A method to study the interannual variation of eddy kinetic energy in the South Pacific subtropical countercurrent region and its relationship with ENSO

Abstract

The present invention discloses a method for studying the interannual variation of eddy kinetic energy in the South Pacific subtropical countercurrent region and its connection with ENSO, the method comprising: acquiring data; obtaining the interannual variation characteristics of EKE in the STCC region by power spectrum analysis; determining whether the interannual variation of EKE in the STCC region is modulated by the ENSO process; analyzing the influence of El Niño and La Niña events on the spatial distribution of EKE in the STCC region; determining the relationship between the vertical shear of STCC and SEC velocities in the STCC region and ENSO; analyzing how ENSO affects the changes in wind stress curl and sea level height in the southwest Pacific. The present invention solves the technical problem that the prior art does not involve the interannual variation of eddy kinetic energy in the South Pacific subtropical countercurrent region and its dynamic connection with ENSO, and concludes that the EKE in the STCC region has interannual variation and is positively correlated with ENSO.

Description

Technical Field

[0001] The invention relates to an interannual variation law of eddy kinetic energy in a subtropical countercurrent region, and in particular to a method for studying the interannual variation of eddy kinetic energy in a subtropical countercurrent region of the South Pacific and its connection with ENSO. Background Art

[0002] Mesoscale eddies play a vital role in the transport of ocean momentum and heat, and are the bridge between large-scale, submesoscale and small-scale energy cascade dynamic processes. In the global distribution of mesoscale eddies, in addition to the strong eddy activity at the western boundary of the ocean, the subtropical countercurrent sea area within the subtropical gyre is also a high-value area of ​​mesoscale eddy activity. Compared with other subtropical regions, the sea level height and eddy kinetic energy (EKE) in the South Pacific Subtropical Countercurrent region have relatively linear ocean dynamic processes, and the interannual and interdecadal changes in the atmosphere play an important role in the mesoscale changes in the ocean. As the main feature of the mid-latitude ocean, the South Pacific Subtropical Gyre presents an inclined structure as a whole, and there are two main flows in the subtropical countercurrent region: the eastward subtropical countercurrent (STCC) and the westward South Equatorial Current (SEC).

[0003] Existing studies have shown that STCC is mainly located in the range of 20°S~30°S, about 300 meters in the upper layer. STCC is formed by the main thermocline rising to the surface with shallow isopycnals. The bottom of the flow is located more southward due to its higher density. At the same time, due to vortex disturbance, STCC is not a continuous flow, but a series of eastward branches, which can extend to 300~500 meters in the lower layer. Studies have shown that the intensity of STCC is modulated by seasonal surface winds and buoyancy forcing, reaching its strongest in summer. As the northern wing of the subtropical circulation, SEC extends from 4°N to 30°S. There are three branches of SEC in the South Pacific. The northern branch turns to the equator from the east of the Solomon Islands, the southern branch is south of New Caledonia, and the middle branch flows into the Coral Sea from the north of New Caledonia and the southernmost tip of the Solomon Islands. The seasonal changes in the zonal flow of the three branches of SEC can be reflected by the gradient of sea level anomaly (SLA). At the same time, SEC is strengthened at the surface, and its interannual transport is well correlated with the surface geostrophic current obtained by AVISO. Due to the presence of the large islands in the southwest Pacific, the SEC splits into different jets. There is the North Fiji Jet (NFJ) and the South Fiji Jet (SFJ) in the north and south of Fiji, the North Vanuatu Jet (NVJ) in the north of Vanuatu, and the North Caledonian Jet (NCJ) and the South Caledonian Jet (SCJ) in the north and south of New Caledonia, respectively. Previous studies have used linear Sverdrup dynamics that ignore the existence of islands to find that the jet structure of the large islands is quasi-permanent and is generated in the middle of the ocean east of the islands. These jets are caused by the wind in the middle of the ocean basin, which destroys the overall flow of the SEC and produces strong zonal flows. After the flow encounters a high island, the presence of the wind curl dipole causes the flow velocity to reach the minimum in the leeward direction, and the jet is further narrowed under the action of the island blocking effect. These jets carry warm, salty subtropical waters into the Coral Sea, where they are redistributed at their western boundary, with those transported northwards into the Solomon Sea and eventually to the equator, and those transported southwards polewards through the East Australian Current (EAC).

[0004] As an indicator of the intensity of mesoscale eddy activity, previous studies have conducted a series of studies on the EKE in the subtropical region of the South Pacific. The eddy activity is strongest in the western part of the subtropical countercurrent region and weakens eastward. On a seasonal scale, the average potential vorticity gradients of STCC and SEC in the range of 180°W~140°W and 21°S~29°S have opposite signs. The surface cooling in August causes the vertical shear to increase and the density gradient to decrease. After a 3-month lag response, the EKE reaches its maximum value in the STCC region in the austral summer. On an interdecadal scale, reanalysis data show that the vertical shear of STCC and SEC velocities and stratification jointly regulate the baroclinic instability in the STCC region, among which the baroclinic instability caused by the vertical shear is twice that of the stratification. At the same time, using sensitivity experiments from 1958 to 2009, it is pointed out that the interdecadal variation of EKE in the southern branch of the SEC (175°W~153°W, 25°S~33°S) is mainly affected by the change in STCC intensity caused by the change in the meridional density gradient, while the high EKE in the 1970s was affected by the local wind stress curl anomaly associated with the Interdecadal Pacific Oscillation (IPO). At the same time, the large-scale sea-air process El Niño-Southern Oscillation (ENSO) event on the interannual scale can affect the interannual variation of STCC and SEC. Studies have found that in the strong ENSO event from 1997 to 1998, the sea surface height in the Polynesian waters (160°W~140°W) changed strongly during the El Niño period, and the STCC velocity increased; while during the La Niña period, the STCC branch was more obvious, but weakened in the east (142°W~138°W and eastward). The annual transport of the middle branch of the SEC changes with the cycle of ENSO. Through the long Rossby wave reduced gravity model, it is found that ENSO affects the interannual variation of the transport of the middle branch (10°S~20°S) of the SEC into the Coral Sea by affecting the fluctuation of the thermocline depth from 1985 to 2010. The wind stress curl in La Niña years causes the thermocline to tilt abnormally toward the equator, resulting in a weakening of the SEC, while the SEC is strengthened in El Niño years. On seasonal and interdecadal scales, the EKE in the South Pacific subtropical countercurrent region is regulated by the baroclinic instability caused by the vertical shear between the upper STCC and the lower SEC.

