bending during the forward movement of the Kuroshio Current, have longer lifespans and tend to be anticyclonic (cyclonic) on the cold (warm) side of the Kuroshio. The rotation of eddies is accompanied by sea surface height (SSH) anomalies (SSHA): positive over anticyclones and negative over cyclones. Previous studies suggested that cyclonic (anticyclonic) eddies are related to negative (positive) SST anomalies (Roemmich et al., 2001; Hausmann et al., 2012; Zhang et al., 2015). However, due to the diversity of oceanic eddies, besides conventional cold cyclonic eddies (CCEs) and warm anticyclonic eddies (WAEs), unconventional warm cyclonic eddies (WCEs) and cold anticyclonic eddies (CAEs) also exist in the global ocean. In the statistical study of the North Pacific eddies, Sun et al. (2019) found that WCEs occur most in the California

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Current region while CAEs occur most in the KE region. But the proportions of WCEs and
CAEs in the South China Sea are higher than other regions, accounting for 42% in all cyclonic eddies and 44% in all anticyclonic eddies, respectively (Liu et al., 2020). Ni et al. (2021) also discovered the existence of these unconventional eddies using global satellite data. WCEs (CAEs) account for 19% (22%) of all cyclonic (anticyclonic) eddies in global ocean and these unconventional eddies have a higher proportion in tropical oceans (Ni et al., 2023) and boundary current regions. In addition, they also found that conventional eddies exhibit significantly deeper vertical structures than unconventional eddies (WCEs and CAEs) in the global ocean. However, since the possible influence of the strong western boundary current in the North Pacific on the eddy structure, our understanding of the three-dimensional structure of different eddy types within the KECS front zone remains unclear.

General isolated CCEs and WAEs have been found to have significant local forcing on the marine atmospheric boundary layer (MABL) above. The middle and lower atmosphere was proved to have significant responses to the isolated cyclonic (anticyclonic) eddies in the KE region, showing a decrease (increase) of low-level winds, latent and sensible heat fluxes, cloud liquid water, water vapor content, and rainfall rate (Ma et al., 2015; Hu et al., 2021). Chen et al. (2017) found that isolated eddies in the KE region can affect the atmospheric vertical momentum mixing and the wind convergence field in the lower atmosphere. Moreover, the forcing by eddy-scale SST anomalies on the atmospheric circulations over the mid-latitude North Pacific is discovered by Hu et al. (2022; 2023). On the other hand, the atmosphere will also provide feedback to the ocean after being forced by eddies. For thermal feedback, anomalous turbulent heat fluxes act to damp eddy potential energy and modify near-surface stratification (Shan et al., 2020). Current feedback arises from the difference between surface vector winds and surface ocean currents, leading to a sink of the ocean’s eddy kinetic energy to the atmosphere (Xu et al., 2016; Rai et al., 2021). By estimating the eddy-induced turbulent heat flux, Moreton et al. (2021) quantified regional variations in the strength of the thermal feedback. Considering the diversity of oceanic eddies mentioned above, the different forcing between WCEs and CAEs to the atmosphere in specific regions has been noticed. Liu et al. (2020) discovered the existence of CCEs, WAEs, WCEs and CAEs in the South China Sea, CCEs/WAEs. However, the impact of WCEs and CAEs on the MABL, as well as the feedback effect of air-sea turbulent heat flux on oceanic eddies need to be revealed.

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and proposed the

between the SST anomalies and the air-sea heat flux related to

Motivated by the discussion above, this paper addresses the following key questions: as an important western boundary current in the North Pacific, what are the statistics of the diverse oceanic eddies within the KECS front zone? What are the spatiotemporal variabilities of different oceanic eddy types? Especially, the differences in the coupling relationship between these complex oceanic eddies and the MABL need to be revealed. In order to answer these questions, the structure of this paper is as follows: Section 2 introduces the data and methods used in this study, Section 3 respectively presents the statistics, structural patterns, physical properties and air-sea coupling characteristics of four types of oceanic eddies, as well as the different coupling relationship between these eddies and the MABL through three subsections, and Section 4 provides a summary.
2		Data and Methods
The main oceanic data used in this study is the Global Ocean Physics Reanalysis product GLORYS12V1, which is based largely on the current real-time global forecasting Copernicus Marine Environment Monitoring Service (CMEMS) system (Fernandez & Lellouche, 2021). Along track sea level anomalies, satellite sea surface temperature, sea ice concentration, in-situ temperature and salinity vertical profiles are jointly assimilated by a reduced-order Kalman filter. As a widely-used reanalysis dataset in studies of global and regional ocean circulation (Cai et al., 2021; Travkin et al.,2021; Zhmur et al., 2021), it includes daily and monthly mean files for temperature, salinity, currents, sea level, mixed layer depth and ice parameters in different levels. The GLORYS12V1 provides a product with resolution of 1/12° (approximatively 8 km) and 50 standard levels. In this study, we use the GLORYS12V1 data (116-136°E, 20-36°N, from December to the next year’s February of 1993-2020) to detect oceanic eddies and composite their structure.
Besides, the Hybrid Coordinate Ocean Model (HYCOM) (Chassignet et al., 2009) product 
verify the analysis on oceanic eddies. The HYCOM is a global ocean forecast model developed by the Naval Research Laboratory (NRL). The vertical coordinate of the model is a combination of pressure, density and z coordinate, which can effectively simulate the flow in the upper ocean, thermocline and deep ocean. The HYCOM model is widely used in numerical prediction of ocean circulation on global and regional scale (Metzger et al., 2003; Kara et al., 2005; Counillon et al., 2009; Li et al., 2015). The GOFS 3.1 product used in this study is assimilated by the Navy Coupled Ocean Data Assimilation (NCODA) system (Cummings, 2005; Cummings & Smedstad, 2013). It provides three-hourly data in 1/12° resolution. To keep temporal resolution being consistent with the GLORYS12V1, the three-hourly data are averaged into daily data. Moreover, two group of satellite observations are applied in this study for validation of eddy results. One is the Global Ocean Gridded L 4 Sea Surface Heights And Derived Variables Reprocessed 1993 Ongoing (Pujol et al., 2022. https://doi.org/10.48670/moi-00148). This observation data provides the sea surface height (SSH) data in spatial resolution of 0.125°×0.125° (The climatological average SSH has been compared with that in the GLORYS12V1 in Fig. S1, which exhibits minor difference). The other is the European Space Agency (ESA) SST Climate Change Initiative (CCI) and Copernicus Climate Change Service (C3S) reprocessed SST analyses (https://doi.org/10.48670/moi-00169) in spatial resolution of 0.05°×0.05°.

