Guide updated 20 September 2026

Climate Hazard Engine / Data and methodology / v1

A place becomes
a hazard reading.

Follow the geometry, the source and the calculation. See what each reading can say—and where its evidence stops.

Sources, scenarios and years

Place

London, UK. A qualified name identifies the place.

Geometry

London’s urban footprint, from GHS-UCDB.

Source & sampling

The same boundary meets a source grid. Shown schematically.

Value + unitGeometry + resolutionSource + scenario + periodCaveat + provenance

Reading

The result retains its geometry, source and limitations.

Ambiguous place? Candidates for review. No hazard readings until resolved.

Real UK and London outlines, simplified for display. The grid is illustrative; no hazard values are plotted. London’s urban footprint differs from its administrative boundary. Boundary sources.

Physical hazard only. No asset value, vulnerability, loss estimate or composite risk score.

01 / Precision

The source sets the limit.

A precise location does not make a coarse climate grid more precise. Compare what the same point can resolve in two sources.

Compare source resolution

Point retained · EA declares 5 m positional resolution.

Real London outline and coordinate. EA flood extents are not plotted. Heat mode shows the native 0.25° grid; the highlighted cell indicates spatial support, not temperature. Map sources.

P0effective tier

EA flood zones declare 5 m positional resolution. This London coordinate retains effective tier P0; the map does not assert a flood-zone result.

Point query · fine-scale source geometry

Why precision depends on the source

The same address can be compared with fine flood-zone outlines and a coarse climate grid. A precise query cannot make its source more detailed. The result reports the scale the data can support.

The maps use the same London location. EA flood zones are vector outlines; no flood extent is plotted here. The climate grid uses native 0.25° cells, whose east–west spacing varies with latitude.

P0 · Point

Central London

Coordinate · 51.50853° N, 0.12574° W

A local value or flag

P1 · City

London

Urban footprint · GHS-UCDB

A spatial distribution

P2 · Region

England

Administrative boundary · ONS

A spatial distribution

P3 · Country

United Kingdom

National boundary · Natural Earth

An inventory of hazards

Each outline is fitted independently, not drawn at a shared scale. England is a P2 boundary within the UK; the P3 UK query returns a hazard inventory, never a national hazard number. Boundary sources.

How we identify a place

A coordinate, postcode or qualified place name establishes the query location. Where a name is ambiguous, such as “Newcastle”, the choice must be resolved before a hazard reading is attached. A similar-looking name is not silently substituted.

Place names and boundaries come from GeoNames, GHS-UCDB, Natural Earth and ONS. Urban footprints and administrative boundaries answer different questions; the geometry used is stated with the result. Map sources and licences.

Source details: EA flood zones · Warming delta

02 / Hazard methods

Read the mechanism before the number.

Six hazard families. Each keeps its own unit, spatial basis and limitations.

01 / Flood

Area is not depth.

How much of the boundary is wet, and how deep is the water within its wet cells?

Modelled inundationUrban footprint

London · GHS urban footprint, not an administrative boundary. Native ~90 m flood cells; blue shows extent, not depth.

A Native cell detail

20 columns × 14 rows
84 wet cells / 280 shown

Counted as wetOther boundary cells

Actual ~90 m source cells, enlarged. The totals on this page use the whole London boundary.

How much is wet?

12.69%

44,140 wet cells out of
347,789 boundary cells

Share across the whole boundary

How deep is it?

Median1.76 m

90th percentile4.25 m

Wet cells only. Dry cells are excluded from these depth statistics.

Actual model output, not an observed flood. JRC CEMS-GLOFAS present-day, undefended river flooding over London’s GHS-UCDB urban footprint. Source read 20 September 2026. The Thames Barrier’s protection is not represented. Data and calculation.

Reading limit Undefended river flooding only. Wet area is not a share of collateral, or a building’s flood depth.

Source details: JRC flood · JRC return periods

How to interpret this reading

Flooded-area share describes the boundary; depth statistics describe its wet cells only. The JRC source uses approximately 90 m cells and supplies seven return periods, with 100 years as the headline.

The source represents undefended river flooding. It excludes coastal surge and surface-water flooding. A flooded land share is not a share of collateral, and a grid-cell depth is not a depth at a building.

London example: source and calculation

The JRC 100-year river-flood model is sampled over London’s GHS-UCDB urban footprint. It identifies 44,140 wet cells out of 347,789 boundary cells, or approximately 12.69%. This is a cell-count fraction, not a calculation weighted by each cell’s ground area.

Depth statistics use the wet cells only: median 1.758 m and 90th percentile 4.251 m. The magnified detail shows 280 source cells, including 84 counted as wet.

This present-day model excludes flood defences, coastal surge and surface-water flooding. The source pixels determine the flood pattern; the outline is simplified for display. JRC source and CC BY 4.0 licence · London boundary source.

Measured example: Udaipur’s non-monotonic pair

Udaipur · two measured points

200-year return period19.74%

500-year return period4.06%

A smaller share at a rarer period. JRC publishes separate model outputs. The engine reports and flags this pair; it does not smooth or reorder it.

