Patterns Of Climate Variability Research Articles

The convolutional neural network for pacific decadal oscillation forecast

Abstract The Pacific Decadal Oscillation (PDO) is often described as a long-lived El Niño-like pattern of Pacific climate variability, and it has widespread climate and ecosystem impacts. PDO forecasts can provide useful information for policymakers on how to handle PDO impacts. Nevertheless, due to the long duration of the PDO cycles and their complex formation mechanisms, it remains a challenge to predict long lead time PDO. In this paper, we propose a transfer-learning-enhanced Convolutional Neural Network (CNN) to tackle complex ocean dynamic forecasting and predict PDO events with up to a one-year lead time. Our method first trains the CNN on historical simulations from Coupled Model Intercomparison Project 6 (CMIP6), covering the period from 1850 to 1972. This prior knowledge is then refined by further training the model with observational data from 1854 to 1972, ensuring robust performance on unseen data. Additionally, k-fold cross-validation is also employed to evaluate the model's performance across diverse subsets of data, enhancing its reliability. Throughout the testing phase from 1983 to 2022, the CNN model consistently outperforms existing dynamical forecast systems, exhibiting superior correlation skills in predicting annual mean PDO indices and PDO phases, including displaying resilience to seasonal variations. The transferred CNN is thus a powerful method to predict PDO events and is potentially valuable for a wide range of applications. This work directly supports the objectives of the World Climate Research Programme (WCRP) Grand Challenge on Climate Prediction.

EXPLORING CLIMATIC PATTERNS AMONG BRAZILIAN CAPITALS

This study aims to examine the patterns of climatic variables and delineate climatically homogeneous regions among Brazilian capitals using Principal Component Analysis (PCA) and clustering techniques. Annual climate data from 26 state capitals and the Federal District of Brazil were analyzed, covering the period from 1958 to 2022, representing different regions of the country. The PCA results revealed that the first three principal components accounted for 91.8% of the total data variability. Four climatically homogeneous regions were identified: the East region, the Northeast region, the North region and another region that comprises the rest of the country. Cluster Analysis (CA) also confirmed the formation of four homogeneous groups among municipalities based on climatic variables. The analysis of spatial distribution showed significant variations in annual climate variables between Brazilian capitals, with maximum values observed for maximum and minimum temperatures, precipitation, wind speed, relative humidity, evapotranspiration and soil moisture. These findings contribute to a deeper understanding of climate variability in Brazilian capitals and provide a basis for future studies on climate dynamics and regional impacts. Keywords: Principal Component Analysis, Cluster Analysis, Multivariate Analysis; Biplot

ENSO independent tropical-extratropical signal off the Northeast Pacific

Numerous temporal and spatial patterns of natural climate variability have been characterized. By analyzing standardized and detrended sea surface temperature anomalies (SSTA) along the coast from 1950 to 2023, this study identifies two dominant modes of ocean variability in the Northeast Pacific Boundary Current (NEPBC) which includes the California and Alaska currents. The first mode is the prevalent pattern of interannual variability associated with the El Niño-Southern Oscillation. A second mode arises as an independent dipole between the coasts of North and Central America, with the strongest intensities on a portion of the NEPBC (38°-53°N) and the Eastern Pacific warm pool (EPWP, 2°S-15°N). The difference in SSTA between the two regions appears to be caused by variations in the intensity and distribution of atmospheric pressure fields and it is related with the Pacific Meridional Mode and North Pacific Oscillation. Such coastal mode will provide the opportunity to describe the interactions of coastal processes with climate indices capturing larger-scale phenomena.

A Global Assessment of Groundwater Recharge Response to Infiltration Variability at Monthly to Decadal Timescales

AbstractPredictions of groundwater fluctuations in space and time are important for sustainable water resource management. Infiltration variability on monthly to decadal timescales leads to fluctuations in the water tables and thus groundwater resources. However, connections between global‐scale climate variability and infiltration patterns and groundwater are often poorly understood because the relationships between groundwater conditions and infiltration tend to be highly nonlinear. In addition, understanding is further hampered because many groundwater records are incomplete and groundwater tables are often anthropogenically influenced, which makes identifying the effects of infiltration variability difficult. Previous studies that have evaluated how infiltration variability controls groundwater are based on a limited number of point measurements. Here, we present a global assessment of how infiltration variability is expected to affect groundwater tables. We use an analytical solution derived from Richards' equation to model water level responses to idealized periodic infiltration variability with periods that range from months to decades, to approximate both the effects of short‐term and long‐term climate variability and thus infiltration patterns. Our global‐scale assessment reveals why infiltration variability would lead to periodicity in groundwater recharge in particular regions. The vadose zone strongly dampens short‐term (seasonal and shorter) variations in infiltration fluxes throughout most of Earth's land surface, while infiltration cycles exceeding 1 year would yield transient recharge, except in more arid regions. Our results may help forecasting long‐term groundwater tables and could support improving groundwater resource management.

