Global Climatology of Tropical Cyclone Power Dissipation

1 · Theory

What power dissipation is, and the two substitutions everyone makes

A tropical cyclone extracts energy from the ocean and spends nearly all of it rubbing against the sea surface. The instantaneous spending is a power — an area integral of the cubed surface wind — and what a season dissipates is that power integrated over every storm's footprint and lifetime:

Emanuel could not evaluate the area integral from historical data, so he substituted a point for the field —

— arguing, on the near-core profile similarity of Weatherford & Gray (1988) and Mallen et al. (2005) and the weak reported size–intensity correlation, that size varies mostly randomly, so ignoring it adds noise but little bias. The exact relation the approximation compresses is E = ρC_D·PDI·K, where K is the V³-weighted mean dissipation area — so the operative question is not whether storms differ in size (they do) but whether K is stable enough, per season and per era, for the inference being made. That question was probed rather than ignored in the two decades since: Sriver et al. (2008) compared satellite-integrated dissipation against PDI directly over 1998–2006 and found broad co-variation (with factor-scale calibration differences between sensors); Dean, Emanuel & Chavas (2009) and Chavas & Emanuel (2010) built the size climatologies the question needs; and modeling experiments cut both ways — Sun et al. (2017) and Xu et al. (2020) find size-aware dissipation responding more strongly than PDI under warming, not less. What no study had supplied is the fix-by-fix, all-basin measurement of K and its variability. The companion measurement on this site, from fixes with agency-analysed wind fields, shows that the second assumption fails in a specific, systematic way: the effective dissipation area falls as V^−0.88 while storms intensify, so integrated dissipation follows V^≈2.1, not V³, and grows about % per degree of latitude at fixed intensity. Size is not noise; it carries % of the interannual variance of global dissipation. Those two measured numbers — the exponent and the latitude slope — are the lens this paper reads the historical record through.

There is a second substitution, quieter than the first: taking the best track's V_max as a physical constant of the storm. It is an estimate, made by different agencies with different tools in different decades, and every claim about a PDI trend is a claim about the stability of that estimate. That is why this paper runs on two records instead of one.

2 · The data

Two records of the same storms

The best track. six-hourly tropical and subtropical fixes ≥34 kt from storms, 1960–2025: NHC's HURDAT2 for the Atlantic and eastern/central Pacific, JTWC's fixes (via IBTrACS) for the western Pacific, Indian Ocean and southern hemisphere, and the Neumann and ds824 compilations filling the early southern hemisphere where JTWC has no record. This is the operational memory of every storm — and it embeds every change in how storms were observed: aircraft reconnaissance ending in the western Pacific in 1987, the Dvorak technique spreading through the 1970s–80s, scatterometry and microwave sounders arriving around 2000. No bias corrections are applied anywhere; this is the record as the agencies wrote it.

The satellite record. ADT-HURSAT version 01 (NCEI accession 0307249, released February 2026): the Advanced Dvorak Technique, one fixed algorithm (ADT 9.0), run over the homogenised 8-km, 3-hourly HURSAT-B1 geostationary infrared archive — ocean fixes from storms, 1978–2024. It extends by seven years the record behind Kossin et al. (2020). At any single fix it is the worse estimate: 8-km pixels blur small eyes and 3-hourly sampling clips intensity peaks. But it is the same worse estimate in 1980 and in 2024, which is precisely what a trend needs and the best track cannot offer.

The supporting layers. Four further datasets feed the deep sections. Size: the agency wind radii of the size layer (43,086 analysed fixes) and, for the pre-radii era, the Xu et al. (2024) ERA5 reconstruction — the ESSD global size dataset, 1959–2022, validated against the extended best track in the companion note (structure and interannual variability survive its drifting bias; trends do not). The younger reanalysis-size literature — Schenkel et al. (2017) against QuikSCAT, Thompson (2024) — corroborates that reanalyses carry credible outer size, which is the size that matters for the integrals here. SST: ERSSTv5, monthly, 1950–2026, for Emanuel's genesis boxes and the AMV index. Indices: ONI, the ERSST PDO, and AMV computed here. Potential intensity: this site's own MPI store — tcpyPI (Gilford 2021) on ERA5 at 0.25°, daily grids for August and September, 1996–2025.

