The Rise of Severe
Convective Storms
United States · 2023 – 2025

Executive Summary — A Structural Shift, Not a Streak

The three-year period from 2023 to 2025 represents not an unusual cluster of bad luck but the crystallisation of a structural shift in the U.S. catastrophe loss landscape. Between 2023 and 2025, losses accumulated to a total in excess of USD 200 billion, according to Gallagher Re. The U.S. is the number one SCS hotspot, accounting for more than 80% of the value of insured losses globally. Cumulative losses from severe convective storms now exceed those from hurricanes, challenging the traditional classification of these events as secondary perils.

The reclassification of severe convective storms — encompassing tornadoes, hailstorms, straight-line winds, and derechos — from secondary to primary peril is the most significant categorical shift in the U.S. insurance loss landscape since the recognition of earthquake risk following the 1994 Northridge earthquake. It reflects not merely a change in the physical hazard but a convergence of four mutually reinforcing trends: expanding urban exposure in storm-prone areas, sharply rising construction and repair costs driven by inflation and supply chain disruption, social inflation increasing claim settlement values, and a growing body of evidence suggesting that climate change is expanding the geographic range and seasonal window of SCS activity.

This case study differs structurally from others in this series, which focus on single landmark events. SCS in 2023–2025 is examined as a multi-year accumulation of losses — an aggregation of hundreds of individual events, none of which alone would qualify as a peak-zone catastrophe, but whose cumulative financial impact rivals or exceeds the largest single-event catastrophes in U.S. history. This distinction — between single catastrophic events and sustained high-frequency attritional loss — is itself one of the most important analytical features of the SCS problem for cat modellers and reinsurers.

Three Years of Record Losses — An Overview

The Anatomy of Severe Convective Storms — Four Distinct Hazards

Severe Convective Storms (SCS) is an umbrella category covering four distinct meteorological phenomena that share a common origin in convective atmospheric instability but produce very different damage patterns, affect different asset classes, and present fundamentally different modelling challenges.

The Physics of the SCS Hazard — Why the U.S. Is the Global Epicentre

The Perfect Atmospheric Conditions for SCS

The United States — particularly the corridor from Texas to the Canadian border known as Tornado Alley, and the expanding Dixie Alley across the southeastern states — experiences the most frequent and intense SCS activity in the world. This is not coincidental but a direct product of North America's unique geography and atmospheric dynamics:

• The Rocky Mountain barrier: The Rocky Mountains force Pacific air masses to rise and cool before descending as dry, compressed air over the western Great Plains — creating the dry line, a sharp moisture boundary that is one of the primary triggers for supercell thunderstorm development
• Gulf moisture access: The Gulf of Mexico provides an unrestricted pathway for warm, moist air to flow northward across the flat terrain of the Great Plains and Southeast — providing the high atmospheric moisture content that fuels convective instability
• The jet stream interaction: Strong upper-level winds from the jet stream provide the vertical wind shear necessary for supercell formation — the specific storm structure responsible for producing the most intense tornadoes and hail
• Flat terrain: Unlike Europe, where mountain ranges fragment and limit the spatial extent of convective systems, the flat terrain of the U.S. central plains allows supercell thunderstorms and mesoscale convective systems to develop and travel hundreds of miles without terrain disruption

The Supercell — The Engine of Severe SCS

The most dangerous and loss-generating SCS events are typically produced by supercell thunderstorms — organised, long-lived thunderstorms with a rotating updraft called a mesocyclone. The mesocyclone is the critical feature that distinguishes supercells from ordinary thunderstorms and enables them to produce large hail (the rotation extends updraft longevity, allowing hailstones to cycle through the updraft multiple times and grow larger), violent tornadoes (the mesocyclone provides the vorticity that can be stretched into a tornado under the right conditions), and extreme wind gusts (the organised structure creates efficient inflow-outflow circulation).

The spring tornado season in the U.S. — typically March through June — corresponds to the period when Gulf moisture, Rocky Mountain dry air, and jet stream wind shear align most frequently and most intensely. Activity is rising. Cotality reported 142 days of hail of two inches or greater across the country in 2025, against a 20-year average of 122. More hail days of significant size means more opportunity for insured losses from each season.

