Method for researching northern bay ocean heat wave interannual change rule

Abstract

The invention discloses a method for researching a northern bay ocean heat wave interannual change rule. The method comprises the following steps: acquiring OISST data, ERA5 data, ORAS5 data and a Nio 3.4 index; spatial distribution characteristics and linear variation trend characteristics of the north bay ocean heat waves are explored; analyzing the relation between the northern bay ocean heat wave intensity and the ENSO process through lead-lag correlation; spatial evolution of northern bay heat wave intensity and ocean surface temperature abnormity in the ENSO event process is researched; analyzing the energy contribution of the ocean and the atmosphere to the ocean heat wave event in the ENSO event process; and determining the influence of latent heat flux, long-wave radiation and short-wave radiation modulated by the ENSO process on heat waves in the north bay. The method solves the problems of lack of analysis of long-term change rules of the northern bay ocean heat waves and incomplete understanding of a driving mechanism in existing research, analyzes spatial distribution characteristics and interannual change rules of the northern bay ocean heat waves, and reveals a forming power mechanism of the northern bay ocean heat waves.

Description

TECHNICAL FIELD

[0001] The present application relates to a method for studying the interannual variation law of marine heatwaves, in particular to a method for studying the interannual variation law of marine heatwaves in the Beibu Gulf. BACKGROUND

[0002] As a persistent event of abnormal warming of seawater in the ocean, marine heatwaves are changing significantly with the rise of global ocean average temperature. From 1925 to 2016, the duration of marine heatwaves increased by 17%, and the frequency increased by 34%. This phenomenon has a significant impact on the marine ecological environment and social economy. The sharp decline in biodiversity, the decrease in fishing rate, the damage to aquaculture, and the change in species behavior have followed.

[0003] In recent years, the research on marine heatwaves in the South China Sea has gradually increased. Literature 1 (Yao, Y., and Wang, C. (2021), Variations in Summer Marine Heatwaves in the South China Sea, 1925-2016, Geophysical Research Letters, 48, e2020GL090748) found that the duration of marine heatwaves in the central South China Sea was the longest, and severe marine heatwaves were mostly crescent-shaped distributed along the eastern coast of Vietnam and the nearshore area of the northern South China Sea. Journal of Geophysical Research: Oceans , 126 (10) found that the abnormal enhancement of the Northwest Pacific Subtropical High and the northeast wind anomaly over the South China Sea suppressed the southwest monsoon and the upwelling current along the coast of Vietnam, resulting in the inability of the surface seawater to cool down, which led to severe summer marine heatwaves. Literature 2 (Liu, K., Xu, K., Zhu, C., and Liu, B. (2022), Diversity of Marine Heatwaves in the South China Sea Regulated by ENSO Phase, 1925-2016, Geophysical Research Letters, 49, e2021GL094593) found that the diversity of marine heatwaves in the South China Sea was regulated by the ENSO phase, and the duration of marine heatwaves was longer during the El Niño phase than during the La Niña phase. Journal of Climate , 35(2), 877-893) The South China Sea Basin Ocean Heatwave is regulated by ENSO on an interannual scale, and the inducing factors are different under different phases: from September of El Nino development year to February of El Nino decay year, due to the enhancement of solar shortwave radiation and the reduction of latent heat flux loss; from June to September of El Nino decay year, due to the enhancement of solar shortwave radiation, the reduction of latent heat loss and the weakening of the South China Sea upwelling; from February to May of La Nina decay year, it is due to the reduction of latent heat loss. The above-mentioned literature 2 also found that the Beibu Gulf, located in the northwest of the South China Sea, is a semi-enclosed continental shelf gulf with rich coral reef resources and an important fishing ground, with multiple marine ranches distributed along the coast. Literature 3 (Wang, Y. F., Yao, L. J., Chen, P. M., Yu, J., and Wu, Q. E. (2020), Environmental Influence on the Spatiotemporal Variability of Fishing Grounds in the Beibu Gulf, South China Sea, Journal of Marine Science and Engineering , 8 (12))The study showed that sea surface temperature had a significant impact on the unit catch of the Beibu Gulf fishery. Literature 4 (Smith, J. G., Free, C. M., Lopazanski, C., Brun, J., Anderson, C. R., Carr, M. H., et al. (2023), A marine protected area network does not confer community structure resilience to a marine heatwave across coastal ecosystems, Global Change Biology , 29Feng, Y., Bethel, B. J., Dong, C., Zhao, H., Yao, Y., and Yu, Y. (2022), Marine heatwave events near Weizhou Island, Beibu Gulf in 2020 and their possible relations to coral bleaching, Science of the Total Environment, 823, 153414) showed that in the summer of 2020, affected by the abnormal strengthening and westward extension of the Northwest Pacific Subtropical High, the reduction of typhoon activity and the abnormal rise of sea level, a serious marine heat wave event occurred in the Beibu Gulf.

[0004] It can be seen that the existing research on the Beibu Gulf marine heat wave has certain limitations, and most of them focus on the 2020 summer case, and the research on the overall marine heat wave of the Beibu Gulf is lacking. Moreover, the characteristics of heat waves in different regions are different, therefore, the existing technology lacks in-depth analysis of the long-term variation of the Beibu Gulf marine heat wave, and fails to systematically explore its characteristics in different time scales (such as interdecadal, long-term trend). The driving mechanism of the formation of the Beibu Gulf marine heat wave has not been fully understood, in addition to some known large-scale climate factors, the influence of local ocean circulation, mixed layer depth and other factors on marine heat wave is less studied. SUMMARY

[0005] The purpose of the present application is to provide a method for studying the interannual variation of the Beibu Gulf marine heat wave, which solves the problems of lack of long-term variation analysis of the Beibu Gulf marine heat wave and incomplete understanding of the driving mechanism in the existing research, systematically analyzes the spatial distribution characteristics, variation trend and interannual variation of the Beibu Gulf marine heat wave, and reveals its formation mechanism. It not only provides a scientific basis for understanding the evolution of regional marine heat waves, but also provides an important reference for the protection of marine ecosystems.

[0006] In order to achieve the above purpose, the present application provides a method for studying the interannual variation of the Beibu Gulf marine heat wave, which comprises: Step one, obtaining OISST data, ERA5 data, deep current speed, temperature and mixed layer depth data of ORAS5, and Niño 3.4 index; Step two, according to the OISST data, the spatial distribution characteristics and linear variation trend characteristics of the Beibu Gulf marine heat wave are explored, and the Beibu Gulf heat wave intensity is obtained; Step 3: Combining the Niño 3.4 index with the intensity of the Beibu Gulf heat wave, conduct a lead-lag correlation analysis to determine the relationship between the intensity of the Beibu Gulf marine heat wave and the ENSO process; The ENSO mentioned is El Niño-Southern Oscillation; Step 4: Based on the analysis results of Step 3, synthetic analysis was used to study the spatial evolution of heat wave intensity and sea surface temperature anomalies in the Beibu Gulf during the ENSO event, and it was found that the ENSO event regulates the interannual variation of the Beibu Gulf marine heat wave by affecting the sea surface temperature of the Beibu Gulf. Step 5: Combining OISST data, ERA5 data, and ORAS5 data on deep current velocity, temperature, and mixing layer depth, quantitatively analyze the energy contributions of the ocean and atmosphere to the ocean heat wave event during the ENSO event using the mixing layer heat budget. Step Six: Based on the impact of the ENSO event on the Beibu Gulf heat wave obtained in Step Five, determine whether the Beibu Gulf heat wave is affected by the latent heat flux, longwave radiation, and shortwave radiation modulated by the ENSO process through synthetic analysis.

[0007] Preferably, in step one, the OISST data is the Daily Optimum Interpolation Sea Surface Temperature V2.1, with a horizontal resolution of 0.25°×0.25°, covering the period from January 1982 to December 2023, and integrating actual observed sea surface temperature data and satellite sea surface temperature data; the ERA5 data is the monthly average data of 500 hpa, 850 hpa geopotential height, 10 m wind field, sea surface latent heat flux, sensible heat flux, shortwave radiation, and surface longwave radiation from the fifth-generation global climate atmospheric reanalysis data ERA5 of the European Centre for Medium-Range Weather Forecasts (ECMWF), with a horizontal resolution of 0.25°×0.25°; the ORAS5 deep current velocity, temperature, and mixing layer depth data are all from the Ocean Reanalysis System 5 global ocean reanalysis dataset, provided by ECMWF, and are used for calculating the heat budget of the ocean mixing layer; the Niño The 3.4 index comes from the Physical Sciences Laboratory Global Climate Observing System provided by the National Oceanic and Atmospheric Administration (NOAA).