A Simple Statistical Postprocessing Scheme for Enhancing the Skill of Seasonal SST Predictions in the Tropics

Abstract Seasonal prediction systems are subject to systematic errors, including those introduced during the initialization procedure, that may degrade the forecast skill. Here we use a novel statistical postprocessing correction scheme that is based on canonical correlation analysis (CCA) to relate errors in ocean temperature arising during initialization with errors in the predicted sea surface temperature fields at 1–12-month lead time. In addition, the scheme uses CCA of simultaneous SST fields from the prediction and corresponding observations to correct pattern errors. Finally, simple scaling is used to mitigate systematic location and phasing errors as a function of lead time and calendar month. Applying this scheme to an ensemble of seven seasonal prediction models suggests that moderate improvement of prediction skill is achievable in the tropical Atlantic and, to a lesser extent, in the tropical Pacific and Indian Ocean. The scheme possesses several adjustable parameters, including the number of CCA modes retained, and the regions of the left and right CCA patterns. These parameters are selected using a simple tuning procedure based on the average of four skill metrics. The results of the present study indicate that errors in ocean temperature fields due to imperfect initialization and SST variability errors can have a sizable negative impact on SST prediction skill. Further development of prediction systems may be able to remedy these impacts to some extent. Significance Statement The prediction of year-to-year climate variability patterns, such as El Niño, offers potential benefits to society by aiding mitigation and adaptation efforts. Current prediction systems, however, may still have substantial room for improvement due to systematic model errors and due to imperfect initialization of the oceanic state at the start of predictions. Here we develop a statistical correction scheme to improve prediction skill after forecasts have been completed. The scheme shows some moderate success in improving the skill for predicting El Niño and similar climate patterns in seven prediction systems. Our results not only indicate a potential for improving prediction skill after the fact but also point to the importance of improving the way prediction systems are initialized.

Decadal (2010–2019) variability in the marine ecosystems of the North Atlantic

Abstract The “Symposium on Decadal Variability of the North Atlantic and its Marine Ecosystems: 2010–2019” took place in Bergen, Norway, from 20 to 22 May 2022. This event, hosted by the Institute of Marine Research, was jointly sponsored by ICES and NAFO and constitutes the fourth in a series of these symposia that started in 1991. The first symposium’s aim was to review the hydrobiological variability in the decade of the 1980s, addressing the physical environment, plankton, invertebrates, and fish. Subsequent symposia maintained the classical structure, whilst a new theme session covering social sciences was added to the programme in the 2022 edition. Studies of climate impacts on marine ecosystems and living marine resources, including trends and regime shifts, emerged from increasingly longer ecosystem time series across the North Atlantic and subarctic regions. This symposium collection presents key findings discussed during the symposium. Whilst some progress has been made in advancing our ability to understand new trends and patterns of climate change and variability across physical, plankton, and fish communities, more work is needed to integrate these physical-ecological processes and scales with social science.

GEOSPATIAL TECHNIQUES FOR MAPPING AND ANALYSIS OF CLIMATIC VARIABLES IN GOMBE STATE, NORTH-EAST NIGERIA.