The Expanding Tornado Alley — Dixie Alley's Rise

Traditional Tornado Alley encompasses Kansas, Oklahoma, Nebraska, and northern Texas — the historical core of U.S. tornado activity. But research over the 2010s and 2020s has documented a systematic eastward shift in tornado activity, with Dixie Alley — the southeastern states from Mississippi and Alabama through Tennessee and the Carolinas — experiencing increasing tornado frequency and, critically, a higher proportion of nocturnal and EF3+ events.

This geographic shift has direct insurance implications. Dixie Alley has higher population density than the traditional Tornado Alley plains, older and less tornado-resilient housing stock, a higher proportion of mobile homes, and a greater proportion of nocturnal events — when residents are asleep and warning system effectiveness is lower. The Rolling Fork, Mississippi EF4 of March 2023 — which struck at night and killed 17 people in a community of 1,800 — exemplifies the Dixie Alley risk pattern. The same tornado striking a Kansas wheat field would have been an agricultural loss event, not a human tragedy.

The Four Loss Amplifiers — Why USD 45B is the New Baseline

The SCS loss data for 2023–2025 cannot be explained by atmospheric trends alone. Detailed attribution analysis by Allianz, Munich Re, Swiss Re, and CoreLogic consistently identifies four non-meteorological factors as the dominant drivers of the loss trajectory:

Amplifier 1 — Urbanisation and Exposure Growth

Urbanisation and development into hazard-prone areas have dramatically expanded exposure. Oklahoma City's building stock increased by an estimated 40% and its developed land area by 60% between 1990 and 2025. This expansion is not unique to Oklahoma City — it reflects a national pattern in which the fastest-growing metropolitan areas are disproportionately located in the SCS-prone South and Midwest. Dallas-Fort Worth, Houston, Nashville, Kansas City, Oklahoma City, and Indianapolis have all experienced rapid suburban expansion into areas that have always been exposed to hail and tornado risk but previously contained far less insured value.

The mathematical consequence is straightforward: the same hailstorm that struck an underdeveloped suburb in 1990 now strikes a neighbourhood of high-value homes, commercial buildings, and parked vehicles. The hazard has not changed. The exposure has changed. Hailstorms pose a threat to 41 million homes at moderate or greater risk, representing a reconstruction cost value of USD 13.4 trillion. For tornadoes, 66 million homes are at risk, valued at USD 21 trillion RCV.

Amplifier 2 — Construction Cost Inflation

Roof replacement is the single most common and most expensive SCS insurance claim. Asphalt shingles — the dominant residential roofing material in the United States — are the primary component of hail damage claims. The cost of asphalt roof replacements has reportedly surged 250% since 2000, with a 45% increase in the last five years alone. Supply chain disruptions, skilled labour shortages and aging infrastructure further amplify costs.

This cost inflation is not fully captured in standard insurance policy limits, which are typically set at inception and updated infrequently. The gap between insured limits set three or five years ago and current replacement costs produces systematic underinsurance — meaning that even policyholders who have been paying premiums for years may find their coverage inadequate when a hailstorm hits. This underinsurance problem is structurally similar to the Turkey earthquake building code gap: the policy says one thing, the economic reality at time of loss says another.

Amplifier 3 — Social Inflation

Social inflation — the increase in insurance claims costs attributable to litigation trends, jury award escalation, plaintiff attorney strategies, and shifting legal interpretations — has materially increased SCS loss costs beyond what physical damage alone would suggest. In the SCS context, social inflation manifests primarily through:

• Public adjuster proliferation: Third-party public adjusters, contingent-fee attorneys, and damage assessment firms have created an industry around maximising hail damage claim payments — often for marginal or disputed damage that pre-existing hail may have caused
• Roofing contractor referral networks: Door-to-door contractor solicitation after hail events drives claim filing rates well above the underlying physical damage rate, as contractors identify incremental damage that homeowners had not noticed or intended to claim
• Assignment of Benefits (AOB) litigation: In some states, contractors can receive an assignment of insurance benefits from the policyholder, allowing them to sue the insurer directly — shifting negotiating dynamics and increasing settlement costs
• Nuclear verdicts: In commercial SCS liability cases, jury awards have escalated dramatically, with verdicts in SCS-related litigation increasingly in the multi-million-dollar range for injuries and business interruption claims