[0008] Preferably, in step two, the study area of ​​the Beibu Gulf heatwave is the region from 105°E to 110°E and from 17°N to 22°N; marine heatwaves exist within the study area of ​​the Beibu Gulf heatwave, with an average annual frequency of approximately 3.7 times in the central Beibu Gulf; the total number of days can reach as high as 53 days on average on the west side of Hainan Island; the average annual duration of marine heatwaves can reach 16 days / event on the west side of the Leizhou Peninsula and the southwest side of Hainan Island; the high-value areas of maximum intensity, average intensity, and cumulative intensity are all located on the west side of the Leizhou Peninsula, with an annual average of 5°C, 2°C, and 31°C*days, respectively.

[0009] Preferably, in step two, the exploration of the spatial distribution characteristics and linear variation trend characteristics of marine heat waves in the Beibu Gulf is obtained by analyzing the trend distribution of six characteristic indices of marine heat waves.

[0010] Preferably, in step three, the method includes: by comparing the time series of marine heat wave intensity in the Beibu Gulf with the time series of Nino3.4 index, it is found that the two have consistent time variation patterns, and the lead-lag correlation analysis shows that the time series of marine heat wave intensity in the Beibu Gulf is positively correlated with the 3-month lagged Nino3.4 index.

[0011] Preferably, in step four, the method includes: performing a composite analysis of the intensity of marine heat waves in the Beibu Gulf in 1997 / 1998, 2009 / 2010, and 2018 / 2019 based on OISST. The spatial composite results show that the intensity of heat waves in the Beibu Gulf region peaks three months after the ENSO peak, which is consistent with the phenomenon that marine heat wave intensity lags the Nino3.4 index by three months according to the lead-lag correlation. In 1997 / 1998, 2009 / 2010, and 2018 / 2019, the intensity preceded the El Niño peak by three months to lagged it by five months. The spatial composite evolution of sea surface temperature anomalies in the Beibu Gulf shows a good correlation between the spatial distribution of positive sea surface temperature anomalies and the spatial distribution of marine heat waves, with high-intensity marine heat waves also occurring at the high-value centers of positive sea surface temperature anomalies. Therefore, the ENSO process may regulate the interannual variation of marine heat waves in the Beibu Gulf by influencing sea surface temperature.

[0012] Preferably, in step five, the quantitative analysis refers to calculating the relative contributions of each forcing factor to the temperature change of the mixed layer during the three El Niño periods of 1997 / 1998, 2009 / 2010, and 2018 / 2019, and finding that sea surface heat flux forcing is the main factor affecting the temperature change of the mixed layer in the Beibu Gulf.

[0013] Preferably, in step five, the equation for the thermal balance of the hybrid layer is expressed as: (1); In formula (1), The term indicating the trend of temperature. This represents the sea surface heat forcing term, indicating the contribution of sea surface heat flux to the temperature change of the mixed layer. This refers to net heat flux at the sea surface, including longwave radiation flux, shortwave solar radiation flux, latent heat flux, and sensible heat flux. The density of seawater, The specific heat capacity of seawater, The thickness of the hybrid layer; For horizontal advection heat flux, The velocity vector of the seawater. The average temperature of the mixing layer. For vertically coiled neck, The vertical winding speed is... , The vertical convolution velocity at the bottom of the hybrid layer. and These are the latitudinal and meridional flow velocities, respectively. Temperature at the bottom of the mixing layer; The remainder term includes turbulent mixing at the bottom of the mixing layer, horizontal mixing and diffusion, and numerical model errors; each term in the formula is taken as its outlier after removing climatological influences.

[0014] The physical mechanism of the Beibu Gulf marine heat wave was obtained by studying the changes in the mixed layer depth during El Niño events. The results showed that the mixed layer depth in the Beibu Gulf generally exhibited a negative anomaly, ranging from 3 months before to 3 months after the peak of El Niño. The shallower mixed layer depth was conducive to the heating of the mixed layer by sea surface heat flux, thereby promoting the development of the Beibu Gulf marine heat wave.

[0015] Preferably, in step six, the method includes: obtaining the role of sea surface heat flux in the Beibu Gulf marine heat wave changes in step five, and combining ERA5 data to analyze the contributions of the four components of sea surface heat flux—longwave radiation, shortwave radiation, latent heat flux, and sensible heat flux—to obtain the influence of longwave radiation, shortwave radiation, and latent heat on the changes in sea surface heat flux.

[0016] Preferably, in step six, the method further includes: since the change in latent heat flux is related to the wind field, in order to explore the impact of El Niño events on the wind field, synthesizing the spatial evolution of the 850 hpa geopotential height anomaly and the 10 m wind field anomaly of ERA5 during the period from 3 months before the peak of El Niño to 5 months after the peak of El Niño, thereby analyzing the impact of the wind field on the change in latent heat flux; since longwave radiation is related to high clouds, in order to explore the impact of El Niño events on high clouds in the Beibu Gulf, synthesizing and analyzing the spatial evolution of high cloud cover of ERA5 during the period from 3 months before the peak of El Niño to 5 months after the peak of El Niño, thereby analyzing the impact of El Niño events on high clouds.

[0017] Preferably, in step six, the method further includes: since shortwave radiation is related to low clouds, in order to explore the impact of El Niño events on low clouds in the Beibu Gulf, a synthetic analysis is performed on the spatial evolution of low cloud cover in ERA5 during the period from 3 months before the peak of El Niño to 5 months after the peak of El Niño, thereby analyzing the impact of El Niño events on low clouds.

[0018] This invention provides a method for studying the interannual variation patterns of marine heat waves in the Beibu Gulf, which solves the problems of insufficient analysis of long-term variation patterns and incomplete understanding of driving mechanisms in existing studies of marine heat waves in the Beibu Gulf, and has the following advantages: 1. This invention utilizes satellite observation and reanalysis data from 1982 to 2023, combined with mixed-layer heat budget analysis, to find that: the spatial distribution of marine heat waves in the Beibu Gulf varies, with more frequent occurrences in the northeast, the western coast of Hainan Island having the most total number of days, fewer occurrences in the western Leizhou Peninsula but longer duration and higher intensity, and lower intensity in the south than in the north. During this period, all characteristic indices increased, with the fastest growth in frequency and total number of days west of Hainan Island, a faster growth in the duration of individual events in the south, and a more significant increase in intensity in the western Leizhou Peninsula. The growth of all indices accelerated after 2013.

[0019] 2. This study found that, on an interannual scale, marine heat waves in the Beibu Gulf are affected by ENSO, and are significantly enhanced during El Niño years. The intensity of marine heat waves lags behind the Nino3.4 index by 3 months and shows a significant positive correlation (correlation coefficient 0.42, passing the 95% confidence test). The main cause of the change is sea surface heat flux forcing, and there are different maintenance mechanisms during the El Niño decline phase and the 4-month lag peak.

[0020] 3. This invention finds that the mechanism by which ENSO events affect heat waves in the Beibu Gulf is different from that in the South China Sea Basin. Strong heat waves also occur in some La Niña years, and the heat waves show significant interdecadal variations, with the characteristic index rising sharply after 2013. Attached Figure Description

[0021] Figure 1 This represents the multi-year average spatial distribution of the Beibu Gulf marine heatwave characteristic index from 1982 to 2023.

[0022] Figure 2 The spatial distribution of the linear trend of the Beibu Gulf marine heatwave characteristic index from 1982 to 2023.

[0023] Figure 3 The time series distribution of the weighted average marine heat wave characteristic index in the Beibu Gulf from 1982 to 2023.

[0024] Figure 4 The correlation between the Niño 3.4 anomaly and the leading and lagging effects of monthly marine heat wave intensity is shown.

[0025] Figure 5The spatial composite evolution of the average intensity of marine heat waves in the Beibu Gulf during the years 1997 / 1998, 2009 / 2010, and 2018 / 2019, ranging from 3 months ahead to 5 months behind the peak of El Niño.

[0026] Figure 6 This represents the synthetic evolution of sea surface temperature anomalies in the Beibu Gulf that occurred 3 months before the peak of El Niño in 1997 / 1998, 2009 / 2010, and 2018 / 2019, and lagged behind the peak of El Niño by 5 months.

[0027] Figure 7 The composite evolution of the heat budget of the Beibu Gulf mixed layer during the El Niño peak periods of 1997 / 1998, 2009 / 2010, and 2018 / 2019, ranging from 3 months ahead to 5 months behind.

[0028] Figure 8 The spatial composite evolution of the sea surface thermal forcing term in the Beibu Gulf during the El Niño peak periods of 1997 / 1998, 2009 / 2010, and 2018 / 2019, ranging from 3 months ahead to 5 months behind.

[0029] Figure 9 The spatial synthesis and evolution of the mixed layer depth anomaly in the Beibu Gulf during the El Niño peaks of 1997 / 1998, 2009 / 2010, and 2018 / 2019, ranging from 3 months ahead to 5 months behind.