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Ocean Forecasting System

3.1 output (Metzger et al., 2017) is also used to

The atmospheric data used in this study is the fifth generation European Centre for MediumRange Weather Forecasts (ECMWF) reanalysis (ERA5) for the global climate and weather for the past eight decades, which is available from 1940 onwards (Hersbach et al., 2017, 2023). The ERA5 provides hourly estimates for various atmospheric, ocean-wave and land-surface quantities. Uncertainty estimates are sampled by an underlying 10-member ensemble at three- hourly intervals. For convenience, ensemble mean and spread are pre-computed. Such uncertainty estimates are closely related to the information of the available observation system which has considerably evolved over time. Flow-dependent sensitive areas are also indicated. The horizontal resolution of the atmospheric ERA5 data is 0.25° × 0.25°. Similarly, the hourly ERA5 data are averaged into daily data and interpolated into the same grid as the

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In order to detect oceanic eddies in the GLORYS12V1 and GOFS data, the geometry-based detection algorithm of velocity vector filed (Nencioli et al., 2010) is adopted in this study. In general, the minimum velocity of oceanic eddies is located in the approximate eddy center. Tangential velocity increases linearly away from the center till reaching a peak then decreasing, and the distance between the center and the peak of tangential velocity is considered as the radius of the eddy. Moreover, the directions of current must rotate in a consistent orientation, which can be quantitatively implemented by analyzing the latitudinal and longitudinal component of current and constraining adjoining velocity vectors into same or adjacent quadrants. Locations of eddy centers and radius of each eddy can be identified through the six constraints proposed by Wen et al. (2020). The grid points which satisfy the six constraints are determined as the eddy centers and the corresponding radius are computed by grid number times horizontal resolution. Our tracking algorithm identifies the same eddy in consecutive time steps if its center displaces within a predefined maximum distance of 50km. Four types of oceanic eddies: cold cyclonic eddies (CCEs), warm anticyclonic eddies (WAEs), warm cyclonic eddies (WCEs) and cold anticyclonic eddies (CAEs) are detected respectively in the GLORYS12V1 and GOFS data. Cold (warm) eddies indicate the value of SST anomaly at the eddy center is negative (positive). Hereinafter, all anomalies are obtained by subtracting daily climatology.
3.1		Spatiotemporal distribution and three-dimensional structures of conventional and unconventional eddies
Using the GLORY12V1 daily reanalysis data, we detected CCEs, WAEs, WCEs and CAEs in the ECS (116°-136°E, 20°-36°N) during winters from 1993-2020. In order to quantify the spatial distribution of these eddies, we defined the oceanic eddy occurrence frequency at each grid as the number of eddy-covered days (Fig. 1). Based on the strong horizontal velocity shear of Kuroshio current (Qiu et al. 1991; Kawabe et al. 1995), the position of climatological maximum sea surface current velocity is defined as the Kuroshio main axis, and the region spanning ±2° latitudes around this axis is designated as the KECS front zone (dashed purple box area in Fig. 1). Abundant eddies are observed, with frequencies peaking near the main axis. 
Cyclonic eddies are predominantly located on the north side of the Kuroshio main axis, while anticyclonic eddies concentrate on the south side. The eddy frequency within the front zone exhibits high homogeneity along the main axis. Notably, the numbers of unconventional eddies (WCEs and CAEs) are significantly lower than that of conventional eddies (CCEs and WAEs). The spatial distribution results of the four eddy types in the HYCOM output GOFS data (Fig. S2) and the satellite observations (Fig. S3) are consistent with that in the GLORY12V1 data, indicating that the detection of oceanic eddies is insensitive to the choice of reanalysis data. Additionally, a few localized areas with high eddy occurrence are observed in the northern ECS and Yellow Sea in Fig. S4. Areas with the occurrence frequency of eddies exceeding 600 times are marked in the terrain height map (Fig. S4). The areas of high eddy frequency are located on the slopes of the ECS continental shelf at depths of 30-100 meters. The consistency in rotational properties among these eddies indicates that their formation was likely driven by ocean currents surging onto the continental shelf and spinning due to terrain constraints. Dynamic mechanisms (i.e. oceanic current instabilities and topographic interactions) dominate

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across

Fig. 1. The spatial distribution of eddy occurrence frequency (shadings, units: occurrences) of (a) cold cyclonic eddies (CCEs), (b) warm anticyclonic eddies (WAEs), (c) warm cyclonic eddies (WCEs), and (d) cold anticyclonic eddies (CAEs) identified by the GLORYS12V1 reanalysis during winters since 1993. The dashed purple lines represent the Kuroshio main axis and the boundary of the Kuroshio front zone in the East China Sea (KECS front zone).

