ENSO and Climate Inequality: Who Benefits,Who Loses when El Niño and La Niña Amplify Extremes?

Introduction: From Climate Change to Distribution Shock

El Niño–Southern Oscillation (ENSO) is often referred to as an annual climate fluctuation. But from a social impact perspective, it resembles a risk orchestrator more than a pure weather indicator (McPhaden et al., 2006). Teleconnections triggered by ENSO can alter the probability of droughts, floods, and heatwaves in areas far from the tropical Pacific center, causing extreme events to appear in opposite directions across regions within the same period (Power et al., 2013). Because of this uneven extreme map, ENSO should be interpreted as a distributed shock—a shock that creates beneficiaries and losers, not one that everyone experiences equally (Dell et al., 2014; IPCC, 2022). This perspective clearly argues that ENSO acts as an amplifier of impact distribution. It transforms existing differences in exposure, vulnerability, and adaptive capacity into welfare disparities after a shock (Hallegatte et al., 2016). According to the Intergovernmental Panel on Climate Change (IPCC) risk framework, damage comes not only from hazard but also from exposure and vulnerability, so if vulnerable groups are already near the edge, a single ENSO shake can push them further down (IPCC, 2022). The Shock Waves framework emphasizes this mechanism by showing that climate shocks often trigger negative coping (asset sales, reduced investment in education and health care), turning short-term losses into long-term disadvantages (Hallegatte et al., 2016).

The research gap addressed in this Perspective lies in the fact that much discussion of ENSO still tends to describe average impacts (meteorological average or GDP average). While the most important aspect is the concentration of losses in vulnerable groups and regions (Dell et al., 2014; IPCC, 2022). Even when there is evidence of ENSO impacts on crop yields and commodity prices, these are often interpreted as individual outcomes rather than a chain of interconnected distribution mechanisms (Brunner, 2002; Iizumi et al., 2014). The second is the implementation gap between early warning and early action. This occurs when forecasting information exists but does not translate into action early enough to prevent negative coping effects on poor households. As a result, the objectives of this discussion are comprised of three main points: (i) to generalize ENSO as a distributed shock in the language of hazard–exposure–vulnerability; (ii) to systematize the transmission channels that exacerbate inequality after El Niño and La Niña; and (iii) to derive the principle of right-target policy to reduce amplification mechanisms. Here, right-target is not a slogan but a technical and ethical requirement. If intervention targets the wrong people or comes too late, policy can inadvertently exacerbate inequality (Bowen et al., 2020). Because ENSO is monitored and updated periodically at the international level, the discussion also considers ENSO a rare opportunity to transform seasonal forecasting into targeted social protection. We employ the integrative synthesis approach, linking evidence from climate science (teleconnection and rainfall variability), agriculture and food (yield), macroeconomics (prolonged impacts), and risk management (adaptive welfare and early action financing). The focus of this approach is to follow the flow from physical shocks to distributional outcomes, rather than stopping at climate descriptions or aggregate economic indicators. Simultaneously, this discussion uses the lens of forecast-based early action as a viable institutional design to transform forecasting advantages into equity, drawing on experiences and guidance in anticipatory action and forecast-based financing (RCCC, 2026; Red Cross EU Office, 2026).

Our perspective clarifies the following four points. First, ENSO creates beneficiaries and losers through livelihood, price, and recovery channels. Second, distributive losses are often greatest where risk overlaps with poverty. Third, policy effectiveness must be measured by who is protected? rather than just total losses. Finally, early intervention can block mechanisms that amplify inequality, such as asset sales and usurious borrowing. Evidence of ENSO’s impact on crop productivity shows that the geographical beneficiary-loss map is real (Iizumi et al., 2014). Therefore, policy must be viewed from a sub-regional and livelihood perspective, not a one-size-fits-all approach. Furthermore, evidence of cash support before shocks within the framework of early action also shows the potential to reduce negative coping and protect assets if interventions are early enough and targeted (Gros et al., 2023; Improta, 2026). Therefore, this perspective contributes conceptually by placing ENSO within the language of distributive shock and inequality amplifier. Simultaneously, it systematizes an interdisciplinary channel map from climate to welfare. Furthermore, we propose the governance approach that prioritizes equity, linking early warning with targeted interventions and distributive measures. Overall, the goal of the discussion is not to redescribe ENSO but to redefine it as a distributive event that requires policy responses targeting vulnerable groups.

