Global Extreme Weather and Climate Change Dashboard

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Detection & Attribution: IPCC AR6 vs. This Site

IPCC AR6 (2021) stands as the most current, most rigorously reviewed formal climate assessment with a dedicated extreme-events chapter (WG1 Chapter 11) -- see the Methodology page for the underlying IPCC detection/attribution definitions behind this whole site. Unlike the sibling US dashboard's version of this page (which compares against AR6's US-regional Chapter 12 findings), this table compares against AR6's global-scope SPM and Chapter 11 findings, matching the dashboard's global scope. Each row's "GWX finding" column computes live from the exact same data as that hazard's phenomena page, so this page can never silently drift out of sync with those pages.

Detection rather than attribution. This page (and every page on this site) assesses whether a change has occurred rather than why -- attribution (evaluating specific causal factors, e.g. how much of a change traces to human-caused warming) requires model-based analysis this project hasn't undertaken. See the Methodology page for the IPCC's definitions of the two terms.

Detection and Time of Emergence →

What the IPCC means by detection, by emergence and by time of emergence, where the two come apart when read backwards, AR6 Chapter 12's Table 12.12 reproduced in full, and the drought case where this site and AR6 reach different conclusions.

Read backwards, detection and time of emergence separate in four places.AR6 puts emergence at the date a signal first exceeds a natural-variability reference, so a date in the past means the signal exceeds that reference today. Detection and emergence share that much, and four differences in AR6's definitions separate them. AR6 defines a time of emergence around "a specific anthropogenic signal" and defines detection "without providing a reason for that change", so a past time of emergence names human influence where a verdict on this page names none. The two apply different statistics: a likelihood test against a signal-to-noise ratio. AR6 Chapter 12 measures from a pre-industrial baseline no instrument recorded, and the verdicts here rest on the observational record. Detection returns a verdict over a window; emergence returns a date. The answers also disagree in both directions: a long, quiet record can clear the significance bar on a change smaller than the year-to-year variation, and a shift measured from a pre-industrial baseline can have emerged while the trend inside the observed window misses that bar. The full treatment sits on the Detection and Time of Emergence page.

What's New Since AR6

AR6 (2021) stands as the most current formal assessment, but the record and literature have moved since its cutoff. The list below presents evidence -- published post-2021, or computed directly on this site -- that complicates or narrows specific AR6 detection findings. It does not add up to a comprehensive new assessment:

  • Tropical cyclones, proportion of Category 3-5 storms (AR6 SPM A.3.4). Kossin et al.'s late-2020 correction -- published before AR6's citation deadline -- narrowed the statistically significant result from global to just 2 ocean basins (under 20% of global TC activity), a revision AR6's "likely... increased" language does not appear to reflect. Independently, the NATL+WPAC robustness check below finds the %-major-hurricanes finding holds over 1980-2025 but does not survive extension to the full 1945-2025 record for those two basins -- see the Tropical Cyclones page and this page's tropical-cyclone row.
  • Wildfire, "fire weather" vs. realized fire. Jones et al. 2022 (a 500+-study post-AR6 synthesis) and the GWIS burned-area series tracked here both confirm global burned area has declined even as fire weather conditions become more favorable in some regions -- AR6's fire-weather finding and the burned-area decline don't contradict each other, but public discussion often conflates the two. See the Wildfire page.
  • Heat extremes, pace of the hottest days vs. the seasonal average. McKinnon, Simpson & Williams (2024, PNAS), using 90 years of station data, found the hottest summer days have warmed at essentially the same rate as the seasonal median -- the widening of the warm tail traces to the cold tail warming more slowly rather than to any acceleration in the hot tail. This nuances AR6's frequency/intensity finding for heat extremes without contradicting it.

Read the "Consistency" column as a qualitative judgment call rather than a formal statistical test: AR6's findings synthesize many studies and multiple lines of evidence globally, while the GWX findings in the table below come from single-site, live-computed metrics built on specific data sources. Where this site tracks several alternative metrics for one hazard, the table below shows every metric's verdict, including the ones that disagree with AR6.

HazardIPCC AR6 finding (global)GWX findingConsistency
Heat Waves

"It is virtually certain that hot extremes (including heatwaves) have become more frequent and more intense across most land regions since the 1950s."

AR6 WG1 SPM A.3.1

  • Heat wave index (GSN stations): computing…
  • Heat wave magnitude (HWMId-style, GSN stations): computing…
  • TXx (annual max daily high temperature): computing…
  • WSDI (warm spell duration index): computing…
  • TN90p (warm nights): computing…
Consistent

The bespoke heat wave index and all three standard ETCCDI/CLIMDEX metrics (TXx, WSDI, TN90p) -- built from an entirely independent station network (GHCN-Daily's global GSN rather than any US-specific dataset) -- all show a detected increase over their reliable windows (1949-present). A clean, direct match across four independently-constructed metrics on an independent global station network, not one headline number on its own.