This study focuses on eddies within the KECS front zone, where the annual winter occurrence of the four eddy types is quantified (Fig. 2). A total of 33427 CCEs (42.3% of all eddies), 24653 WAEs (31.2% of all eddies), 9726 WCEs (12.3% of all eddies) and 11222 CAEs (14.2% of all eddies) are identified. Among cyclonic eddies, CCEs accounted for 77.5% and WCEs for 22.5%, while among anticyclonic eddies, WAEs accounted for 68.7% and CAEs for 31.3%. The proportions of WCEs and CAEs are slightly higher than those within global oceans reported by Ni et al. (2021), supporting their conclusion that unconventional eddies are more

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likely to occur in boundary current regions.

Fig. 2. Bar chart of the number of four types of oceanic eddies in the KECS front zone during each year’s winter in the GLORYS12V1 reanalysis.

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The composite three-dimensional structures of each eddy type are analyzed from the sea surface down to 400 meters depth, as clearly illustrated in Fig. 3. All eddy types exhibit pronounced SST anomalies and well-defined vorticity centers at the sea surface. Under the strong influence of the Kuroshio current, all eddies displayed an elongated oval shape with their major axes aligned along the southwest-northeast direction. With increasing depth, an eastward displacement is observed for the vorticity centers of cyclonic eddies (CCEs and WCEs), while those of anticyclonic eddies (WAEs and CAEs) remained vertically aligned. In conventional eddies (CCEs and WAEs), the temperature core almost perfectly matches the vorticity center, whereas in unconventional eddies (WCEs and CAEs), they are off-centered. The vorticity structures of all eddies extend below 400 meters, as well as the temperature structures of CCEs (negative temperature anomalies) and WAEs (positive temperature anomalies). However, a dipole pattern is identified in the vertical temperature structures of WCEs and CAEs. For WCEs (CAEs), although the positive (negative) vorticities extend to 400-meters depth, a notable reversal occurs in the temperature anomalies, which turn negative (positive) between 200 to 300 meters depth. The composite results of WCEs and CAEs at sea surface using the GOFS (Fig. S5) and the observations (Fig. S6) are in high agreement with those by the GLORYS12V1 confirming the reliability of the results.

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250	Fig. 3. three-dimensional structures of four types of eddies and the proportion statistics of these 251	eddies within the KECS front zone during winters since 1993 in the GLORYS12V1 reanalysis.
252	The composite sea temperature anomalies (shadings, units: K), horizontal current anomalies 253	(vectors, units: m/s), and the vorticity anomalies (contours with intervals of 6×10-7, units: s-1
254	for (a) CCEs, (b) WAEs, (c) WCEs, and (d) CAEs. The solid lines represent positive values, 255	dashed lines represent negative values, bold lines represent the value of zero. The purple dashed 256	lines indicate mixed layers. Blue (red) crosses represent the locations of minimum (maximum) 
vorticity. The x and y axis are relative longitude and latitude (depth) from surface to 400 meters respectively.
3.2		Physical properties and air-sea coupling of conventional and unconventional eddies
The differences in distribution and eddy parameters between conventional and unconventional oceanic eddies are further related to their physical properties and air-sea coupling characteristics. The probability density of the lifespan (determined by the duration of positive or negative SST and vorticity without reversing thermal and rotating property for an eddy) and radius of four eddy types are provided in Fig. 4. The average radius of all oceanic eddies is approximately 25 km. Fig. 4 shows that eddies with radius about 18 km are the most prevalent. To place this observed scale more precisely, we note that it falls between the commonly used definitions for the lower bound of mesoscale eddies (25 km, as reported by Chelton et al., 2011; Tang et al., 2019; Uchida et al., 2021; Ren et al., 2023) and the typical scale of submesoscale eddies (10 km, as reported by Zhang et al., 2019; Ni et al., 2021). The average radius of unconventional eddies is larger than that of conventional eddies. The average lifespans of CCEs, WAEs, WCEs and CAEs are 2.79, 2.49, 2.31 and 2.18 days respectively. The average lifespan of CCEs (WAEs) is 20.62% (14.47%) longer than that of WCEs (CAEs). In addition, the depths of eddies (defined by the depth at which the temperature anomaly changes sign compared to the surface) are also provided (Fig. 4e, f). In CCEs and WAEs, the depth of 160m accounts for the largest proportion, while in WCEs and CAEs, the depth with the largest proportion reaches over 200 meters. As the depth reaching around 320m, the proportion of each eddy type sharply decreases. Notably, the average depth of conventional eddies is deeper than that of unconventional eddies, indicating that the temperature anomaly at depth present stronger in CCEs and WAEs while weaker in WCEs and CAEs. Conventional eddies exhibit a smaller horizontal temperature and vorticity structure range compared to unconventional eddies. In contrast, for unconventional eddies, the heat and momentum structures are more likely to dispersed in the horizontal plane. This observed structural difference may also correspond to the surface mismatch of temperature and vorticity anomaly centers mentioned when describing

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structures.

Fig. 4. The probability density of the lifespan, radius and depth of CCEs, WCEs, WAEs and CAEs within the Kuroshio front in the ECS during winters since 1993 in the GLORYS12V1, respectively.