ENSO in the Warming Climate: In What Ways Does It Amplify Extremes?

The question of ENSO under the influence of greenhouse gases has been debated for a long time due to biased models and because the Pacific Ocean’s average state changes through multiple mechanisms. While uncertainty remains regarding the trend of ENSO amplitude, some studies point to relatively clearer changes in rainfall patterns related to El Niño in the 21st century. The results of Power et al. (2013) emphasize that ENSO-induced rainfall variability in the equatorial Pacific may increase, and this is a driver of the spread of effects to teleconnection regions. Another important branch of evidence is the possibility of increased frequency of extreme La Niña under warming, with mechanisms related to the warming contrast between the Maritime Continent and the Central Pacific. Cai et al. (2015) highlight that a significant portion of the increase in extreme La Niña may occur in the years following extreme El Niño, implying successive opposing shake-ups year after year. The strong El Niño leading to extreme La Niña sequences are socially significant because they compress recovery time, increasing the likelihood of poor households falling into poverty traps due to the recurrence of the shock (Hallegatte et al., 2016).

Furthermore, literature on ENSO diversity shows that the Central Pacific El Niño (also known as the Modoki- or Central Pacific-El Niño) may increase relatively in warming scenarios. Yeh et al. (2009) assert that changes in the Central Pacific-El Niño or Eastern Pacific-El Niño ratio can alter teleconnection, so the impact of ENSO depends not only on the phase but also on the flavor of ENSO. If teleconnection changes, risk hotspots may shift, making policies based on historical statistics less effective or mistargeted (IPCC, 2022).

As a result, the term amplify in the context of the present discussion can be interpreted in two different ways: a warmer climate increases the likelihood of extreme events, whereas ENSO spreads that risk in a manner that is both temporally and regionally distributed. The issue of justice is closely connected to this understanding: when ENSO amplifies to extremes, who is able to absorb and recuperate, and who is left behind in the long run?

ENSO as a Distribution Amplifier: From Climate to Inequality

ENSO does not create inequality as a baseline. Instead, it exacerbates already existing inequality by disproportionately affecting vulnerable livelihood groups, pricing, growth, and resilience (IPCC, 2022). There are four main channels that may be described systematically: output-livelihoods, price inflation, prolonged macroeconomic, and vulnerability-governance (Dell et al., 2014). These channels are linked because productivity shocks can create price shocks, which can reduce health and labor productivity, resulting in growth. Because of this dependency, ENSO can be a systemic shock to long-term development, particularly if social protection networks are weak (Bowen et al., 2020).

Who Benefits, Who Loses: Distribution Map by Region, Group, and Time

To assess who benefits and who loses? from the effects of El Niño and La Niña, it is essential to see ENSO as a mechanism for the regional redistribution of extreme probabilities via teleconnection, rather than as a homogeneous shock (McPhaden et al., 2006). The distribution map is represented along three axes: region (spatial), group (social), and time (recovery trajectory). The IPCC risk framework demonstrates that welfare outcomes are simultaneously affected by hazard, exposure, and vulnerability (IPCC, 2022).

ENSO creates spatial beneficiaries and losers by shifting rainfall and temperature across subregions. The same ENSO phase can cause drought or flooding in one place and heavy precipitation in another (Power et al., 2013). Separate ENSOs, such as the Central Pacific or Modoki, worsen the situation. Different ENSO expressions can have diverse teleconnections, reallocating risk across places (Yeh et al., 2009). A country or territory may be classified as a beneficiary in one El Niño event while simultaneously being deemed a loser in another if policies persist in depending on a predetermined historical map. The El Niño phenomenon has diverse consequences across Latin America, as evidenced by compiled data. For example, some subregions may benefit from increased rainfall to support farming, while others may suffer from drought, flooding, or disruptions to certain businesses (IMF, 2023). Humanitarian reports indicate that El Niño and La Niña have a disproportionate impact on vulnerable communities, including poverty, limited services, and sensitive livelihoods. This means that even when the weather isn’t particularly poor, the consequences can be severe (OCHA, 2023). The spatial loser map is not entirely consistent with the rain-heat anomaly map. It is more closely aligned with the risk and vulnerability overlap map, as described by the IPCC (2022).