Measured JRC model outputs, 17 September 2026. Bars share a 0–25% scale. Only these two Udaipur points are shown; they are not a complete curve.

02 / Heat

Three quantities. Different meanings.

How do average warming, hot days and humid heat differ?

Warming delta

How much does the average change?

ΔT · kelvin

Projection mean − baseline mean.

Five models · ensemble median + spread

Dry-bulb exceedance

How often is the air hotter than 35 °C?

Days / year

Count only days strictly above 35 °C.

Five models · baseline, projection + change

Wet-bulb exceedance

How often does humid heat exceed 31 °C?

Days / year

Count only days strictly above 31 °C wet bulb.

Four models · MIROC6 lacks humidity

Illustrative sequences, not place-specific or annual readings. A day exactly at either threshold is excluded.

Reading limit Wet bulb uses daily-mean humidity at maximum temperature and can understate the true daily wet-bulb maximum.

Source details: Warming delta · Threshold days · Wet-bulb days

How to interpret this reading

The example uses NEX-GDDP-CMIP6, SSP2-4.5, 2050–2060 against 1991–2010. Warming is a change in mean daily maximum temperature; threshold measures count days strictly above the stated value.

Dry-bulb results use five models. Wet-bulb results combine temperature, humidity and estimated pressure; only four models supply humidity. Wet bulb is approximated near the daily temperature maximum and can understate the true daily wet-bulb maximum.

The headline thresholds are 35 °C dry bulb and 31 °C wet bulb. The approximately 25 km climate grid smooths variation within cities.

Ensemble selection and acquired members

Default ensemble filter

TCR 1.4–2.2 K

AR6 likely range

Five acquired members

GFDL-ESM4
MIROC6 no humidity file
MPI-ESM1-2-HR
MRI-ESM2-0
NorESM2-LM

Five for dry bulb; four for wet bulb. The member spread is not a probability distribution.

The default ensemble screens transient climate response (TCR) to the AR6 likely range of 1.4–2.2 K, following Hausfather et al. (2022), as documented in the reference. This addresses the CMIP6 hot-model problem.

The acquired subset contains five named members. A full-ensemble mode and a single-model mode are available and must be named when used.

The five-member median and spread are not a probability distribution. Eligibility under the screening rule does not mean every eligible model is in this acquired subset.

03 / Tropical cyclone

One storm, one closest pass.

Which nearby observations count as one storm pass?

Recorded trackRetained positionSearch boundary

Retained observation · 11 Nov 2020, 18:00 UTC · 64.9 km

01 / Follow the observations

A track is a sequence of records.

Follow the recorded positions westward towards Manila.

Markers are recorded observations; no positions are interpolated.

02 / Apply the search radius

Keep the records within 100 km.

Two records lie within 100 km: 64.9 km and 77.9 km away.

Both observations belong to Vamco, the same storm.

03 / Retain the closest pass

Two records. One storm.

2
track positions

1
storm pass

Two positions belong to Vamco. Count the storm once, at its closest recorded approach.

Closest approach: 64.9 km
Retained timestamp: 11 Nov 2020 · 18:00 UTC
Wind at retained position: 70 knots · WMO

Wind at the storm’s position, not the wind experienced in Manila.

FrequencyCount distinct qualifying storms across the complete declared record, then express passes per decade.

IntensityReport the strongest retained pass separately. A nearby track does not establish landfall or damage.

Real IBTrACS track, GeoNames Manila point and Natural Earth coastline. This is one storm’s worked example, not the city’s full storm history. Only recorded main-track positions are tested; connecting lines do not add observations.

Reading limit Track proximity does not establish landfall, local wind or a damage footprint. Extratropical passes are counted separately.

Source details: IBTrACS

How to interpret this reading

Observed IBTrACS tracks since 1980 are counted once per storm at their closest approach within the stated radius, normally 100 km. Frequency and strongest-pass intensity remain separate.

Track proximity is not landfall, local wind speed or a damage footprint. Wind averaging periods depend on the reporting source. Storms that are extratropical at closest approach are counted separately; a zero count in a successfully read record differs from missing data.

About this storm example

The query is Manila (14.6042° N, 120.9822° E). The observations describe Vamco in November 2020; the closest retained position is 15.1° N, 121.3° E. The diagram uses recorded track positions, not an interpolated local wind footprint. NOAA IBTrACS source.

04 / Wildfire

Detections become a density.

How do vegetation-fire detections become a density per area and day?

Type 0 · presumed vegetation fireTypes 1–3 · other thermal detections

3,979 detections shown; repeated locations may overlap.

01 / Keep vegetation-fire detections

3,979
all detections

2,017
type 0 retained

02 / Account for area and time

2,017 retained detections130,541.3 km² × 365 days

× 1,000

0.0423

detections per 1,000 km² per day

The density always uses type 0, whichever map view is selected.

Actual locations and counts from the archived FIRMS files, clipped to the ONS England boundary. 1,962 detections of other types are excluded from density. Detections are not distinct fires, burned area or a future probability. Cloud and overpass limits still apply.

