Method for distinguishing chlorophyll concentration of upwelling region influenced by different types of cyclones

Abstract

The invention provides a method for distinguishing chlorophyll a concentration of an upwelling region influenced by different types of cyclones, and relates to the technical field of ocean remote sensing and environment monitoring. Preliminarily judging the influence of vortex on chlorophyll a concentration distribution; dividing the research area into a near-shore area and a far-shore area according to the water depth, respectively drawing vortex center-chlorophyll a concentration fusion maps for the two areas, and comparing the influence of cyclone and anti-cyclone of the two areas on chlorophyll a concentration distribution; dividing the vortex into a near-shore vortex and a far-shore vortex according to the ratio of the distance from the vortex center to the coastline to the vortex radius, respectively drawing vortex center-chlorophyll a concentration fusion graphs, and comparing the influence of cyclone and anti-cyclone on the chlorophyll a concentration distribution; and matching the temperature and salt data of the Argo buoy with the vortex position, analyzing the correlation between the potential density abnormity and the chlorophyll a concentration, and distinguishing the influence mechanism of vertical nutrition input and horizontal advection on the chlorophyll a concentration.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of marine remote sensing and environmental monitoring, and particularly relates to a method for distinguishing chlorophyll a concentration in upwelling area influenced by different types of cyclones. BACKGROUND

[0002] The Somali coastal upwelling in the Arabian Sea is one of the strongest east-coast upwelling systems in the world. It is driven by the summer monsoon, which forms a strong offshore flow and in turn induces the upwelling of surface water. However, recent observations and simulation studies have found that the upwelling process in this region is not solely controlled by the strength of wind stress. Mesoscale eddies play an important role in regulating the thermal structure of the surface water and the nutrient transport pathway.

[0003] Mesoscale eddies are widely present in the global ocean, with a scale of tens to hundreds of kilometers and a lifetime of several weeks to months. The influence mechanism of mesoscale eddies on the chlorophyll a concentration in the upwelling area is complex and spatially heterogeneous. Cyclonic eddies usually induce upward motion, promote the upwelling of nutrients, and thus enhance the chlorophyll a concentration. Anticyclonic eddies, on the other hand, suppress the upward motion or cause sinking flow, leading to a decrease in chlorophyll a concentration, but may enhance local biomass through edge transport. In the Somali upwelling system, the anticyclonic “Great Whirl” that dominates the regional dynamic structure from June to September each year has a particularly significant regulating effect on the regional horizontal transport pattern, but the related biological response mechanism has not yet formed a systematic quantitative evaluation framework.

[0004] Existing studies have focused on global eddy-chlorophyll a statistical correlation, simplified ideal simulation, or single-eddy case analysis, and there is still a lack of a technical method that can systematically distinguish the influence of nearshore and offshore, cyclonic and anticyclonic eddies on the chlorophyll a concentration in the upwelling area. In addition, due to the sparsity of marine field observations and the high-frequency variability of marine processes, the quantitative identification of eddy structure, the coupled analysis of chlorophyll a concentration, and the process attribution of different types of eddies are still technical challenges in current marine remote sensing ecological monitoring and dynamic process diagnosis.

[0005] Therefore, there is an urgent need for a comprehensive method system that integrates multi-source remote sensing data and Argo float data, eddy kinetic energy estimation, eddy identification and classification, eddy center and chlorophyll a concentration fusion analysis, nearshore and offshore eddy division, and Argo float data and eddy matching method, to accurately identify the influence of cyclonic and anticyclonic eddies on the chlorophyll aThe differentiation of the distribution and its variation mechanism. It has important scientific significance and application value for in-depth understanding of the coupling mechanism of mesoscale dynamic process and biogeochemistry, and improving the regional ecological monitoring and early warning capability. SUMMARY

[0006] To solve the above problems, the application provides a method for distinguishing the influence of cyclone and anticyclone eddy on the chlorophyll a concentration in upwelling area, which integrates multi-source remote sensing data acquisition, eddy kinetic energy estimation, eddy identification and classification, eddy center and chlorophyll a concentration fusion analysis, nearshore and offshore eddy division, and Argo float data and eddy matching method, aiming to reveal the important mechanism of eddy in regulating the chlorophyll a concentration variation of Somali upwelling system.