This study was carried out to apply satellite- based climatic data in geospatial environment to downscale climatic data into smaller political units and to generate and analyse thematic maps of climatic variables in Gombe State. Spatial climatic data on rainfall, minimum and maximum temperature were obtained from DivaGIS climatic data, while water vapour, solar radiation and wind speed were derived from the WorldClim climatic data. Monthly climatic records from 1981-2021 in twenty-four points evenly spread across Gombe State on rainfall, minimum/maximum temperature and relative humidity were obtained from NASA Power Project to generate the trends and seasonal patterns of temperature and rainfall. Daily climatic records of rainfall were also acquired from globalweather climatic data between 1979 and 2013 and processed to derive the values of rainfall indices using Nieuwolt formula. The monthly climatic records were processed using the kriging module of ArcGIS to transform the point climatic data to spatial data. The result revealed that rainfall in Gombe State occurs mainly between May and September with the peak in August, while the trends in rainfall was decreasing at the southern and northern parts of the state but increasing at the central region. Rainfall onset occurs in the 1st or 2nd week of May in the south, but late (1st week of June) in the north. Rainfall cessation at the central and northern parts of the state occurs in the 3rd or 4th weeks of September, while the southern part experiences late cessation between the 1st and 3rd week of October. The LRS ranges from 95-111 and 160-175 days in the northern and southern parts respectively. High relative humidity was recorded between May and October with the peak in August. Spatial patterns of solar radiation and wind speed were also generated and analyzed. Awareness of the use of satellite based climatic data and geospatial techniques for downscaling climatic data were recommended in order to ease the problems of lack or inadequate climatic data for spatial mapping. Causal factors for the spatial patterns of climatic variables in Gombe state was suggested for further studies.

Causal oceanic feedbacks onto the winter NAO

Of the climate variability patterns that influence the weather in the North Atlantic region in winter, the North Atlantic Oscillation (NAO) is the most dominant. The effects of the NAO span from cold air outbreaks to unseasonably warm conditions and unusual precipitation, with significant impacts on human activities and ecosystems. While a connection between the NAO and antecedent sea surface temperature (SST) conditions has been recognised for decades, the precise causal interaction between the ocean and the atmosphere remains enigmatic. In this study we uncover a robust statistical relationship between North Atlantic SSTs in November and the NAO throughout the subsequent winter in the extended ERA5 reanalysis back to 1940. We apply a well-established causal inference technique called mediation analysis, commonly used in social science and now adopted in climate research. This analysis highlights the roles of low-level baroclinicity, latent heat fluxes, and latent heat release in mediating the effect of November SSTs on the NAO in January and February. It is important to recognise that these mediators are interrelated. Moreover, our analysis reveals bidirectional relationships, where the NAO reciprocally mediates the effects of the November SSTs on these variables. This is evidence of a complex web of feedback mechanisms which collectively contribute to the response of the winter NAO to late autumn/early winter SSTs.

Adapting reservoir operation to climate change in regions with long-term hydrologic persistence

Large-scale climate variability patterns such as El Niño-Southern Oscillation (ENSO) influence the hydrology and hence affect the management of water resources in numerous regions around the globe. The presence of multiyear drought and wet periods is already challenging as these long, extreme, events tend to stress water resources systems much more than multiple, isolated, ones. This manuscript presents a variant of a hydrologically-driven approach to assess the performance of large-scale water resources systems in regions where the long-term persistence that characterizes the flow regime is likely to be affected by climate change. This approach comprises several steps including the construction of a large ensemble of hydrological projections which are bias-corrected in the frequency domain to account for the long-term persistence; the clustering of these projections based on hydrologic attributes to identify likely alterations of the flow regime; and the use of an optimization model to derive allocation policies tailored to identified alterations of the flow regime. The proposed approach is tested on the Senegal River basin which has experienced multiyear dry, normal, and wet periods in the past. The analysis of allocation policies highlights the relevance of climate-tailored policies in adapting to climate change, with climate tailored policies yielding moderate gains under the most extreme alterations, while they remain meaningful under more moderate ones.

Paradoxical behaviour of rainfall and temperature over ecologically sensitive areas along the Western Ghats.

Initial reports signify some specific isolated locations in different latitudes, revealing a paradoxical increase in both heavy and very heavy rainfall events and also an increment in total, i.e., in both rainfall and temperature, over ecologically sensitive areas along the Western Ghats (WG). This paper presents a coherent study of the full-scale of daily rainfall and temperature over 27 well-spaced stations in the study area to determine its extent and investigate whether or not this contradictory behaviour is real. Also, an attempt has been made to assess the differential behaviour of rainfall, temperature, and heavy rainfall events in association with land use and land cover change (LULC). The analysis revealed that rainfall and temperature over the study area are increasing, whereas heavy rainfall events have increased during 1981-2020 with strong peaks after 2000 around 18-19°N (Mumbai metropolitan region), 14-16°N (mining and quarrying regions in Goa), and 9-12°N (a narrow strip of land spanning across the coastal towns of Karnataka and Kerala) latitudes. The majority of the rainfall excess years coincided with El Nino years, indicating that El Nino does not affect rainfall negatively. However, rainfall over the WG is influenced by local relief and cascading topography. The spatial pattern of average annual rainfall shows a decreasing trend from south to north because the elevation and span of rainfall occurrence are higher in the southern part of WG. The findings of the current research will help in building a strategy to address trends and patterns of climatic variables in association with LULC.