Reading limit Detections are not distinct fires or burned area. The 2025 observation window is not a climatology.

Source details: FIRMS

How to interpret this reading

NASA FIRMS VIIRS records thermal anomalies at approximately 375 m resolution. The worked example covers the full 2025 calendar year without counting overlapping records twice.

Only presumed vegetation-fire detections contribute to the density per 1,000 km² per day; other thermal detections are counted separately. Detections are not distinct fires or burned area.

Cloud cover and satellite overpass timing affect detection. No detections does not establish no fire. Comparisons require the same observation window and season; this is not a future probability.

Monthly counts, observation window and source checks

When were detections recorded?

The example covers 1 January–31 December 2025, excluding overlapping records. Counts describe satellite detections, not unique fires; the chart separates presumed vegetation-fire detections from other thermal sources.

England · 2025 · counts of detections
Month	Type 0	Other types	All
Jan	13	111	124
Feb	21	65	86
Mar	263	176	439
Apr	260	206	466
May	229	246	475
Jun	113	224	337
Jul	191	190	381
Aug	670	199	869
Sep	109	265	374
Oct	38	118	156
Nov	102	114	216
Dec	8	48	56

Other thermal detections: type 1, 0; type 2, 1,893; type 3, 69. FIRMS source details · Boundary source.

05 / Drought

Anomaly is relative to a place.

How does this place’s water balance compare with its own history?

Scroll the chart sideways to see the full record →

Below local normalAbove local normalDecades compared

December 2022 · SPEI-12: -0.288

Last decade − first decade

+0.348 SPEI

A shift towards wetter conditions in this cell.

1981–1990 mean: -0.012
2013–2022 mean: +0.335

London query → nearest cell
51.50°N, 0.15°W · 1.93 km away

Zero is local normal.Two places at SPEI 0 can have very different climates. This series does not measure absolute aridity or water stress.

Missing months stay missing.11 initial months have no SPEI-12 value. The means use 109 available months in the first decade and 120 in the last.

Real monthly data from the nearest cell to the page’s central London coordinate; not an average over the London boundary. Dark mean lines compare the first and last ten calendar years. The 1981–2022 standardisation period already contains warming.

Reading limit This is not absolute aridity or water stress. The 1981–2022 baseline already includes warming.

Source details: SPEI

How to interpret this reading

Hydro-JULES SPEI combines precipitation and potential evapotranspiration on 5 km cells, monthly over 1981–2022. Three-month and twelve-month timescales describe different durations of water-balance conditions.

The index compares a cell with its own history. The headline change compares the last decade’s mean with the first decade’s mean. A desert at zero remains a desert: anomaly is not aridity or water stress.

The reference period already includes warming, so it does not represent a pre-industrial baseline. Country-level aggregation can conceal local anomalies.

The seven source-literature categories

Seven source-literature categories, without severity colours
Extremely dry	≤ −2.0
Severely dry	−2.0 to −1.5
Moderately dry	−1.5 to −1.0
Near normal	−1.0 to 1.0
Moderately wet	1.0 to 1.5
Severely wet	1.5 to 2.0
Extremely wet	≥ 2.0

McKee et al. (1993), carried into SPEI by Vicente-Serrano et al. (2010). SPEI ≤ −2 is about the 2.3rd percentile of the standard normal.

How the drought point is sampled

The example uses the nearest source-grid cell when the query contains no grid-cell centre. The location and spatial resolution belong to the result; they do not describe a site-specific measurement. Hydro-JULES source and licence.

06 / Sea level

Two workflows, two distributions.

How do two sea-level workflows compare at the same coast, scenario and year?

Scroll sideways to compare the full ranges →

Median17th–83rd percentiles5th–95th percentiles

The medians and ranges are close in this example. Low confidence adds processes; it does not prescribe a fixed extra rise.

One coast. Two readings.

Both workflows select AR6 location 286, a tide-gauge location 11.19 km from Hull’s urban boundary.

Distance is measured from the boundary, not its centroid.

Medium confidenceIncludes processes assessed at medium confidence or better.Archive through 2150.

Low confidenceAdds ice-sheet expert judgement and marine ice-cliff instability.Archive through 2300 · no SSP3-7.0 file.

Actual archived AR6 quantiles for the same Hull geometry, scenario and year. Each workflow has its own distribution; low confidence is not an error bar around medium confidence. These are changes in mean relative sea level, not inundation depths.

Reading limit Mean sea level is not storm surge or inundation extent. Coastal eligibility is checked before choosing a nearby location.

Source details: AR6 medium · AR6 low

How to interpret this reading

IPCC AR6 projects relative mean sea-level change against 1995–2014, including vertical land motion. Each result names its scenario, year and eligible coastal location, with its median and uncertainty range.

Medium- and low-confidence workflows return separate distributions. The low-confidence workflow includes additional ice-sheet processes. A missing scenario is not replaced silently; a landlocked location has no coastal reading.

Mean sea-level change is not storm surge, extreme water level or inundation extent. These are scenario projections, not forecasts.