[0007] A method for distinguishing the influence of cyclone and anticyclone eddy on the chlorophyll a concentration in upwelling area, which integrates multi-source remote sensing data acquisition, eddy kinetic energy estimation, eddy identification and classification, eddy center and chlorophyll concentration fusion analysis, nearshore and offshore eddy division, and Argo float data and eddy matching method, aiming to reveal the important mechanism of eddy in regulating the chlorophyll a concentration variation of Somali upwelling system. (1) Obtain chlorophyll concentration data, sea level anomaly data, geostrophic current data and Argo float data of the study area; a (2) Calculate the eddy kinetic energy based on the geostrophic current data, identify the high and low value areas of the kinetic energy in the study area, and determine the activity characteristics of the mesoscale eddy; a (3) Divide the study area into nearshore and offshore areas according to water depth, and divide the eddies according to the area; (4) Normalize and spatially fuse the chlorophyll concentration based on the eddy center, and generate the chlorophyll a concentration composite map of cyclone and anticyclone eddy respectively; a (5) Calculate the distance from the eddy center to the coastline, and divide the eddy into nearshore and offshore eddy according to the ratio of distance to eddy radius; (6) Match the temperature and salinity data of Argo float with the position of eddy, calculate the potential density anomaly, analyze the correlation between potential density anomaly and chlorophyll

[0008] concentration, and distinguish the influence mechanism of vertical nutrient input and horizontal advection on chlorophyll concentration. ; Wherein, u' and v' are the anomaly values of the horizontal component and the vertical component of the geostrophic current respectively.

[0009] Further, in step (3), the research area is divided into nearshore and offshore areas according to water depth, so as to divide eddies according to areas.

[0010] Further, in step (4), the chlorophyll a The concentration synthesis map is generated by spatial fusion within a range of twice the normalized radius of the eddy center.

[0011] Further, in step (5), the eddy division method based on the distance of the coastline specifically comprises: calculating the ratio of the distance D of the eddy center to the coastline and the eddy radius R; a nearshore cyclone: 0 < D ≤ 1.5R; an offshore cyclone: 1.5R < D ≤ 3R; a nearshore anticyclone: 0 < D ≤ 1.5R; an offshore anticyclone: 1.5R < D ≤ 3R.

[0012] Further, in step (7), when the Argo buoy data is matched with the eddy, only the buoy profile data within a range of 1 times the eddy radius from the eddy center is selected.

[0013] Further, in step (7), the potential density anomaly is obtained by calculating the potential density anomaly of each layer within a water depth of 20 meters of the vertical profile of the Argo buoy and taking the maximum value.

[0014] Further, in step (7), the correlation analysis is used to distinguish the following mechanisms: If the chlorophyll a concentration is positively correlated with the potential density anomaly, it indicates that the increase of the chlorophyll a concentration is mainly driven by vertical nutrient input; If the chlorophyll a concentration is negatively correlated with the potential density anomaly or has no significant correlation, it indicates that the increase of the chlorophyll a concentration is mainly dominated by horizontal advection.

[0015] Compared with the prior art, the present application has the following beneficial effects: The present application first constructs a comprehensive method system integrating multi-source remote sensing and measured data, successfully distinguishes the effects of cyclones and anticyclones, nearshore and offshore eddies on the chlorophyll a concentration by coupling eddy kinetic energy estimation, automatic eddy identification and division methods based on water depth and coastline distance, and overcomes the limitations of ideal simulation or single eddy case analysis in previous studies.

[0016] By means of two key technologies of "offshore and onshore eddy division" and "Argo buoy matching", the present application not only describes the influence of eddies on the spatial distribution of chlorophyll a a, but also quantitatively reveals the driving mechanism behind it: it is clear that anticyclonic eddies mainly affect the chlorophyll a distribution through horizontal advection, while cyclonic eddies are dominated by horizontal advection and vertical nutrient input in the offshore and offshore, respectively. This provides key evidence for understanding the coupling mechanism of mesoscale physical and biological processes.

