Catastrophe bond spreads compressed sharply between 2024 and mid-2026, falling from post-Hurricane Ian highs back toward 2021 levels. On the surface, that looks like a market shrugging off climate risk. Beneath the surface, the picture is more complicated: the models that generate a bond's expected loss have been quietly recalibrated upward, secondary perils have taken over as the dominant loss driver, and rating agencies have rebuilt their methodologies around climate-conditioned scenarios — even as nominal spreads fell.
The honest answer to "is climate change repricing cat bonds?" is not a clean yes or no. It depends on which layer of the pricing stack you look at, and which peril you're asking about.
The Headline Spread Number Is Misleading
Cat bond multiples — the ratio of risk spread to expected loss — spiked to roughly 5.0x in early 2023 after Hurricane Ian forced a sweeping repricing across the market. Since then, record capital inflows have compressed that multiple back down. Global reinsurance capital reached a record $790 billion by mid-2026, outstanding cat bond capacity passed $65 billion, and the average risk spread fell to 6.63% in Q2 2026 — a multiple of roughly 2.5x, close to where the market sat in 2021.
Read in isolation, that trend says the market has stopped pricing in elevated catastrophe risk. But spread is only one half of the equation. The other half — expected loss — is the modeled baseline the spread is a multiple of, and that baseline has moved. Modeling agencies have shifted from long-run historical averaging toward near-term, climate-conditioned loss estimates, which pushes expected loss higher even as the market-cycle premium on top of it shrinks. A 5% nominal spread in 2026 is not directly comparable to a 5% spread in 2016, because the expected-loss figure underneath it now carries a heavier climate load. The capital cycle has masked, not eliminated, a structural repricing happening one layer down.
How Modeling Firms Are Recalibrating for a Non-Stationary Climate
The two dominant catastrophe modeling firms have both moved away from treating historical loss data as a stationary baseline.
Verisk (formerly AIR) raised its global average annual insured loss (AAL) estimate to $152 billion in its 2025 Global Modeled Catastrophe Losses report, up sharply from the $132 billion average observed between 2020 and 2024. Verisk attributes roughly 1% of the year-on-year AAL increase across perils directly to long-term climate change, distinct from inflation and exposure growth. The firm has also rolled out a near-present-climate wildfire model for the US that shows a "markedly increased hazard relative to historical records," tied to large-scale warming and drying trends rather than just population growth into fire-prone areas.
Moody's RMS has built high-definition modeling into its platform, translating financial impact (OpEx and CapEx exposure) across horizons from five to fifty years. For North Atlantic hurricanes specifically, Moody's RMS applies a "near-term view" that formally bends the exceedance probability curve — assuming higher storm intensities and more frequent rapid-intensification events, tied to sustained anomalous sea surface temperatures.
Both approaches mean the same thing for cat bond investors: the expected-loss number a bond is priced against is no longer a pure historical average. It already contains a forward-looking climate assumption, whether or not that shows up as a separate line item in the spread.
Secondary Perils Are Where the Signal Is Clearest
If there is one place the climate signal is unambiguous, it is in secondary perils — wildfire, severe convective storm, and flood — rather than in peak hurricane risk.
Swiss Re Institute data puts secondary perils at 92% of the $107 billion in global insured losses in 2025, an extraordinary share for events that were historically treated as background noise around peak-peril tail risk. Frequency perils now account for $98 billion of Verisk's $152 billion modeled AAL, a 12-percentage-point increase in share over 2024 alone.
Wildfire has been the fastest-moving peril by far. The $40 billion Los Angeles County wildfires in early 2025 forced a discrete, visible repricing of wildfire risk across the ILS market rather than a gradual drift. Severe convective storm generated $51 billion in insured losses in 2025 — the third-costliest year on record for the peril — and its rising frequency has pushed ILS managers to recalibrate attachment points on aggregate-trigger bonds, which are otherwise vulnerable to erosion from a string of mid-sized storms rather than one large event. Flood risk crossed a credibility threshold of its own in 2026, when German insurer Gothaer sponsored Yardstick Re Series 2026-1 — the first investment-grade, pure-flood catastrophe bond. A single-peril flood bond reaching investment grade signals that investors are now willing to underwrite isolated secondary-peril risk directly, rather than only accepting it bundled into diversified multi-peril structures where the signal gets diluted.
Trigger Design Is Shifting in Response
Climate-driven model uncertainty and basis risk are pushing sponsors and investors toward specific trigger types.