[0005] Through the above analysis, the problems and defects of the existing technology are as follows: Insufficient research on the interannual scale: Although the existing technology has conducted a series of studies on the seasonal and interdecadal changes of EKE in the STCC region, the interannual variation law and driving factors of EKE in the STCC region are still unclear on the interannual scale; Incomplete analysis of influencing factors: The existing technology mainly focuses on the relationship between the subtropical North and South Pacific meridional mode and ENSO, as well as the ocean-atmosphere dynamic mechanism of the seasonal changes in the kinetic energy of the tropical unstable wave vortex in the Pacific, but the impact of ENSO and other ocean-atmosphere interaction processes and ocean dynamic processes on the interannual changes of EKE in the STCC region needs further study. Summary of the invention

[0006] The purpose of the present invention is to provide a method for studying the interannual variation of eddy kinetic energy in the South Pacific subtropical countercurrent region and its connection with ENSO, which solves the technical problem that the prior art does not involve the interannual variation of eddy kinetic energy in the South Pacific subtropical countercurrent region and its dynamic connection with the El Nino-Southern Oscillation. Through the present invention, it can be concluded that there is a significant interannual variation in eddy kinetic energy in the South Pacific subtropical countercurrent region and it is affected by the El Nino-Southern Oscillation event, and the El Nino (La Nina) year corresponds to strong (weak) eddy kinetic energy in the region. Under the action of geostrophic force, the eastward South Pacific subtropical countercurrent and the westward South Equatorial Current are strengthened (weakened), and ultimately affect the interannual variation of eddy kinetic energy in the South Pacific subtropical countercurrent region.

[0007] In order to achieve the above object, the present invention provides a method for studying the interannual variation law of eddy kinetic energy in the South Pacific subtropical countercurrent region and its connection with ENSO, the method comprising:

[0008] Step 1: Obtain SLA data, AVISO data, global ocean gridded data with a spatial resolution of 0.25°×0.25°, 10-meter wind field data with a spatial resolution of 0.25°×0.25°, Niño3.4 index and SAM index; use the Niño3.4 index to characterize ENSO events, the SAM index to characterize SAM, use the daily and monthly average flow field data with a spatial resolution of 0.25°×0.25° and 75 layers of unequal vertical spacing, and GLORYS2V4 to study the vertical changes of ocean circulation; the SAM is the Southern Hemisphere Annular Mode; the SLA data is the sea surface height anomaly data distributed by CMEMS.

[0009] Step 2: Calculate EKE based on the absolute geostrophic velocity anomaly in AVISO data, remove seasonal cycles from the EKE time series and perform one-year low-pass filtering to obtain the EKE interannual anomaly; standardize the EKE interannual anomaly and perform wavelet analysis to obtain the EKE power spectrum, and obtain the interannual variation characteristics of EKE in the STCC region through power spectrum analysis; the EKE is eddy kinetic energy, and the STCC region is the South Pacific subtropical countercurrent region.

[0010] Step 3: Study whether ENSO can affect the interannual variation of EKE in the STCC region on an interannual scale, and determine whether the interannual variation of EKE in the STCC region is modulated by the ENSO process through lead-lag correlation and partial correlation; define the months with a value greater than 0.5 times the standard deviation of the Niño3.4 index as El Niño years, and those with a value less than 0.5 times the standard deviation as La Niña years; the El Niño is El Niño, and the La Niña is La Niña.

[0011] Step 4: Explore the response of EKE to ENSO and analyze the impact of El Niño and La Niña events on the spatial distribution of EKE in the STCC region.

[0012] Step 5: Explore the dynamic mechanism of the EKE in this region on an interannual scale and determine the relationship between the vertical shear of STCC and SEC velocities in the STCC region and ENSO. The SEC is the South Equatorial Current.

[0013] Step 6: Analyze how ENSO affects the changes in wind stress curl and sea level height in the southwest Pacific, and affects the interannual changes in velocity vertical shear and EKE in the STCC region.

[0014] Preferably, in step one, the time resolution of the global ocean gridded data is daily average and monthly average, and the time resolution of the 10-meter wind field data is monthly average.

[0015] Preferably, in step 2, the EKE is defined as: In formula (1), is the latitudinal geostrophic velocity anomaly, It is the anomaly of the meridional geostrophic flow velocity.

[0016] Preferably, in step five, the interannual anomaly of EKE obtained by AVISO data is reanalyzed with CMEMS data to obtain the interannual variation law of surface EKE anomaly, and the interannual variation law of EKE in the STCC region is studied by reanalyzing CMEMS data.

[0017] Preferably, since the STCC and SEC cores are located in different latitudinal ranges and depths, the STCC region is divided into two latitudinal ranges, 18°S~21°S and 22°S~28°S, and the vertical variation of the latitudinal velocity is analyzed.

[0018] Preferably, in step five, STCC and SEC are selected again using CMEMS data to calculate the vertical shear of STCC and SEC in the STCC region; and the lead-lag correlation is used to determine how ENSO affects the interannual variation of EKE in the STCC region by affecting the vertical shear of STCC and SEC.

[0019] Preferably, when selecting STCC and SEC, the STCC core is at a depth of 50 meters in the range of 22°S~28°S in the 170°E longitudinal section, and the SEC core is at a depth of 275 meters in the range of 18°S~21°S, which are used to calculate the vertical shear of STCC and SEC in the STCC area.

[0020] Preferably, in step six, the ERA5 wind field data and SLA data are used to obtain the anticyclonic wind stress curl in the STCC region in the El Niño year, which makes the Ekman convergence in the region produce positive SLA, while the cyclonic wind stress curl in the north of the STCC makes the Ekman divergence produce negative SLA, and it is obtained how the generated SLA affects EKE by affecting the surface STCC and SEC under the geostrophic effect.

[0021] Preferably, in step six, in the STCC region in a La Niña year, the cyclonic wind stress curl causes the positive SLA corresponding to the Ekman divergence in the region, while the anticyclonic wind stress curl in the north of the STCC causes the Ekman convergence to produce a positive SLA, and it is determined how the generated SLA gradient affects EKE by affecting the surface STCC and SEC under the geostrophic effect.

[0022] The method of the present invention for studying the interannual variation of eddy kinetic energy in the South Pacific subtropical countercurrent region and its connection with ENSO solves the technical problem that the prior art does not involve the interannual variation of eddy kinetic energy in the South Pacific subtropical countercurrent region and its dynamic connection with El Nino-Southern Oscillation, and has the following advantages:

[0023] 1. The present invention uses satellite altimeter and reanalysis data for a total of 30 years from 1993 to 2022 to explore the interannual variation law and dynamic mechanism of EKE in the STCC region (21°S~29°S, 167°E~130°W). The study shows that there is a significant interannual variation in EKE in the STCC region, which is significantly positively correlated with ENSO. The correlation between the two is strongest when the Niño3.4 index lags behind by 6 months. At the same time, the present invention also studies the relationship between EKE and SAM. The correlation between the two is weaker than ENSO. Through further partial correlation analysis, it is found that the partial correlation coefficient between EKE and ENSO is larger, with a coefficient of 0.46, while the partial correlation coefficient between EKE and SAM is 0.37, so the impact of ENSO on EKE is more significant. The present invention mainly studies the impact of ENSO on EKE. The study of the 170°E longitudinal section found that both STCC and SEC were enhanced in strong EKE years, and weakened in weak EKE years.