[0017] The present application can dynamically evaluate the ecological response of key sea areas based on long-term satellite data. This method can accurately identify the role of key dynamic structures such as "large eddies" in regulating marine primary productivity, and has important application value for predicting changes in fishery resources, evaluating the potential of marine carbon sinks, and responding to changes in marine ecosystems under climate change, and provides an advanced scientific tool for marine environmental management and ecological early warning. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is a sea level height anomaly and chlorophyll a concentration superimposed graph of the Somali upwelling region provided by the embodiment of the present application; Figure 2 is a spatial distribution graph of eddy kinetic energy in the Somali upwelling region provided by the embodiment of the present application; Figure 3 is a monthly composite graph of cyclonic eddies and chlorophyll a concentration in the offshore and offshore divided according to water depth; wherein (a), (b), (c) and (d) are the composite graphs of cyclonic eddies and chlorophyll a concentration in June, July, August and September, respectively; (e), (f), (g) and (h) are the composite graphs of cyclonic eddies and chlorophyll a concentration in June, July, August and September, respectively; Figure 4 is a monthly composite graph of anticyclonic eddies and chlorophyll a concentration in the offshore and offshore divided according to water depth; wherein (a), (b), (c) and (d) are the composite graphs of anticyclonic eddies and chlorophyll a concentration in June, July, August and September, respectively; (e), (f), (g) and (h) are the composite graphs of anticyclonic eddies and chlorophyll a concentration in June, July, August and September, respectively; Figure 5 is a schematic diagram of an eddy division method based on the distance from the coastline provided by the embodiment of the present application; Figure 6The nearshore and offshore cyclones and chlorophyll concentration according to the distance from the vortex center to the coastline provided by the embodiment of the present application a The monthly composite chart of the nearshore and offshore cyclones and chlorophyll concentration; wherein (a), (b), (c) and (d) are the composite charts of the nearshore and offshore cyclones and chlorophyll concentration in June, July, August and September respectively a The monthly composite chart of the nearshore and offshore cyclones and chlorophyll concentration; wherein (a), (b), (c) and (d) are the composite charts of the nearshore and offshore cyclones and chlorophyll concentration in June, July, August and September respectively a The monthly composite chart of the nearshore and offshore cyclones and chlorophyll concentration; wherein (a), (b), (c) and (d) are the composite charts of the nearshore and offshore cyclones and chlorophyll concentration in June, July, August and September respectively Figure 7 The nearshore and offshore anticyclones and chlorophyll concentration according to the distance from the vortex center to the coastline provided by the embodiment of the present application a The monthly composite chart of the nearshore and offshore anticyclones and chlorophyll concentration; wherein (a), (b), (c) and (d) are the composite charts of the nearshore and offshore anticyclones and chlorophyll concentration in June, July, August and September respectively a The monthly composite chart of the nearshore and offshore anticyclones and chlorophyll concentration; wherein (a), (b), (c) and (d) are the composite charts of the nearshore and offshore anticyclones and chlorophyll concentration in June, July, August and September respectively a The monthly composite chart of the nearshore and offshore anticyclones and chlorophyll concentration; wherein (a), (b), (c) and (d) are the composite charts of the nearshore and offshore anticyclones and chlorophyll concentration in June, July, August and September respectively Figure 8 The chlorophyll concentration based on Argo buoy matching provided by the embodiment of the present application a The correlation analysis result chart of chlorophyll concentration and potential density anomaly; wherein (a), (b), (c) and (d) are the analysis results based on spatial average value; (e), (f), (g) and (h) are the analysis results based on matching value in the pixel. DETAILED DESCRIPTION

[0019] The present application will be described in detail below with specific embodiments. The following embodiments will help those skilled in the art to further understand the present application, but do not limit the present application in any form. It should be pointed out that those skilled in the art can make several changes and improvements without departing from the concept of the present application. These all belong to the protection scope of the present application.