Similarly, the statistical results of the lifespan and radius of various eddies detected by the GOFS are in high agreement with the results derived from the GLORYS12V1 (Fig. S7). It suggests that the characterization of the basic properties of each eddy type by different reanalysis data is consistent. In order to systematically explore the characteristics of air-sea interactions over various types of eddies, the remaining content of this section uses the spatiotemporal statistical results of various oceanic eddies combined with the ERA5 atmospheric reanalysis data, to thoroughly discuss the air-sea coupling process and the atmospheric response caused by various eddies.
The probability density distributions of SST anomalies, vorticity, turbulent heat flux (sensible and latent heat flux) anomalies and the MABL height anomalies at each eddy center point are

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further analyzed in Fig. 5. The peaks in the distribution of various physical quantities for four

types of eddies show some disparities, and the distribution of SST, air-sea heat flux and the MABL height above conventional and unconventional eddies present opposite behavior. The average positive (negative) SST anomaly corresponds to upward (downward) air-sea heat flux and positive (negative) MABL height anomalies in theory. It is worth noting that the magnitude of averaged SST anomalies and surface vorticity are substantially greater in CCEs and WAEs than in WCEs and CAEs. These results have raised several critical questions regarding: what are the possible physical mechanisms for the discrepancies in physical properties between different types of eddies? Does the atmospheric feedback on the ocean determine the shorter lifespan of WCEs and CAEs and longer lifespan of CCEs and WAEs? These questions form the basis for our subsequent study on the air-sea interaction processes in each eddy type.

Fig. 5. The probability density of sea surface temperature (SST), vorticity, air-sea heat flux and marine atmospheric boundary layer (MABL) height anomalies of CCEs, WCEs, WAEs and

AEs within the Kuroshio front in the ECS during winters since 1993, respectively.
Previous studies (Frankignoul et al., 1985; Wu et al., 2006; Bai et al., 2019) suggested that the lag-lead correlations between the SST (or SST tendency) and net air-sea heat flux can reflect the interaction between sea and atmosphere. The positive correlation between SST and heat

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flux indicates that the SST forces the atmosphere, whereas the negative correlation between
SST tendency and heat flux indicates the feedback of atmosphere on the SST. The lag-lead correlation is defined as:
CC(t’) = Cor (SST(t-t’), Q(t)).
Where t’ is the lag (positive when SST leads). For each lag, we align the two time series by offsetting the SST record backward by t’ days, then correlate only the overlapping segments of the offset SST series and the original Q series, ensuring both arrays have the same length and correspond to the same calendar days. This procedure is repeated across all lags in our analysis. Figure 6 illustrates the lag-lead correlations between the regional average SST (or SST tendency) and air-sea heat flux of the KECS front zone and that of the area without eddy occurrence in the KECS front zone (Fig. 6a, b), as well as the lag-lead correlation between SST (or SST tendency) and air-sea heat flux at four types of eddy centers (Fig. 6c-f). The length of the regional average time series are 28 years × 90 days of the winters. The correlation between SST and heat flux of each type of eddies decreases as the days of SST leading heat flux decreases, and simultaneously shows a weak positive correlation. Further, the correlation between SST tendency and heat flux of each type of eddies maintains predominantly negative, reaching the most significant correlation at the concurrent day. The two correlations including oceanic eddies within the KECS front zone are stronger than those without oceanic eddies, demonstrating that the existence of oceanic eddies enhances both the forcing effect of SST on atmosphere and the feedback effect of atmosphere on SST through the exchange of air-sea heat flux.
Opposite air-sea relationships emerge between conventional and unconventional eddies. Compared to conventional eddies of CCEs and WAEs, unconventional eddies of WCEs and CAEs exhibit weaker simultaneous SST-heat flux correlations and their correlations decay more rapidly when SST lags heat flux. The maximum negative correlations between SST tendency and heat flux occur at approximately 2 days that SST tendency lagging heat flux for conventional eddies of CCEs and WAEs, while it appears with no lagging or leading for unconventional eddies of WCEs and CAEs. Furthermore, the maximum negative correlations between SST tendency and heat flux of CCEs and WAEs are weaker than -0.5, while that of

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WCEs and CAEs reach about -0.55, which are slightly stronger than that of CCEs and WAEs.

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353 Fig. 6. The lag-lead correlations between the SST (or SST tendency) and air-sea heat flux with 354 the KECS front zone during winters since 1993, including: (a) the correlations calculated by 355 regional average of SST (or SST tendency) and heat flux, (b) same as (a) but for areas with 356 eddy occurrences are removed, as well as the composite correlations on (c) CCEs, (d) WAEs, 357 (e) WCEs, and (f) CAEs. The x-axis is the number of leading days, where the negative values 358 represent the SST leading and the positive values represent the heat flux leading. The orange bold lines represent the average correlation between SST and air-sea heat flux, while the purple bold lines represent the average correlation between SST tendency and air-sea heat flux. The areas between the maximum and minimum correlation (orange and purple thin lines) are shaded in yellow and light purple, respectively. The orange triangles (purple circles) represent the maximum (minimum) of the average correlation between SST (tendency) and air-sea heat flux. The maximums (minimums) of each correlation have exceeded 95% significance level. |cor| indicates the 95% significance level for the correlations, calculated based on the effective sample size for each panel.
To more intuitively reflect this air-sea forcing relationships, we composited the evolution of heat flux around the time when the SST peaks (to highlight eddy forcing on the atmosphere), and the evolution of SST tendency around the time when the heat flux peaks (to highlight atmospheric feedback to the eddy) (Figs. 7&8 for WAEs and WCEs. Cold eddies are similar, thus not given). The times of middle panels (b&e) are the occurring times when correlations reach the peaks. According to Fig. 6, the heat flux-SST correlation peaks at day -3 for both WAEs and WCEs, and the heat flux-SST tendency correlation peaks at day 2 for WCEs and day 0 for WCEs. We then show composites of heat flux at the time when the heat flux-SST correlation peaks (panels b), as well as two days before (panels a) and two days after (panels c). Similarly, composites of SST tendency are shown when the heat flux-SST tendency correlation peaks (panels e), together with two days before (panels d) and two days after (panels f). For both conventional and unconventional eddies, the air-sea heat flux reaches maximum amplitude at the time when the heat flux-SST correlation peaks (Figs. 7b&8b), while the SST tendency reaches maximum when the heat flux-SST tendency correlation peaks (Figs. 7e&8e). Notably, the magnitude of the air–sea heat flux is substantially larger for conventional eddies than for unconventional eddies, indicating a stronger oceanic forcing on the atmosphere by conventional eddies. In contrast, unconventional eddies exhibit a much larger SST tendency than conventional eddies, suggesting a stronger atmospheric feedback on the evolution of