Exact quantiles and source selection

Hull · SSP2-4.5 · 2100 · metres relative to 1995–2014
Workflow	5th	17th	Median	83rd	95th
Medium	0.270	0.384	0.586	0.844	1.055
Low	0.224	0.364	0.573	0.844	1.063

06 continued / Extreme water level

The same height, more often.

How often would today’s 100-year water level recur after mean sea level rises?

Scroll the chart sideways to see the full curve →

Present-day central curveCurve + selected risePresent-day 5th–95th fit bounds

The same water level, reached more frequently under the selected rise.

01 / Fix the reference height

Keep today’s 100-year water level.

Fix the reference at 5.735 m above the GTSM baseline.

The pale band describes uncertainty in the present-day curve fit.

02 / Add the selected sea-level rise

The mean rises. The reference stays.

The dashed curve uses the selected AR6 quantile. Storm climate is held fixed.

03 / Read the intersection

Trace the same height to a new frequency.

100 → 16.2 years

Return period of the same water level

6.2× as often

At the median rise of 0.586 m

Read the intersection on the return-period axis. Frequency comparison only; no loss estimate.

The source location matters

GTSM station 39352 is 10.8 km from Hull’s urban boundary and 17.7 km from its centroid. AR6 location 286 is 11.19 km from the boundary. These coastal levels do not model flood defences.

GTSM stationAR6 location

Real GTSM and AR6 inputs; a conditional calculation, not a forecast. The 1985–2014 GTSM baseline differs from AR6’s 1995–2014 baseline; that offset is unremoved. Storm climate is held fixed, and ERA5 under-resolves tropical cyclones. The pale fit band and the AR6 quantiles describe different uncertainties.

Reading limit Storm climate is held fixed. GTSM under-resolves tropical cyclones, and its 1985–2014 baseline differs from AR6’s 1995–2014 baseline; the offset is unremoved.

Source details: GTSM · Amplification

How to interpret this reading

Projected mean sea-level rise shifts the present-day water-level curve. The same height can then recur more often. Results are evaluated across the sea-level quantiles, holding the storm climate fixed.

No result is extrapolated beyond the published 1–100-year curve. GTSM under-resolves tropical cyclones, and its 1985–2014 baseline differs from AR6’s 1995–2014 baseline; that offset is not removed.

Coastal-station location matters. The London example uses a station seaward of the Thames Barrier, so its open-coast water levels do not represent the Barrier’s protection. Input uncertainty remains part of the result.

Published curve, quantile results and calculation limits

Subtract each AR6 rise from the 5.735 m present-day 100-year level, then interpolate linearly in log(return period) on the published central curve. No extrapolation beyond 1–100 years: if the shifted level falls below the 1-year endpoint, report a frequency bound of at least 100×, not an exact recurrence. The selected Hull quantiles remain within that range.

GTSM station 39352 · metres above its 1985–2014 mean sea level
Return period · yr	Central level · m	5th–95th fit bounds · m
1	4.257	4.139–4.331
2	4.479	4.284–4.599
5	4.772	4.444–4.970
10	4.995	4.553–5.282
25	5.289	4.675–5.675
50	5.512	4.753–6.006
75	5.643	4.798–6.221
100	5.735	4.826–6.372

All archived AR6 quantiles applied to the central GTSM curve; not a combined uncertainty interval
Rise quantile	Rise · m	Recurrence · yr	Frequency factor
5th	0.270	43.20	2.3×
17th	0.384	30.31	3.3×
50th	0.586	16.16	6.2×
83rd	0.844	7.24	13.8×
95th	1.055	3.75	26.7×

08 / Subsoil clay

Read the soil. Keep the gaps.

How much clay is predicted at 60–100 cm—and how much of the place has a prediction?

01 / Choose the depth

A defined soil interval.

A fixed depth below the surface. Foundation depth is not measured.

02 / Check the coverage

Most cells are unpredicted.

418 predicted1,446 unpredicted

One square = one counted cell.
Sorted by status; not a geographic map.

03 / Keep both facts

A reading, with limited coverage.

35.3%

Median predicted clay
60–100 cm · predicted cells only

90th percentile 40.5%

22.4% of boundary cells predicted

Map colour withheld

The median is published.
The city stays unshaded.

Unpredicted does not mean zero clay. Built-up land and other masked surfaces have no prediction. The 50% rule governs map shading, not susceptibility.

London urban footprint · GHS-UCDB 1912. Counts and percentiles are measured from the source; the depth section is schematic. Clay content is a susceptibility proxy, not a subsidence hazard. Mineralogy, plasticity, foundations, trees and the drying cycle are not measured here. SoilGrids source details · Boundary source.