Coupling uncertain patterns of climatic variables in estimating evaporation from open water bodies

Coupling uncertain patterns of climatic variables in estimating evaporation from open water bodies

Data-model comparisons of isotopic and hydrological variabilities of the karstic vadose zone above Villars Cave, SW-France based on 20 years' monitoring record

Because of the great heterogeneity of the limestone fissures, conduits, and reservoirs in karst areas, the understanding of the infiltration in caves and karst terrains is complicated. For example, the time delays observed between rainfall and the various flows into caves, such as shaft flow and seepage flow, exhibit significant variability. To better understand the infiltration above a typical shallow cave, Villars Cave, South-west France, we used both a very long monitoring (>20 years) isotopic data set of rainfall and dripping rates at two different cave gallery levels (14 m and 36 m below the surface, respectively) and a conceptual model (KarstFor) that mix water flows and isotopes. In order to determine the most appropriate reservoir and flow settings, we used one time-lapse electrical resistivity tomography (ERT) image made above the cave, which were incorporated into the KarstFor model. The modeled variations in storage water and infiltration flows are in a good agreement with the observed dripping discharge rates, indicating seasonal variability and various time delays between water excess ((Rainfall-Evapotranspiration) > 0) and drip rates in the different cave levels. The fact that the model strikingly simulates the small, but constant, isotopic difference of drip water δ18O (δ18Od) values between the upper and the lower galleries of Villars Cave, not only reinforces reliability in the model itself but also reveals the impact of multiple infiltration routes and karst reservoir dynamics on the δ18Od. On an inter-annual scale, the observed δ18Od values follow the variations of the water excess and of the cave temperature, which, in the period analyzed, show a marked trend, possibly induced by the climate variability patterns above the cave. Overall, these results are not only important to better understand the infiltration in karstic zones, but also to better interpret speleothem isotopic records widely used in paleo-climate studies.

Fingerprinting Low-Frequency Last Millennium Temperature Variability in Forced and Unforced Climate Models

Abstract Constraining unforced and forced climate variability impacts interpretations of past climate variations and predictions of future warming. However, comparing general circulation models (GCMs) and last millennium Holocene hydroclimate proxies reveals significant mismatches between simulated and reconstructed low-frequency variability at multidecadal and longer time scales. This mismatch suggests that existing simulations underestimate either external or internal drivers of climate variability. In addition, large differences arise across GCMs in both the magnitude and spatial pattern of low-frequency climate variability. Dynamical understanding of forced and unforced variability is expected to contribute to improved interpretations of paleoclimate variability. To that end, we develop a framework for fingerprinting spatiotemporal patterns of temperature variability in forced and unforced simulations. This framework relies on two frequency-dependent metrics: 1) degrees of freedom (≡N) and 2) spatial coherence. First, we use N and spatial coherence to characterize variability across a suite of both preindustrial control (unforced) and last-millennium (forced) GCM simulations. Overall, we find that, at low frequencies and when forcings are added, regional independence in the climate system decreases, reflected in fewer N and higher coherence between local and global mean surface temperature. We then present a simple three-box moist-static-energy-balance model for temperature variability, which is able to emulate key frequency-dependent behavior in the GCMs. This suggests that temperature variability in the GCM ensemble can be understood through Earth’s energy budget and downgradient energy transport, and allows us to identify sources of polar-amplified variability. Finally, we discuss insights the three-box model can provide into model-to-model GCM differences. Significance Statement Forced and unforced temperature variability are poorly constrained and understood, particularly that at time scales longer than a decade. Here, we identify key differences in the time scale–dependent behavior of forced and unforced temperature variability using a combination of numerical climate models and principles of downgradient energy transport. This work, and the spatiotemporal characterizations of forced and unforced temperature variability that we generate, will aid in interpretations of proxy-based paleoclimate reconstructions and improve mechanistic understanding of variability.