[0024] 2. Further research in the present invention shows that ENSO modulates the interannual variation of EKE by affecting the vertical shear intensity of the upper STCC and the lower SEC in the subtropical countercurrent region. In El Niño years (La Niña years), the average STCC in the range of 22°S~28°S and the SEC in the range of 18°S~21°S are both enhanced (weakened). The vertical shear between STCC and SEC is most positively correlated when it lags the Niño3.4 index by 6 months, and the correlation is most significant when the vertical shear and EKE occur simultaneously. ENSO's modulation of the vertical shear of STCC and SEC is achieved by affecting the local wind stress curl in the southwest Pacific. The anticyclonic wind stress curl in the STCC region in El Niño years causes the Ekman convergence in the region to produce positive SLA, while the cyclonic wind stress curl in the northern STCC causes the Ekman divergence to produce negative SLA. The resulting SLA gradient strengthens the surface STCC and SEC under the geostrophic effect. As the SEC deepens, it affects the strength of the deep SEC. Therefore, the vertical shear strength between the STCC and SEC increases, leading to an enhancement of the EKE in the STCC region. The effect of the wind stress curl in La Niña years causes the STCC and SEC to weaken, and ultimately the EKE weakens. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is the distribution map of eddy kinetic energy in the southwest Pacific.

[0026] Figure 2 This is the seasonal variation diagram of the average eddy kinetic energy in the STCC region. The shaded part represents the standard deviation of the seasonal variation of the eddy kinetic energy.

[0027] Figure 3 Time series, continuous wavelet transform graph and wavelet power spectrum in the STCC region.

[0028] Figure 4 The interannual variations, lead-lag correlations, and partial correlations between the EKE anomaly averaged over the STCC region and the Niño3.4 index and SAM index.

[0029] Figure 5 This is the El Niño annual evolution diagram of the EKE anomaly in the STCC region.

[0030] Figure 6 This is the La Niña annual evolution diagram of the EKE anomaly in the STCC region.

[0031] Figure 7 This is the climatological flow field diagram obtained from AVISO and CMEMS data.

[0032] Figure 8 This is a comparative analysis of the interannual variations of surface EKE obtained from CMEMS data and the interannual variations of EKE in AVISO.

[0033] Fig. 9 This is the vertical distribution map of the latitudinal geostrophic current along the 170°E section.

[0034] Fig.10 This is a vertical composite map of the latitudinal geostrophic flow along the 170°E section.

[0035] Fig.11 This is a graph showing the correlation between the vertical shear anomalies of STCC and SEC velocities and the interannual variation and lead-lag of the Niño3.4 index in the STCC region.

[0036] Fig.12 This is the evolution diagram of the zonal velocity in the STCC region along the 170°E section in El Niño years and La Niña years.

[0037] Fig.13 This is a graph showing the temporal variation and lead-lag correlation between EKE anomaly and vertical shear anomaly.

[0038] Fig.14 This is a graph showing the temporal variation and lead-lag correlation between wind stress curl anomaly and the Niño3.4 index.

[0039] Fig.15 Composite maps of wind stress curl anomalies and 10-meter wind speed anomalies during El Niño and La Niña periods from January 1993 to December 2022 calculated for ERA5 data.

[0040] Fig.16 Composite maps of SLA and geostrophic velocity anomalies during El Niño and La Niña periods from January 1993 to December 2022 obtained from AVISO data after removing the long-term trend. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] A method for studying the interannual variation of eddy kinetic energy in the South Pacific subtropical countercurrent region and its relationship with ENSO, the method comprising:

[0043] Step 1: Obtain SLA data (SLA data is the sea surface height anomaly data distributed by CMEMS, and the SLA data used have all long-term trends removed), AVISO data (absolute geostrophic velocity anomaly is derived from AVISO daily average flow field data, Archiving, Validation, and Interpretation of Satellites Oceanographic data (AVISO) absolute geostrophic flow, absolute geostrophic velocity anomaly and sea surface height anomaly data (SLA data) are from Copernicus Marine Environment Monitoring Service (CMEMS)), and global ocean gridded data with a spatial resolution of 0.25°×0.25° and a temporal resolution of daily and monthly averages (by the French Collecte Localisation The global ocean gridded data from 1993 to 2022 initially released by CLS Satellites (CLS) is based on the 20-year average sea level from 1993 to 2012, integrating multiple satellite altimeter data such as Topex / Poseidon, Jason-1, OSTM / Jason-2, etc.) with a spatial resolution of 0.25°×0.25° and a temporal resolution of 10-meter wind field data averaged monthly (the 10-meter wind field data comes from the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis dataset (ECMWF Reanalysisv5, ERA5, ERA5 wind field data comes from Copernicus Climate Change Service (C3S) Climate DataStore (CDS)). This dataset is based on the Integrated Forecasting System (IFS) Cy41r2 assimilation system, including near-real-time single-layer wind field data from 1940 to the present), Niño3.4 index and SAM index (both Niño3.4 index and SAM index are released by the Climate Prediction Center (CPC) of the United States and can be downloaded from the NOAA Climate Prediction Center).

[0044] The Niño3.4 index is used to characterize ENSO events, and the SAM (Southern Annular Mode) index is used to characterize SAM. The daily and monthly average flow field data from 1993 to 2022 with a spatial resolution of 0.25°×0.25° and 75 layers of unequal vertical spacing from existing literature, as well as GLORYS2V4 (GLORYS2V4, a global ocean physical reanalysis system product from Mercator ocean, is a numerical ocean model that assimilates satellite and in-situ data. The numerical model used is NEMOv3.1, and the sea ice model is coupled to achieve an eddy-compatible resolution. GLORYS2V4 can also be obtained from CMEMS) are used to study the vertical changes in ocean circulation.

[0045] The Niño3.4 index is calculated from the sea surface temperature anomaly in the 5°N~5°S, 170°W~120°W region released by the Extended Reconstructed Sea Surface Temperature version 5 (ERSST v5) of the National Oceanic and Atmospheric Administration (NOAA). The SAM index is obtained from the first mode of the empirical orthogonal analysis (EOF) of the 700 hPa monthly average geopotential height anomaly in the 20°S poleward region of the southern hemisphere based on the average from 1979 to 2000. The present invention defines the month with a standard deviation greater than 0.5 times the Niño3.4 index as an El Niño year, and a month with a standard deviation less than 0.5 times the standard deviation as a La Niña year.