A multi-decade study (2002–2025) by Neuberger Berman found that industry-index cat bonds materially outperformed indemnity bonds on a mark-to-market basis following Hurricanes Ian and Irma. Industry-index bonds for peak perils posted a realized loss ratio of just 0.1% — 2.8 percentage points below their modeled expected loss — acting as a buffer against the idiosyncratic claims-management and inflation-driven loss creep that has plagued indemnity-triggered bonds. Parametric triggers are gaining momentum for a related reason: they remove loss-adjustment ambiguity and pay out fast, as in Jamaica's $150 million payout after Hurricane Melissa in 2025. But parametric bonds have also historically carried the highest realized loss ratios outside peak-peril regions, since a purely objective trigger (wind speed, rainfall) is only as good as the model's ability to translate that metric into actual loss — exactly the kind of basis risk that a shifting climate makes harder to calibrate.
Rating Agencies Are Recalibrating Too
Credit rating agencies have rebuilt parts of their methodology around climate-conditioned stress scenarios rather than pure historical loss experience.
Moody's Ratings finalized a revised ILS rating methodology in late 2025. In assigning a rare Baa2 investment-grade rating to the Yardstick Re flood bond, Moody's explicitly went beyond the headline modeled outcome, examining stochastic scenarios for unmodeled risks like coastal storm surge and variable reset mechanisms that adjust attachment probabilities dynamically over the bond's life. S&P Global Ratings ran portfolio stress tests simulating a 1-in-250-year climate disaster and found that heavy use of reinsurance and retrocession cuts the top 50 global insurers' net catastrophe exposure from 34% of capital to roughly 15% (a net $225 billion) — but S&P still applies up to 55 negative rating-notch adjustments across those same insurers to reflect concentrated catastrophe and earnings-volatility risk. KBRA flagged a different risk in mid-2026: with property-cat rates falling 10–25% at June renewals, cheaper reinsurance is only credit-positive if primary carriers hold the line on attachment points and rate adequacy. A soft market, in other words, can quietly undo the discipline that climate-conditioned models are trying to enforce.
The Case Against a Climate Premium
Not every analyst agrees that hazard-side climate change is what's moving the numbers. A significant body of research argues the opposite: that rising losses are overwhelmingly a story about exposure, not hazard.
Gallagher Re's Q1 2026 report estimates that 80–90% of the nominal growth in US severe-convective-storm losses — which have grown roughly 10% annually over 25 years — comes from non-hazard variables: inflation, construction and labor costs, housing growth, and urbanization into higher-risk areas. Only 10–20% is attributable to hazard volatility or climate change itself. Swiss Re has made a similar point in blunter terms: more valuable property is simply being built in harm's way, and it costs more to rebuild when it's destroyed.
There is also a temporal mismatch argument, raised by analysts at Schroders Capital: cat bonds typically carry one- to three-year maturities, while climate change operates on multi-decadal timelines. Over a bond's actual life, short-term capital supply and demand — plus natural climate variability like El Niño and La Niña cycles — dominate pricing far more than any underlying long-term climate trend, which makes a genuine climate signal nearly undetectable in year-to-year spread movements at issuance.
So Is Climate Change Repricing Cat Bonds?
The honest answer is layered, not binary. Nominal spreads compressed to 2021 levels by mid-2026 because $790 billion in global reinsurance capital overwhelmed demand for risk transfer — a capital-cycle effect that has little to do with climate. But underneath that nominal number, the expected-loss baseline itself has been structurally raised by modelers incorporating near-term climate views, which means a given spread today reflects a higher risk-adjusted floor than the same spread would have a decade ago.
The clearest, least contestable climate signal is not in peak hurricane risk at all — it is in secondary perils. Wildfire and severe convective storm losses have grown fast enough, and visibly enough, to force real structural changes: new attachment points, new single-peril bond structures, and rating agencies building climate-conditioned stress tests directly into their methodology. Whether that growth is "climate change" or "more expensive stuff built in worse places" is genuinely contested — Gallagher Re's demographic-forcing argument is hard to dismiss — but the market's structural response is happening regardless of which explanation dominates. For an investor, the practical takeaway is the same either way: scrutinize expected-loss assumptions and trigger design in climate-sensitive perils rather than relying on the headline spread number alone.
For how cat bond pricing works mechanically, see How Cat Bonds Work. For the broader 2026 spread and returns picture this analysis builds on, see our 2026 Market Outlook. For how RMS and AIR build the expected-loss models discussed here, see The Role of Catastrophe Modeling Firms. For trigger mechanics referenced above, see Understanding Trigger Mechanisms and our Triggers section. For current market size and peril breakdown, see Market Data.