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388 Fig. 7. The lag-lead composites of WAEs with lifespans of more than 5 days. Upper row: (a- 389 c) Centered on the time of peak SST anomaly (Day 0_SST). Shadings: heat flux anomaly (Q) 390 (unit: W/m2) at (a) Day 0_SST -4, (b) Day 0_SST -2, (c) Day 0_SST. Contours: SST anomaly 391 (unit: ℃) at Day 0_SST (identical in a-c). Lower row (d-f): Centered on the time of peak heat 392 flux anomaly (Day 0_Q). Shading: SST tendency (unit: ℃) at (d) Day 0_Q, (e) Day 0_Q +2, 393 (f) Day 0_Q +4. Contours: heat flux anomaly (unit: W/m2) at Day 0_Q (identical in d-f). Lag 394 days are chosen based on peak correlations in Fig. 6.

Fig. 8. The lag-lead composites of WCEs with lifespans of more than 5 days. Upper row: (a-c)
Centered on the time of peak SST anomaly (Day 0_SST). Shading: heat flux anomaly (Q) (unit: W/m2) at (a) Day 0_SST -4, (b) Day 0_SST -2, (c) Day 0_SST. Contours: SST anomaly (unit: ℃) at Day 0_SST (identical in a-c). Lower row (d-f): Centered on the time of peak heat flux anomaly (Day 0_Q). Shading: SST tendency (unit: ℃) at (d) Day 0_Q -2, (e) Day 0_Q, (f) Day 0_Q +2. Contours: heat flux anomaly (unit: W/m2) at Day 0_Q (identical in d-f). Lag days are chosen based on peak correlations in Fig. 6.
These temporal and amplitude differences shown in Figs. 6-8 imply that the atmospheric thermal feedback on conventional eddies lags behind the development of the heat flux anomaly, whereas SST anomalies respond almost immediately to changes in heat flux over unconventional eddies. This delayed feedback for conventional eddies may allow SST anomalies to persist and even amplify, thus contributing to their longer lifespans (consistent with Fig. 4). In contrast, the more immediate and stronger atmospheric feedback on unconventional eddies promotes rapid thermal damping and suppresses further growth of SST anomalies, likely shortening their lifespans.
Given the different turbulent heat flux responses on various eddy types, more specific

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on how heat flux influences the SST anomaly maintenance is required. The ocean
heat budget, which directly influences the atmosphere through heat flux, was analyzed through the heat balance equation (Orvik and Skagseth, 2005; Jiang et al., 2024; Lu et al, 2025) as below:
𝜕𝑇	𝑄	- 𝑞(-ℎ )	𝑤 𝛥𝑇
𝑒 = net	𝑒	-𝑢𝑒	⋅ 𝛻𝑇𝑒	-𝑢𝑒	⋅	𝛻𝑇𝑏	-𝑢𝑏	⋅	𝛻𝑇𝑒	+𝜅𝛻2𝑇𝑒	-	𝑒
𝜕𝑡	𝜌0 𝐶𝑝ℎ𝑒	ℎ𝑒
Where Qnet is the sea surface net heat flux including net short-wave radiation flux Qsw, net longwave radiation flux Qlw, sensible heat flux Qsh, and latent heat flux Qlh. Variable q(-he) represents the downward heat flux through the bottom of the eddy:
[
ℎ𝑒	ℎ𝑒
𝑅𝑒𝛾1 + (1 - 𝑅)𝑒𝛾2]
Where q(0) is the surface downward short-wave radiation. R, γ1 and γ2 are constants which are set to 0.67, 1.0, and 17.0, respectively. Te is the eddy temperature, Tb is the background temperature, he is the eddy depth (the depth at which the temperature anomaly changes sign compared to its surface value), Cp and ρ0 are the specific heat and seawater density, ue is the eddy velocity, ub is the background velocity, we is the coil clamp velocity (𝑤𝑒 = 𝜕ℎ𝑒 + ∇ ∙ ℎ𝑒𝑣⃑, 𝑣⃑ is the horizontal velocity), κ is the eddy diffusion coefficient, ΔT is the temperature difference between the eddy bottom and the average from sea surface to eddy bottom. To the right side of the equation, the first term represents the surface heat flux, the second-to-fourth term represents the temperature advection, and the fifth and sixth terms represent the dissipation and the entrainment processes, respectively. Each term of the heat balance equation is calculated for each type of eddy (Fig. 9a). For the convenience of comparison, we processed the dT/dt values of each eddy type into absolute values. In this figure, the dT/dt term is directly derived from the existing eddy data in GLORYS12V1, independent of the heat balance equation above (i.e. the temperature variation over time for eddies). The remainder term is the dT/dt term minus the sum of the heat flux, advection, dissipation and entrainment terms (i.e. all terms on the right side of the heat balance equation). The difference between the directly derived dT/dt term and the calculated dT/dt by the equation is acceptably minor, indicating that this equation can generally describe the heat budget of four types of eddies. It is suggested that the heat flux term plays a most important role and the advection term is not dominant in heat balance processes. The dissipation and entrainment term plays an almost negligible role. Notably, unconventional