Compare five measured places · coverage and clay content

Measured over the gazetteer’s own boundaries, headline interval 60–100 cm
Place	Cells predicted / in boundary	Share predicted	Median clay	90th percentile	Map colour
London · ghs_ucdb:1912	418 / 1,864	22.4 %	35.3 %	40.5 %	withheld — under half predicted
Bristol · ghs_ucdb:1771	40 / 163	24.5 %	29.2 %	32.6 %	withheld
Manchester · ghs_ucdb:1780	232 / 671	34.6 %	20.8 %	23.7 %	withheld
Houston · ghs_ucdb:315	559 / 3,399	16.4 %	36.0 %	49.1 %	withheld
United Kingdom · adm0:GB	222,938 / 243,344	91.6 %	21.8 %	33.4 %	shaded

How to interpret this reading

SoilGrids predicts clay content at 60–100 cm and 100–200 cm. Statistics describe the cells with predictions; masked cells remain in the coverage denominator and are never treated as zero clay.

A place is shaded only when at least half of its cells have predictions. This is a coverage rule, not a susceptibility threshold. London’s median is published while its map remains unshaded.

Clay content alone does not establish subsidence risk. The reading does not measure foundations, tree influence, soil plasticity or conditions beneath buildings. Clay and soil-moisture evidence remain separate.

Coverage and missing predictions

Built-up land, water and other masked areas have no clay prediction. A nearby predicted cell may be used for an otherwise unsampled location, with the distance stated; an area with no usable predictions has no result. SoilGrids source and licence.

09 / Soil-moisture deficit

Its own fifth percentile, not anyone else’s.

How far, and how often, did the deep soil water here fall below this ground’s own record?

Bristol’s nearest land point (6.7 km from the boundary): annual shortfall below its own 5th percentile, threshold 29.5
Year	Days below threshold	Magnitude (SWI·days)	Jul–Sep mean SWI_100
2010	243 of the record’s, most of them	460.5	25.7
2013	—	74.0	—
2018	0	0.0	33.2
2022	0	0.0	33.1
2025	—	47.5	—

Bristol: 32.7 SWI·days a year · mean over 18 usable years, 2007 excluded as too short

Reading limit Relative, like SPEI: the threshold is this point’s own, so the index says how unusual the shortfall was here, never how dry the ground is. A whole-record 5th percentile admits about 350 days, and 2010’s long deep event took most of them; 2018 and 2022 reached the threshold and stopped on it. The 2010 shortfall sits in July–November with the surface unfrozen and the quality flag at 100 %, so it is the record and not an artefact. Source details: Copernicus SWI.

How to interpret this reading

The Copernicus Soil Water Index represents soil-water conditions inferred from satellite surface observations. This example uses its deep-response indicator, SWI_100. Frozen or melting conditions are excluded rather than treated as dry.

Shortfall is measured below each location’s own fifth percentile and accumulated over the year. The reported average uses years with sufficient observations. Where a boundary contains no source point, a nearby point may be used and its distance is stated.

This is a relative historical measure, not absolute dryness, water stress, future probability or a ranking of places by dryness. It is presented alongside clay content without combining the two into a score.

Source and observation period

Copernicus Land Monitoring Service, Soil Water Index, deep-response indicator SWI_100. This example uses daily observations from 2 January 2007 to 31 December 2025, read on 20 September 2026. The selected land point is 6.7 km from Bristol’s boundary. Copernicus soil-moisture products.

03 / Joining evidence

Connect the place.
Keep the evidence.

The place links a disclosure to a hazard reading. What that reading means depends on the exposure.

One place · two exposure contexts

London P1 · urban footprint

Modelled inundation

GHS-UCDB boundary · Geometry source

Disclosure context

Illustrative exposure

Residential mortgages

London, UK

A portfolio distributed across a place.

Disclosure reference + any filed amount stay with the exposure.

Place match

“London, UK” resolves to its GHS urban footprint.

This is not Greater London’s administrative boundary. Unresolved names remain unresolved.

Hazard reading

River flood · 100-year model

12.69% of the boundary is wet

JRC · present-day · ~90 m cells

Undefended model. Thames Barrier protection is excluded.

Reading, source & calculation ↗

What this supports

Screen the portfolio’s geography.

The reading describes land within the named area. It does not say that 12.69% of the mortgages or their value are exposed; that needs asset locations.

Illustrative disclosure, real London hazard sample. No firm or amount is assumed. The hazard reading keeps its units, source and caveats; the join produces no loss estimate or composite score. How the link is made.

What stays separate

The company disclosure retains its amount, reporting scope and source reference. The hazard result retains its physical unit, geometry, scenario, period and limitations. Their shared place links the evidence without multiplying the values into a loss estimate.

Unresolved or missing locations remain gaps. An area statistic describes land within a boundary, not the distribution of a company’s assets.

Which hazards are asked for each exposure family

Readings are retrieved, never recomputed at this join. Unresolved places yield an unresolved row. Hazards outside a family’s stated question appear as “not asked” rows with reasons; the table below lists the hazards asked.

