Unadapted

Methodology, version 2

How the numbers are worked out

For each event Unadapted shows four things: what it cost, how often it happens at that place, what adapting would have cost, and how the two compare over the life of the measures. This page explains each step, the formulas, and where the numbers are weakest.

What counts as an event

A specific episode of a hazard that climate change makes more likely or more severe, which has already happened and caused harm: heatwaves, floods and extreme rainfall (including rain-triggered landslides), wildfires, droughts and weather-driven crop failures, tropical cyclones and severe storms, storm surges and coastal erosion, glacier and permafrost hazards, and ecological impacts such as mass coral bleaching.

Not included: earthquakes, volcanoes and tsunamis; industrial and transport accidents; forecasts or warnings with no impact yet; and research, policy or opinion pieces that don't describe one specific event. A cyclone and the floods and landslides it causes count as one event.

How events are found

  1. Every 6 hours, news searches across each hazard find new articles. Syndicated copies of the same story are skipped.
  2. An AI model reads a factual summary of each article and decides whether it reports a qualifying event, extracting the place, dates and toll.
  3. Articles about the same event are grouped together, by the model and by matching hazard, country and dates. Events causing only local disruption wait until more coverage confirms them.
  4. Each event is then analysed against numbered sources: its own coverage, reports of losses, the place's history and existing protection, and examples of adaptation elsewhere. Events are re-analysed a few days and a few weeks later, as loss figures firm up. Every version is kept.

The cost of an event

The total economic cost: damage to homes, property and infrastructure, losses to farming and business, and the cost of the emergency response. Where a government, insurer, reinsurer or the World Bank has published a total, we use it and mark it reported. Otherwise we build an estimate from the parts and mark it estimated. Every cost has a low, central and high figure.

All money is in US dollars at 2026 prices. Other currencies are converted at the rate of the time, and older figures are adjusted for inflation. Deaths are reported separately and are not given a money value.

How often it happens

Climate-driven hazards recur. Some towns flood every few years; parts of Spain's Mediterranean coast are hit by cut-off-low ("DANA") storms most autumns. Comparing the cost of adapting with a single event understates what adaptation is worth, because a flood wall or a warning system protects against every repeat over its life. So each event is placed in a hotspot: the hazard at the place one set of measures would protect, such as river flooding in one town. Events in the same hotspot are linked on the site.

For each hotspot we record:

The cost of adapting

The package of measures appropriate for that place and hazard, sized for the affected area and priced at local costs, with a real precedent where one exists. For each measure:

Measures are judged on their own, and overlapping measures that protect the same assets in the same way are not both counted. Two further shares capture the limits of any design: the share of this event's losses that were beyond what the measures are built for, and the share of expected annual losses that come from events that big.

How they compare

The model supplies the inputs above. The arithmetic is done in code, the same way for every event:

Combined effectiveness = 1 − (1 − e₁)(1 − e₂)…, capped at 95%

Each measure acts on the losses the others leave, so effectiveness doesn't simply add up, and no package avoids every loss.

Annualised cost = Σ (up-front cost × CRF) + Σ running costs

CRF, the capital recovery factor, spreads an up-front cost over the measure's life as equal yearly amounts: r(1 + r)ⁿ ÷ ((1 + r)ⁿ − 1), with lifetime n in years and a discount rate r of 3% a year in real terms. That sits between the 2% in the US government's Circular A-4 (2023) and the 3.5% in the UK Treasury's Green Book.

Losses avoided a year = expected annual loss × combined effectiveness × (1 − share beyond design)

Lifetime return (benefit-cost ratio) = losses avoided a year ÷ annualised cost

Comparing yearly amounts like this is equivalent to comparing present values over the measures' lives. A ratio above 1 means the measures save more than they cost. The low and high ratios use the low and high expected annual loss.

Payback = up-front cost ÷ (losses avoided a year − running costs)

This event alone: losses avoided = event cost × combined effectiveness × (1 − this event's share beyond design)

A worked example

A town floods every few years, with expected losses of $6M a year. The latest flood cost $30M. The package is flood walls ($40M up front, $200K a year, 50 years, avoiding 80%) and a warning system ($1M, $100K a year, 10 years, avoiding 25%). 10% of expected losses come from floods bigger than the walls are built for.

Judged against the latest flood alone, the same package looks poor value: it would have avoided about $25.5M against $41M up front. That is why the lifetime return is the headline figure.

Is it climate change?

Each event carries one of three levels of evidence:

"Fits the warming trend" relies on the IPCC's Sixth Assessment Report, which finds that some hazards, such as hot extremes, are becoming more frequent and intense almost everywhere, while the evidence for others, such as heavy rainfall in some regions, is weaker.

The cost shown is the full cost of the event, not just the part caused by climate change. Where a formal attribution study gives a probability ratio (PR: climate change made the event PR times more likely), we also show the climate-attributable share using the fraction of attributable risk, 1 − 1/PR (Stott and others, 2004), applied to the cost as in Newman and Noy (2023). For example, an event made twice as likely has half its risk, and so roughly half its cost, attributed to climate change. Adaptation pays off whatever caused the event, so the lifetime return doesn't depend on attribution.

Existing protection

Each event records what protection was in place or planned beforehand:

Lives

Deaths are reported, not priced, and are left out of the cost comparison. That makes the lifetime return conservative for hazards where the main harm is loss of life, such as heatwaves. Where there is evidence that the measures save lives (for example heat-health warning systems or flood warnings), we show an estimate of the lives they would likely have saved, with its basis.

Uncertainty

Costs, expected losses and returns come as low, central and high figures, and each analysis carries a confidence level (low, medium or high) with its key assumptions. Reported costs for recent large events are usually the most reliable figures. Expected annual losses, effectiveness and costs for places with thin records are the least reliable.

Edge cases

Limitations

AI and review

Articles are found with Exa's search. Screening and analysis are done by Anthropic's Claude Opus 5.5 working from the numbered sources on each event page. Analyses are published automatically and are not reviewed by a person before they appear. Every figure links to the sources it relies on, so it can be checked.

Changes

References