Atmospheric Modeling Study on Convection-Triggered Teleconnections Driving the Summer North American Dipole

Abstract The summer North American dipole (NAD) is a pattern of climate variability linked to variations in boreal forest seed production and migration of seed-eating birds. This is a modeling investigation of two teleconnections identified as drivers of the NAD in prior observational work: 1) tropically sourced atmospheric Rossby waves associated with anomalies in the phase distribution of the Madden–Julian oscillation (MJO) (i.e., phases 1 and 6 are anomalously prominent), and 2) a pan-Pacific atmospheric Rossby wave linked to East Asian monsoonal (EAM) convection. Sea surface temperature (SST) boundary forcing experiments were conducted with the Community Earth System Model 2 (CESM2) to trigger convection patterns that align with those observed during EAM and nonuniform phase distributions of MJO. For the EAM case, an El Niño–like SST dipole pattern combined with cool southern Japan SST forcing produced a convection and jet stream shift anomaly over East Asia and the northern Pacific with a positive NAD pattern downstream over North America, similar to the observed pattern when precipitation over East Asia (PEA) is relatively high. A companion experiment with only ENSO-like SST forcing also produced the NAD but featured a different structure over the Eurasian continent with a response resembling the summer east Atlantic (SEA) pattern over eastern North America and the eastern Atlantic. Simulation results suggest that the southern Japan SST forcing region has a secondary importance in triggering the NAD, producing only a somewhat NAD-like pattern by itself and only slightly improving the NAD produced by ENSO-like forcing. Simulations using SST forcing to induce seasonal convection anomalies with spatial patterns similar to anomalously frequent occurrence of MJO phase 1 (phase 6) produced circulation response patterns resembling the positive NAD (negative NAD).

Recent Increase in a Recurrent Pan-Atlantic Wave Pattern Driving Concurrent Wintertime Extremes

Abstract Wintertime extremes such as cold spells and heavy precipitation can have severe socioeconomic impacts, disrupting critical infrastructures and affecting human well-being. Here, we relate the occurrence of local and concurrent cold or wet wintertime extremes in North America and Europe to a recurrent, quasi-hemispheric wave-4 Rossby wave pattern. We identify this pattern as a fundamental mode of the Northern Hemisphere (NH) winter circulation, since wave 4 exhibits phase-locking behavior. Thus, the associated atmospheric circulation and surface anomalies reoccur over the same locations when the pattern’s wave amplitude is high. The wave pattern is most pronounced over the pan-Atlantic region, and increases the probability of extreme cold or wet events by up to 300% in certain areas of North America and Europe, as well as favoring their concurrence at different locations. High-amplitude wave-4 events have increased significantly in frequency over the past four decades (1979–2021), although no clear evidence is found relating this to modes or patterns of climate variability. The identified wave pattern may provide pathways for early prediction of local and concurrent cold or wet wintertime extremes in North America and Europe.

Last glacial hydroclimate variability in the Yucatán Peninsula not just driven by ITCZ shifts

We reconstructed hydroclimate variability in the Yucatán Peninsula (YP) based on stalagmite oxygen and carbon isotope records from a well-studied cave system located in the northeastern YP, a region strongly influenced by Caribbean climate dynamics. The new stalagmite isotopic records span the time interval between 43 and 26.6 ka BP, extending a previously published record from the same cave system covering the interval between 26.5 and 23.2 ka BP. Stalagmite stable isotope records show dominant decadal and multidecadal variability, and weaker variability on millennial timescales. These records suggest significant precipitation declines in the broader Caribbean region during Heinrich events 4 and 3 of ice-rafted discharge into the North Atlantic, in agreement with the antiphase pattern of precipitation variability across the equator suggested by previous studies. On millennial timescales, the stalagmite isotope records do not show the distinctive saw-tooth pattern of climate variability observed in Greenland during Dansgaard–Oeschger (DO) events, but a pattern similar to North Atlantic sea surface temperature (SST) variability. We propose that shifts in the mean position of the Intertropical Convergence Zone (ITCZ), per se, are not the dominant driver of last glacial hydroclimate variability in the YP on millennial timescales but instead that North Atlantic SSTs played a dominant role. Our results support a negative climate feedback mechanism whereby large low latitude precipitation deficits resulting from AMOC slowdown would lead to elevated salinity in the Caribbean and ultimately help reactivate AMOC and Caribbean precipitation. However, because of the unique drivers of future climate in the region, predicted twenty-first century YP precipitation reductions are unlikely to be modulated by this negative feedback mechanism.