Seven exposure families · relevance mapping v1, 2026-09-03
Family / spatial semantics	Hazards asked
Residential mortgage · distributed	Flood, sea level, drought (subsidence proxy on clay), heat threshold days.
Commercial real estate · distributed	Flood, sea level, cyclone, heat threshold days, wildfire. Drought is not asked: commercial structures are typically piled.
Project and infrastructure · single site	All eight: flood, warming delta, heat threshold days, wet-bulb days, cyclone, wildfire, drought and sea level.
Trade finance · single site	Cyclone, flood, sea level.
Insurance concentration · distributed	Cyclone, flood, wildfire, wet-bulb days, drought.
Own office · single site	Flood, heat threshold days, cyclone, wildfire, sea level.
Own data centre · single site	Flood, heat threshold days, cyclone, wildfire, sea level and drought.

04 / Sources and verification

Every reading has a trail.

Eighteen registered layers and one derivation. Check coverage, scenario and period before interpreting a result.

ObservedA recorded historical window

Present-day modelA modelled climate or designation

ProjectedA named scenario and horizon

Data sources, scenarios and years

Follow the original data providers below. Each source has its own coverage, period and interpretation limits. Listed but unused products are explicitly identified.

Source coverage is not a guarantee that every resolved place has a reading. Unacquired layers remain listed with a reason.
Hazard	Data source	Country / coverage	Scenario	Period / scenario year
River floodModelled present-day	JRC / Copernicus EMS GloFAS (opens in a new tab)	Global except Greenland, Antarctica and basins under 500 km²	None — present-day model	present-day
Resolution, licence and interpretation Native resolution 90 m Return period 100 yr Defence state undefended Licence CC-BY-4.0 Present-day river flooding without flood defences. Excludes coastal surge, surface-water flooding, Greenland, Antarctica and river basins smaller than 500 km². Depth statistics describe inundated cells only; a 100-year return period corresponds to a 1% annual chance in the model.
River flood · curveModelled present-day	JRC / Copernicus EMS GloFAS (opens in a new tab)	Global except Greenland, Antarctica and basins under 500 km²	None — present-day model	present-day
Resolution, licence and interpretation Native resolution 90 m Return period 10 · 20 · 50 · 75 · 100 · 200 · 500 yr Defence state undefended Licence CC-BY-4.0 Seven separately modelled return periods, from 10 to 500 years. These outputs are not guaranteed to increase monotonically at every location; decreases are reported rather than smoothed away. The curve is not a financial loss distribution.
Flood zonesModelled present-day	Environment Agency (opens in a new tab)	England	None — present-day model	Present-day; snapshot 2026-06-09
Resolution, licence and interpretation Native resolution 5 m Return period Z3 ≥1% fluvial / ≥0.5% tidal; Z2 0.1–1% Defence state undefended Licence OGL-UK-3.0 Present-day rivers-and-sea flood-zone outlines for England, without the benefit of flood defences. Excludes surface-water flooding. A zone is an extent classification, not a water-depth estimate; 5 m is the declared positional resolution.
Flood · NINot acquired; unvalidated	Department for Infrastructure NI (opens in a new tab)Source overview · not acquired	Northern Ireland	None declared; layer not acquired	Not established; never fetched
Resolution, licence and interpretation Native resolution 5 m Licence unconfirmed — DfI terms not yet read (blocks live use) Listed for coverage context only. This Northern Ireland product has not been acquired or validated, and its licence has not been confirmed. It is not used in the examples.
Flood risk areasAdministrative designation	Environment Agency (opens in a new tab)Source overview · not acquired	England	None — administrative designation	Not applicable to a hazard statistic; never fetched
Resolution, licence and interpretation Native resolution 1,000 m Licence OGL-UK-3.0 An administrative designation of significant flood-risk areas, not a flood extent or depth model. It has not been acquired for the examples.
Heat · warming deltaProjected	NASA NEX-GDDP-CMIP6 (opens in a new tab)	Global land cells; small islands may lack data	SSP2-4.5	2050–2060 vs 1991–2010
Resolution, licence and interpretation Native resolution 25,000 m Licence public-domain (NASA NEX-GDDP-CMIP6) Change in mean daily maximum temperature, not the absolute temperature or a count of heatwaves. Five climate models are used. A coarse climate grid cannot resolve variation at a specific address.
Heat · days above thresholdProjected	NASA NEX-GDDP-CMIP6 (opens in a new tab)	Global land cells; small islands may lack data	SSP2-4.5	2050–2060 vs 1991–2010
Resolution, licence and interpretation Native resolution 25,000 m Licence public-domain (NASA NEX-GDDP-CMIP6) Days strictly above a dry-bulb temperature threshold; the headline is 35 °C. This is air temperature, not a humidity-adjusted physiological limit. The result uses five models and retains the baseline, projection and change.
Heat · wet-bulb daysProjected	NASA NEX-GDDP-CMIP6 (tasmax + huss) (opens in a new tab)	Global land cells; small islands may lack data	SSP2-4.5	2050–2060 vs 1991–2010
Resolution, licence and interpretation Native resolution 25,000 m Licence public-domain (NASA NEX-GDDP-CMIP6) Days strictly above an approximate wet-bulb threshold; the headline is 31 °C. Humidity is available for four of the five models. The approximation is evaluated near the daily temperature maximum and can understate the true daily wet-bulb maximum.
Heat · observed meanObserved	Met Office HadUK-Grid (opens in a new tab)	United Kingdom	None — observed record	1991–2020
Resolution, licence and interpretation Native resolution 1,000 m Licence Open Government Licence (CEDA registration required) Observed mean daily maximum temperature over 1991–2020. A climatological mean does not describe heatwave severity, duration or threshold exceedances.