Along the social group axis, ENSO commonly exacerbates inequality through livelihood channels. As those who rely on rain-fed agriculture, informal labor, and natural resources are more vulnerable to income shocks (Hallegatte et al., 2016). Global crop productivity data demonstrate that ENSO’s effects vary greatly between locations and crop kinds. This generates beneficiary-loser zones within the same ENSO phase (Iizumi et al., 2014). El Niño can boost global soybean production, but its impact on corn, rice, and wheat varies by area. La Niña typically results in reduced crop production compared to normal conditions. If underrepresented populations have access to insurance, credit, and savings, this disparity does not necessarily contribute to inequality. However, in actuality, these groups are usually made up of impoverished or near-impoverished homes that lack resources and hence turn to negative coping techniques. According to the Shock Waves framework, when impoverished households are forced to liquidate productive assets or limit human capital investments to survive, the ENSO shock shifts from immediate injury to long-term disadvantage, worsening inequality (Hallegatte et al., 2016).

The pricing channel is another important distribution layer since ENSO can cause global commodity prices to rise, further harming the welfare of poor households that spend heavily on food and energy (Brunner, 2002). According to multinational macroeconomic studies, the El Niño phenomenon causes short-term inflationary pressures in many economies as energy and nonfuel commodity prices rise. This highlights the importance of the price channel in the distribution of damages (Cashin et al., 2017). This indicates that even if a country’s GDP growth rate remains unchanged or increases, disadvantaged people may still lose money due to increasing food and living prices and a reduction in basic spending (Dell et al., 2014). Price fluctuations also have an impact on countries’ trade balances, with net exporters of items potentially benefiting while net importers of food face real income losses and fiscal difficulties (Brunner, 2002). Thus, the beneficiaries within the pricing channel generally comprise businesses or nations that export and possess the capacity to modify prices, while those at a disadvantage include consumers and economies that import more than they export and endure a significant degree of pass-through.

Across the timeline, the exacerbation of inequality resulting from ENSOs predominantly occurs when their impacts extend beyond a single season. The consequences are yielding enduring effects that obstruct advancement and opportunities for restoration. Callahan & Mankin (2023) illustrate that El Niño can trigger prolonged global growth deficits, leading to substantial cumulative harm. The economic repercussions of El Niño may be exacerbated due to climate change, perhaps resulting in substantial losses during extreme occurrences. Policymakers must meticulously evaluate the possibility of tail risk (Liu et al., 2023). Countries possessing robust assets, stable institutional frameworks, and effective welfare systems typically experience swifter recovery and attain a competitive advantage following prolonged losses. Conversely, nations that are more susceptible experience sluggish recovery and continue along lower-income paths (IPCC, 2022). ENSO functions mainly as a distribution amplifier over time, where recovery gaps evolve into development gaps. This is increasing the susceptibility of individuals to the forthcoming ENSO shock (Hallegatte et al., 2016).

From a worldwide equity perspective, findings suggest that global warming has exacerbated economic inequalities among countries. Temperature effects differ across latitudes and adaptive capacities, with the likelihood of severe ENSOs exacerbating this variation (Diffenbaugh and Burke, 2019). A singular ENSO event can advantage certain economies. However, it may exert a more pronounced adverse effect on tropical nations that are already warm and depend on climate-dependent employment (Hsiang and Meng, 2015). Studies on development in impoverished regions indicate that responses to ENSO may be nonlinear and contingent upon each prevailing state’s conditions. It implies that distributional risk may be increased in countries with little institutional capacity (Smith and Ubilava, 2017). As a result, the loser map over time occurs not just inside a single nation but also within the framework of internation inequality, where ENSO shocks can delay capital accumulation and reduce adaptation capacity (Diffenbaugh and Burke, 2019).