[0020] (I) Research area and data acquisition The research area of the present application is the Somali upwelling region (1.5°N-11°N, 46°E-60°E), located in the west coast of the Arabian Sea, which is one of the strongest monsoon-driven upwelling systems in the world. It is mainly affected by the summer southwest monsoon, which causes the offshore surface water to be transported outward, thereby triggering the upwelling of deep cold water. From June to September each year, the large anticyclonic vortex "Great Whirl" formed by the monsoon-driven forms a significant positive anomaly in the sea surface height anomaly field in the region, which is a core feature affecting the ocean dynamic structure. At the same time, the nearshore chlorophyll concentration in the region is significantly increased, which is mainly controlled by the nutrients carried by the upwelling. Cyclonic vortex further enhances the chlorophyll concentration through vertical nutrient transport a .a Concentration, while anticyclonic vortices inhibit local nutrient upwelling through horizontal transport, thus exhibiting chlorophyll content. a The characteristic is a low concentration.

[0021] This invention employs a comprehensive analysis of multi-source satellite data and Argo buoy data. Chlorophyll... a Concentration data comes from the European Space Agency's Ocean Color Climate Change Programme (OC-CCI) Level 3 gridded product, with a temporal resolution of daily and a spatial resolution of 4 km, covering June to September each year from 1998 to 2019; sea level height anomaly data comes from the European Copernicus Marine Service's AVHRR satellite Level 4 fusion product, with a temporal resolution of daily and a spatial resolution of 0.25°, covering June to September each year from 1998 to 2019; eddy data comes from the Archive-Validation-Interpretation (AVISO) of satellite ocean observation data, also with a daily temporal resolution and a spatial resolution of 0.25°, covering June to September each year from 1998 to 2019; Argo buoy profile data comes from the Global Data Integration Centre (GDAC), with a temporal resolution of approximately once every 10 days and a spatial resolution of 3°, covering June to September each year from 2004 to 2017.

[0022] By fusing chlorophyll a From the concentration data, chlorophyll was obtained. a Concentration composite map, overlaid with sea level height anomaly data, such as Figure 1 As shown in (a). Nearshore chlorophyll a High concentration (>1 mgm) -3 The sea level anomaly was negative, accompanied by multiple cyclones. This aligns with the characteristics of an upwelling region, where offshore winds carry seawater to the far coast, lowering sea level. Simultaneously, Ekman transport occurs, bringing nutrient-rich bottom water to the surface, promoting phytoplankton growth. Within a region ranging from 51°E to 55°E longitude and 6°N to 10.5°N latitude, centered at approximately 8°N latitude and 53°E longitude, an anticyclone with a positive sea level anomaly occurs, exhibiting a shape and location consistent with the large eddy. Within this region, chlorophyll... a Low concentration (<0.3 mg m) -3 ), while in the outer regions of this area, especially in the west and north, chlorophyll a High concentration (>0.5 mg m) -3 This indicates that the large eddy affects chlorophyll in the upwelling region. a Concentration may have a horizontal advection effect.

[0023] (II) Estimation of Vortex Kinetic Energy From Figure 2 It can be seen that an anticyclone appears at the center with latitude about 8°N and longitude about 53°E, which coincides with the position of the large eddy, indicating that the mesoscale eddy may have an important influence on the distribution of water flow in the Somali upwelling region. Therefore, the present application will verify the influence of the large eddy by calculating the eddy kinetic energy.

[0024] For the horizontal component (U) and vertical component (V) data of the geostrophic current provided by the Copernicus service, the average value of each pixel from 1998 to 2019 is calculated first, and then the horizontal component (U) and vertical component (V) data of the pixel are subtracted from the average value to obtain the corresponding anomaly component values u' and v'. The eddy kinetic energy of the pixel is calculated from the anomaly component values, and the calculation formula is as follows: By fusing the eddy kinetic energy data, the eddy kinetic energy composite map is obtained, as shown in Figure 2 In the large eddy, the eddy kinetic energy is low (<2400 m 2 s -2 ), while between the large eddy and the coastal cyclone, the eddy kinetic energy is high (>3600 m 2 s -2 ). This reflects the strong horizontal shear, indicating the important influence of the large eddy on the water flow movement in the upwelling region.

[0025] (Three) Eddy type identification The large eddy is an anticyclone (sea level height anomaly is positive), while the mesoscale eddy also includes cyclones (sea level height anomaly is negative). In order to study the importance of different types of mesoscale eddies in the Somali upwelling region, the present application uses an eddy automatic detection algorithm to identify cyclones and anticyclones.