Heat · UK projectionProjected	UKCP18 land-rcm 12 km (opens in a new tab)	United Kingdom	RCP8.5	1980–2080
Resolution, licence and interpretation Native resolution 12,000 m Licence UKCP18 terms (CEDA registration required) Annual mean temperature from one regional-model member under RCP8.5. It provides no ensemble spread and must not be read as a central ensemble estimate or a heat-extreme measure.
Tropical cycloneObserved	NOAA NCEI IBTrACS v04r01 (opens in a new tab)	Global, subject to source coverage	None — observed record	1980–present in source description; extract pinned 2026-08-27
Resolution, licence and interpretation Native resolution 100,000 m (declared proximity radius, not grid size) Licence public-domain (NOAA NCEI) Observed storm tracks since 1980. A nearby track is not landfall, local wind speed or a damage footprint. Wind averaging periods depend on the reporting source; storm frequency and strongest-pass intensity remain separate.
WildfireObserved	NASA FIRMS VIIRS SNPP (opens in a new tab)	Global, subject to source coverage	None — observed record	2025-01-01 to 2025-12-27
Resolution, licence and interpretation Native resolution 375 m Licence Public domain · NASA FIRMS Satellite thermal detections, not distinct fires, burned area or future wildfire probability. Only presumed vegetation-fire detections enter the density. Cloud cover and satellite overpass timing limit what can be observed.
DroughtObserved	UKCEH Hydro-JULES SPEI (opens in a new tab)	Global domain: 55°S–85°N	None — observed record	1981–2022 monthly · 3 and 12 months
Resolution, licence and interpretation Native resolution 5,000 m Licence OGL-UK-3.0 A standardised water-balance anomaly relative to each location’s own history. It is not absolute dryness or water stress. The historical baseline already includes warming; a zero anomaly does not mean a wet climate.
Sea level · mediumProjected	IPCC AR6 Sea Level Projections v20210809 (opens in a new tab)	Global coastal	SSP2-4.5 (default). Available: SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5	2100 default · 2020–2150 · vs 1995–2014
Resolution, licence and interpretation Native resolution 111,000 m Licence CC-BY-4.0 Relative mean sea-level change against 1995–2014, including vertical land motion. Medium-confidence processes only. Coastal locations must be eligible; a landlocked place has no coastal reading. This is neither storm surge nor inundation extent.
Sea level · lowProjected	IPCC AR6 Sea Level Projections v20210809 (opens in a new tab)	Global coastal	SSP5-8.5 (default). Available: SSP1-2.6, SSP2-4.5, SSP5-8.5	2100 default · 2020–2300 · vs 1995–2014
Resolution, licence and interpretation Native resolution 111,000 m Licence CC-BY-4.0 A separate low-confidence workflow incorporating additional ice-sheet processes. Its own distribution must be read separately from the medium-confidence result. Scenario availability differs, including no SSP3-7.0 in this archive.
Extreme water levelModelled present-day	Copernicus CDS GTSMv3 (opens in a new tab)	Global coastal	None — present-day model	1985–2014 climatology
Resolution, licence and interpretation Native resolution 2,500 m Return period 1 · 2 · 5 · 10 · 25 · 50 · 75 · 100 yr Licence CC-BY-4.0 Total coastal water level combines mean sea level, tide and surge. The model under-resolves tropical cyclones. Published return-period estimates have fit uncertainty; station location matters, especially near flood defences.
Subsoil clayPredicted soil property	ISRIC SoilGrids 2.0 (opens in a new tab)1 km aggregated mean of the 250 m product · Poggio et al. 2021	Global land the source predicts; no cells under built-up land, water, glaciers or bare rock	None — static soil property	No epoch · 60–100 cm headline, 100–200 cm beside it
Resolution, licence and interpretation Native resolution 1,000 m (aggregated from 250 m) Licence CC-BY-4.0 Predicted clay content at 60–100 cm, with 100–200 cm as a companion interval. Built-up land and other masked cells have no prediction, not zero clay. Shading requires at least 50% coverage. Clay content alone is not subsidence probability.
Soil-moisture deficitObserved	Copernicus Land SWI time series v4 (opens in a new tab)Bytes from the Copernicus Data Space Ecosystem · TU Wien / VITO · Metop ASCAT	Global land points on a 12.5 km discrete grid; 308 ten-degree tiles	None — observed record	Daily 2007-01-02 to 2025-12-31 · SWI_100 (T = 100 days)
Resolution, licence and interpretation Native resolution 12,500 m (published grid spacing) Licence Copernicus free, full and open access (Reg. (EU) 1159/2013) Each point’s threshold is the 5th percentile of its own record and the index is the mean annual shortfall below it, so the figure is relative: how unusual the deep-soil deficit was here, never how dry the ground is. One deep event can carry the index while famous droughts stop on the threshold. Observed, no return period; frozen and melting days are missing, not dry. The activation half of the clay question, never combined with the clay layer.
Derivation · amplificationDerived	IPCC AR6 sea level (opens in a new tab) Copernicus GTSM (opens in a new tab)Derived from both inputs	Global coastal; depends on both inputs	Inherits AR6 medium-confidence reading	Inherits AR6 horizon and scenario; GTSM 1985–2014 baseline
Resolution, licence and interpretation Native resolution Not an independent source resolution; inherits input limitations Return period Derived recurrence of today’s 100-year total water level Defence state No independent defence field; inherits the limitations of both inputs Licence CC-BY-4.0 (both inputs) A derived change in the recurrence of today’s 100-year water level, holding the storm climate fixed. No extrapolation is made beyond the published curve. The sea-level and water-level baselines differ and that offset is not removed. This is not inundation extent or financial loss.