The regional-group-time distribution map implies that ENSO policies cannot be optimal based on total losses, but rather on losses to vulnerable groups. Because this is where the mechanism for magnifying inequality functions most strongly. This supports the shift from meteorological forecasting to distributional risk management, linking ENSO alerts with poverty-livelihood-exposure maps to identify support priorities (Bowen et al., 2020). Evidence from forecast-based anticipatory action interventions shows that cash support before the shock peaks can help poor households protect assets and reduce negative coping, thereby directly flattening welfare inequality (Gros et al., 2023). Recent reviews also highlight that early remittances within the welfare framework can improve short-term food security and protect assets when targeting high-exposure groups and when there is sufficient lead time, reinforcing the logic of targeting vulnerable groups (Improta, 2026).

Right-Targeted Policies: From ENSO Forecasting to Early Action to Eliminate Inequality Amplification

World Meteorological Organization (WMO) (2026) provides periodic ENSO updates, creating an information base for designing seasonal fiscal and welfare decisions. However, humanitarian experience shows that early warning often does not translate into early action due to a lack of predisaster financing mechanisms (Red Cross EU Office, 2026). The forecast-based financing framework emphasizes preagreement on forecast thresholds and response actions to automatically disburse funds for mitigation actions before a disaster occurs. Red Cross Red Crescent Climate Center documents emphasize forecast-based anticipatory action as a shift from post-disaster response to proactive risk management (RCCC, 2026). The World Food Program (WFP, 2024) describes climate shock anticipatory action as a program to deploy and finance actions before extreme events occur to protect the food and nutrition security of vulnerable groups. Evidence suggests that forecast-based early remittances in Bangladesh can help households evacuate, protect health, safeguard assets, and reduce borrowing or asset sales during floods (Gros et al., 2023). Studies on early remittances also show that receiving funds earlier, closer to the peak of risk, increases welfare benefits and supports recovery, highlighting the role of lead time in equity (Pople et al., 2024). This evidence is consistent with the ENSO thesis as a distribution amplifier, as early action helps prevent negative coping mechanisms that are concentrated among the poor (Hallegatte et al., 2016).

At the systemic level, World Bank suggests Adaptive Social Protection (ASP) as a way to link social assistance with shock response. This would quickly increase coverage and lower vulnerability (Bowen et al., 2020). ASP stresses the need for coordination among social aid, humanitarian response, and catastrophe risk reduction to address covariate shocks, which are becoming increasingly relevant due to climate change. Marsland (2016) observed El Niño 2015–2016 as a significant and extensive phenomenon, necessitating prompt measures for agriculture and nutrition due to its repercussions surpassing the ENSO peak. Because ENSO sends effects through the price channel, targeted interventions need more tools for managing prices and strategic reserves to lessen regressive welfare shocks (Cashin et al., 2017). ENSO’s evidence of commodity inflation shows that stabilizing prices can be a fair way to help the most vulnerable consumers (Brunner, 2002). Because ENSO can have long-lasting effects, measures should also be taken to help people get back on their feet and make investments that will last, thereby lessening growth scars and long-term income divergence (Callahan and Mankin, 2023). To right-target, it is necessary to map hazards by placing anticipated climate threats atop poverty, livelihoods, and infrastructure exposure within a hazard–exposure–vulnerability framework (IPCC, 2022). An overview of evidence on anticipatory social protection underscores that early remittances are more efficacious when directed toward extremely vulnerable groups with adequate lead time, hence highlighting the significance of targeted design (Improta, 2026). Anticipation Hub (2026) underscores the significance of monitoring, evaluation, and learning in adjusting to evolving triggers and operations, considering the system’s novelty and the fluctuating risk landscape.