[0026] The eddy automatic detection method used in the present application mainly automatically identifies closed sea level height anomaly regions (positive value represents anticyclone, negative value represents cyclone) from satellite sea level height anomaly based on contour analysis, takes the contour extreme point as the center of the eddy, and identifies its radius through spatial geometry and time evolution constraints. The specific detection steps are as follows: (1) Data preprocessing Use the sea level height anomaly data from AVISO, in order to reduce noise, smooth the data (i.e. Gaussian filtering), so as to suppress small scale pseudo-closed structures.

[0027] (2) Find closed contours The contourc module, which comes with MATLAB software, was used to calculate contour lines for daily sea level height anomaly remote sensing images and extract all closed contour lines (i.e., sea level height anomaly curves that coincide at the beginning and end). Each contour line represents a possible vortex boundary.

[0028] (3) Determine the polarity of contour lines If the sea level height anomaly inside the contour lines is positive (>0), it is an anticyclone; if it is negative (<0), it is a cyclone.

[0029] (4) Determine the center of the vortex Within each closed contour line, find the extreme points of sea level height anomalies. For cyclones, take the point with the minimum sea level height anomaly as the vortex center; for anticyclones, take the point with the maximum sea level height anomaly as the vortex center.

[0030] (5) Determine the vortex boundary and radius First, calculate the area A of the closed contour lines, then use the geometric mean method to calculate the equivalent radius R, as shown in the following formula: In addition, to reduce noise, only vortices with radii within a reasonable range (30-300 km) are retained.

[0031] (iv) Eddy division method based on water depth To compare the effects of eddies on chlorophyll in nearshore and offshore regions a To investigate the influence of concentration distribution, the study area was first divided into nearshore and offshore sections based on water depth, as follows: Nearshore area: water depth <= 200 meters; Offshore areas: water depth > 200 meters.

[0032] The vortex was divided into nearshore and offshore regions, and then the chlorophyll at the center of the vortex was used to divide them. a Concentration fusion methods were used to plot fusion maps of the Somali upwelling region for June, July, August, and September, as shown below. Figure 3 As shown. Among them Figure 3 (a), (b), (c), and (d) in the figure represent nearshore regional cyclones and chlorophyll, respectively. a Concentration fusion graphs for June, July, August, and September. Figure 3 (e), (f), (g), and (h) represent offshore cyclones and chlorophyll, respectively. a A composite graph showing chlorophyll concentrations in June, July, August, and September. Chlorophyll concentrations were analyzed during this period. a Concentration data were normalized based on vortex radius and then fused for analysis within a range of twice the vortex radius.

[0033] The results showed that for cyclones, in nearshore areas (water depth <= 200 meters), chlorophyll... a The concentration was higher in the western part of the cyclone center (i.e., the side closer to the coastline), which is similar to the distribution of high vortex kinetic energy areas in nearshore regions, indicating that chlorophyll concentration in this area is higher. a The concentration distribution is likely primarily influenced by shear forces. In offshore areas (water depth > 200 meters), chlorophyll... a The higher concentration at the center of the vortex indicates that chlorophyll content is higher in this region. a Concentration is mainly affected by cyclones. In addition, overall chlorophyll... a The concentration gradually increased from June to September, which is consistent with the growth trend of the southwest monsoon.

[0034] For anticyclones, chlorophyll a concentrations are higher in the western and northern parts of the vortex center in the nearshore region, which is consistent with... Figure 1 Chlorophyll around the medium and large vortex a Concentration distribution and Figure 2 The similar distribution of vortex kinetic energy around the medium and large vortices indicates that chlorophyll in this region is relatively stable. a The concentration distribution is mainly influenced by horizontal advection caused by the interaction between large eddies and cyclones near the coastline. In offshore areas, chlorophyll concentration... a The concentration remained relatively high throughout the anticyclone's cycle, indicating that the region was primarily influenced by anticyclones. From a temporal perspective, chlorophyll... a The concentration also gradually increased from June to September.