3 · The climatology

Where and when the planet dissipates its storm energy

Over the 1991–2020 normal period the globe accumulates a PDI of  ×10¹² m³ s⁻² in an average year. Converting the index to actual energy through the measured wind fields of the size layer, tropical cyclones dissipate roughly exajoules per year against the sea surface — around  TW as a year-round average, concentrated in a few dozen storms.

4 · The nexus

ACE, PDI, IKE and PD are one object with two knobs

The index families look like rival conventions. They are the same integral evaluated with different amounts of information, and the cleanest way to see it is the construction that runs from McTaggart-Cowan et al. (2007) through Maue et al. (2008), Maue (2010, ch. 7) and Fritz (2009): put an idealized modified Rankine vortex under the integrals. Wind rises linearly to V_max at the radius of maximum wind R_m, then decays outward as (R_m/r)^x with x ≈ 0.5:

Substituting analytically and evaluating to the 34-kt radius gives every member of the family at once in closed form — for x = ½ the cubic integral is exactly M₃ = 2πR34²u³(2 − (9/5)·u/V_max) with u = 34 kt — and the exponents below are numerical fits to those forms over realistic intensity ranges. Klotzbach et al. (2022) used the same modified-Rankine construction with observed radii to explain the tightness of the PD–IKE relationship; this table extends that argument across the family. Three scope notes before reading it: these are properties of this profile family, not of storms; the fixed-RMW column's supercubic growth includes an expanding integration domain (the truncation at R34 is physically essential — an r^−½ tail integrates to divergence); and a fit across different storms does not by itself establish that an intensifying storm follows the same path — the within-storm version is an open measurement.

Empirically, the season-level family behaves exactly as the vortex algebra says it must — the point indices cluster, the field integrals cluster, and the two-parameter index Σ V²R34² sits between the camps, nearly interchangeable with full IKE:

5 · Emanuel (2005), re-evaluated

The doubling that held, the one that didn't

Emanuel (2005) introduced PDI, smoothed it with two passes of a 1-2-1 filter, and reported that Atlantic power dissipation had "more than doubled in the past 30 yr", western North Pacific dissipation had risen "by about 75%", and their sum had "nearly doubled" — trends he tied to rising tropical sea surface temperature. The record then ended in 2003. It is now 2025, and the same filter over the same basins tells a more discriminating story:

The SST correlations, re-run on his own boxes

Emanuel's argument was not the trend alone; it was the correlation of smoothed PDI with smoothed SST in each basin's genesis region — r² = 0.65 (Atlantic, September 6–18°N 20–60°W), 0.63 (West Pacific, July–November 5–15°N 130–180°E), 0.69 (combined vs 30°S–30°N annual). Those boxes, that filter, ERSSTv5 through 2025, PDI uncorrected:

And the claim priced in actual dissipated energy

The Xu et al. (2024) ERA5 size reconstruction lets the Emanuel window be re-priced in area-integrated PD rather than the cubic point index. These are reconstruction-dependent sensitivity estimates, not independent measurements: the reconstruction's bias drifts (per the companion note's audit), a drifting multiplicative bias survives ratios as b₂/b₁, and the reconstruction is itself IBTrACS+ERA5 machine learning rather than observation. The 2014–23 column also mixes bases (observed radii carry the years past the reconstruction's 2022 end). Read the table as "what the claims look like if the reconstruction's era-to-era scale is roughly right":

6 · Webster et al. (2005), updated

The Category 4–5 doubling, split into storm and instrument

Webster, Holland, Curry & Chang (2005) counted 171 Category 4–5 storms globally in 1975–1989 and 269 in 1990–2004 — a near-doubling in number, and a rise from roughly 20% to 35% as a share of all hurricanes, with no trend in total storm counts. Klotzbach & Landsea (2015) revisited the claim ten years on and found the rise concentrated in the earliest, least reliable years. Both windows can now be extended a full generation, in both records:

7 · Kossin et al. (2020) × ADT-HURSAT v01

The exceedance trend, seven years on

Kossin, Knapp, Olander & Velden (2020) asked the cleanest version of the intensity question: among all hurricane-strength intensity estimates, what fraction are major (≥100 kt)? In ADT-HURSAT over 1979–2017 that exceedance probability rose about +5% per decade (95% CI [0.4, 11]), from 0.340 in 1979–1997 to 0.373 in 1998–2017, with the triad time-series trend at ~+6%/decade — the values of the published correction (PNAS, November 2020), which revised the widely-quoted original figures (+8%/decade [2, 15], 0.27 → 0.31) after a threshold error was found, without changing the conclusion. The February 2026 release of ADT-HURSAT v01 extends the homogeneous record through 2024 — seven more seasons, spanning both record-active and record-quiet years. Recomputed here on identical definitions:

8 · The stress test

"Stronger storms are getting stronger," interrogated five ways

The exceedance trend of Section 7 is the strongest global signal in the record, so it gets the adversarial treatment: every way the claim could be an artifact of window, threshold, basin mix, or metric definition, tested in both records. (The storm-by-storm decomposition of these aggregates — which individual Cat 4–5 storms the record missed, which it overcalled, and per-decade count bands — is the Storm Ledger, a standing page built from this paper's data.)

1 · Does the trend depend on where you start the clock?

2 · Are the strongest storms peaking higher, or are there just more majors?

3 · Which basins carry it?

4 · Trend or step?

5 · Threshold sensitivity

6 · Is it the storms, or the tracks?

9 · The connection

What an intensity trend is worth in energy — a conditional sensitivity experiment

Here the two halves of this research program meet, with the label stated up front: what follows applies a modern, cross-sectional relationship (dissipation area falling as V^−0.88 across the 2002–2025 population, latitude and basin controlled) to historical wind distributions. That is a conditional sensitivity experiment — "if the modern structure–intensity relationship transfers, then…" — not an observed historical energy change; the mixture of sizes, latitudes and lifecycle stages behind the modern exponent need not be the historical mixture, and the regression's construction (A_D contains V³ in its denominator) shares errors with its regressor, both audited in the companion note. With that scope:

10 · Landfalls

Weinkle, Maue & Pielke (2012), extended fifteen seasons

What ultimately matters is what reaches a coast. Weinkle et al. (2012) built the global landfall record 1970–2010 — about 15 hurricane-strength landfalls a year, about 5 of them Category 3+, and no trend in either — and it became the observational backbone of the normalized-damage literature. The same method (NHC-glossary landfall against a land mask, quarter-degree position buffer, landfall intensity from the landfall fix and the fix before it), applied to the merged best track and extended through 2025. The complete record — both definitions, the landfall map, and the fix-by-fix reproduction of the 2012 method against its published Table 2 — is a standing page at /tropical/landfalls/; this section carries the verdicts.

11 · Rapid intensification

The change that survives both records — and what size has to do with it

Bhatia et al. (2019) found rising 24-hour intensification rates in the high quantiles of both the best track and ADT-HURSAT over 1982–2009, and it has since become the strongest-credentialed of the change claims. Recomputed on both of this paper's records, through 2025, with RI defined as ≥30 kt in 24 h:

Size selects for rapid intensification

12 · The modes

ENSO, PDO, AMV — and the Maue (2011) minimum, fifteen years on

Interannual-to-decadal variability is the dominant term in this record, and it has an address. Correlating each basin's PDI (1966–2025) against the three canonical indices — ONI (ASO), the PDO (ASO), and the Atlantic Multidecadal Variability index computed here from ERSSTv5 (North Atlantic 0–60°N minus the 60°S–60°N global mean):

13 · From SST to potential intensity

The thermodynamic speed limit, measured instead of proxied

Section 5 showed the SST correlations that carried the 2005 argument have largely dissolved. That is not evidence against thermodynamic control; it is evidence that SST was always the wrong variable — a proxy for potential intensity (Emanuel 1986; Bister & Emanuel 2002), which depends on the difference between the sea surface and the whole tropospheric column, and which Emanuel (2007) himself moved to after the SST framing came under fire. PI is computed here rather than proxied: the tcpyPI algorithm (Gilford 2021) run on ERA5 at 0.25°, daily, for the two peak northern months, 1996–2025 — this site's own MPI store.