Map outlines: geometry sources and licences

These are real source geometries simplified for display. Each map is north-up and independently fitted using a local equirectangular projection with longitude scaled at its mid-latitude. The drawings do not share a scale and must not be used to measure area or distance. Hazard sampling continues to use the source geometry.

London urban footprint: European Commission, Joint Research Centre, GHS-UCDB R2019A V1.2, urban-centre ID 1912. CC BY 4.0. Snapshot 2026-08-27. This is the geometry referenced by the engine’s London entry, not Greater London’s administrative boundary.
Central London coordinate: GeoNames entry 2643743, London, UK: 51.50853° N, 0.12574° W. CC BY 4.0. Snapshot 2026-08-27. It locates an illustrative P0 query, not a sampled asset.
Precision comparison grid: NEX-GDDP-CMIP6 native 0.25° coordinates. The London query selects the cell centred at 51.625° N, 0.125° W. No temperature values are read or shown in the comparison.
England: ONS Countries (December 2025) Boundaries UK BUC, E92000001. Captured 2026-09-17. Contains public sector information licensed under the Open Government Licence v3.0. Contains OS data © Crown copyright and database right 2025.
United Kingdom: Natural Earth, 1:10m Admin 0 Countries, GBR. Public domain. Snapshot 2026-08-27. Northern Ireland and the source’s UK islands are included; small features are simplified at display scale.

GHS-UCDB · GeoNames London · ONS geography · Natural Earth public domain · CC BY 4.0 · OGL v3.0

Coverage and important limits

Hazard is not financial risk. These readings do not include asset values, vulnerability or financial loss. Different hazards are not combined into one score.

Missing is not zero. A source may not cover a place, period or requested scenario. A landlocked place has no coastal reading; it does not have zero sea-level rise.

Coverage differs by source. Global datasets and finer UK products have different footprints and periods. National flood products for Scotland and Wales and the listed Northern Ireland product are not included in these examples. Surface-water flooding and undisclosed supply-chain locations are outside this guide.

Defences matter. The sampled flood sources do not represent the benefit of flood defences. A modelled wet area can coexist with real-world protection. The sea-level examples do not calculate inundation extent.

Observed records describe the past; projections depend on their scenario and model assumptions. These examples are dated illustrations, not a guarantee of current coverage in every hosted instance.

How examples can be checked

Each measured example identifies its place, source, observation or projection period and units. Use the original sources linked above to check those definitions; selecting a different boundary, source version or scenario can change the result.

Illustrative diagrams are labelled and are not measured observations. Sources and limitations are provided alongside each example.

Month	Type 0	Other types	All
Jan	13	111	124
Feb	21	65	86
Mar	263	176	439
Apr	260	206	466
May	229	246	475
Jun	113	224	337
Jul	191	190	381
Aug	670	199	869
Sep	109	265	374
Oct	38	118	156
Nov	102	114	216
Dec	8	48	56

Month	Type 0	Other types	All
Jan	13	111	124
Feb	21	65	86
Mar	263	176	439
Apr	260	206	466
May	229	246	475
Jun	113	224	337
Jul	191	190	381
Aug	670	199	869
Sep	109	265	374
Oct	38	118	156
Nov	102	114	216
Dec	8	48	56

A place becomesa hazard reading.

Place

Geometry

Source & sampling

Reading

Central London

London

England

United Kingdom

How much is wet?

How deep is it?

Warming delta

Dry-bulb exceedance

Wet-bulb exceedance

A track is a sequence of records.

Keep the records within 100 km.

Two records. One storm.

Keep today’s 100-year water level.

The mean rises. The reference stays.

Trace the same height to a new frequency.

A defined soil interval.

Most cells are unpredicted.

A reading, with limited coverage.

Residential mortgages

Screen the portfolio’s geography.

A place becomes
a hazard reading.

Month	Type 0	Other types	All
Jan	13	111	124
Feb	21	65	86
Mar	263	176	439
Apr	260	206	466
May	229	246	475
Jun	113	224	337
Jul	191	190	381
Aug	670	199	869
Sep	109	265	374
Oct	38	118	156
Nov	102	114	216
Dec	8	48	56