Cold Extremes

"...cold extremes (including cold waves) have become less frequent and less severe [across most land regions since the 1950s], with high confidence that human-induced climate change is the main driver of these changes."

AR6 WG1 SPM A.3.1

  • TNn (annual minimum daily low temperature): computing…
  • CSDI (cold spell duration index): computing…
  • TN10p (cold nights): computing…
  • Frost days (TMIN < 0°C): computing…
Consistent

2 of 4 cold-side ETCCDI/CLIMDEX metrics (CSDI and TN10p) show a detected decrease over their reliable window (1949-present) -- directly matching AR6's "less frequent and less severe" finding, and both by wide margins (CSDI p=<0.001, TN10p p=<0.001). The other two move the same way without clearing their bars: Frost Days at Mann-Kendall p=0.053 and TNn, the annual coldest night, at p=0.103. Both exceed this site's magnitude-vs-variability check; they miss only the significance bar, TNn against the flat 10% standard and Frost Days against its tighter false-discovery-adjusted bar of 0.049. All four point the direction AR6 states; not all of them clear the bar to say so.

Tropical Cyclones

"It is likely that the global proportion of Category 3-5 tropical cyclone instances has increased over the past four decades."

AR6 WG1 SPM A.3.4

  • Global ACE (all basins): computing…
  • Storm count by peak intensity category: computing…
  • Mean lifetime ACE per named storm: computing…
  • % of hurricanes that are Cat 3+: computing…
  • % of storms undergoing rapid intensification: computing…
  • Landfalls at hurricane strength or above: computing…
Partially consistent

This finding traces to Kossin et al. (2020). Roger Pielke Jr.'s documented critique of how it reached AR6 raises three objections. First, the citation chain drifts semantically: operational storm "fixes" (individual satellite observations) become Kossin's "exceedances," then Ch.11's "instances," then the SPM's "occurrences" -- obscuring that the study measured observation density rather than distinct-storm frequency. Second, Kossin et al.'s late-2020 correction, filed before AR6's citation deadline, narrowed the significant result from global to 2 ocean basins (under 20% of global TC activity), a narrowing that stops at the paper, never reaching AR6's SPM text. Third, the paper itself states its results "do not constitute a traditional formal detection" and cannot precisely quantify anthropogenic contribution -- and the SPM's "likely... increased" framing keeps neither caveat. An independent check here lands in the same place: the share of hurricanes reaching major intensity shows a detected change over 1980-2025 globally (p=0.03) and barely replicates in the NATL+WPAC-only subset over that window (p=0.053), but fails to survive the full 1945-2025 NATL+WPAC record (p=0.66); the Category-4-specific increase detected globally never replicates in that 2-basin subset at any window length. Global landfalls, added here in September 2026, sit alongside that result and behave the same way. Cat 1+ landfalls show no detected change over 1980-2025 (p=0.202) while Cat 3+, Cat 4+ and Cat 5 landfalls each show one (p=0.036, 0.043, 0.021) -- and all four fall to no-detected-change once the window starts in 1990 instead, as does the NATL+WPAC landfall record over its full 1945-2025 span at every intensity. Over that same 1980-2025 window the share of hurricanes that reach land at all climbs +3.30 percentage points per decade (p=0.015), which fits improving best-track position accuracy rather than storms finding land more often. Ryan Maue's independent compilation at climatlas.com reproduces each of these results from a separate source chain and a different landfall convention -- r=0.93 on major landfalls, the same verdict at both window starts -- which confirms the processing rather than the underlying record. The signal holds only in the specific recent decades the literature examined, not across the basin-general, long-record result "likely increased" implies -- the fragility at the centre of that critique. Full robustness check: Tropical Cyclones.

Drought

"Human-induced climate change has contributed to increases in agricultural and ecological droughts in some regions due to increased land evapotranspiration (medium confidence)."

AR6 WG1 SPM A.3.2

  • % of land in D2+ (severe or worse) meteorological drought: computing…
  • % of land in D2+ (severe or worse) soil-moisture deficit: computing…
  • % of pour-point cells in D2+ (severe or worse) low flow: computing…
Consistent

AR6's quote names AGRICULTURAL drought and evapotranspiration as the mechanism, and this site tracks three drought types against it. All three now show a detected global increase: the AED-inclusive SPEI-style series at every severity level (D0-D4), the soil-moisture index (p=0.013), and the river low-flow index. **This row changed on 15 September 2026, when an audit corrected the grid-cell weighting behind all three.** Until then the aggregation counted 5-degree cells equally, which gave Antarctica 3.08 times its share of the land area and gave Africa, Asia, South America and Oceania between 0.55 and 0.66 of theirs -- discounting the continents that hold the signal. Area weighting raised the precipitation-only global series from no detected change into a detected increase, and the soil-moisture series with it. The earlier reading here rested on the precipitation-only series staying flat while the AED-inclusive one rose, and that contrast no longer holds: both detect. The SIZE of the gap survives, and still points at evaporative demand -- comparing 1980-2002 with 2003-2025 the AED-inclusive series rises about twice as far as the precipitation-only series. AR6's qualifier "in some regions" holds up per continent rather than globally: meteorological drought detects in Africa and South America, soil moisture in Asia, North America and South America, river low flow in Africa and South America, and South America detects on all three at once. Africa detects on the meteorological and hydrological measures, and its soil-moisture p of 0.066 clears the flat 10% bar while missing its false-discovery-adjusted bar of 0.051 -- close, and reported precisely instead of rounded into agreement.