Amplifier 4 — Climate and Atmospheric Trends

The climate change contribution to the SCS loss trend is the most complex and contested of the four amplifiers. The physical science is not settled in the way that the link between warming sea surface temperatures and tropical cyclone intensification is settled. The evidence for individual SCS hazard components points in different directions:

• Hail: Climate modelling suggests that total hail frequency may decrease under warming (fewer but stronger hailstorms) while the frequency of large hail (≥5 cm) may increase. The 2024 warning for DVD-sized hail in Texas — the first warning for 5-inch hail on record — is consistent with this projection
• Tornadoes: There is evidence of a poleward shift and eastward shift in tornado activity, with the Dixie Alley pattern representing the latter. There is also some evidence of increased variability — more tornadoes in winter and fall, expanding the seasonal risk window
• Wind shear and moisture: Increasing atmospheric moisture (a clear climate change fingerprint) provides more fuel for convective storms. The effect on wind shear — the other key ingredient for severe convection — is less clear, as climate change affects the jet stream in complex ways

Climate risk models from CoreLogic and Cotality suggest that by 2030 and especially by 2050, regions like the South and Midwest will face even greater exposure to hail, tornadoes, and high-wind events. More atmospheric moisture and changing wind shear patterns are already shifting the geography and severity of risk.

Key Events — 2023–2025 Selected Case Studies

The Rolling Fork, Mississippi Tornado — Anatomy of a Dixie Alley Catastrophe

Of all individual events in the 2023–2025 period, the Rolling Fork EF4 of March 24, 2023 warrants particular attention for what it reveals about vulnerability patterns in the expanding SCS loss geography. Rolling Fork is a community of approximately 1,800 people in Sharkey County, Mississippi — a rural Delta community with high poverty rates, majority-Black population, and a building stock dominated by manufactured homes, older wood-frame structures, and tenant housing.

On the evening of March 24, a large, violent, long-tracked multi-vortex wedge tornado struck Rolling Fork, Silver City, and Midnight. The tornado killed 17 people and injured at least 165 others, with peak winds of 195 mph over a path length of 59.4 miles and width of 0.75 miles. The entire business district on Highway 61 was destroyed.

The Rolling Fork event illustrates several SCS-specific risk dimensions that are distinct from hurricane and earthquake risk:

• Rural community amplification: A tornado of equivalent intensity striking an urban area with modern construction would have caused far more property damage in absolute dollar terms but far fewer fatalities — because urban building stock is more resilient and evacuation resources are more available. Rural communities face the reverse: lower absolute losses but higher human vulnerability relative to the storm's intensity
• Mobile home and manufactured housing vulnerability: Mobile homes are approximately 15–20 times more likely to be destroyed in a given tornado than site-built homes at equivalent wind speeds. They represent the most vulnerable element of the U.S. residential building stock to tornado impacts and are disproportionately concentrated in the SCS-prone rural South
• Community-scale total loss: When a tornado destroys the business district and a significant proportion of the residential stock of a community of 1,800 people simultaneously, the recovery capacity of that community is essentially zero. Reconstruction requires external resources, and the timeline is measured in years, not months
• Pre-existing vulnerability: As with Hurricane Maria and Puerto Rico, the Kahramanmaraş earthquake and southeastern Turkey — Rolling Fork's pre-existing poverty and inadequate housing stock amplified the impact of a physical event that, in a more affluent community, would have been devastating but survivable

The Houston Derecho — When Straight-Line Winds Hit a Major City

The May 16, 2024 Houston derecho warrants specific treatment as a case study within the case study, because it demonstrated something that had not been clearly established in the insurance record: that a non-tornadic convective wind event — with no rotating supercell structure — could produce concentrated losses in a major metropolitan area comparable to a weak hurricane.

A derecho with winds of up to 100 mph occurred in Houston, causing significant damage and at least eight fatalities. The storm caused more structural damage to downtown Houston's modern high-rise buildings than Hurricane Beryl — which made direct landfall on Houston as a Category 1 hurricane six weeks later. This comparison is counterintuitive and analytically important: a Category 1 hurricane, with its rotating wind structure and broader geographic footprint, caused less damage to the same buildings than a derecho's straight-line winds.