Fair Measurement and Accountability: Who is Protected? must be the Central Metric

If ENSO serves as a distribution amplifier, policy evaluation cannot depend solely on total economic losses or the number of individuals receiving assistance. It must also consider who is protected, at the appropriate moment, and how to alleviate the harm (Hallegatte et al., 2016). The IPCC risk framework stresses that risk is based on hazard, exposure, and vulnerability. This means that fairness measurements should show how much less vulnerable highly exposed groups are, not only how much less hazard there is or how much more investment there is (IPCC, 2022). According to the Shock Waves approach, equity indices should focus on determining whether interventions effectively avert detrimental coping strategies (such as asset liquidation, high-interest borrowing, and reductions in health and education funding) that facilitate the transformation of ENSO shocks into enduring poverty (Hallegatte et al., 2016).

Consequently, the index must encompass risk coverage: the percentage of impoverished and near-impoverished households in high-risk regions receiving assistance to circumvent paper benefits while neglecting genuinely needy populations (Bowen et al., 2020). The index also needs the right-target: it needs to measure undercoverage and leakage because targeting the wrong group can make the support program itself less fair (Improta, 2026). Another important aspect is timeliness (lead time), the number of days between the trigger threshold and when the household receives help. Evidence suggests that initiating early actions and adopting proactive strategies prior to the peak of risk might more successfully protect assets and mitigate negative coping mechanisms (Gros et al., 2023; Pople et al., 2024). To evaluate distribution results, it is essential to examine preventing poverty, protecting livelihood assets, and improving food security among beneficiaries. The indicators clearly illustrate the removal of mechanisms that exacerbate inequality due to ENSO (Hallegatte et al., 2016; Improta, 2026). It is essential to integrate accountability into the system by establishing clear trigger points, ensuring verified payments, and providing mechanisms for individuals to submit complaints and provide feedback. This is because forecast-based systems only work when the rules governing how money is distributed are public and can be independently monitored (Anticipation Hub, 2026; Red Cross EU Office, 2026).

Policy Limitations and Pitfalls: Why Right-Target is Difficult but Essential

Although ENSO can be monitored and predicted seasonally, translating forecasts into right-target protection often encounters hurdles related to climate uncertainty, forecasting errors, and operational capacity, leaving a persistent gap between early warning and early action. More importantly, according to the IPCC risk framework, social impacts depend not only on hazard but also on exposure and vulnerability, so a technically optimal policy that is distributively biased may inadvertently amplify inequality instead of mitigating it (IPCC, 2022). Therefore, we continue to discuss common policy limitations and pitfalls—from the illusion of forecast accuracy, mistargeting, short-term bias, and lack of accountability—to emphasize that targeting vulnerable groups correctly, while difficult, is essential if ENSO is to be considered an amplifier of impact distribution. First, the uncertainty of forecasting and the variability of ENSO impact footprints over time make determining who loses based on a fixed scenario prone to errors without continuous updating of forecast and observational information (Cai et al., 2015). The accompanying policy trap is the illusion of accuracy, in which policymakers assume the ENSO index is sufficient to define intervention areas, while diverse ENSOs (e.g., Central Pacific or Modoki) can shift teleconnections and change risk geography depending on the event (Power et al., 2013; Yeh et al., 2009). Second, right-targeting is difficult when poverty, livelihood, and informal data are incomplete, leading to undercoverage or leakage that reproduces inequality within the support program itself (Bowen et al., 2020). Equity-washing is a common trap. In which programs report success based on the number of recipients, while failing to ensure that the most vulnerable groups (poor and near-poor people who rely on rain for a living) are actually covered by the hazard-exposure-vulnerability framework (Hallegatte et al., 2016; IPCC, 2022). Third, timeliness (lead time) is critical, as the benefits of responding early are strongly reliant on lead time and the ability to promptly distribute cash. If there are delays of a few days, disadvantaged households may have to sell their goods or take out high-interest loans before receiving assistance (Pople et al., 2024). An operational trap associated with this is an impractical trigger, which refers to setting trigger thresholds that are excessively complicated or not linked to clear standard operating procedures and early action protocol processes. This leads to unrealistic estimates (Red Cross EU Office, 2026). Fourth, the pricing channel is missing because policies exclusively address direct damage and ignore regressive commodity-food inflation. This indicates that, despite getting support, households facing economic difficulties persist in sustaining losses (Brunner, 2002; Cashin et al., 2017). Fifth, there are enduring, nonlinear repercussions. ENSO may lead to enduring growth impairments, and timely actions alone are inadequate to avert long-term economic disparities (Callahan and Mankin, 2023; Liu et al., 2023). The short-term bias of these programs leads to programs that prioritize swift, immediate results, overlooking essential elements of the preservation of human capital and livelihood rehabilitation. Shock Waves believes that these mechanisms are critical for avoiding the poverty trap (Bowen et al., 2020; Hallegatte et al., 2016). Finally, politicization and a lack of accountability can result in unequal resource distribution that excludes vulnerable individuals. To ensure that the right-target is fair, transparency triggers, auditability, and appeals processes are required (IPCC, 2022).