Wildfire

"Fire weather conditions (compound hot, dry and windy events) have become more probable in some regions (medium confidence)."

AR6 WG1 Ch.11 Executive Summary

  • Global dry matter combusted: computing…
  • Global burned area: computing…
Not directly comparable

This page tracks two quantities distinct from AR6's subject here, and under the 30-year minimum record-length standard, neither currently renders a detection verdict: GFED5's dry-matter-combusted record starts 2001 (the record drops its pre-MODIS 1997-2000 years as lower-quality, see the Wildfire page), only 23-24 years so far; GWIS's burned-area record starts 2002, only 22-23 years. Both clear the 30-year bar in the early 2030s. Earlier, shorter-window checks found GFED5's total showing no detected change while GWIS's global burned area showed a detected decline (matching Andela et al. 2017's documented decline in global burned area) -- valid results at the time, retired here under a stricter standard and not left on display over a record too short to trust. Neither quantity matches "fire weather conditions" (AR6's subject here, an atmospheric-favorability measure): both measure realized combustion and burned area, which also depend on fuel availability, land management, and suppression, beyond whether conditions favored fire.

Extratropical Cyclones / Winter Storms

"There is low confidence in past changes of maximum wind speeds and other measures of dynamical intensity of extratropical cyclones." Separately: "Mid-latitude storm tracks have likely shifted poleward in both hemispheres since the 1980s, with marked seasonality in trends (medium confidence)."

AR6 WG1 Ch.11 Executive Summary

  • Most extreme storm's minimum pressure (annual): computing…
Consistent

The annual most-intense-storm minimum pressure shows no detected change (p=0.49) -- matching AR6's low-confidence characterization of intensity trends specifically. This page doesn't track storm-track position, so it can't test the poleward-shift finding either way.

Flooding

"Significant trends in peak streamflow have been observed in some regions over the past decades (high confidence)... Regional changes in river floods are more uncertain than changes in pluvial floods because complex hydrological processes and forcings, including land cover change and human water management, are involved."

AR6 WG1 Ch.11 Executive Summary

  • Global % of pour-point cells in high flow: computing…
Consistent

AR6 declines to state a clean global river-flood direction, citing regional inconsistency -- the GloFAS-based high-flow-cell index shows the same pattern: no detected change globally (the raw Mann-Kendall p=0.070 clears IPCC's flat 10% example threshold, but not the multiple-comparisons-adjusted bar for testing 57 variables at once -- see the Methodology page), which itself masks regional divergence underneath -- Africa and South America both show a detected decrease, while Asia, Europe, North America, and Oceania show no detected change at all. AR6's hedged wording anticipates this patchy, regionally inconsistent picture rather than a uniform trend.

Severe Convective Storms

"There is low confidence in past trends in characteristics of severe convective storms, such as hail and severe winds, beyond an increase in precipitation rates."

AR6 WG1 Ch.11 Executive Summary

  • US significant tornado count (F/EF2+): computing…
  • Mean global CAPE: computing…
  • Days with widespread or extreme instability: computing…
Not directly comparable

US tornado counts (the one direct severe-convective-storm dataset available -- no unified global tornado database exists) split by severity: the all-tornado total's reliable window (1997-present) remains under the 30-year minimum and renders no detection verdict until 2027. Significant tornadoes (F/EF2+), far less exposed to the NEXRAD-era weak-tornado detection artifact that sets the total's window, support a longer, separately reliable window back to 1980 (added 2026-08-19) and show no detected change over that 46-year record -- a real finding, not an insufficient-data non-result. Global CAPE, this page's proxy for atmospheric instability favorable to severe convection, spans a longer, 1979-based record and DOES clear detection on all three of its series -- but not uniformly in one direction: mean CAPE shows a detected DECREASE, while high-CAPE-day counts show a detected INCREASE and widespread-instability-day counts a detected decrease. CAPE measures instability potential rather than realized storm occurrence, and AR6's statement concerns storm characteristics (hail, wind) specifically rather than the broader thermodynamic environment -- a mixed-direction, detected change in the ingredient doesn't mechanically imply any particular change in the outcome, so this isn't read as contradicting or confirming AR6's low-confidence framing, just measuring something related but distinct.