14 · The record of the argument

2005–2026: claims, corrections, and what stands

The two founding papers entered the most receptive news environment in the history of the field. Emanuel's letter was submitted in January 2005 and published on 4 August; Hurricane Katrina made landfall twenty-five days later. Webster, Holland, Curry and Chang appeared in Science on 16 September, between Katrina and Rita, with Wilma still to come. "Doubling" and "destructiveness" became the public shorthand for what tropical cyclone data showed, and they have never fully left the discourse.

The pushback was immediate — and it was technical, not rhetorical. Landsea's Nature comment identified two specific defects: the smoothed series retained unsmoothed end-points, so that "about one-third of the increase in Atlantic PDI in Emanuel's graph for the past ten years is incorrect owing to inappropriate plotting of the data"; and the pre-1970 Atlantic bias-removal reached −12.2 m s⁻¹ on the strongest storms, far beyond the 2.5–5 m s⁻¹ the underlying pressure–wind inconsistency justified. Pielke showed normalized US hurricane damage carried no trend, so either the index was mismeasuring destructiveness or the trend was not real. Chan (2006) read the western Pacific rise as one phase of a documented multidecadal oscillation. Landsea, Harper, Hoarau & Knaff (2006) argued that operational intensity estimates outside the Atlantic could not support trend analysis at all. Gray said the same, less diplomatically.

Emanuel's reply conceded both technical points — "I neglected to drop the end-points"; "I accept his revision to my analysis" — while maintaining the conclusion, and by 2007 had rebuilt the argument on potential intensity rather than SST: a quiet retreat from the boldest 2005 framing. The more consequential response was institutional: the homogenization program the critics' argument demanded was actually built, by Kossin, Knapp, Olander and Velden — mainstream scientists, not skeptics — and its first product (Kossin et al. 2007) found exactly what Landsea, Harper, Hoarau and Knaff had predicted: outside the North Atlantic, the best-track trends largely evaporated in homogeneous data. Kossin et al. (2013) repeated the verdict at higher resolution. Then the atmosphere weighed in: global accumulated energy collapsed to multi-decade lows by 2010 (Maue 2011 — the minimum year of the smoothed global series in Section 3), the western Pacific kept falling, and Webster's Category 4–5 count stopped rising the year after his paper. Klotzbach & Landsea (2015) made the accounting explicit; Kossin et al. (2020) — a model of careful framing next to 2005 — salvaged what was real as a modest exceedance trend with honest error bars.

Read as a whole, the record is one of a field correcting itself — unevenly, but genuinely, and from both directions. The technical objections of 2005–2006 were largely incorporated: Emanuel accepted the end-point and correction revisions within months and rebuilt his argument on sounder footing in 2007; the homogenization program that the critics' argument demanded was built by the original community, and it is what converted "doubling of the most dangerous storms" into a defensible "+5% per decade in the major share, CI [0.4, 11]" — a number this paper independently reproduces. Equally, the core physical intuition of the 2005 papers — that a warming ocean should leave a fingerprint on the intensity distribution — is what the corrected, extended, homogeneous record now supports, at a fraction of the originally headlined amplitude. The early cautions were, on the specific checkable points, well taken; the early physical instinct was, at reduced scale, also right. Both halves of the 2005 exchange contributed pieces of what now stands, and the milepost table above is best read as that joint construction — not as a scoreboard of winners.

15 · Implications

What follows, for science, risk and the public argument

16 · Conclusions

What sixty-six years and two instruments support

Method & caveats

Definitions, choices, and what could be wrong

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