[0030] Figure 10 Spatial composite evolution of temperature trends in the Beibu Gulf mixed layer, ranging from 3 months ahead to 5 months behind the peak of El Niño in 1997 / 1998, 2009 / 2010, and 2018 / 2019. Figure 11 The spatial composite evolution of the four components of the Beibu Gulf surface heat flux anomaly during the 1997 / 1998, 2009 / 2010, and 2018 / 2019 El Niño peaks, ranging from 3 months ahead to 5 months behind.

[0031] Figure 12 This represents the spatial composite evolution of the 850 hPa geopotential height anomaly and wind field anomaly in the Beibu Gulf during the El Niño peaks of 1997 / 1998, 2009 / 2010, and 2018 / 2019, ranging from 3 months ahead to 5 months behind.

[0032] Figure 13 This represents the spatial evolution of the average 10 m wind field in the Beibu Gulf from August to April, 1982 to 2023.

[0033] Figure 14The spatial composite evolution of the monthly average 10m wind field anomaly in the Beibu Gulf during the years 1997 / 1998, 2009 / 2010, and 2018 / 2019, which occurred 3 months ahead of the peak of El Niño and 5 months behind it.

[0034] Figure 15 The spatial synthesis evolution of anomalous high cloud cover in the Beibu Gulf during the 1997 / 1998, 2009 / 2010, and 2018 / 2019 periods, which occurred 3 months ahead of the peak of El Niño and 5 months behind it.

[0035] Figure 16 The spatial synthesis evolution of anomalous low cloud cover in the Beibu Gulf during the 1997 / 1998, 2009 / 2010, and 2018 / 2019 periods, which occurred 3 months ahead of the peak of El Niño and 5 months behind it. Detailed Implementation

[0036] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] Example 1 A method for studying the interannual variation of marine heat waves in the Beibu Gulf, comprising: Step 1: Obtain OISST data, ERA5 data, ORAS5 deep flow velocity, temperature and mixing layer depth data, and Niño 3.4 index.

[0038] The OISST data used in this invention is the Daily Optimum Interpolation Sea Surface Temperature V2.1, sourced from the National Oceanic and Atmospheric Administration (NOAA), with a horizontal resolution of 0.25° × 0.25°. This data can be obtained from: https: / / www.ncei.noaa.gov / data / sea-surface-temperature-optimum-interpolation. This invention primarily utilizes data from January 1982 to December 2023. Because this dataset integrates observed and satellite sea surface temperature data, it is comprehensive and has high resolution, making it widely used in marine heatwave research.

[0039] The ERA5 data used in this invention are monthly averages of 500 hpa and 850 hpa geopotential height, 10 m wind field, sea surface latent heat flux, sensible heat flux, shortwave radiation (positive downwards), and surface longwave radiation (positive downwards) from the fifth generation atmospheric reanalysis data (ERA5) of the European Centre for Medium-Range Weather Forecasts (ECMWF), with a horizontal resolution of 0.25° × 0.25°.

[0040] In addition, the deep current velocity, temperature, and mixing layer depth data were all obtained from the OceanReanalysis System 5 dataset, provided by ECMWF, for calculating the heat budget of the ocean mixing layer. The mixing layer depth data used was defined as the depth at which the average seawater density in the ocean exceeds the near-surface density by 0.01 kg / m³. Its horizontal resolution is 0.25° × 0.25°, with 75 layers vertically, and the time range is from January 1982 to December 2023.

[0041] The Niño 3.4 index comes from the Physical Sciences Laboratory Global Climate Observing System provided by the National Oceanic and Atmospheric Administration (NOAA).

[0042] The definition of marine heatwaves in this invention references existing technology (Hobday, AJ, Alexander, LV, Perkins, SE, Smale, DA, Straub, SC, Oliver, ECJ, et al. (2016), A hierarchical approach to defining marine heatwaves). Progress in Oceanography , 141The method described in (pp. 227-238) is widely used in current marine heatwave research. Specifically, at a defined grid point, the 90th percentile of the sea surface temperature (SST) within the climatological baseline period is used as the threshold for a marine heatwave at that point. If the SST at that point exceeds the threshold for five consecutive days, this abnormal warming event is defined as a marine heatwave event. When the time interval between two consecutive marine heatwave events is less than two days, they are considered as a single consecutive marine heatwave event. Considering that a 30-year climatological baseline period offers higher accuracy, this invention selects 1982-2011 as the climatological baseline period. Furthermore, the threshold for a marine heatwave is determined by calculating the 90th percentile of the daily temperature over 11 days centered on the current day from 1982 to 2023, and then smoothing it for 31 days. This method ensures a sufficient sample size and allows for threshold adjustment with seasonal variations.

[0043] To better study the impact and trends of marine heatwave events, this invention selects six physical attributes—occurrence frequency, duration, total number of days, average intensity, maximum intensity, and cumulative intensity—to describe the basic characteristics of marine heatwaves. The specific definitions and calculation methods are shown in Table 1.

[0044] Table 1 Definition of Heat Wave Characteristic Indices

[0045] Step 2: Based on OISST data, explore the spatial distribution characteristics and linear variation trend characteristics of marine heat waves in the Beibu Gulf, and obtain the intensity of heat waves in the Beibu Gulf.

[0046] OISST data was used for marine heatwave detection. Using OISST data and existing heatwave detection methods (Hobday, AJ, Alexander, LV, Perkins, SE, Smale, DA, Straub, SC, Oliver, ECJ, et al. (2016), A hierarchical approach to defining marine heatwaves, Progress in Oceanography, 141, 227-238, doi:https: / / doi.org / 10.1016 / j.pocean.2015.12.014), six characteristic indices of Beibu Gulf heatwaves were calculated to explore the spatial distribution characteristics and linear variation trend characteristics of marine heatwaves in Beibu Gulf.

[0047] This invention selects 105°E to 110°E and 17°N to 22°N as the research area for the Beibu Gulf heatwave. Marine heatwaves exist in this area, with an average annual frequency of about 3.7 times in the central Beibu Gulf; the total number of days can reach as high as 53 days on average on the west side of Hainan Island; the average annual duration of marine heatwaves is 16 days / event on the west side of Leizhou Peninsula and the southwest side of Hainan Island; the areas with the highest values ​​of maximum intensity, average intensity and cumulative intensity are located on the west side of Leizhou Peninsula, with an annual average of 5°C, 2°C and 31°C*days, respectively.

[0048] like Figure 1 As shown, the spatial distribution of the multi-year average of the characteristic index of marine heat waves in the Beibu Gulf from 1982 to 2023 is as follows: (a) spatial distribution of frequency (times / year); (b) spatial distribution of total number of days (days); (c) spatial distribution of duration (days); (d) spatial distribution of maximum intensity (°C); (e) spatial distribution of average intensity (°C); (f) spatial distribution of cumulative intensity (°C*days); LZ represents the Leizhou Peninsula, and HN represents Hainan Island. Figure 1 As shown in (a), the frequency of marine heat waves is relatively high in the central Beibu Gulf, averaging about 3.7 times per year. In the waters west of the Leizhou Peninsula, there is a relatively low frequency range, averaging less than 3 times per year. Figure 1 As shown in (b), the high-value area of ​​total days is located on the western side of Hainan Island, with an annual average of up to 53 days. Figure 1 As shown in (c), the average annual duration of marine heat waves is significantly longer on the western side of the Leizhou Peninsula and the southwestern side of Hainan Island than in other sea areas, reaching up to 16 days per event. Figure 1 As shown in (d) to (f), the maximum intensity, average intensity, and cumulative intensity are spatially consistent, with high-value areas located on the western side of the Leizhou Peninsula, where the annual average intensity reaches 5℃, 2℃, and 31℃*days, respectively. In summary, although the frequency of marine heat waves is relatively low on the western side of the Leizhou Peninsula, their duration is long, and their average intensity is high; therefore, the cumulative intensity in this sea area is significantly higher than in other sea areas.

[0049] To further explore the spatial distribution differences in the changing trends of marine heat waves in the Beibu Gulf from 1982 to 2023, the trend distribution of six characteristic indices of marine heat waves was analyzed.