The explanation lies in the specific combination of wind direction persistence, building aerodynamics, and the element of surprise. The derecho's sudden onset with little geographic pre-warning meant that building management had not taken preparatory actions (securing exterior elements, adjusting HVAC dampers) that would reduce hurricane exposure. The straight-line, sustained wind direction also produced different loading patterns on building facades than the rotating wind signature of a hurricane. Post-event engineering surveys found glazing failures on specific building faces that the wind direction had loaded most severely — a lesson for both building design and SCS vulnerability model development.

Cat Model Performance — The Accumulation Problem

Why SCS Is the Hardest Peril to Model

SCS presents cat modellers with a set of challenges that are genuinely different from those of hurricane, earthquake, or flood modelling:

• Spatial specificity: A hailstorm's damage footprint can be as small as a few square kilometres. The same storm system may produce no damage two kilometres away. This fine spatial granularity requires much higher-resolution modelling than hurricane or earthquake hazard, which produces more spatially uniform hazard fields
• No single peak event: Unlike hurricanes, where cat models can identify clear scenario events (Category 5 direct hit on Miami, for example), SCS risk is characterised by hundreds of events per year with highly variable individual severity. There is no single "SCS Andrew" that defines the tail risk — the tail is populated by aggregations of many events across a season
• Short historical database: Reliable, spatially detailed SCS loss data is available only for the past few decades. The combination of population growth in SCS-prone areas and rising construction costs means that the loss environment today is structurally different from the loss environment that populates the historical database
• High data inconsistency: According to Moody's, SCS events are highly localised and frequent, and historical data is often inconsistent, making traditional modelling approaches unreliable. The combination of inconsistent historical reporting (particularly for events before widespread weather radar coverage) and the rapid change in the exposure base makes historical calibration of SCS models more uncertain than for other perils

The Aggregation Challenge — Annual Accumulation vs. Single-Event Models

Most cat models are designed around the concept of a single catastrophic event — a hurricane, an earthquake, a flood. They estimate the loss from that single event against the portfolio, producing a single-event loss distribution. SCS, by contrast, is fundamentally an accumulation problem: the insurance industry's concern is not any single hailstorm but the total of all hailstorms across an annual season, which collectively generate USD 45+ billion in losses even though no individual event approaches that magnitude.

This aggregation structure has profound implications for reinsurance treaty design and pricing. Traditional catastrophe excess of loss reinsurance (Cat XL) is structured around individual occurrence limits — it responds to a single large event but does not aggregate across the multiple smaller events that collectively drive SCS losses. The result is that much of the SCS loss falls in the frequency layer — below Cat XL attachment points — and is retained by primary insurers as attritional loss. The primary market's attritional loss from SCS in 2023–2025 was a direct driver of the personal lines insurance market hardening that has pushed homeowners premiums sharply higher across the South and Midwest.

The Non-Stationarity of SCS Risk

The most fundamental challenge for SCS cat models is the same one identified for wildfire models in the LA 2025 case study: the historical data that calibrates the model is from a world with different exposure values, different construction costs, and potentially different SCS hazard frequency and severity than the world in which losses will actually occur. Losses continue to escalate, driven primarily by increasing property exposure, urban sprawl, and rising replacement costs and inflation. A model calibrated to historical SCS losses will systematically underestimate current and future SCS losses unless it explicitly accounts for exposure growth, cost inflation, and climate trends — which most legacy SCS models did not do adequately entering the 2023–2025 period.