Conclusion: From ENSO Forecasts to Governance Prioritizing Equity

If ENSO can be tracked and anticipated seasonally, the primary concern is no longer whether or not to predict, but rather how that prediction translates into the ability to protect fairness in policy implementation. According to the IPCC risk framework, the social result of ENSO is determined by hazard, exposure, and vulnerability. As a result, research should prioritize distributional concerns, such as who is most vulnerable, who recovers the slowest, and what factors cause inequality to accrue over time. Based on this, we propose several policy recommendations and research directions from forecast to governance to link interdisciplinary evidence (climate-economic-well-being) with institutional design and equity measures. So that ENSO no longer acts as an amplifier of inequality but rather serves as a test case for governance that prioritizes vulnerable groups.

The equity-oriented research should begin by quantifying the ENSO → climate anomaly → yield → price → group welfare causal chain. The climate-economic literature indicates that weather impacts frequently traverse multiple channels concurrently and exhibit significant variability depending on the context (Dell et al., 2014). The immediate aim in the food system channel is to predict how ENSO affects agricultural production across different regions, so we can determine where it occurs most frequently. Iizumi et al. (2014) found that El Niño and La Niña have differing impacts on diverse crop varieties and geographic areas. It is crucial to analyze ENSO’s transmission mechanism into commodity inflation and the degree of pass-through to the consumption baskets of low-income households through the pricing channel. ENSO is associated with fluctuations in essential commodity prices and has the potential to induce short-term inflationary pressures across different economies (Brunner, 2002; Cashin et al., 2017). In the long-term macroeconomic channel, it is essential to strengthen the evidence on the enduring, nonlinear effects of ENSO on growth and income inequality. Recent findings indicate that El Niño can inflict lasting growth detriments and that losses may escalate amid warming (Callahan and Mankin, 2023; Liu et al., 2023).

Simultaneously, research on ENSO diversity and teleconnection shifts needs to be integrated into distributed risk assessment, as changes in ENSO patterns can alter impact footprints and distort historical risk maps (Power et al., 2013; Yeh et al., 2009). Second, trigger adjustments and lead time optimization are crucial for early action, as forecast-based financing systems emphasize triggers as the bottleneck determining whether forecasts translate into action (Anticipation Hub, 2026; Red Cross EU Office, 2026). Third, equity impact evaluation is essential, using the measure of who is protected? as the IPCC emphasizes risk dependence on hazard-exposure-vulnerability, and policy objectives should focus on reducing vulnerability for highly exposed groups (IPCC, 2022). Empirical evidence on forecast-based early money transfers suggests that pre-shock interventions can protect assets and reduce negative coping, so research needs to compare before–after and true–false target effectiveness across poor and near-poor groups (Gros et al., 2023; Improta, 2026). Fourth, institutional design is needed to integrate early action into adaptive social security, as the Adaptive Social Protection framework emphasizes rapid scalability and reduction of poverty fallout when climate shocks occur (Bowen et al., 2020; Hallegatte et al., 2016).

In summary, if ENSO is a distribution amplifier, then effective governance must transform seasonal forecast updates into governance that prioritizes equity—transparency triggers; targets vulnerable groups; coordinates tools (cash, food, insurance, and price shock mitigation); and measures success by distribution outcomes rather than just total losses.

Authors’ Contributions

T.V.N: Conceptualization, writing—original draft and editing, and formal analysis. A.B: Writing—review and editing.