[0046] Step 2: EKE is calculated based on the absolute geostrophic velocity anomaly in the AVISO data. The EKE time series is filtered for one year after removing the seasonal cycle to obtain the EKE interannual anomaly. The EKE interannual anomaly is standardized and then subjected to wavelet analysis to obtain the EKE power spectrum. The interannual variation characteristics of EKE in the STCC region are obtained through power spectrum analysis.

[0047] Among them, the mesoscale eddy kinetic energy EKE is defined as: In formula (1), is the latitudinal geostrophic velocity anomaly, It is the anomaly of the meridional geostrophic flow velocity.

[0048] like Figure 1 As shown in the figure, the distribution of kinetic energy of the southwest Pacific eddy. Figure 1 It can be seen that the average value of the eddy kinetic energy in the STCC region is 195±39 cm 2 / s 2 , which is similar to the research results of the prior art.

[0049] like Figure 2 As shown in Figure 2, the seasonal variation of the average eddy kinetic energy in the STCC region, the shaded area represents the standard deviation of the seasonal variation of the eddy kinetic energy. Figure 2 It can be found that the EKE is the smallest in June (149±21 cm 2 / s 2 ), the largest in November (254±43 cm 2 / s 2 ), which is consistent with the existing technology that the subtropical mesoscale vortex activity in the Southern Hemisphere is strong in summer.

[0050] like Figure 3 As shown, the time series, continuous wavelet transform map and wavelet power spectrum in the STCC region, including (a) the time series of the standardized EKE anomaly in the STCC region, (b) the continuous wavelet transform map of the standardized EKE anomaly, and (c) the wavelet power spectrum of the standardized EKE anomaly. Figure 3 It can be seen that there is an interannual signal of 4 to 7 years in EKE, which passes the 95% confidence test. Therefore, EKE in the STCC region has significant interannual variation.

[0051] Step 3: In step 2, we found that the EKE in the STCC region (the STCC region is the South Pacific subtropical countercurrent region) has an interannual variation with a period of 4 to 7 years. By comparing the EKE time series in the STCC region with the Niño3.4 index, we found that they have a consistent temporal variation pattern. We further considered whether ENSO can affect the interannual variation of EKE in the STCC region on an interannual scale, and determined whether the interannual variation of EKE in the STCC region is modulated by the ENSO process through lead-lag correlation and partial correlation.

[0052] like Figure 4 As shown, the interannual variation, lead-lag correlation and partial correlation of the STCC average EKE anomaly with the Niño3.4 index and the SAM index, including (a) the interannual variation of the STCC average EKE anomaly (gray filling) with the Niño3.4 index (red solid line) and the SAM index (blue solid line) after one year of low-pass filtering, (b) the lead-lag correlation of the EKE anomaly with the Niño3.4 index and the SAM index, and (c) the lead-lag partial correlation of the EKE anomaly with the Niño3.4 index and the SAM index. Among them, positive values ​​represent EKE lags, and gray dashed lines represent 95% confidence intervals. Figure 4From (a), we can see that the time series of EKE and Niño3.4 index in the STCC region show that El Niño years correspond to strong EKE years, especially the strong El Niño events of 1997-1998 and 2015-2016, while La Niña years correspond to weak EKE years. At the same time, the interannual variation of EKE and SAM index shows that the positive phase of SAM mainly corresponds to strong EKE years. Therefore, the present invention analyzes the relationship between EKE, ENSO and SAM through lead-lag correlation. Figure 4 As shown in (b), when EKE lags Niño3.4 index by 6 months, SAM and Niño3.4 have the strongest correlation, with a correlation coefficient of 0.41, which passes the 95% confidence test and has a significant positive correlation. That is, the EKE in the STCC region is enhanced in El Niño years, and the EKE is weakened in La Niña years. However, the lead-lag correlation between EKE and SAM index is weaker than that of ENSO, and does not pass the 95% significance test. Figure 4 (c) shows that through further partial correlation analysis, the present invention finds that when EKE lags 5 months, the partial correlation coefficient between the Niño3.4 index obtained by removing the SAM signal and EKE reaches 0.46, passing the 95% confidence test; the influence of SAM on EKE is weaker than ENSO, and the partial correlation coefficient between EKE and the SAM index when EKE lags 4 months is only 0.37, passing the 95% confidence test. The above results show that ENSO has a significant impact on EKE, and the impact of SAM on EKE is weaker than ENSO. Therefore, the present invention will further study the relationship between the interannual variation of EKE and ENSO.

[0053] Step 4: In step 3, it was found that ENSO has an impact on the interannual variation of EKE in the STCC region. In order to explore the response of EKE to ENSO, the impact of El Niño and La Niña events on the spatial distribution of EKE in the STCC region was analyzed.

[0054] like Figure 5 As shown in Figure 1, the evolution of EKE anomaly in the STCC region during El Niño years. Figure 5 It can be seen that when the peak period of El Niño is 2 months ahead, the positive anomaly of EKE in the STCC region is dominant, and the negative anomaly is mainly concentrated in the central part of the STCC region. With the demise of El Niño, the positive anomaly of EKE continues to strengthen. When the peak period of El Niño is 6 months behind, the positive anomaly of EKE is the strongest, and the strong value area is mainly concentrated in the north of 27°S. After that, the range and intensity of the positive anomaly of EKE continue to decrease.

[0055] like Figure 6 As shown in Figure 1, the La Niña annual evolution diagram of the EKE anomaly in the STCC region. Figure 6 It can be seen that the EKE in most areas shows negative anomalies in La Niña years, and the negative anomaly of EKE continues to increase with the lag time. The range and intensity of the negative anomaly of EKE reach the maximum 6 months after the peak of La Niña.

[0056] Step 5: In step 3, we obtained that ENSO has an impact on the interannual variation of EKE in the STCC region, and in step 4, we obtained that ENSO has an impact on the spatial distribution of EKE in the STCC region. Since the EKE in the STCC region on seasonal and interdecadal scales is dominated by the baroclinic instability of the vertical shear of the STCC and SEC, in order to explore the dynamic mechanism of EKE in this region on the interannual scale, the relationship between the vertical shear of the STCC and SEC velocities and ENSO in the STCC region is determined.

[0057] The present invention uses CMEMS reanalysis data to obtain the deep flow velocity in the STCC region. In order to verify the quality of the data set, the present invention obtains the distribution of the surface flow field in the southwest Pacific climatological state through AVISO and CMEMS reanalysis data. The overall flow characteristics are similar, and the surface layer in the STCC region presents a counterclockwise flow field characteristic.