[0050] like Figure 2The figure shows the spatial distribution of the linear trend of the Beibu Gulf marine heatwave characteristic index from 1982 to 2023, where (a) is the spatial distribution of frequency (times / year); (b) is the spatial distribution of total days (days); (c) is the spatial distribution of duration (days); (d) is the spatial distribution of maximum intensity (°C); (e) is the spatial distribution of average intensity (°C); and (f) is the spatial distribution of cumulative intensity (°C*days). LZ represents the Leizhou Peninsula, and HN represents Hainan Island. Figure 2 As shown in (a) to (b), the frequency, total number of days, duration, maximum intensity, and cumulative intensity of marine heat waves all show an increasing trend in the Beibu Gulf. The frequency and total number of days show the most significant increasing trend on the west side of Hainan Island, reaching 0.2 times / year and 4 days / year, respectively (see details). Figure 2 ab). By Figure 2 As shown in (c), the increasing trend in duration is more significant in the southern part of the Beibu Gulf than in the northern part, reaching a maximum of 0.5 days / event / year. Figure 2 As shown in (d), the maximum intensity of the increase is significantly higher on the northwest side of Hainan Island than in other sea areas, reaching 0.05℃ / year. Figure 2 As shown in (e), the average intensity of marine heat waves in the nearshore waters northwest of Hainan Island and the northern Beibu Gulf exhibits a significantly higher growth trend than in other sea areas, reaching 0.01℃ / year. However, in the southern Beibu Gulf, the growth trend is slow, and in some areas, the growth trend is not obvious or even shows a slight decreasing trend. Figure 2 As shown in (f), the cumulative intensity of marine heat waves shows a more significant increasing trend in the eastern part of the Beibu Gulf, especially in some coastal areas, such as the western side of the Leizhou Peninsula, where it can reach 0.9℃*day / year. The coastal areas of the Leizhou Peninsula and Hainan Island are the main areas for the construction of marine ranches, consistent with reference 10 (Yao, Y., and Wang, C. (2021), Variations in Summer Marine Heatwaves in the South China Sea, Journal of Geophysical Research: Oceans , 126 (10) The results are consistent, and longer duration and higher intensity marine heat wave events have an increasingly important impact on them.

[0051] like Figure 3The figure shows the time series distribution of the weighted average of the marine heat wave characteristic index in the Beibu Gulf from 1982 to 2023 (resulting in the intensity of the Beibu Gulf heat wave). (a) is the time distribution of frequency (times / year); (b) is the time distribution of total days (days); (c) is the time distribution of duration (days); (d) is the time distribution of maximum intensity (°C); (e) is the time distribution of average intensity (°C); and (f) is the time distribution of cumulative intensity (°C*days). The black solid line represents the characteristic value, the red dashed line represents the linear trend, the blue solid line is the average from 1982 to 2013, the red solid line is the average from 2013 to 2023, and k is the linear trend coefficient. Figure 3 As can be seen from (a) to (c), the main characteristic indices of marine heat waves in the Beibu Gulf showed varying degrees of upward trend between 1982 and 2023. The total number of days increased the fastest, by approximately 2.86 days per year, the duration increased by an average of 0.32 days per year, and the frequency increased by an average of 0.14 times per year. Figure 3 As can be seen from (d) to (e), the growth trends of average intensity and maximum intensity are relatively slow, with linear trend coefficients of 0.01 and 0.03 respectively, meaning an average annual increase of 0.01℃ and 0.03℃. Figure 3 As shown in (f), the cumulative intensity is increasing relatively rapidly, averaging an increase of 0.62℃*days per year. Therefore, while the average and maximum intensity of the Beibu Gulf marine heatwave are increasing slowly, the cumulative intensity is increasing rapidly, indicating that the total number of days is becoming increasingly significant in assessing the impact of Beibu Gulf marine heatwave events. Furthermore, the average value of the marine heatwave characteristic index from 2013 to 2023 is higher than that from 1982 to 2013. During 1982-2013, the average annual total number of days was 25.7 days, the duration was 9.5 days, the frequency was 2.5 events, the average intensity was 1.6℃, the maximum intensity was 2.3℃, and the cumulative intensity was 15.7℃*days. During 2013-2023, the average annual total number of days was 109.7 days, the duration was 18.6 days, the frequency was 6.3 events, the average intensity was 1.8℃, the maximum intensity was 2.9℃, and the cumulative intensity was 33.8℃*days. The increases in total days, duration, frequency, and cumulative intensity are significant. It is noteworthy that peaks were observed in total number of days, duration, frequency, and maximum intensity during El Niño years (e.g., 1989, 1998, 2015, and 2019), indicating a correlation between the Beibu Gulf marine heatwave and El Niño events. Based on this phenomenon, this invention will further explore the relationship between the Beibu Gulf marine heatwave and ENSO, as well as its potential impact mechanisms.

[0052] Step 3: Combining the Niño 3.4 index with the intensity of the Beibu Gulf heat wave, conduct a lead-lag correlation analysis to determine the relationship between the intensity of the Beibu Gulf marine heat wave and the ENSO process; To further explore the relationship between marine heat waves in the Beibu Gulf and ENSO (El Niño-Southern Oscillation), this invention, based on OISST calculations, found that the time series of marine heat wave intensity in the Beibu Gulf exhibits a consistent temporal variation pattern with the Nino3.4 index. Lead-lag correlation analysis showed a positive correlation between the time series of marine heat wave intensity in the Beibu Gulf and the 3-month lag Nino3.4 index. The specific process is as follows: like Figure 4 As shown, the correlation between the Niño 3.4 anomaly and the monthly marine heatwave intensity and its leading-lag relationship is illustrated. (a) compares the time series of the Nino3.4 index, with the average intensity of the Beibu Gulf marine heatwave represented by a solid magenta line (detrended); red shading represents El Niño events, and blue shading represents La Niña events; the Nino3.4 index is represented by a solid black line. (b) shows the leading-lag correlation analysis between marine heatwave intensity and Nino3.4, with the solid black line representing the correlation coefficient and the dashed blue line representing the 95% Monte Carlo confidence level test. Figure 4 As found in (a), positive anomalies in heat wave intensity were observed in most El Niño events, such as 1982 / 1983, 1987 / 1988, 1994 / 1995, 1997 / 1998, 2009 / 2010, 2015 / 2016, and 2018 / 2019. However, negative anomalies were observed in La Niña events (1984 / 1985, 1988 / 1989, 1995 / 1996, 2007 / 2008, and 2010 / 2011). Figure 4 The leading-lag correlation analysis in (b) shows a significant positive correlation between the average marine heatwave intensity in the Beibu Gulf and the Nino3.4 index, lagged by 3 months, with a correlation coefficient as high as 0.42 (passing the 95% confidence test). This indicates that the interannual variation of marine heatwave intensity in the Beibu Gulf is regulated by ENSO. That is, heatwave intensity is stronger during El Niño events and weaker during La Niña events.

[0053] Step 4: Based on the analysis results of Step 3, analyze the spatial evolution of heat wave intensity and sea surface temperature anomalies in the Beibu Gulf during the El Niño event, and find that the El Niño event regulates the interannual variation of marine heat waves in the Beibu Gulf by affecting the sea surface temperature of the Beibu Gulf. The leading-lag correlation analysis obtained in step three shows a positive correlation between the time series of Beibu Gulf marine heatwave intensity and the 3-month lag Nino3.4 index. Further detailed analysis of the spatial evolution of Beibu Gulf marine heatwaves during El Niño development reveals the spatial evolution characteristics of Beibu Gulf heatwave intensity from 3 months before the peak of El Niño to 5 months after the peak of El Niño. The spatial evolution of Beibu Gulf sea surface temperature anomalies during El Niño development is consistent with the spatial evolution of Beibu Gulf marine heatwave intensity. Therefore, El Niño events can regulate the intensity of Beibu Gulf marine heatwaves by influencing sea surface temperature. The specific process is as follows: To better analyze the relationship between marine heat waves in the Beibu Gulf and ENSO, this invention performs synthetic analysis on strong marine heat wave events (1997 / 1998, 2009 / 2010, 2018 / 2019).

[0054] like Figure 5 As shown, the spatial composite evolution of the average intensity of marine heat waves in the Beibu Gulf during the years 1997 / 1998, 2009 / 2010, and 2018 / 2019, ranging from 3 months before the El Niño peak to 5 months after. (a) represents a 3-month lead time to the El Niño peak; (b) 2 months before the El Niño peak; (c) 1 month before the El Niño peak; (d) the El Niño peak; (e) 1 month after the El Niño peak; (f) 2 months after the El Niño peak; (g) 3 months after the El Niño peak; (h) 4 months after the El Niño peak; and (i) 5 months after the El Niño peak. Unit: °C. Figure 5 The synthesis results indicate that the heatwave intensity in the Beibu Gulf region peaks three months after the ENSO peak, particularly in the northeastern part of the Beibu Gulf, where it can reach a maximum of 3.4°C. This is consistent with the phenomenon observed in the lead-lag correlation that the intensity of marine heatwaves lags the Nino3.4 index by three months (see details). Figure 4 (b)). During El Niño, the heatwave intensity in the northern Gulf of Tonkin was significantly higher than in the southern Gulf. During the development phase of El Niño, marine heatwaves occurred only in certain areas, with an average intensity of approximately 1.3°C (see details). Figure 5 (a)~(c)). During the peak of El Niño, marine heat waves completely cover the entire Gulf of Tonkin, and their intensity increases significantly, with even stronger heat waves in the northern part of the Gulf of Tonkin (see details). Figure 5 (d)). During the El Niño attenuation phase, the overall heat wave intensity in the Beibu Gulf initially weakened slightly before continuing to increase (see details). Figure 5 (e)~(f)). Three months after the peak of El Niño, the intensity of the marine heat wave rapidly increases to its peak, with its high-value center located in the northeastern part of the Beibu Gulf, distributed in a south-north direction (see details). Figure 5(g)). Four months after the peak of El Niño, the high-intensity center of the marine heat wave gradually weakens and spreads westward. Therefore, although the marine heat wave in the eastern part of the Gulf of Tonkin weakens slightly, the marine heat wave in the southwestern part continues to intensify (see details). Figure 5 (h)). The marine heatwave in the Gulf of Tonkin gradually weakened until five months after the peak of El Niño (see details). Figure 5 (i)).