[0035] (v) Eddy division method based on coastline distance The above method of dividing nearshore and offshore areas according to water depth, while reflecting to some extent the impact of cyclones and anticyclones on chlorophyll production nearshore and offshore, does not provide a definitive answer. a While the differences in concentration distribution are observed, they cannot accurately reveal the interaction between vortices and upwellings and their impact on chlorophyll a concentration distribution. Therefore, this invention constructs a method to distinguish between nearshore and offshore vortices based on the distance from the vortex center to the coastline. First, an automatic vortex detection algorithm is applied to sea level anomaly data to obtain the center positions (longitude and latitude) and radii (R) of cyclones and anticyclones. Then, the distance (D) from the vortex center to the coastline is calculated, and this distance is divided by the radius to obtain the radius multiple of the vortex center's distance to the coastline. Next, a sensitivity analysis is performed on the radius multiple, based on the chlorophyll concentration at the vortex center... a Chlorophyll concentration fusion diagram a The concentration distribution was analyzed, with the radius multiple that maximized the difference in chlorophyll a concentration distribution between the nearshore and offshore plots serving as the optimal threshold. Eddies with a distance less than or equal to 1.5 R were classified as nearshore eddies, while those with a distance greater than 1.5 R but less than 3 R were classified as offshore eddies. This classification method can be expressed as follows: Nearshore cyclones: 0 <D≤1.5 R; Offshore cyclone: ​​1.5 R <D≤3 R; Nearshore anticyclone: ​​0 <D≤1.5 R; Far-shore anticyclone: ​​1.5 R <D≤3 R。

[0036] like Figure 5 As shown, multiple parallel lines are drawn along a direction parallel to the coastline, at distances of unit radius, with the distance between each pair of parallel lines representing 1 R. There are two concentric circles in the diagram; according to the previous definition, the radius of the inner concentric circle is 1 R, and the radius of the outer concentric circle is 3 R.

[0037] Following the above method, eddies are divided into nearshore eddies and offshore eddies. For each type of eddy, chlorophyll at the eddy center is plotted for June, July, August, and September. a Concentration fusion diagram ( Figure 6 and Figure 7 ).

[0038] Cyclones have higher chlorophyll content a Concentrations are most pronounced in nearshore areas, with filamentous structures extending outwards into the open sea. Figure 6 The composite image of the offshore vortex retains a more regular ring-shaped structure, with the core region clearly discernible. In contrast, the anticyclone exhibits lower chlorophyll content in its core region. a Concentrations were higher in the periphery, particularly in the western and northwestern borders, where chlorophyll a concentrations were significantly increased. Figure 7 ).

[0039] Nearshore chlorophyll a The concentration distribution relative to eddies differs significantly from that on the far coast. For nearshore cyclones, chlorophyll concentration... a The concentration was highest near the coastline outside the vortex center, while for offshore cyclones, chlorophyll concentration was higher. a The concentration of chlorophyll differs little between the eddy region and near the coastline. For both nearshore and offshore cyclones, chlorophyll concentration... a Concentrations were lowest at the vortex center and higher near the coastline and in the northern part of the vortex. This distribution is consistent with the low-value distribution structure of the vortex kinetic energy, reflecting the influence of the anticyclone on chlorophyll in the upwelling region. a The horizontal advection effect of concentration.

[0040] (vi) Argo buoy data and vortex matching method To study chlorophyll at the center of the vortex a The mechanism by which spatial distribution of concentration is influenced was investigated in this invention. Temperature and salinity data from Argo buoys were used to calculate density anomalies, which were then correlated with surface chlorophyll. a Correlation analysis was performed on the concentrations. The specific procedure is as follows: The observation time of Argo float vertical profile data (2004-2017, every June-September) is matched with the eddy, and only Argo float data within 1 R distance from the eddy center is selected. For each matched vertical profile, the absolute salinity, conservative temperature and potential density anomaly are calculated. Among them, the potential density anomaly is calculated by the temperature and salinity of each layer within 20 meters of water depth of the Argo float vertical profile, and the maximum value is selected as the final value used. In addition, the surface chlorophyll concentration and sea level height anomaly are interpolated to the Argo float position and time. a

[0041] The original data of Argo float includes practical salinity , in-situ temperature t, pressure p, longitude lon and latitude lat. The process of calculating absolute salinity SA, conservative temperature CT and potential density anomaly from these data is as follows.

[0042] (1) Absolute salinity SA Convert practical salinity to reference salinity (independent of location), formula as follows: , . Unit is g / kg.