[0058] like Figure 7 As shown in the figure, the climatological flow field diagram obtained by AVISO and CMEMS data, including (a) the climatological flow field of the southwest Pacific from 1993 to 2022 obtained by AVISO data, and (b) the climatological flow field averaged in the upper 100 meters obtained by CMEMS data. Figure 7 It can be seen that the surface layer of the subtropical countercurrent area presents a counterclockwise flow field characteristic, which is mainly composed of the westward SEC and the eastward STCC.

[0059] The present invention uses the interannual anomaly of EKE obtained by AVISO data and reanalyzes CMEMS data to obtain the interannual variation law of surface EKE anomaly, and uses CMEMS data reanalysis to study the interannual variation law of EKE in the STCC area.

[0060] like Figure 8 As shown, the interannual variation of surface EKE obtained from CMEMS data is compared with the interannual variation of EKE in AVISO, where (a) the interannual variation of EKE anomaly in the STCC region in AVISO data after one year of low-pass filtering, (b) the interannual variation of EKE anomaly in the STCC region in CMEMS reanalysis data. Among them, red coloring represents strong EKE years, and blue coloring represents weak EKE years. Figure 8 It can be seen that the correlation coefficient between the two reaches 0.9, and through the 95% confidence test, there is a significant correlation.

[0061] In the STCC region, due to the presence of the Norfolk Ridge sea ridge, the EKE near 170°E is particularly active, so the present invention selects the 170°E longitudinal section for the following research.

[0062] like Fig. 9As shown in the figure, the vertical distribution of latitudinal geostrophic current along the 170°E section, including (a) the change of climatological latitudinal geostrophic current with depth from 1993 to 2022, (b) the change of latitudinal geostrophic current with depth in strong EKE years, and (c) the change of latitudinal geostrophic current with depth in weak EKE years. Red represents eastward flow and blue represents westward flow. Fig. 9 From (a), we can see that along the 170°E section, within the range of 21°S~27°S, the climatological STCC has two velocity cores, mainly located in the upper 200 meters. Within 18°S~27°S, the velocities of multiple cores of STCC continue to increase and deepen with increasing latitude. Among them, the southern branch of STCC can extend to a depth of 200 meters in the deep layer, with a velocity core of 5 cm / s, and the northern branch is weaker, extending vertically to a depth of 150 meters, with a core velocity of 3 cm / s. For the westward SEC, the maximum value of the climatological velocity core is -5 cm / s, with a depth of 500 meters in the upper layer, mainly located in the range of 18°S~21°S. At the same time, within 18°S~27°S, SEC can extend southward to the lower layer of STCC with a velocity of -2 cm / s, and the depth of the SEC core deepens with increasing latitude. In summary, the STCC velocity core is located to the south, within the range of 21°S~27°S, and the SEC velocity core is located to the north, within the range of 18°S~21°S.

[0063] The present invention determines the year of strong and weak eddy kinetic energy (0.5 times the standard deviation of EKE anomaly obtained from AVISO data Figure 8 (a)). In strong and weak EKE years, the extent and intensity of STCC and SEC are different. Fig. 9 (b)), STCC and SEC are both higher than the climate state ( Fig. 9 (a) is stronger. In strong EKE years, the STCC surface flow range is wide, occupying the south of 21°S. STCC has strong values ​​near 24°S, with a maximum velocity core of 6 cm / s, located at a depth of 300 meters. At the same time, the core of SEC is located within 100~600 meters, with a core velocity of -6 cm / s in the north and -5 cm / s in the south. In weak EKE years ( Fig. 9 (c)), STCC has two velocity cores. The northern core is smaller, with a maximum velocity of 6 cm / s, located in the upper 200 meters; the southern velocity core is stronger, extending down to 300 meters, and the overall structure is similar to the climatological state. In weak EKE years, STCC is still very strong but splits into multiple cores, and the core in the north near SEC is weaker than that in strong EKE years. So in general, STCC is weaker in weak EKE years. At the same time, Fig. 9From the c, we can see that the SEC core is mainly located at 200-500 m in weak EKE years, with the maximum velocity of the northern core being -5 cm / s and the velocity in the southern core being only -4 cm / s. The SEC core extending to the lower layer of the STCC is enhanced, and the two SEC cores in the range of 23°S-24°S and 26°S-27°S are enhanced and extend to the surface. In short, the STCC and SEC are stronger in strong EKE years, and they are split into multiple cores in weak EKE years, and the intensity and range of the cores are reduced.

[0064] Since the latitudinal ranges and depths of the STCC and SEC cores are different, this paper divides the STCC region into two latitudinal ranges, 18°S~21°S and 22°S~28°S, to further analyze the vertical changes in velocity. Since the STCC region is dominated by latitudinal flow, this paper focuses on the latitudinal velocity changes.

[0065] like Fig.10 As shown, the vertical composite map of the latitudinal geostrophic flow along the 170°E section, where (a) the 22°S~28°S latitudinal geostrophic flow component varies with depth, and (b) the 18°S~21°S latitudinal geostrophic flow component varies with depth. The black solid line represents a strong EKE year, the blue dashed line represents a weak EKE year, the red line in (a) represents a depth of 50 meters, and the red line in (b) represents a depth of 275 meters. Fig.10 From (a), we can see that the meridional average STCC in the range of 22°S~28°S is mainly located in the upper 200 meters. The maximum zonal velocity of STCC in strong EKE years is 3.6 cm / s, located at a depth of 26 meters, and the maximum zonal velocity in weak EKE years is 2.9 cm / s, located at a depth of 27 meters. Therefore, for STCC, the maximum zonal velocity difference between strong and weak years is located at a depth of 50 meters in the upper layer. In the range of 22°S~28°S, the part deeper than 500 meters is the extension of SEC to the lower layer of STCC. The SEC is stronger in strong EKE years and weaker in weak EKE years. From Fig.10 From (b), we can see that in the range of 18°S~21°S, the SEC flows westward as a whole, with the strongest velocity being -5.1 cm / s in strong EKE years and -4.4 cm / s in weak EKE years. The maximum zonal velocity difference between strong and weak years is at a depth of about 275 meters. Therefore, the vertical change of zonal velocity shows that in strong EKE years, both the eastward STCC and the westward SEC are strengthened, while in weak EKE years, both are weakened.

[0066] ENSO can affect the interannual variation of the intensity of the middle branch of the SEC (10°S-20°S), and the prior art discloses that the relative changes of SEC and STCC play an important role in vertical shear. Therefore, the present invention discusses the relationship between ENSO and vertical shear on an interannual scale, selects STCC and SEC using CMEMS data, and calculates the vertical shear of STCC and SEC (SEC is the South Equatorial Current) in the STCC region; and determines how ENSO affects the interannual variation of EKE in the STCC region by affecting the vertical shear of STCC and SEC using the lead-lag correlation.