[0055] like Figure 6 As shown, the composite evolution of sea surface temperature anomalies in the Beibu Gulf during the El Niño peak periods of 1997 / 1998, 2009 / 2010, and 2018 / 2019 ranged from 3 months ahead of the peak to 5 months behind the peak. (a) represents a 3-month lead time to the peak; (b) a 2-month lead time; (c) a 1-month lead time; (d) the peak of El Niño; (e) a 1-month lag time; (f) a 2-month lag time; (g) a 3-month lag time; (h) a 4-month lag time; and (i) a 5-month lag time. Unit: °C. Figure 6 As shown in (a) to (b), 2-3 months before the peak of El Niño, the sea surface temperature in most parts of the Beibu Gulf exhibits a negative anomaly. Figure 6 As shown in (c) to (e), sea surface temperature (SST) turns positive one month before the peak of El Niño, and its intensity continues to increase until it reaches its maximum value three months after the peak of El Niño. During El Niño, the SST in the Beibu Gulf is significantly positive. The figure shows that the high-value center of the positive SST anomaly is in the northeastern part of the Beibu Gulf, where the anomaly value can reach as high as 2.4℃.

[0056] Combination Figure 5 and Figure 6 The study found a strong correlation between positive sea surface temperature anomalies and marine heat waves, with high-intensity marine heat waves also occurring at centers of high-value positive sea surface temperature anomalies. Therefore, the ENSO process may regulate the interannual variation of marine heat waves in the Beibu Gulf by influencing sea surface temperature.

[0057] Step 5: Combining OISST data, ERA5 data, and ORAS5 data on deep current velocity, temperature, and mixing layer depth, quantitatively analyze the energy contributions of the ocean and atmosphere to the ocean heat wave event during the ENSO event using the mixing layer heat budget. Step four reveals that El Niño events can influence the intensity of marine heat waves in the Beibu Gulf by affecting sea surface temperature. Further analysis, combining OISST, ERA5, and ORAS5 data on deep current velocity, temperature, and mixing layer depth, utilizes the mixing layer heat budget equation to quantitatively analyze the energy contributions of the ocean and atmosphere to marine heat wave events during El Niño development. This invention calculates the relative contributions of various forcing factors to mixing layer temperature changes during the three El Niño events of 1997 / 1998, 2009 / 2010, and 2018 / 2019. The calculation results show that sea surface heat flux forcing is the most significant factor influencing mixing layer temperature changes in the Beibu Gulf, occurring 3 months before to 5 months after the peak of El Niño. The temporal variation of sea surface heat flux is consistent with the SST trend term (calculated based on OISST), indicating that sea surface heat flux plays a role in the changes of marine heat waves in the Beibu Gulf. The specific analysis process is as follows:

[0058] This invention performs mixed-layer heat budget analysis. The mixed-layer heat budget equation is based on the method in the prior art (Huang, B., Xue, Y., Zhang, D., Kumar, A., and McPhaden, MJ (2010), The NCEP GODASOcean Analysis of the Tropical Pacific Mixed Layer Heat Budget on Seasonal to Interannual Time Scales, Journal of Climate, 23(18), 4901-4925, doi:https: / / doi.org / 10.1175 / 2010JCLI3373.1), as follows: (1); Left side of the equation This is the temperature trend item. The first item on the right. Represents the sea surface heat flux forcing term, in which This refers to the net heat flux at the sea surface, including longwave radiation flux, shortwave solar radiation flux, latent heat flux, and sensible heat flux. , , This represents the thickness of the mixing layer. The second term on the right is the horizontal advection thermal forcing term. The velocity vector of the seawater. This represents the average temperature of the mixed layer. The third item on the right is the vertical roll-up term. The vertical winding speed is... , The vertical convolution velocity at the bottom of the hybrid layer. and These are the latitudinal and meridional flow velocities, respectively. This is the temperature at the bottom of the mixing layer. This is the remainder term, which includes turbulent mixing at the bottom of the mixing layer, horizontal mixing and diffusion, and numerical model errors. Each term in the formula is taken as its outlier after removing climatological influences.

[0059] Mixing layer temperature Figure 7 As shown, the composite evolution of the heat budget of the mixed layer in the Beibu Gulf during the El Niño seasons of 1997 / 1998, 2009 / 2010, and 2018 / 2019, ranging from 3 months ahead to 5 months behind the peak of El Niño. Blue represents the mixed layer temperature trend, orange the sea surface heat flux, yellow the advection, purple the vertical entrainment, and green the residual. Unit: °C / month. Figure 7 It is known that during the development and maturity stages of El Niño, the warming of the ocean mixed layer caused by the sea surface heat flux forcing term is very significant, reaching up to 2.8°C / month. Four months after the peak of El Niño, the sea surface heat flux forcing term turns negative, exerting a cooling effect on the mixed layer temperature. Furthermore, the horizontal advection effect of the ocean, occurring one month before the peak of El Niño and three months after, also contributes positively to the temperature change of the mixed layer, but this contribution is much smaller than that of the sea surface heat forcing term and is therefore not discussed in this invention.

[0060] like Figure 8 As shown, the spatial composite evolution of the sea surface thermal forcing term in the Beibu Gulf during the El Niño peak periods of 1997 / 1998, 2009 / 2010, and 2018 / 2019 ranged from 3 months ahead of the peak to 5 months behind the peak. (a) represents a 3-month lead time to the peak; (b) a 2-month lead time; (c) a 1-month lead time; (d) the peak of El Niño; (e) a 1-month lag time; (f) a 2-month lag time; (g) a 3-month lag time; (h) a 4-month lag time; and (i) a 5-month lag time. Unit: °C. Figure 8 It can be seen that during El Niño, sea surface thermal forcing has a significant impact on the temperature variation of the mixed layer. One and three months before the peak of El Niño, the temperature trend of the mixed layer caused by sea surface thermal forcing shows a significant positive anomaly, with values ​​reaching as high as 6.2℃ / month (see details). Figure 8 (a) and (c)). Although the sea surface thermal forcing term was negative in most sea areas two months before the peak of El Niño, its value was smaller than that of the previous month, so the resulting cooling effect was not significant and had a weak impact on the overall warming trend of the mixed layer (see details). Figure 8 (b)). During the peak of El Niño, the contribution of sea surface heat flux is small, and even shows a negative contribution in the northern seas (see details). Figure 8(d)), resulting in a negative anomaly in the temperature trend of the mixed layer in the northern sea area (see details). Figure 10 (d) This is unfavorable for the maintenance of marine heat waves, and therefore the intensity of the Beibu Gulf marine heat waves decreased one month after the peak of El Niño (see details). Figure 5 (e)). Following the peak of El Niño, sea surface heat flux continued to contribute positively, reaching its maximum at a lag of 6.0 °C / month two months later, leading to a significant increase in mixed-layer temperature. This resulted in a significant positive anomaly in sea surface temperature two months after the peak of El Niño (see details). Figure 6 (f)~(h)), and reaches its maximum value 3 months after the peak of El Niño (see details). Figure 6 (g)), and at the same time, the intensity of the marine heat wave also reaches its maximum (see details). Figure 5 (g)). Four months after the peak of El Niño, the sea surface heat forcing term becomes negative (see details). Figure 8 (h)

[0061] The sea surface heat forcing term in the mixed layer heat budget equation is obtained by dividing the net surface heat flux by the seawater density, seawater specific heat capacity, and mixed layer depth (Formula (1)). Therefore, this invention further studies the variation of the mixed layer depth in the Beibu Gulf during El Niño events. From 3 months before the peak of El Niño to 3 months after the peak of El Niño, the mixed layer depth in the Beibu Gulf generally shows a negative anomaly. The shallower mixed layer depth is conducive to the heating of the mixed layer by the sea surface heat flux, thereby promoting the development of marine heat waves in the Beibu Gulf.