[0043] Considering the regional component difference, introduce absolute salinity anomaly : . Where represents longitude, represents latitude, represents pressure, is a three-dimensional field from the global absolute salinity anomaly atlas, obtained by spatial interpolation; it has no simple analytical expression, and is a table / interpolation quantity.

[0044] (2) Conservative temperature CT CT is proportional to the reference enthalpy at 0dbar, formula as follows: , . Where is the potential enthalpy at 0dbar (specific enthalpy after adiabatic transfer of seawater to 0dbar), is the potential temperature (refer to 0dbar).

[0045] (3) Potential density anomaly .​ in, , wait.

[0046] Given SA and CT, let (e.g., 0, 1000 dbar), find .

[0047] right Figure 7 (a)-(d) and Figure 7 The potential density anomalies in (e)-(h) are represented using the spatial mean and intra-pixel Argo buoy data and surface chlorophyll, respectively. a Concentration matching value. The spatial average value refers to the average of the potential density anomalies calculated from all buoy data within a distance of 1 R from the vortex center on a given day. Intra-pixel Argo buoy data and surface chlorophyll... a Concentration matching value refers to the simultaneous presence of Argo buoy data and surface chlorophyll within a pixel at a certain time. a Concentration data.

[0048] Figure 8 The results showed that offshore cyclones exhibited significant chlorophyll content. a The positive correlation between concentration and potential density anomaly ( Figure 8 (b) and (f) indicate its chlorophyll content. a The increased concentration mainly comes from vertical nutrient input; while nearshore cyclone chlorophyll a The correlation between concentration and potential density anomalies is weak or negative. Figure 7 (a) and (e) indicate the chlorophyll content in this region. a Increased concentrations are more likely to be dominated by lateral horizontal advection. Anticyclonic vortices, on the other hand, maintain lower chlorophyll levels in all regions. a Concentration level ( Figure 8 (c) and (d) further highlight the dominant role of the large eddy in horizontal transport rather than local nutrient enrichment. Argo buoys and pixel-level chlorophyll. a The concentration matching values ​​showed a certain positive correlation. Figure 8 (g), (h)), which may originate from the edge of the vortex and its adjacent region, where strong vertical velocity and nutrient flux are usually present.

[0049] This invention integrates eddy kinetic energy estimation, mesoscale eddy automatic detection algorithm, nearshore and offshore eddy segmentation methods based on water depth and coastline distance, and eddy center chlorophyll, based on multi-source high-resolution satellite observations and Argo buoy data. a A combined approach of concentration fusion and Argo buoy data with vortex matching was developed to reveal the role of vortices in regulating chlorophyll in the Somali upwelling system. aImportant mechanisms relating to concentration changes and marine productivity. Specifically, a seasonal anticyclonic vortex—a large vortex centered at approximately 53°E, 8°N—dominates sea surface height anomalies and vortex kinetic energy variations in the region from June to September each year. The results indicate that chlorophyll in the core region of the anticyclonic vortex... a Low concentration (<0.5 mg / m³) -3 ), while its northwest edge chlorophyll a The concentration level was significantly elevated, consistent with the circulation structure around the large vortex; conversely, the chlorophyll concentration in the cyclonic vortex was significantly higher. a High concentration (>0.8 mg / m³) -3 This indicates a strong supply of nutrients. Further analysis revealed that the chlorophyll in the nearshore cyclone vortex... a The concentration was approximately twice that of the offshore shore, but co-analysis based on Argo data showed that chlorophyll concentrations were higher in both nearshore and offshore areas. a Concentration and density anomalies showed an inverse relationship: a negative correlation near the shore and a positive correlation far from the shore. This indicates that near-shore chlorophyll... a The increase in concentration was mainly driven by lateral transport, while the concentration of distal chlorophyll was... a The increase in concentration originates from vertical nutrient transport. The stability of the anticyclonic vortex structure further highlights the dominant role of large vortices in horizontal transport. This study reveals the role of vortices in regulating chlorophyll in the Somali upwelling region. a The study reveals important mechanisms related to concentration changes and marine productivity, providing crucial evidence for understanding marine biogeochemical processes in the region.