[0067] The present invention selects the 50-meter depth of the 22°S~28°S range in the 170°E longitudinal section to represent the STCC core, and the 275-meter depth of the 18°S~21°S range to represent the SEC core, which are used to calculate the vertical shear of STCC and SEC in the STCC area ( u).

[0068] like Fig.11 As shown in the figure, the vertical shear anomaly of STCC and SEC velocity in the STCC region and the interannual variation and lead-lag correlation of the Niño3.4 index, where (a) after one year of low-pass filtering, the vertical shear anomaly of STCC and SEC velocity in the STCC region ( u, red line) and the interannual variation of the Niño3.4 index (black line), the blue solid line represents the 275-meter SEC zonal velocity (u(SEC)), and the blue dashed line represents the 50-meter STCC zonal velocity (u(STCC)). (b) The lead-lag correlation between the velocity vertical shear anomaly and the Niño3.4 index, where a positive value indicates that the vertical shear lags behind the Niño3.4 index. Fig.11 It can be seen that the interannual variation of SEC is negatively correlated with the Niño3.4 index, and the positive correlation between STCC and Niño3.4 index is not obvious. The interannual variation of vertical shear between the two shows that vertical shear is enhanced in El Niño years and weakened in La Niña years. In addition, the lead-lag correlation between vertical shear and Niño3.4 index shows that the correlation between the two is best when vertical shear lags Niño3.4 index by 6 months, with a correlation coefficient of 0.43, exceeding the 95% confidence test, and showing a significant positive correlation. Therefore, ENSO can affect the vertical shear of STCC and SEC on an interannual scale.

[0069] The present invention further analyzes the spatial evolution of STCC and SEC during the ENSO period.

[0070] like Fig.12 As shown in the figure, the evolution of the zonal velocity in the STCC region along the 170°E section in El Niño and La Niña years, where blue represents the westward velocity and red represents the eastward velocity. Fig.12From (a), we can see that during the peak of El Niño, STCC has two velocity cores, both with a maximum value of 4 cm / s, mainly located at a depth of 200 meters; the velocity of the northern core of SEC is -5 cm / s, and the velocity of the southern core is -4 cm / s, and the core is mainly located in the upper 500 meters. There is a SEC velocity core in the range of 23°S~25°S, with a maximum value of -3 cm / s, extending to the surface. Fig.12 From (a) to (c), we can see that with the continuous development of El Niño, the velocity of STCC continues to increase, with the maximum values ​​of the two cores increasing to 5 cm / s, and the velocity of the northern core of SEC increases to -6 cm / s, and the range is also expanding, while the southern core does not change much. Fig.12 From (d), we can see that when the peak period of El Niño lags behind by 6 months, the maximum values ​​of the two velocity cores of STCC are still 5 cm / s, but the range reaches the maximum, and the westward branch of the surface disappears; the maximum velocity of the core of the northern SEC is -6 cm / s, and the range of the velocity strength is expanded to a depth of 600 meters. At the same time, the maximum value of the core of the southern SEC is -4 cm / s, and the range reaches the maximum, located at a depth of 200~600 meters. At this time, the vertical shear between STCC and SEC reaches its maximum. Fig.12 (e)~(f) As the lag time increases, the intensity and range of the two velocity cores of STCC decrease; while for SEC, the two velocity cores continue to strengthen. During the peak of La Niña, STCC has two velocity cores. The maximum velocity core in the south is 5 cm / s, mainly located in the upper 200 meters, while the northern core is only 2 cm / s, located in the upper 100 meters. At this time, the maximum values ​​of the two velocity cores of SEC are both -5 cm / s, extending to a depth of 500 meters. Fig.12 From (h) to (j), we know that with the continuous development of the lag time, the two cores of STCC continue to strengthen and deepen downward, while the intensity and range of SEC continue to decrease. When the lag time is 6 months after the peak of La Niña, the maximum value of the northern core of STCC increases to 4 cm / s, and the southern core increases to 9 cm / s, extending to a depth of 300 meters; at this time, the velocity core of the southern SEC decreases to -4 cm / s, and the range of the northern core decreases; at the same time, in the lower layer of STCC, the SEC core located near 23°S and 26°S is strengthened and lifted to the surface, and the westward branch of the surface increases. Fig.12 From (k)~(l), we can see that with the continuous disappearance of La Niña, the intensity of STCC increases to the maximum value and then weakens, while the intensity and range of the two velocity cores of SEC continue to decrease.

[0071] Therefore, both STCC and SEC are enhanced in El Niño years, and SEC is weakened in La Niña years. The intensity of STCC is still strong, but the average intensity of STCC in the range of 22°S~28°S is weakened due to the lifting of the lower SEC and the increase of the westward branch of the surface STCC. ENSO can affect the intensity of the upper STCC and the lower SEC, thereby affecting the velocity vertical shear of STCC and SEC.

[0072] The present invention finds that EKE is significantly positively correlated with ENSO, and the vertical shear of STCC and SEC is also significantly positively correlated with ENSO. Next, the present invention further analyzes the relationship between EKE and vertical shear.

[0073] like Fig.13 As shown in the figure, the temporal variation and lead-lag correlation between EKE anomaly and vertical shear anomaly, where (a) after one year of low-pass filtering, the temporal variation of EKE anomaly (black line) and vertical shear anomaly (red line) in the STCC region, (b) the lead-lag correlation between EKE anomaly and vertical shear anomaly, where a positive value means that EKE lags behind vertical shear. Fig.13 It can be seen that the time series of EKE anomaly and vertical shear anomaly indicate that strong vertical shear corresponds to strong EKE value, while when vertical shear is weak, EKE also presents a small value. The lead-lag correlation relationship shows that vertical shear and EKE occur simultaneously, with a correlation coefficient of 0.35, exceeding the 95% confidence test, showing a significant positive correlation. The research results are consistent with Figure 4 and Fig.11 Therefore, ENSO can affect the interannual variation of EKE by affecting the vertical shear between STCC and SEC.

[0074] Step 6: In step 5, we found that ENSO affects the interannual variation of EKE in the STCC region by affecting the vertical shear of STCC and SEC. We analyzed how ENSO affects the changes in wind stress curl and sea level in the southwest Pacific, and affects the interannual variation of vertical shear of velocity and EKE in the STCC region.

[0075] Existing studies have shown that there is a connection between the annual variation of the South Pacific subtropical circulation and the phase of wind stress curl. At the same time, the change of local wind stress curl during ENSO on an interannual scale can affect the strength of the SEC middle branch (10°S-20°S). In order to explore the impact of wind stress curl anomaly on the subtropical circulation, this paper studies the interannual variation of wind stress curl anomaly along 170°E in the STCC region and its relationship with ENSO.