[0062] like Figure 9 As shown, the spatial synthesis evolution of the mixed layer depth anomaly in the Beibu Gulf during the El Niño peak periods of 1997 / 1998, 2009 / 2010, and 2018 / 2019, ranging from 3 months before the peak to 5 months after. (a) represents a 3-month period before the peak; (b) a 2-month period before the peak; (c) a 1-month period before the peak; (d) the peak; (e) a 1-month period after the peak; (f) a 2-month period after the peak; (g) a 3-month period after the peak; (h) a 4-month period after the peak; and (i) a 5-month period after the peak. Unit: meters. Figure 9 It can be seen that during the period from 3 months before the peak of El Niño to 3 months after the peak of El Niño, the depth of the mixed layer in the central Beibu Gulf generally exhibits a negative anomaly (see details). Figure 9 (a)~(g)) show a weaker positive anomaly only when lagging behind the peak of El Niño by one month (see details). Figure 9 (e)). However, in coastal areas, the negative anomaly in the mixed layer depth is not significant, and it even shows a positive anomaly two months before the peak of El Niño (see details). Figure 9(b)). Four months after the peak of El Niño, the depth of the mixed layer in the Beibu Gulf turned into a positive anomaly (see [details omitted]). Figure 9 (h)). Combination Figure 8 Analysis revealed that during the period 1-3 months after the peak of El Niño, in areas with high positive anomalies in sea surface thermal forcing (see details...), Figure 8 (e)~(g)), the mixed layer depth exhibits a negative anomaly (see details). Figure 9 (e)~(g)). This indicates that during El Niño, changes in the depth of the mixed layer in the Gulf of Tonkin can affect the response of the mixed layer temperature to sea surface heat flux, with shallower mixed layer depths being more conducive to the heating of the mixed layer by sea surface heat flux.

[0063] like Figure 10 As shown, the spatial composite evolution of temperature trends in the Beibu Gulf mixing layer during the El Niño peak periods of 1997 / 1998, 2009 / 2010, and 2018 / 2019 ranged from 3 months ahead of the peak to 5 months behind the peak. (a) represents a 3-month lead time to the peak; (b) a 2-month lead time; (c) a 1-month lead time; (d) the peak of El Niño; (e) a 1-month lag time; (f) a 2-month lag time; (g) a 3-month lag time; (h) a 4-month lag time; and (i) a 5-month lag time. Unit: °C / month. Figure 10 It can be seen that 1-3 months before the peak of El Niño, the temperature change trend of the mixed layer in the Beibu Gulf is positive, indicating that the mixed layer is undergoing a warming process (see details). Figure 10 (a)~(c)). The mixed layer depth also exhibits a negative anomaly (see details). Figure 9 (a)~(c)) While the mixed layer warms, its decreasing depth contributes to sea surface warming and the occurrence of marine heat waves. During the peak of El Niño, although the temperature change trend of the mixed layer near the northern coast is negative, other sea areas are still positive, and the overall temperature of the mixed layer in the Beibu Gulf shows a warming process (see details). Figure 10 d). The temperature change trend in the mixed layer is most significant when it lags behind the peak of El Niño by 1-2 months, reaching 0.6℃ / month (see details). Figure 10 (ef, Lag1-2). This indicates that the mixed layer temperature in the Beibu Gulf continued to rise during the period from 3 months before the peak of El Niño to 2 months after the peak of El Niño. The rising temperature of the mixed layer not only facilitated rapid sea surface warming but also helped maintain a high sea surface temperature, providing favorable conditions for the occurrence of marine heat waves. Three months after the peak of El Niño, the temperature trend of the mixed layer in the northeastern part of the Beibu Gulf turned negative, indicating a cooling trend, while the temperature trend in the western part of the Beibu Gulf remained positive, indicating continued warming (see details). Figure 10(g)). Lagging behind the peak of El Niño by 4-5 months, the overall mixed layer temperature trend in the Beibu Gulf shows a negative value (see details). Figure 10 (h)~(i)), and the depth of the mixed layer shows a positive anomaly (see details). Figure 9 (h)~(i)), the deepening and cooling process of the mixed layer is not conducive to the development of marine heat waves (see details). Figure 5 (h)~(i)). Therefore, in the northeastern part of the Beibu Gulf, the mixed layer temperature peaks three months after the El Niño peak, while in the western part it peaks four months later. This phenomenon coincides with the fact that heat wave intensity reaches its peak three to four months after the El Niño peak (see details). Figure 5 (g) ~ (h)), which further illustrates that the heat balance of the mixed layer can well reflect the changes in sea surface ocean heat waves.

[0064] In general, the temperature variation trend of the sea surface heat forcing term is consistent with the overall temperature variation trend of the mixed layer, and their spatial distributions also roughly match, especially when lagging behind the peak of El Niño by 3 months, both are negative anomalies in the northeastern part of the Beibu Gulf and positive anomalies in the southwest. This indicates that the temperature variation of the mixed layer in the Beibu Gulf during El Niño is mainly affected by sea surface heat flux, thus demonstrating that changes in sea surface heat flux during El Niño play an important role in the development of marine heat waves.

[0065] Step 6: Based on the ENSO event impact on the Beibu Gulf heat wave obtained in Step 5, determine whether the Beibu Gulf heat wave is affected by the latent heat flux, longwave radiation, and shortwave radiation modulated by the ENSO process through synthetic analysis. In step five, it was found that sea surface heat flux plays a role in the changes of marine heat waves in the Beibu Gulf. Further analysis of the contributions of the four components of sea surface heat flux—longwave radiation, shortwave radiation, latent heat flux, and sensible heat flux—in conjunction with ERA5 data revealed that the changes in sea surface heat flux are affected by longwave radiation, shortwave radiation, and latent heat. like Figure 11 As shown, the spatial composite evolution of the four components of the surface heat flux anomaly in the Beibu Gulf during the El Niño seasons of 1997 / 1998, 2009 / 2010, and 2018 / 2019, ranging from 3 months ahead to 5 months behind the peak of El Niño. (a1)–(a9) represent shortwave radiation flux; (b1)–(b9) represent longwave radiation flux; (c1)–(c9) represent sensible heat flux; and (d1)–(d9) represent latent heat flux anomalies. Unit: W / m² 2 .from Figure 11 As can be seen, during El Niño events, longwave radiation consistently shows a positive anomaly, indicating that the atmosphere is transferring heat to the ocean (see details). Figure 12 (b)). As the El Niño event develops, it is gradually intensifying (see details). Figure 11(b1)~(b5)), reaching its maximum two months after the peak of El Niño (see details). Figure 11 (b6)), approximately 18W / m 2 The abnormality then gradually weakened (see details). Figure 11 (b7)~(b9)). Furthermore, 0-3 months before the peak of El Niño, solar shortwave radiation at the surface of the Beibu Gulf (see details). Figure 11 (a1)~(a3)), sensible heat flux (see details) Figure 11 (c1)~(c3)) and latent heat flux (see details) Figure 11 The trends of (d1) to (d3) are roughly the same. Positive anomalies are observed both 3 months and 1 month before the peak of El Niño, indicating that heat is being transferred from the atmosphere to the ocean. The latent heat flux shows the largest positive anomaly 1 month before the peak of El Niño, ranging from 20 to 50 W / m³. 2 (See details) Figure 11 (d3)). And two months before the peak of El Niño (see details). Figure 11 (a2), (b2) and (c2)) at their peak (see details) Figure 12 (a4), (b4), and (c4) show negative anomalies, indicating that the ocean is transferring heat to the atmosphere. During the 1-3 month lag behind the peak of El Niño, the northern part of the Beibu Gulf shows a negative anomaly in solar shortwave radiation, indicating that the ocean is losing heat, while the southern part shows a positive anomaly, indicating that the ocean is receiving heat from the atmosphere (see details). Figure 11 (a5)~(a7)). Meanwhile, the sensible heat flux in most parts of the Beibu Gulf is positive anomaly (see details). Figure 11 (c5)~(c7) also make a positive contribution to ocean warming, but their contribution is smaller compared to the other three fluxes. When lagging behind the peak of El Niño by 1-2 months, longwave radiation (see details...) Figure 11 Both (b5)~(b6) and latent heat flux are positive anomalies (see details). Figure 11 (d5)~(d6)), the latent heat flux value is 8W / m 2 -42W / m 2 The data indicates that atmospheric latent heat flux and longwave radiation flux play a dominant role in the development of marine heat waves in the Beibu Gulf, causing the intensity of marine heat waves to reach its maximum three months after the El Niño peak (Lag3). Subsequently, longwave radiation gradually weakens (see details). Figure 11 (b7)~(b9)), the latent heat flux turned into a negative anomaly (see details). Figure 6 (d7)~(d9)), the ocean is losing heat, and the sea surface temperature is gradually decreasing abnormally (see details). Figure 11 (h) ~ (i)). It is worth noting that, four months after the peak of El Niño, solar shortwave radiation showed a significant positive anomaly, reaching 25 W / m. 2(See details) Figure 5 (a8)). The significant enhancement of shortwave radiation mitigated the ocean cooling effect caused by latent heat, thus contributing to the maintenance of the ocean heat wave and keeping its intensity in the Beibu Gulf at a high level that month (see details). Figure 12 (h)

[0066] Since latent heat flux and longwave radiation are the main factors influencing marine heat waves in the Beibu Gulf, this invention will further explore the dynamic mechanisms affecting latent heat flux and longwave radiation. Because changes in latent heat flux are related to the wind field, to investigate the impact of El Niño events on the wind field, the spatial evolution of the 850 hpa geopotential height anomaly and the 10 m wind field anomaly of ERA5 during the period from 3 months before the peak of El Niño to 5 months after the peak of El Niño was synthesized, thereby analyzing the influence of the wind field on changes in latent heat flux.