443

eddies exhibit a stronger heat flux term along with a weaker advection term compared to conventional eddies. This means the atmospheric thermal feedback (damping) is not only stronger but also less counteracted by oceanic processes in unconventional eddies, leading to more rapid SST anomaly decay. Therefore, it is believed that the turbulent heat flux may be a crucial physical mechanism responsible for the accelerated thermal damping and shorter lifespans of unconventional eddies. Moreover, the response rate dQ/dT (Q is surface heat flux and T is SST) is a crucial metric for quantifying the strength of the heat flux’s thermal feedback on SST anomalies. Following the methodology of Yuan et al. (2022) and Wu & Mahadevan (2024), we have calculated the dQ/dT values for the four eddy types (Fig. 9b) as:
𝑑𝑄𝑠	𝑑𝑄𝐿	𝑑𝑞𝑠𝑎𝑡
= 𝜌𝑎𝑐𝑎𝑐ℎ𝑢𝑎,	= 𝜌𝑎𝐿𝑒𝑐𝑒𝑢𝑎	|𝑆𝑆𝑇0.
ρa, ca, and ua are the density, specific heat capacity, and wind speed of the surface air. Le is the latent heat of evaporation. ch and ce represent transfer coefficients of sensible and latent heat flux. qsat is the sea surface saturated specific humidity. SST0 is time averaged SST. The first equation represents the sensible heat flux term while the second equation represents the latent heat flux term. The sum of the two terms above is the total response rate dQ/dT. As Yuan et al. (2022) and Wu & Mahadevan (2024) pointed, a larger dQ/dT indicates stronger damping (negative feedback) of SST anomalies by the atmosphere. In our calculation, the four types of eddies exhibit different dQ/dT values. The dQ/dT for unconventional eddies are slightly higher than those for conventional eddies. A higher dQ/dT indicates a more efficient atmosphere-to-ocean heat flux adjustment per unit of SST anomaly. Therefore, the marginally stronger feedback over unconventional eddies creates favorable conditions for more rapid thermal damping of their SST anomalies, possibly contributing to their shorter lifespans compared to conventional eddies. Moreover, the above findings of contrast relationships between conventional and unconventional eddies are consistent with the more discernible linearized scatterplots of SST and heat flux anomalies for conventional eddies which are 468

469

470	Fig. 9. (a) The average values of each term of the heat balance equation for each eddy type
471	(unit: ℃/day). (b) The response rate dQ/dT (W·m-2·K-1) of four types of eddies. “S” represents
472	the sensible heat flux component and “L” represents the latent heat flux component.
473
474	Additionally, Ni et al. (2023) suggested that conventional eddies can convert into
475	unconventional eddies. They proposed that under the wind stress forcing and turbulent heat
476	flux, the thermal property of eddy center over the mixed layer will be reversed through Ekman
477	pumping. We calculated the conversion between conventional and unconventional eddies and
478	SST anomalies for each eddy types within the KECS front zone in Fig. S9. The proportions of
479	CCEs, WAEs, WCEs and CAEs with conversions into opposite thermal types are 20.32%, 480	21.12%, 35.04% and 36.57%, respectively. It costs more (less) days for conventional 481	(unconventional) eddies to be transformed into unconventional (conventional) eddies since
482	their genesis. The persistence of conventional eddies during each conversion period is generally
483	longer than that of unconventional eddies. Besides, the SST anomalies become weaker when the conversion frequency rises for each eddy types. This discovery is consistent with the longer lifespans of conventional eddies than unconventional eddies, which may also be attributable to the later atmospheric feedback that weakens negative (positive) SST on conventional CCEs (WAEs) and the earlier atmospheric feedback that weakens positive (negative) SST on unconventional WCEs (CAEs). However, in-depth research on detailed dynamic and thermal mechanism of the eddy transformation from unconventional to conventional needs to be conducted in the future.
3.3 Mid-low atmospheric Responses to conventional and unconventional eddies
The atmospheric responses to four types of eddies also exhibit distinct differences, primarily dominated by the thermal forcing of oceanic eddies on the MABL vertical structure via air-sea heat flux exchange. Fig. 10 provides the composites of air-sea heat flux and the MABL height anomalies in four types of eddies. It can be seen that the maximums of heat flux and MABL height anomalies are both located in the eddy centers with anomaly intensities gradually weakening toward the periphery. The spatial ranges of various physical quantity anomalies span larger area than that of oceanic fields such as SST anomalies. Due to the forcing by eddy SST, CCEs and CAEs (WCEs and WAEs) can lead to the occurrence of downward (upward) anomalies in air-sea heat flux and reduce (increase) the MABL height. The response of heat flux and MABL height to cyclonic eddies (CCEs and WCEs) is slightly stronger than that to

503

anticyclonic eddies (WAEs and CAEs).

Fig. 10. The compositions of air-sea heat flux anomalies (shadings, W/m2) and MABL height anomalies (contours, m) over all identified eddies in their entire lifespans within the KECS front zone during winters since 1993: (a) CCEs, (b) WAEs, (c)WCEs and (d) CAEs.