[0076] like Fig.14As shown, the time variation and lead-lag correlation between wind stress curl anomaly and Niño3.4 index, including (a) the time variation of the average wind stress curl anomaly (red line) and Niño3.4 index (black line) in the 21°S~29°S region along the 170°E section calculated by ERA5 data, (b) the lead-lag correlation between wind stress curl anomaly and Niño3.4 index, where a positive value means that the wind stress curl anomaly lags behind the Niño3.4 index. Fig.14 It can be seen that the interannual variation of wind stress curl anomaly shows that El Niño years correspond to increased wind stress curl, while La Niña years correspond to weakened wind stress curl. The present invention further finds through the lead-lag relationship that the wind stress curl anomaly lags the Niño3.4 index by 2 months and has the strongest correlation, with a correlation coefficient of 0.61, which exceeds the 95% confidence test and is significantly positively correlated. Therefore, ENSO can affect the wind stress curl anomaly in the STCC region.

[0077] In order to further study the spatial variation of wind stress curl anomaly during the ENSO period, the present invention then uses ERA5 data to obtain the evolution of wind stress curl anomaly in the southwest Pacific from 2 months ahead of the ENSO peak to 8 months behind the peak, and uses ERA5 wind field data and SLA data to obtain that the anticyclonic wind stress curl in the STCC region in the El Niño year makes the Ekman convergence in the region produce positive SLA, while the cyclonic wind stress curl in the north of the STCC makes the Ekman divergence produce negative SLA, and it is concluded that the generated SLA affects EKE by affecting the surface STCC and SEC under the geostrophic effect; the cyclonic wind stress curl in the STCC region in the La Niña year makes the positive SLA corresponding to the Ekman divergence in the region, while the anticyclonic wind stress curl in the north of the STCC makes the Ekman convergence produce positive SLA, and it is concluded that the generated SLA gradient affects EKE by affecting the surface STCC and SEC under the geostrophic effect.

[0078] like Fig.15 As shown, the wind stress curl anomalies during the El Niño and La Niña periods from January 1993 to December 2022 calculated from ERA5 data (coloring, unit: N / m 3 ) and 10-meter wind speed anomaly (arrow, unit: m / s), with wind stress curl anomaly filled in (unit: N / m 3 ; Wind speed anomaly arrow, unit: m / s; Black box represents STCC area. Fig.15 From (a), we can see that when the El Niño peak period is 2 months ahead, there are westerly anomalies at the equator, cyclonic wind stress curl exists in the equatorial western Pacific region, and anticyclonic wind stress curl is dominant in the STCC region. Fig.15From (b) to (c), we can see that in the year when El Niño disappears, the equatorial cyclonic wind stress curl continues to expand southeastward and its intensity continues to increase; by 2 months after the peak lag, the intensity and range of the cyclonic and anticyclonic wind stress curls reach their maximum. The cyclonic wind stress curl in the northern part of the STCC region produces Ekman divergence, which causes the sea level in the region to drop, while the anticyclonic wind stress curl center is located in the western part of the STCC region, and the Ekman convergence causes the sea level in the region to rise. Fig.15 From (d) to (f), we can see that as the El Niño continues to disappear, the intensity and range of the cyclonic wind stress curl gradually decreases, and the intensity of the anticyclonic wind stress curl in the STCC region also decreases. Fig.13 From (g), we can see that two months before the peak of La Niña, easterly anomalies appeared at the equator, and the anticyclonic wind stress curl formed in the equatorial western Pacific expanded to the central South Pacific, and cyclonic wind stress curl existed in the western part of the STCC region. In the year when La Niña disappeared, the intensity and range of cyclonic and anticyclonic wind stress curl continued to increase. Fig.15 From (i), we can see that at the 2-month lag peak, the anticyclonic wind stress curl intensity in the northern part of the STCC region is the largest, and the Ekman convergence causes the sea level in this region to rise; Fig.15 From (j) to (l), we can see that the cyclonic wind stress curl in the western part of the STCC region also reaches its maximum, and the Ekman divergence causes the sea level in this region to drop. With the continuous disappearance of La Niña, the intensity and range of the cyclonic wind stress curl in the western part of the STCC and the anticyclonic wind stress curl in the northern part of the STCC show a decreasing trend.

[0079] Therefore, ENSO affects the changes in wind stress curl and sea level height in the STCC region and its northern part.

[0080] Previous studies have shown that basin-scale wind forcing plays a dominant role in large-scale sea level changes in the tropical Pacific, and other studies have shown that the sea level in the subtropical South Pacific is also related to changes in wind stress curl. At the same time, existing technologies have shown that the interannual changes in the SEC are well correlated with the SLA gradient, such as Figure 7 It can also be seen that the geostrophic current part is dominant in SEC, so the present invention further studies the evolution of sea level anomaly and geostrophic current from 2 months ahead of the ENSO peak to 8 months behind.

[0081] like Fig.16 As shown in the figure, after removing the long-term trend, the composite map of SLA and geostrophic velocity anomalies during the El Niño and La Niña periods from January 1993 to December 2022 obtained from AVISO data, where SLA is filled in cm; geostrophic velocity anomaly arrows, cm / s; black boxes represent STCC areas. Fig.16From (a), we can see that 2 months before the peak of the El Niño year, under the influence of westerly winds, there is a strong westward geostrophic anomaly at the equator, a strong positive SLA in the equatorial central and eastern Pacific, and a negative SLA north of 15°S in the equatorial western Pacific. Corresponding to the cyclonic wind stress curl in this region, the weaker negative SLA is dominant in the STCC region. Fig.16 From (a) to (c), we can see that with the continuous development of El Niño, the negative SLA in the equatorial western Pacific continues to expand southeastward. Under the geostrophic effect, there is a westward geostrophic flow anomaly near 170°E in the northern part of the STCC region, which leads to the enhancement of the westward SEC. Fig.16 From (d), we can see that when the lag is 2 months, the wind stress curl in the STCC region and its northern part reaches its maximum value. At this time, the negative SLA in the equatorial western Pacific is very strong, and the positive SLA in the western part of the STCC region continues to increase. Lagging 2 to 6 months after the peak of El Niño, accompanied by strong cyclonic wind stress curl, the negative SLA intensity reaches its maximum, the SEC intensity is still very strong, and the positive SLA intensity in the eastern part of the equator continues to weaken. The geostrophic flow anomaly in the eastern part of the equator reverses and continues to strengthen westward. At the same time, Fig.16 From (e) to (f), we can see that due to the enhancement of the anticyclonic wind stress curl in the western STCC region, the positive SLA in the region also increases, and the STCC eastward anomaly increases. Subsequently, the negative SLA in the equatorial western Pacific gradually spreads and its intensity continues to weaken, and the positive SLA in the western STCC region does not change significantly.