[0067] like Figure 12 As shown, in 1997 / 1998, 2009 / 2010, and 2018 / 2019, the Beibu Gulf experienced El Niño events that preceded or lagged the peak of El Niño by 3 months to 5 months. Spatial composite evolution of hPa geopotential height anomalies and wind field anomalies, where (a) is 3 months ahead of the El Niño peak; (b) is 2 months ahead of the El Niño peak; (c) is 1 month ahead of the El Niño peak; (d) is the El Niño peak; (e) is 1 month behind the El Niño peak; (f) is 2 months behind the El Niño peak; (g) is 3 months behind the El Niño peak; (h) is 4 months behind the El Niño peak; (i) is 5 months behind the El Niño peak; geopotential height anomalies (filled in, unit: geopotential height meters), wind field anomalies (vector arrows, unit: meters per second), and the black solid line represents the extent of the Western Pacific subtropical high. From Figure 12 As can be seen, three months before the peak of El Niño, the 850 hPa geopotential height in the South China Sea and the Northwest Pacific showed a negative anomaly, and an anomalous cyclonic circulation existed in the upper atmosphere (see details). Figure 12 (a)). As the El Niño event developed, the 850 hpa geopotential height in the South China Sea gradually turned positive, and the anomalous cyclonic circulation gradually weakened and turned into an anomalous anticyclonic circulation (see details). Figure 12 (b)~(c)). Previous studies have shown that during El Niño winters, the Siberian High weakens, resulting in a low-pressure center in East Asia. Simultaneously, an anomalous anticyclonic circulation center and a positive geopotential height anomaly center are located in the central South China Sea (see details). Figure 12 (d)). Influenced by the anticyclonic circulation and the low-pressure center, the wind field over the Beibu Gulf shifted from northwesterly anomalies to southwesterly anomalies. During the El Niño attenuation phase, the Western Pacific subtropical high intensified and extended westward, leading to an increase in the pressure gradient between the Asian continent and the South China Sea, which in turn further strengthened the southwesterly anomalies over the Beibu Gulf (see details).Figure 12 (e)~(g)), reaching its peak 3 months after the peak of El Niño (see details) Figure 13 (g) The weakening of the Siberian High, the formation of the South China Sea anticyclone, and the westward extension of the Western Pacific subtropical high provided favorable atmospheric conditions for the occurrence of marine heat waves in the Beibu Gulf.

[0068] Since the peak of the three El Niño events selected in this invention (1997 / 1998, 2009 / 2010, and 2018 / 2019) all occurred in November, this invention defines November as the peak of El Niño.

[0069] like Figure 13 The image shows the spatial evolution of the average 10 m wind field in the Beibu Gulf from August to April, 1982 to 2023. (a) represents August; (b) September; (c) October; (d) November; (e) December; (f) January of the following year; (g) February of the following year; (h) March of the following year; and (i) April of the following year. The spatial evolution of the wind field is shown by vector arrows, with the color representing wind speed in meters per second. Figure 13 It can be seen that the wind field in the Beibu Gulf in August was mainly controlled by southerly winds (see details). Figure 13 (a)). September is the monsoon transition period, with weak easterly winds (see details). Figure 13 (b)). During autumn and winter (October-December), the northeast monsoon gradually strengthens (see details). Figure 13 (c)~(e)), reaching their strongest in December, with the maximum wind speed in the Beibu Gulf located in the central region, reaching 7 m / s (see details). Figure 13 (e)). In January of the following year, the northeast monsoon began to weaken (see details). Figure 13 (f)). In February of the following year, the northern part of the Beibu Gulf was dominated by northeasterly winds, while the southern part was dominated by easterly winds (see details). Figure 13 (g)). Starting in March of the following year, the southeasterly winds in the south gradually expanded northward and intensified (see details). Figure 14 (h) ~ (i)).

[0070] like Figure 14 As shown, the spatial evolution of the monthly average 10 m wind field anomalies in the Beibu Gulf during the years 1997 / 1998, 2009 / 2010, and 2018 / 2019, ranging from 3 months ahead of the El Niño peak to 5 months behind it. (a) represents a 3-month lead time to the El Niño peak; (b) a 2-month lead time; (c) a 1-month lead time; (d) the El Niño peak; (e) a 1-month lag time; (f) a 2-month lag time; (g) a 3-month lag time; (h) a 4-month lag time; and (i) a 5-month lag time. The spatial evolution of the wind field (vector arrows) is shown, with the color representing wind speed in meters per second.Figure 12 It can be seen that during the period 1-2 months after the peak of El Niño, due to the low-pressure center over East Asia and the anomalous anticyclonic circulation over the South China Sea (see details...), Figure 14 An anomaly in southwesterly winds was observed in the 10 m wind field of the Beibu Gulf (see details). Figure 13 (g) suppressed the original northeasterly winds in the bay (see details) Figure 13 (g) The decrease in wind speed reduces latent heat loss from the sea surface, promoting the occurrence of ocean heat waves. Four months after the peak of El Niño, the background wind field gradually shifts to the southeast (see details). Figure 14 (h)), abnormal southerly winds caused an increase in wind speed (see details). Figure 11 (h)) increases latent heat loss from the sea surface (see details) Figure 7 (d8)), leading to ocean cooling (see details) Figure 5 (h)), thus hindering the occurrence and maintenance of marine heat waves (see details). Figure 15 (h)

[0071] Since longwave radiation lags El Niño by 1-3 months to significantly promote the development of marine heat waves in the Beibu Gulf, this invention further analyzes the influencing factors of longwave radiation in the Beibu Gulf during El Niño events. Because longwave radiation is related to high clouds, to explore the impact of El Niño events on high clouds in the Beibu Gulf, a synthetic analysis was performed on the spatial evolution of high cloud cover in ERA5 during the period from 3 months before the El Niño peak to 5 months after the El Niño peak, thereby analyzing the impact of El Niño events on high clouds.

[0072] like Figure 15 As shown, the spatial composite evolution of high cloud cover anomalies in the Beibu Gulf during the El Niño peak periods of 1997 / 1998, 2009 / 2010, and 2018 / 2019, ranging from 3 months before the peak to 5 months after the peak, is shown in %. (a) represents a 3-month period before the peak; (b) a 2-month period before the peak; (c) a 1-month period before the peak; (d) the peak of El Niño; (e) a 1-month period after the peak; (f) a 2-month period after the peak; (g) a 3-month period after the peak; (h) a 4-month period after the peak; and (i) a 5-month period after the peak. The spatial evolution of the wind field (vector arrows) is also shown, with the color representing wind speed in meters per second. Figure 15 As shown in (a) to (b), the high cloud cover in the Beibu Gulf exhibits a significant phase change during the development of El Niño. Two to three months before the peak of El Niño, the high cloud cover in the Beibu Gulf is in a negative anomaly phase. Figure 11 As shown in (c), one month before the peak of El Niño, the high cloud cover in the Beibu Gulf turned into a positive anomaly, corresponding to a positive anomaly in longwave radiation (see...). Figure 15 (b3)). ByFigure 15 As can be seen from (d), with the development of the El Niño event, the high cloud coverage in the Beibu Gulf is abnormally and continuously increasing, from Figure 11 As can be seen from (e) to (f), the peak is reached 1-2 months after the peak of El Niño, corresponding to the peak of longwave radiation in the Beibu Gulf (see...). Figure 15 (b5)~(b6)). The increase in high-altitude clouds enhances the insulating effect of the atmosphere, increasing the amount of long-wave radiation absorbed by the sea surface, thus providing thermal support for the occurrence of ocean heat waves. Figure 16 As shown in (g), although high cloud cover decreased 3 months after the peak of El Niño, its positive anomaly was still maintained. Therefore, the positive anomaly in high cloud cover in the Beibu Gulf during the period from 1 month before the peak of El Niño to 3 months after the peak of El Niño is conducive to the growth of longwave radiation, thus promoting the development of marine heat waves.

[0073] Since shortwave radiation plays a major role in promoting the development of marine heat waves in the Beibu Gulf four months after the peak of El Niño, this invention further analyzes the spatial evolution of low clouds during El Niño events. Because shortwave radiation is related to low clouds, to explore the impact of El Niño events on low clouds in the Beibu Gulf, a composite analysis was performed on the spatial evolution of low cloud cover in ERA5 during the period from three months before the peak of El Niño to five months after the peak of El Niño, thereby analyzing the impact of El Niño events on low clouds.