Furthermore, Fig. 11 presents the three-dimensional response of air temperature and wind speed over different eddy types ranging from 1000 to 750 hPa. The spatial distribution patterns of composited temperature and wind speed fields are similar to that of air-sea heat flux and MABL. Cyclonic eddies (CCEs and WCEs), which generate greater heat flux and higher MABL, produce stronger atmospheric heating or cooling and more pronounced wind speed modifications compared to anticyclonic eddies (WAEs and CAEs). The structure of air temperature anomalies is similar to that of the SST anomalies of eddies. The peak air temperature anomaly over four types of eddies occurs at the pressure of approximately 875 hPa,

517

not in the lower atmosphere, while the maximum wind speed anomaly occurs in the lower

atmosphere around 975 hPa.

Fig. 11. The compositions of air temperature anomalies (shadings, ℃) and wind speed anomalies (contours, cm/s) over (a) CCEs, (b) WAEs, (c)WCEs and (d) CAEs within the KECS front zone during winters since 1993, including the horizontal section at 1000 hPa and a latitudinal vertical section from 1000 to 750 hPa.

Similarly, Fig. 12 shows the three-dimensional response of atmospheric geopotential and vertical velocity over four types of eddies from 1000 to 750 hPa. The composites of geopotential and vertical velocity also show a similar pattern where the central extremum weakens towards the periphery. Unlike air temperature and wind speed, the change in

529

geopotential is not significantly different between conventional and unconventional eddies.
The increase or decrease in vertical velocity caused by CCEs and WAEs is greater than that caused by WCEs and CAEs. The peak geopotential height anomaly occurs above the eddies close to the sea surface. The peak vertical velocity anomaly occurs at approximately 875 hPa, which is at the same level as the center of air temperature anomaly (the level of peak vertical
velocity anomaly above warm eddies WCEs and WAEs is even higher than that of air

temperature anomaly).

Fig
. 12. The compositions of geopotential anomalies (shadings, m2/s2) and vertical velocity ,
anomalies (contours, m/s) over (a) CCEs, (b) WAEs, (c)WCEs and (d) CAEs within the KECS front zone during winters since 1993, including the horizontal section at 1000 hPa and a latitudinal vertical section from 1000 to 750hPa.

542

to more

response

to

types of

Table S1 provides specific extreme value anomalies (from the eddy composite) of various physical quantities at the sea surface. For oceanic eddies, positive (negative) SST anomalies invariably cause positive (negative) anomalies of various physical quantities. The extreme values of various physical quantities above the eddy sea surface are basically at the same order of magnitude. There is no significant difference in the degree of forcing of the lower atmosphere between CCEs and CAEs (WAEs and WCEs), which also suggests that the atmospheric response mainly comes from the thermal forcing of seawater, regardless of the rotating characteristics of eddies. In summary, the SST anomalies of eddies force the atmosphere through the air-sea heat flux, which extends from the sea surface to the upper MABL. The response of vertical velocity and temperature in the middle layer changes the MABL height and also changes the downward transfer of momentum in the upper atmosphere causing responses in lower wind speed.
4 Conclusions and discussion
Oceanic eddies widely occur in the upper ocean, which have complex spatial structures and significant impacts on the marine atmospheric boundary layer above (Ma et al., 2015; Chen et al., 2017; Hu et al., 2021). Previous studies have found the cold cyclonic eddies (CCEs), warm anticyclonic eddies (WAEs), warm cyclonic eddies (WCEs), and cold anticyclonic eddies (CAEs) widely exist in global ocean (Sun et al., 2019; Liu et al.,2020; Ni et al., 2021, 2023), and some of these studies emphasized the response of the air-sea heat flux and low-level atmospheric wind to the forcing of a certain eddy type. However, the large eddy kinetic energy in the Kuroshio front zone of the East China Sea (KECS front zone) leads to more occurrence of eddies in this region (Shi et al., 2021). At present, the three-dimensional structure and the air-sea interaction processes of the four types of eddies in the KECS front zone remain unclear. Using the daily GLORYS12V1 reanalysis and the ocean model output dataset Global Ocean Forecasting System (GOFS) during winters since 1993, this study provides the threedimensional structures and spatiotemporal distribution features of four eddy types in the KECS front zone, respectively. Through the analysis on probability densities of various oceanic eddies are discovered. With the combination of the fifth generation European Centre for Medium-Range Weather Forecasts reanalysis (ERA5), the coupling feedback between the sea surface temperature (SST) and turbulent heat fluxes, as well as the three-dimensional structures of middle and lower atmospheric responses are also revealed among diverse eddies.

571

quantities,

and

structures of

and unconventional

In winter, both conventional eddies (CCEs and WAEs) and unconventional eddies (WCEs and CAEs) widely exist in the both sides of the main axis of KECS. In Kuroshio front region, CCEs, WAEs, WCEs and CAEs respectively account for 42.3%, 31.2%, 12.3%, and 14.2% among all eddies. Cyclonic (anticyclonic) eddies are more likely to occur on the north (south) side of the Kuroshio main axis. The detailed mechanisms of the formation of unconventional eddies, including the transformations from conventional eddies by the wind stress forcing (Ni et al., 2023), are to be further explored in the future. In terms of the three-dimensional structure of eddies, the positive (negative) current vorticity anomalies of cyclonic (anticyclonic) eddies extend to the depth deeper than 400 meters. The vertical structure of conventional eddies (CCEs and WAEs) presents the same sign for temperature anomalies from the sea surface to the deep ocean, while that of unconventional eddies (WCEs and CAEs) shows a dipole pattern with opposite temperature anomalies between the depth of 400 meters and the sea surface. Tilted vertical structures are found in CCEs and WCEs, which are possibly resulted from the vertical shear of background current, especially cyclonic eddies appear more frequently and closer to the KECS axis. Statistically analysis shows that the mean lifespans of conventional eddies are longer than that of unconventional eddies, which may be influenced by the strength of the coupling relationship between the SST anomalies and air-sea heat flux. Smaller horizontal ranges for conventional eddies indicate that heat and momentum are more likely to concentrate within eddies, which may be more conducive to the long-term maintenance of their structures. Wider horizontal ranges for unconventional eddies indicate that the heat and momentum structures are more likely to dispersed in the horizontal plane, creating less favorable conditions for the long-term maintenance of eddy structures. The lagged composites of eddy SST tendencies and heat flux show that the forcings of WCEs and CAEs on lower atmosphere are weaker than CCEs and WAEs while the atmospheric feedbacks to the SST of the WCEs and CAEs are stronger than that of the CCEs and WAEs. On the other hand, it takes longer time