Long‐term observed changes of air temperature, relative humidity and vapour pressure deficit in Bolivia, 1950–2019

AbstractThis study analyzes the long‐term observed changes of mean (Tmean), maximum (Tmax) and minimum (Tmin) air temperatures, relative humidity (RH) and vapour pressure deficit (VPD) at different elevation ranges across Bolivia from 1950 to 2019. The linear trends in air temperature series present a significant increase, with no substantial seasonal or spatial differences. On an annual basis, RH exhibited a non‐significant decrease (−0.08% decade−1), while VPD showed a significant increase (0.01 hPa decade−1) (p < 0.05). Although prior research has suggested that highland elevations experience faster warming than the global average, we have not identified a distinct correlation between elevation gradients and differential warming rates in Bolivia. Future research could investigate elevation‐dependent climate trends by examining seasonal and monthly patterns of climatic variables in relation to topographical gradients in various highland regions.

Amplified Decadal Variability of Extratropical Surface Temperatures by Stratosphere‐Troposphere Coupling

AbstractThe dominant pattern of Northern Hemisphere extratropical climate variability is the Northern Annular Mode (NAM), which in wintertime represents the coupling of the stratospheric and tropospheric circulations. The internal variability associated with the NAM has been shown to give rise to substantial uncertainty in climate projections of regional surface air temperatures (SATs), but it's unclear how much of this variability arises from stratosphere‐troposphere coupling processes. Here, using three large‐ensemble coupled climate model simulations from 1850 to 2100 with varying fidelity of stratosphere‐troposphere coupling processes, we demonstrate that regional SAT variability across timescales is amplified when the tropospheric NAM is coupled to the stratospheric NAM. Moreover, models that lack adequate simulation of stratosphere‐troposphere coupling processes may not capture the magnitude of uncertainty in near‐term SAT projections associated with this coupling.

Detecting the main driving force of runoff change in the Beiluo River Basin, China.

Understanding the evolution of runoff and identifying the main driving force of hydrological cycle changes are essential for water resource management. In this study, the spatial and temporal patterns of climate variables and hydrological factors were explored by applying geostatistical analysis and trend analysis in the Beiluo River Basin (BRB), China, and conversions of land use/cover change (LUCC) were assessed using chord diagrams. Contributions of climate change and human activities to runoff change were quantified employing multiple methods. The results show that annual precipitation and actual evapotranspiration increased significantly during the impact period (2004-2014) (p < 0.05), at rates of 19.3 mm/a and 11 mm/a, respectively, and there was a minor upward trend in annual runoff, at a rate of 0.38 mm/a, while annual potential evapotranspiration decreased slightly at a rate of - 3.3 mm/a. Climate variables were the primary contributor to runoff decrease from 2004 to 2011, with an average contribution of - 79% according to the three methods. Human activities were estimated to account for - 81% of runoff change from 2012 to 2014, which was inextricably linked to the increasing LUCC. The results of this study can provide a theoretical basis for regional water resource management under the influence of climate change and human activities.

Lagrangian Characterization of Surface Transport From the Equatorial Atlantic to the Caribbean Sea Using Climatological Lagrangian Coherent Structures and Self‐Organizing Maps

AbstractThis study presents an assessment of the transport of suspended material by surface ocean currents, which have a critical role in determining the connectivity and distribution of living and non‐living material. Lagrangian experiments reveal pathways from the Equatorial Atlantic to 10 strategic regions within the Caribbean Sea, determined by considering the space‐time variability of climatological Lagrangian Coherent Structures, which act as recurrent attracting pathways and transport barriers. Due to windage or Stokes drift, wind forcing is a significant factor in determining the spatial locations where particles cluster and the time needed to reach the Caribbean from the Equatorial Atlantic. Pathways shift westward within the Caribbean and take less time to arrive with increasing wind influence. Depending on the wind effect, the particles show higher confluence in different areas of the Caribbean. A case study is presented for the Mexican Caribbean nearshore area, isolated from ocean‐current trajectories. Here, wind weakens the transport barrier responsible for this isolation and causes particle confluence toward that region. Spatial patterns of the Eulerian velocity identified through Self‐Organizing Maps, with time dependence given by their best matching units, can reproduce the characteristic Lagrangian patterns of surface current climate variability. Our study demonstrates the application of tools from dynamical systems and unsupervised neural networks to understand Lagrangian patterns and identify the processes that drive them. These findings improve our understanding of transport mechanisms of suspended material by surface ocean currents in the Western Atlantic and the Caribbean Sea, which is essential for managing and conserving marine ecosystems.