[0074] like Figure 16 As shown, the spatial composite evolution of low cloud cover anomalies in the Beibu Gulf during the El Niño peak periods of 1997 / 1998, 2009 / 2010, and 2018 / 2019 ranged from 3 months before the peak to 5 months after the peak. (a) represents a 3-month period before the peak; (b) 2 months before the peak; (c) 1 month before the peak; (d) the peak; (e) 1 month after the peak; (f) 2 months after the peak; (g) 3 months after the peak; (h) 4 months after the peak; and (i) 5 months after the peak. The spatial evolution of the wind field (vector arrows) is also shown, with the color representing wind speed (in %). Nature As shown in (b) to (g), during the period from 2 months before the peak of El Niño to 3 months after the peak of El Niño, the low clouds in the northern part of the Gulf of Tonkin exhibited a positive anomaly, indicating a significant increase in low cloud cover in the region. (Previous technology (Slingo, A. (1990), Sensitivity of the Earth's radiation budget to changes in low clouds, Figure 11 , 343(6253), 49-51) states that due to the strong reflection of shortwave solar radiation by low clouds, the amount of shortwave radiation absorbed by the sea surface in the Beibu Gulf is reduced (see...). Figure 16 (a2)~(a7)), thereby suppressing the occurrence of ocean heat waves. Figure 11 As can be seen from (h), four months after the peak of El Niño, the low cloud anomaly turns negative, and the decrease in cloud cover leads to a significant increase in shortwave radiation reaching the sea surface (see h). Figure 6 (a8)), which helps maintain the high temperature of the sea surface (see Figure 5 (h)), thereby maintaining the intensity of ocean heat waves (see ​ (h)

[0075] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A method for studying the interannual variation of marine heat waves in the Beibu Gulf, characterized in that, The method includes: Step 1: Obtain OISST data, ERA5 data, ORAS5 deep flow velocity, temperature and mixing layer depth data, and Niño 3.4 index; Step 2: Based on OISST data, investigate the spatial distribution characteristics and linear variation trend of marine heat waves in the Beibu Gulf, and obtain the intensity of heat waves in the Beibu Gulf; Step 3: Combining the Niño 3.4 index with the intensity of the Beibu Gulf heat wave, conduct a lead-lag correlation analysis to determine the relationship between the intensity of the Beibu Gulf marine heat wave and the ENSO process; The ENSO mentioned is El Niño-Southern Oscillation; Step 4: Based on the analysis results of Step 3, synthetic analysis was used to study the spatial evolution of heat wave intensity and sea surface temperature anomalies in the Beibu Gulf during the ENSO event, and it was found that the ENSO event regulates the interannual variation of the Beibu Gulf marine heat wave by affecting the sea surface temperature of the Beibu Gulf. Step 5: Combining OISST data, ERA5 data, and ORAS5 data on deep current velocity, temperature, and mixing layer depth, quantitatively analyze the energy contributions of the ocean and atmosphere to the ocean heat wave event during the ENSO event using the mixing layer heat budget. Step Six: Based on the impact of the ENSO event on the Beibu Gulf heat wave obtained in Step Five, determine whether the Beibu Gulf heat wave is affected by the latent heat flux, longwave radiation, and shortwave radiation modulated by the ENSO process through synthetic analysis.

2. The method according to claim 1, characterized in that, In step one, the OISST data is the Daily Optimum Interpolation Sea Surface Temperature V2.1, with a horizontal resolution of 0.25°×0.25°, covering the period from January 1982 to December 2023, and integrating actual observed sea surface temperature data and satellite sea surface temperature data; the ERA5 data is the monthly average data of 500 hpa, 850 hpa geopotential height, 10 m wind field, sea surface latent heat flux, sensible heat flux, shortwave radiation, and surface longwave radiation from the fifth-generation global climate atmospheric reanalysis data ERA5 of the European Centre for Medium-Range Weather Forecasts (ECMWF), with a horizontal resolution of 0.25°×0.25°; the ORAS5 deep current velocity, temperature, and mixing layer depth data are all from the Ocean Reanalysis System 5 global ocean reanalysis dataset, provided by ECMWF, and are used for calculating the heat budget of the ocean mixing layer; the Niño The 3.4 index comes from the Physical Sciences Laboratory Global Climate Observing System provided by the National Oceanic and Atmospheric Administration (NOAA).

3. The method according to claim 1, characterized in that, In step two, the study area for the Beibu Gulf heatwave is the region from 105°E to 110°E and from 17°N to 22°N. Marine heatwaves exist within the study area of ​​the Beibu Gulf heatwave, with an annual average frequency of 3.7 times in the central Beibu Gulf. The total number of days can reach as high as 53 days per year on the west side of Hainan Island. The annual average duration of marine heatwaves is 16 days / event on the west side of the Leizhou Peninsula and the southwest side of Hainan Island. The high-value areas of maximum intensity, average intensity, and cumulative intensity are all located on the west side of the Leizhou Peninsula, with annual averages of 5°C, 2°C, and 31°C*days, respectively.

4. The method according to claim 1, characterized in that, In step two, the exploration of the spatial distribution characteristics and linear variation trend characteristics of marine heat waves in the Beibu Gulf is obtained by analyzing the trend distribution of six characteristic indices of marine heat waves.

5. The method according to claim 1, characterized in that, In step three, the method includes: by comparing the time series of marine heat wave intensity in the Beibu Gulf with the time series of Nino3.4 index, it was found that the two have consistent time variation patterns, and the lead-lag correlation analysis showed that the time series of marine heat wave intensity in the Beibu Gulf is positively correlated with the 3-month lagged Nino3.4 index.

6. The method according to claim 1, characterized in that, In step five, the quantitative analysis refers to calculating the relative contributions of each forcing factor to the temperature change of the mixed layer during the three El Niño periods of 1997 / 1998, 2009 / 2010, and 2018 / 2019, and finding that sea surface heat flux forcing is a factor affecting the temperature change of the mixed layer in the Beibu Gulf.

7. The method according to claim 1, characterized in that, In step five, the equation for the thermal balance of the hybrid layer is expressed as: (1); In formula (1), The term indicating the trend of temperature. This represents the sea surface heat forcing term, indicating the contribution of sea surface heat flux to the temperature change of the mixed layer. This refers to net heat flux at the sea surface, including longwave radiation flux, shortwave solar radiation flux, latent heat flux, and sensible heat flux. The density of seawater, The specific heat capacity of seawater, The thickness of the hybrid layer; For horizontal advection heat flux, The velocity vector of the seawater. The average temperature of the mixing layer. For vertically coiled neck, The vertical winding speed is... , The vertical convolution velocity at the bottom of the hybrid layer. and These are the latitudinal and meridional flow velocities, respectively. Temperature at the bottom of the mixing layer; The remainder includes turbulent mixing at the bottom of the mixing layer, horizontal mixing and diffusion, and numerical model errors; each term in the formula is taken as its outlier after removing climatological influences. The physical mechanism of the Beibu Gulf marine heatwave was obtained by studying the changes in the depth of the Beibu Gulf mixed layer during El Niño.

8. The method according to claim 1, characterized in that, In step six, the method includes: obtaining the role of sea surface heat flux in the Beibu Gulf marine heat wave changes in step five, and combining ERA5 data to analyze the contributions of the four components of sea surface heat flux—longwave radiation, shortwave radiation, latent heat flux, and sensible heat flux—to obtain the influence of longwave radiation, shortwave radiation, and latent heat on the changes in sea surface heat flux.

9. The method according to claim 1, characterized in that, In step six, the method further includes: since latent heat flux changes are related to the wind field, in order to explore the impact of El Niño events on the wind field, the spatial evolution of the 850 hpa geopotential height anomaly and 10 m wind field anomaly of ERA5 during the period from 3 months before the peak of El Niño to 5 months after the peak of El Niño is synthesized and analyzed, thereby analyzing the impact of the wind field on latent heat flux changes; since longwave radiation is related to high clouds, in order to explore the impact of El Niño events on high clouds in the Beibu Gulf, the spatial evolution of high cloud cover of ERA5 during the period from 3 months before the peak of El Niño to 5 months after the peak of El Niño is synthesized and analyzed, thereby analyzing the impact of El Niño events on high clouds.

10. The method according to claim 1, characterized in that, In step six, the method further includes: since shortwave radiation is related to low clouds, in order to explore the impact of El Niño events on low clouds in the Beibu Gulf, a synthetic analysis is performed on the spatial evolution of low cloud cover in ERA5 during the period from 3 months before the peak of El Niño to 5 months after the peak of El Niño, thereby analyzing the impact of El Niño events on low clouds.

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