[0082] During the La Niña period, 2 months ahead of the maximum, there is a positive SLA in the equatorial western Pacific, corresponding to an anticyclonic wind stress curl, while there is a negative SLA in the equatorial eastern Pacific. There is a weak positive SLA in the STCC region. Under the geostrophic effect, there is an eastward geostrophic flow anomaly near 170°E in the northern part of the STCC, which leads to a weakening of the westward SEC. Fig.16 From (h) to (j), we can see that the positive SLA in the central equatorial western Pacific continues to extend southeastward and its intensity continues to increase. The positive SLA in the STCC region does not change significantly. The westward geostrophic flow anomaly in the eastern equator continues to decrease and then reverses to the east, while the eastward geostrophic flow anomaly in the SEC continues to increase. The westward geostrophic flow anomaly in the STCC increases, and both the SEC and STCC weaken. Fig.16 From (k), we can see that 6 months after the peak of La Niña, the positive SLA in the equatorial western Pacific reaches its maximum value. Due to the existence of cyclonic wind stress curl, the positive SLA in the STCC region is still weaker than that in the north. Fig.16 From (k)~(l), we can see that as La Niña continues to disappear, the intensity of positive SLA in the equatorial western Pacific decreases.

[0083] Therefore, under the geostrophic effect, the SLA gradient generated in the El Niño year strengthens the STCC and SEC, while the SLA gradient generated in the La Niña year weakens the STCC and SEC. Due to the influence of the underlying SEC uplift and vortex disturbance, the surface of the STCC presents an alternating east-west geostrophic flow anomaly. The changes in the surface SEC and STCC caused by the SLA affect the changes in the deep SEC as the SEC deepens, thereby affecting the vertical shear between the SEC and the STCC, and ultimately leading to high EKE values ​​in the STCC region through baroclinic instability, thus affecting the interannual variation of EKE.

[0084] Although the content of the present invention has been described in detail through the above preferred embodiments, it should be appreciated that the above description should not be considered as a limitation of the present invention. After reading the above content, it will be apparent to those skilled in the art that various modifications and substitutions of the present invention will occur. Therefore, the protection scope of the present invention should be limited by the appended claims.

Claims

1. A method for studying the interannual variation of eddy kinetic energy in the South Pacific subtropical countercurrent region and its relationship with ENSO, characterized in that: The method includes: Step 1: Obtain SLA data, AVISO data, global ocean gridded data with a spatial resolution of 0.25°×0.25°, 10-meter wind field data with a spatial resolution of 0.25°×0.25°, Niño3.4 index and SAM index; use the Niño3.4 index to characterize ENSO events, the SAM index to characterize SAM, use the daily and monthly average flow field data with a spatial resolution of 0.25°×0.25° and 75 layers with unequal vertical spacing, and GLORYS2V4 to study the vertical changes of ocean circulation; The SAM is the Southern Hemisphere Annular Mode; the SLA data is the sea surface height anomaly data distributed by CMEMS; Step 2: EKE is calculated based on the absolute geostrophic velocity anomaly in AVISO data. The EKE time series is filtered for one year after removing the seasonal cycle to obtain the EKE interannual anomaly. The EKE interannual anomaly is standardized and then subjected to wavelet analysis to obtain the EKE power spectrum. The interannual variation characteristics of EKE in the STCC region are obtained through power spectrum analysis. The EKE is eddy kinetic energy, and the STCC region is the South Pacific subtropical countercurrent region; Step 3: Study whether ENSO can affect the interannual variation of EKE in the STCC region on an interannual scale, and determine whether the interannual variation of EKE in the STCC region is modulated by the ENSO process through lead-lag correlation and partial correlation; Months with a value greater than 0.5 times the standard deviation of the Niño 3.4 index are defined as El Niño years, and months with a value less than 0.5 times the standard deviation are defined as La Niña years; the El Niño is El Niño, and the La Niña is La Niña; Step 4: Explore the response of EKE to ENSO and analyze the impact of El Niño and La Niña events on the spatial distribution of EKE in the STCC region; Step 5: Explore the dynamic mechanism of the EKE in this region on an interannual scale and determine the relationship between the vertical shear of STCC and SEC velocities and ENSO in the STCC region; The SEC is the South Equatorial Current; The interannual variation of EKE anomaly obtained by AVISO data and reanalysis of CMEMS data were used to obtain the interannual variation of surface EKE anomaly, and the interannual variation of EKE in the STCC region was studied by reanalysis of CMEMS data; Step 6: Analyze how ENSO affects the changes in wind stress curl and sea level height in the southwest Pacific, and affects the interannual changes in velocity vertical shear and EKE in the STCC region.

2. The method according to claim 1, characterized in that In step 1, the time resolution of the global ocean gridded data is daily average and monthly average, and the time resolution of the 10-meter wind field data is monthly average.

3. The method according to claim 1, characterized in that In step 2, the EKE is defined as: In formula (1), is the latitudinal geostrophic velocity anomaly, It is the anomaly of the meridional geostrophic flow velocity.

4. The method according to claim 1, characterized in that Due to the different latitudinal ranges and depths of the STCC and SEC cores, the STCC region is divided into two latitudinal ranges, 18°S–21°S and 22°S–28°S, to analyze the vertical variations of the latitudinal velocity.

5. The method according to claim 1, characterized in that In step five, STCC and SEC are selected again using CMEMS data to calculate the vertical shear of STCC and SEC in the STCC region; the lead-lag correlation is used to determine how ENSO affects the interannual variation of EKE in the STCC region by affecting the vertical shear of STCC and SEC.

6. The method according to claim 5, characterized in that When selecting STCC and SEC, the 50-meter depth in the 22°S~28°S range in the 170°E longitudinal section is taken as the STCC core, and the 275-meter depth in the 18°S~21°S range is taken as the SEC core, which are used to calculate the vertical shear of STCC and SEC in the STCC area.

7. The method according to claim 1, characterized in that In step six, the ERA5 wind field data and SLA data are used to obtain the anticyclonic wind stress curl in the STCC region in the El Niño year, which causes the Ekman convergence in the region to produce a positive SLA, while the cyclonic wind stress curl in the north of the STCC causes the Ekman divergence to produce a negative SLA. It is then concluded how the generated SLA affects EKE by affecting the surface STCC and SEC under the action of geostrophic forces.

8. The method according to claim 1, characterized in that In step six, in the STCC region in La Niña years, the cyclonic wind stress curl causes the positive SLA corresponding to the Ekman divergence in the region, while the anticyclonic wind stress curl in the northern STCC causes the Ekman convergence to produce a positive SLA. It is concluded how the generated SLA gradient affects EKE by affecting the surface STCC and SEC under the action of geostrophic forces.

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