[0050] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method to differentiate the effects of different types of cyclones on chlorophyll in upwelling regions a The concentration method is characterized by, The method comprises the following steps: (1) Obtain chlorophyll concentration data, sea level anomaly data, geostrophic current data, and Argo float data for the study region; a (1) Obtain chlorophyll concentration data, sea level anomaly data, geostrophic current data, and Argo float data for the study region; (2) calculating eddy kinetic energy based on the geostrophic current data, identifying high and low value areas of kinetic energy in the study area, and determining the activity characteristics of mesoscale eddy; (3) dividing the study area into nearshore and offshore areas according to water depth, and dividing eddies according to the areas; (4) The chlorophyll concentration is normalized and spatially fused with the center of the vortex as the reference, and the chlorophyll concentration composite maps of cyclonic and anticyclonic vortices are generated, respectively. a (4) The chlorophyll concentration is normalized and spatially fused with the center of the vortex as the reference, and the chlorophyll concentration composite maps of cyclonic and anticyclonic vortices are generated, respectively. a (4) The chlorophyll concentration is normalized and spatially fused with the center of (5) calculating the distance from the eddy center to the coastline, and dividing the eddy into nearshore and offshore eddies according to the ratio of the distance to the eddy radius; (6) Match the temperature-salinity data of Argo floats with the eddy locations, calculate the potential density anomaly, and analyze the correlation between the potential density anomaly and chlorophyll a concentration, distinguish the influence mechanism of vertical nutrient input and horizontal advection on chlorophyll a concentration.

2. The method of distinguishing between different types of cyclone-influenced upwelling regions chlorophyll concentration according to claim 1, characterized in that, a In step (2), the formula for calculating the eddy kinetic energy EKE is: ​ ； Where u' and v' are the abnormal values of the horizontal and vertical components of the geostrophic current, respectively.

3. The method of distinguishing different types of cyclone-influenced upwelling regions chlorophyll concentration according to claim 1, characterized in that, a In step (3), the study area is divided into nearshore and offshore areas according to water depth, and the eddies are divided according to the areas. ​ 4. The method described in claim 1 for distinguishing the effects of different types of cyclones on chlorophyll in upwelling regions a The concentration method is characterized by, In step (4), the chlorophyll a The concentration synthesis map is generated by spatial fusion within a range of twice the vortex radius after radius normalization, with the vortex center as the reference.

5. The method for distinguishing the effects of different types of cyclones on chlorophyll a concentration in upwelling regions according to claim 1, wherein, In step (5), the eddy division method based on the distance from the coastline comprises: Calculating the ratio of the distance D from the eddy center to the coastline to the eddy radius R; Nearshore cyclone: 0 < D ≤ 1.5R; Offshore cyclone: 1.5R < D ≤ 3R; Nearshore anticyclone: 0 < D ≤ 1.5R; Offshore anticyclone: 1.5R < D ≤ 3R.

6. The method of distinguishing between cyclone types affecting upwelling regions chlorophyll concentration according to claim 1, characterized in that, a In step (6), when matching the Argo buoy data with the eddy, only the buoy profile data within 1 times the eddy radius range from the eddy center is selected. ​ 7. The method for distinguishing the effects of different types of cyclones on chlorophyll in upwelling regions as described in claim 1. a The concentration method is characterized by, In step (6), the potential density anomaly is obtained by calculating the potential density anomaly of each layer within 20 meters of water depth in the vertical profile of the Argo buoy, and taking the maximum value.

8. The method of distinguishing between different types of cyclone-influenced upwelling regions chlorophyll concentration according to claim 1, characterized in that, a In step (6), the correlation analysis is used to distinguish the following mechanisms: ​ Chlorophyll a Concentration was positively correlated with the abnormality of potential density, indicating that the increase of chlorophyll a Concentration was positively correlated with the abnormality of potential density, indicating that the increase of chlorophyll Chlorophyll a The concentration of chlorophyll was negatively correlated with the potential density anomaly, indicating that the increase of chlorophyll concentration was mainly caused by horizontal advection. a The concentration of chlorophyll was negatively correlated with the potential density anomaly, indicating that the increase of chlorophyll concentration was mainly caused by horizontal advection.

Images