Comparison — SCS vs. Hurricane: A Reversal of Roles

The Market Response — Hardening, Deductibles, and E&S Growth

The insurance market response to three years of SCS losses above USD 45 billion has been significant and structural. The primary market has responded through four main channels:

• Higher wind and hail deductibles: The industry standard deductible for wind and hail losses in SCS-prone states has moved from flat dollar amounts (USD 1,000–2,500) to percentage deductibles — typically 2–3% of insured value. On a USD 400,000 home, a 2% wind and hail deductible creates a USD 8,000 homeowner retention before insurance responds, substantially reducing claim frequency for moderate hail events and transferring attritional SCS losses from insurer to policyholder
• Geographic restrictions: Standard market insurers have implemented ZIP-code-level restrictions on new business in the highest-SCS-exposed areas — particularly in Texas, Oklahoma, Colorado, and portions of the Southeast — mirroring the California wildfire market withdrawal pattern
• E&S market growth: US excess and surplus lines have been absorbing more of the load. E&S direct premiums reached USD 86.47 billion in 2023, representing 9.2% of total US direct premiums, and had grown for a fifth consecutive year by 2024. E&S carriers are increasingly writing standalone wildfire, wind and hail cover.
• Reinsurance repricing: After absorbing above-trend SCS losses for multiple years, reinsurers have repriced SCS-exposed property cat programmes significantly, with rate increases of 20–40% at the 2024 and 2025 renewals for the most exposed books

Emerging SCS Exposures — New Asset Classes in the Storm Zone

The period 2023–2025 also saw the emergence of new, rapidly growing asset classes in SCS-prone geography that present novel vulnerability and modelling challenges:

• Utility-scale solar: The rapid expansion of solar farms and data centres in storm-prone areas has introduced new vulnerabilities. In March 2024, thousands of solar panels at a large solar installation were damaged by a single hailstorm. Solar panels are acutely vulnerable to hail — the glass and cell structure is not designed for impact resistance, and large-format panels are more vulnerable than smaller residential installations. As the U.S. solar fleet expands rapidly across the SCS-prone South and Plains, the aggregate hail exposure of the energy sector is growing at extraordinary speed
• Data centres: The explosion of AI and cloud computing infrastructure has driven rapid development of hyperscale data centres across Texas, the Carolinas, and other SCS-exposed states. These facilities have high replacement cost density (high insured values per square metre), roof damage sensitivity, and business interruption exposure that amplifies the insured loss from any hail or wind event affecting them
• Electric vehicles: EV battery damage from hail is a growing claims category, with total-loss determinations being more common for hail-damaged EVs than for conventional vehicles due to battery pack vulnerability and the difficulty of partial battery replacement
• Wind turbines: Leading-edge erosion from hail reduces wind turbine efficiency and ultimately requires blade replacement — an expensive claim category that is growing in proportion with the U.S. wind energy fleet

Legacy — What 2023–2025 Changed

Summary — Key Analytical Takeaways

1. USD 45 billion is the new baseline, not a record: Three consecutive years above USD 45 billion in SCS insured losses is not statistical noise — it represents a structural shift in the U.S. loss landscape driven by exposure growth, cost inflation, and social inflation. Cat models and business plans calibrated to the pre-2023 SCS loss environment are systematically underestimating current risk.
2. Hail, not tornadoes, drives most SCS losses: Tornadoes generate headlines and fatalities. Hail generates insurance claims — 50–80% of all SCS insured losses. A comprehensive SCS cat strategy must treat hail as the primary financial risk and tornado as the primary life-safety risk, and model them separately using appropriate methods for each.
3. SCS is an accumulation problem, not a single-event problem: No individual SCS event in 2023–2025 approached the scale of a major hurricane or earthquake in absolute loss terms. The USD 50+ billion annual totals are built from hundreds of events, none catastrophic in isolation. Models, reinsurance programmes, and capital frameworks designed around single catastrophic events systematically underestimate SCS risk.
4. Exposure growth is the dominant loss driver: Atmospheric trends explain only a fraction of the SCS loss escalation. The expansion of insured value into SCS-prone areas — driven by sunbelt urbanisation — combined with rising construction costs has more than doubled the loss potential of any given SCS hazard event relative to 20 years ago. Models that do not continuously update their exposure base underestimate risk as soon as they are calibrated.
5. New asset classes are materially increasing SCS exposure: The rapid expansion of utility-scale solar, data centres, and EV infrastructure in SCS-prone geography has created substantial new insured exposure for which calibrated vulnerability functions barely exist. The combined RCV of solar, wind, and data centre infrastructure in the SCS zone now represents trillions of dollars of exposure that was negligible a decade ago.