Rich Countries Get Far Better Weather Forecasts Than Poor Ones, Study Finds

When a storm approaches, the difference between a reliable seven-day forecast and a vague one can be measured in lives and livelihoods. Yet the quality of the weather predictions people receive depends heavily on where they live, according to a new global analysis published in Nature Communications. Manuel Linsenmeier, an economist affiliated with Columbia University’s Climate School, Princeton University, and Goethe University Frankfurt, and Jeffrey G. Shrader of Columbia University’s School of International and Public Affairs, assembled a worldwide picture of temperature forecast accuracy and found a stark divide: the weather forecasts available in high-income countries are dramatically more accurate than those available in low-income countries. The gap is so large that a seven-day-ahead temperature forecast in a wealthy nation is, on average, roughly as accurate as a one-day-ahead forecast in a poor one. In other words, residents of some of the world’s most vulnerable countries effectively live with forecasts that are six days shorter than those enjoyed in the richest economies.

The finding matters because weather forecasts are not a luxury. They underpin decisions in agriculture, energy, transportation, construction, disaster preparedness, and public health. Farmers decide when to plant, irrigate, and harvest based on expected temperatures and rainfall. Power grid operators schedule generation around anticipated heating and cooling demand. Emergency managers position resources before heat waves and cold snaps. When forecasts are less accurate, every one of these decisions is made with worse information, and the economic losses compound. The authors frame the problem in explicitly economic terms: differences in forecast accuracy across regions can exacerbate existing economic inequalities and even create new ones, a concern that becomes more urgent as climate change increases the frequency and intensity of extreme weather events that forecasts help people anticipate and survive.

To establish the scale of the disparity, the researchers analyzed the accuracy of temperature predictions across the globe, comparing how well forecasts perform in countries at different income levels. Their analysis produced two central stylized facts. The first is the accuracy gap itself: temperature forecasts are much more accurate in high-income countries than in low-income countries, with the seven-day-versus-one-day comparison capturing the magnitude of the difference. The second is a troubling trend over time. Forecast accuracy has improved steadily worldwide since 1985, reflecting decades of advances in atmospheric modeling, satellite observation, and computing power. But that progress has not closed the divide. A persistent gap between high- and low-income countries remains, meaning that poorer nations have been riding the same wave of technological improvement without catching up to the accuracy levels that richer countries already enjoy.

Why does this gap exist? The study points to a combination of factors, and importantly, not all of them are about money or technology in the abstract. Some of the difference stems from the inherent scientific challenge of weather predictability, which varies across regions for reasons of geography and atmospheric dynamics. Forecasting the weather over a landlocked continental interior, a mountainous region, or a zone of complex convective activity can be genuinely harder than forecasting over other areas, regardless of how much infrastructure a country possesses. This component of the gap is a physical reality that no investment can fully erase. But the researchers show that a substantial share of the disparity arises from something far more tractable: unequal weather observing infrastructure. The quality of any forecast depends fundamentally on the quality and density of the observations that feed the forecasting models, and here the world is deeply unequal.

The observational deficit in poorer countries takes several forms. Low-income countries have fewer land-based weather stations and fewer radiosondes, the instrument packages carried aloft by weather balloons that measure temperature, humidity, and pressure through the atmosphere. These surface and upper-air observations are the raw material of numerical weather prediction; global models assimilate them to initialize their simulations of the atmosphere. Where stations are sparse, models have less information to work with, and forecast accuracy suffers not just locally but potentially downstream, because atmospheric conditions in one region influence weather elsewhere. Compounding the hardware shortfall, the study finds that existing infrastructure in low-income countries reports at lower rates. A weather station that exists on paper but fails to transmit data consistently contributes far less to forecast quality than one that reports reliably around the clock.

Institutional capacity adds a further layer to the problem. The researchers note that low-income countries also appear to have lower institutional capacity to issue official, local weather forecasts. Producing a useful national or regional forecast requires more than access to global model output; it requires trained meteorologists, computing resources, communication channels, and the organizational machinery to translate model guidance into actionable local predictions. Where these institutions are under-resourced, even the global forecast information that does exist may not reach the people who need it in a form they can use. The result is a compounding disadvantage: fewer observations feed the models, the models perform worse over the region, and the local institutions that could bridge the gap are themselves weaker.

The economic implications of this accuracy gap are significant, particularly in the context of a warming climate. Weather forecasts are one of society’s primary tools for preventing damage from climate-related hazards. Advance warning of extreme heat allows cities to open cooling centers and utilities to brace for demand spikes. Foreknowledge of frosts lets farmers protect crops. As extreme events become more frequent and severe, the value of accurate, early, and localized forecasts grows accordingly. If the countries most exposed to climate hazards also have the least accurate forecasts, the burden of climate change will fall even harder on populations least equipped to adapt. The study’s framing suggests that forecast inequality is not merely a technical curiosity but a distributional issue with direct consequences for who bears the costs of a changing climate.

There is, however, a constructive message embedded in the analysis. Because a meaningful portion of the gap traces back to unequal observing infrastructure rather than to immutable atmospheric physics, the study concludes that remedying the differences in monitoring infrastructure could help reduce the divide in forecast accuracy between higher-income and lower-income countries. Investing in weather stations, radiosonde programs, and data transmission systems in underserved regions would not only improve forecasts locally; it would enrich the global observation network from which all forecasts benefit. Weather prediction is a shared enterprise, and observations collected in one part of the world improve predictions everywhere as they are assimilated into global models. This creates a strong case for international cooperation and financing, since the returns to filling observational gaps extend well beyond national borders.

The research arrives at a moment when the scientific community is increasingly attentive to inequities embedded in global information systems, from satellite coverage to internet access to the geographic biases of artificial intelligence training data. Weather forecasting sits at the intersection of physical science and public infrastructure, and the new study demonstrates that even a field often imagined as universally shared, the same atmosphere observed by the same satellites, delivers its benefits unevenly. By quantifying the gap and tracing its origins to stations, balloons, reporting rates, and institutional capacity, Linsenmeier and Shrader have converted a vague sense of unfairness into a measurable, attributable, and potentially fixable problem. The steady global improvement in forecast accuracy since 1985 shows what sustained investment in atmospheric science can achieve. The persistent gap between rich and poor countries shows that those gains have not been shared equally. Closing that gap, the study suggests, is less a question of scientific feasibility than of political and financial will, and the payoff would be measured in better decisions, protected harvests, and lives saved in the places that need good forecasts most.

Subject of Research: Global inequality in temperature forecast accuracy between high-income and low-income countries

Article Title: Global inequalities in weather forecasts

Article References: Linsenmeier, M., & Shrader, J. G. (2026). Global inequalities in weather forecasts. Nature Communications. https://doi.org/10.1038/s41467-026-77630-w

Image Credits: AI Generated

DOI: 10.1038/s41467-026-77630-w

Keywords: weather forecasts, forecast accuracy, global inequality, temperature prediction, weather stations, radiosondes, observing infrastructure, low-income countries, climate change adaptation, economic inequality, institutional capacity, Nature Communications