601

for conventional eddies to be transformed into unconventional eddies compared to the
602 transformation from unconventional eddies to conventional eddies, which is consistent with 603 longer lifespans of conventional eddies. Conventional eddies exhibit stronger thermal 604 properties which is reflected by greater SST anomalies and deeper vertical structure than 605 unconventional eddies. Therefore, conventional eddies are likely to possess larger heat content 606 than unconventional eddies which results in the SST of conventional eddies more difficult to 607 be forced by heat release or absorption while unconventional eddies much quicker to be 608 influenced. The weaker oceanic forcing on atmosphere and quicker atmospheric feedback to 609 ocean, along with the weaker heat content, are contributive to the quicken thermal damping of 610 unconventional eddies, accelerating the dissipation of SST anomalies.
611 The responses of middle and lower atmosphere to the forcings from four eddy types show 612 significant differences (Fig. 13). The composite results show that there are downward (upward) 613 air-sea heat flux anomalies and negative (positive) atmospheric boundary layer height 614 anomalies in the CCEs and CAEs (WAEs and WCEs). Meanwhile, CCEs and CAEs (WAEs 615 and WCEs) cool (heat) the above atmosphere and trigger downward (upward) vertical velocity 616 anomalies, especially in the middle atmosphere (875 hPa) rather than the level near the sea 617 surface. The deceleration (acceleration) of wind speed over the CCEs and CAEs (WAEs and 618 WCEs) are most significant at the level near the sea surface (975 hPa).

Fig. 13. The conceptual diagram of the three-dimensional marine atmospheric boundary layer (MABL) responses to four types of eddies.
In summary, this study shows the three-dimensional structure and the air-sea interaction processes of the conventional eddies (CCEs and WAEs) and unconventional eddies (WCEs and CAEs) within the KECS front zone during winter seasons since 1993. These results can help to further understand the processes of mid-latitude air-sea interactions considering the mesoscale and microscale oceanic eddies. Ni et al. (2021) proposed that inter-seasonal discrepancies exist in the distribution of each eddy type, indicating that the underlying generation and maintenance mechanisms for these eddies, likely tied to inter-seasonal variations in air-sea coupling, are fundamentally different. More detailed oceanic and atmospheric processes during the evolution of oceanic eddies (especially the conversions of eddies) and more mechanisms behind the inter-seasonal differences are supposed to be revealed in the future. While this study has highlighted the dominant role of contrasting thermal feedback processes in governing the air-sea interaction and lifespans of conventional and unconventional eddies, the potential contributions from dynamic coupling mechanisms, such as wind-stress-induced Ekman pumping and its feedback on eddy evolution, represent an important avenue for future research. Last but not least, it is important to note that our definition of unconventional eddies relies on sea surface temperature anomaly. Future work investigating these features using surface buoyancy anomaly, which incorporates the effects of salinity, would provide valuable further insight into their three-dimensional structure and thermodynamic coupling with the atmosphere.
Acknowledgments
The authors thank the anonymous reviewers for their valuable time and insightful comments, which have greatly improved the scientific quality and clarity of this work. The authors would like to thank Haokun Bai from College of Meteorology and Oceanography, National University of Defense Technology for the discussions on this work. This work was supported by the

648

National Key Program for Developing Basic Science (grants 2022YFF0801702 and 2022YFE0106600), the National Natural Science Foundation of China (Grants 42175060 and 42405047), the Youth Independent Innovation Science Foundation (Grant ZK23-56). The authors are thankful for the support of the Jiangsu Provincial Innovation Center for Climate Change.
Data Availability Statement
The datasets used in our study are the GLORYS12V1 reanalysis (https://doi.org/10.48670/moi- 00021) (Fernandez & Lellouche, 2021), the Hybrid Coordinate Ocean Model (HYCOM) product Global	Ocean Forecasting	System (GOFS)	3.1	output (https://www.hycom.org/dataserver/gofs-3pt1/reanalysis) (Metzger et al., 2017), the Global Ocean Gridded L 4 Sea Surface Heights And Derived Variables Reprocessed 1993 Ongoing (https://doi.org/10.48670/moi-00148), the ESA SST CCI and C3S reprocessed sea surface temperature analyses (https://doi.org/10.48670/moi-00169) and the fifth generation European Centre for Medium-Range Weather Forecasts reanalysis (ERA5) for the global climate and weather for the past eight decades (https://cds.climate.copernicus.eu/datasets/reanalysis-era5- single-levels?tab=overview;	https://cds.climate.copernicus.eu/datasets/reanalysis-era5- pressure-levels?tab=overview) (Hersbach et al., 2017, 2023)
Conflicts of interest/Competing interests
The authors have no conflicts of interest to declare that are relevant to the content of this article.
Authors’ contributions
Writing ‐ original draft: Tangxuan Song and Haibo Hu
Writing - Review and Editing: Shengyi Qian, Haibo Hu, Xiaoming Zhai, Xiu-Qun Yang and Weixuan Chen
Visualization: Tangxuan Song
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