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Data Sources

Felipe Santibañez-Leal edited this page Jun 17, 2026 · 2 revisions

Data Sources

This page documents the data sources themselves — the open, global feeds and datasets that CAOS_SEISMIC ingests. It is one of two data pages, and it answers a single question for each source: what is this dataset, how do you get it, what does its license oblige, how often does it update, and how big is it? The companion page, Data-Types-and-Features, answers the different question of what kind of record comes out of these sources and which features the model actually ingests — read it next.

Every source below is open, scriptable, no-auth (or open-attribution), and ingestible in an automated daily job. Each one is given its own clearly-separated subsection so it can be read, cited, or updated in isolation.

Honest framing — read before the catalog. The dominant signal in every published short-term forecasting result is the earthquake catalog itself (its clustering structure). Geodesy, fault geometry, slab geometry, crustal stress, and tides are upside, not foundation: each ships into the live product only if it shows a positive, significant pseudo-prospective information gain over a catalog-only baseline. This page therefore separates the catalog spine (load-bearing, §2–§6) from the complementary global enrichers (covariates, §7–§12), and treats tidal stress (§13) as a regularized covariate with an honestly small, regime-dependent effect.

CAOS_SEISMIC is a global forecaster: it trains on global seismicity plus every complementary global covariate, and runs inference across many countries — high-seismicity (Chile, Japan, Indonesia, Mexico, Türkiye, California, New Zealand) and low-seismicity (United Kingdom, Germany, Australia, Brazil) — so that any bias toward high-seismicity zones can be measured rather than assumed. The data layer is correspondingly global.


1. Architecture of the data layer

flowchart TD
    subgraph SPINE["Catalog spine (load-bearing)"]
        COMCAT["USGS ComCat<br/>(FDSN event)<br/>real-time global, daily"]
        ISCREV["ISC Bulletin REVIEWED + ISC-EHB<br/>relocated, ~24-month lag"]
        ISCGEM["ISC-GEM v12.1<br/>Mw-homogenized, 1904-2021"]
        GCMT["Global CMT (.ndk)<br/>moment tensors, Mw>=5"]
        EMSC["EMSC SeismicPortal<br/>independent cross-check"]
    end
    subgraph ENRICH["Complementary global enrichers (covariates)"]
        SLAB2["Slab2<br/>subduction geometry"]
        FAULTS["GEM Active Faults<br/>fault distance / style"]
        PB2002["Bird PB2002<br/>plate boundaries"]
        GNSS["NGL GNSS / MIDAS<br/>strain-rate field"]
        WSM["World Stress Map<br/>stress orientation"]
        TIDES["Tidal stress (computed)<br/>pygtide + SPOTL/TPXO"]
    end
    SPINE --> HYG["Catalog hygiene<br/>(Mc, homogenize, decluster)"]
    ENRICH --> FEAT["Feature build<br/>(joined on the forecast grid)"]
    HYG --> FEAT
    FEAT --> MODEL["Conditional model<br/>(ETAS reference + neural challenger)"]
Loading

The spine is pulled every day; the enrichers are mostly static or slowly varying and are joined onto the forecast grid at build time. A single access layer — ObsPy's FDSN client (§6) — hits every catalog provider with one API. The split between this page and Data-Types-and-Features mirrors the diagram: this page is the left/top boxes (the sources), that page is the Catalog hygiene → Feature build boxes (what the model ingests).


2. USGS ComCat — the real-time global spine

The ANSS Comprehensive Earthquake Catalog is the single most important real-time, no-auth, daily-current global source. It is the spine of the daily inference loop: it is what gets pulled, deduped, and turned into features every day.

Field Value
What Global event catalog: time, latitude, longitude, depth, magnitude, magnitude type (magType), event IDs, and associated products (ShakeMap, moment tensor, PAGER).
Access FDSN event web service; libcomcat (Python) or ObsPy Client("USGS").
Base URL https://earthquake.usgs.gov/fdsnws/event/1/
Methods query, count, version, contributors, catalogs, application.wadl.
Formats geojson (preferred for scripting — clean nested JSON), quakeml, csv, text, kml.
License US Government work, public domain (USGS-authored content). Non-US networks surfaced through ComCat keep their own attribution.
Cadence Real-time / continuously updated. Stability: very high (national archive on a long-lived federation standard).
Size Streaming; a multi-decade Chile-box pull at M ≥ 2.5 is tens of MB of JSON.
Daily feasibility Excellent. updatedafter returns only events updated since the last successful run — the natural incremental daily delta.

Operational notes.

  • Hard cap: 20,000 events per request (exceeding it returns HTTP 400). Call count first (cheap) to decide whether to tile by time slice or magnitude band, then stitch and dedupe.
  • magType is a first-class field — read and KEEP it. Silently mixing mb / Ms / Mw distorts the magnitude–frequency tail; the homogenization step (see Data-Types-and-Features and Pipeline) depends on it.
  • Be polite: serialize requests, prefer updatedafter deltas, and back off on HTTP 429/503. The public web app never hits upstream services directly — only the daily job pulls and persists.
# Count first (cheap) to decide whether to tile
curl "https://earthquake.usgs.gov/fdsnws/event/1/count?starttime=2010-01-01&endtime=2026-06-16&minmagnitude=2.5"
# Daily incremental: only events updated since the last successful run
curl "https://earthquake.usgs.gov/fdsnws/event/1/query?format=geojson&updatedafter=2026-06-15T00:00:00&minmagnitude=1"
from libcomcat.search import search
from libcomcat.dataframes import get_summary_data_frame
from datetime import datetime
events = search(starttime=datetime(2010, 1, 1), endtime=datetime(2026, 6, 16),
                minmagnitude=2.5)
df = get_summary_data_frame(events)   # id, time, lat, lon, depth, magnitude, magtype, ...

3. ISC Bulletin (REVIEWED) + ISC-EHB — the clean retrospective bulletin

The International Seismological Centre is the definitive retrospective global bulletin: relocated and re-reviewed, the gold standard for completeness and homogenization. It lags real time by roughly 24 months, so it is a training-quality source, not a daily one.

Field Value
What Definitive relocated/reviewed global bulletin (prime preferred hypocentre + magnitudes). The ISC-EHB subset gives the cleanest hypocenters.
Access Catalogue web service http://www.isc.ac.uk/cgi-bin/web-db-run (out_format=CATCSV or CATQuakeML, request=REVIEWED); or ObsPy Client("ISC").
Selectors request=COMPREHENSIVE (full bulletin) vs REVIEWED (analyst-reviewed — use for training quality); searchshape=GLOBAL|RECT|CIRC|FE|POLY; magnitude/type filters.
License Open for research with attribution (check per-product terms).
Cadence ~24-month lag. Stability: very high.
Size Large; ISC throttles big pulls (very large requests may be queued/emailed).
Daily feasibility Not a daily source. Use the REVIEWED DB for training quality; prefer downloadable products over hammering the CGI.

4. ISC-GEM v12.1 — the long-term homogeneous anchor

The Global Instrumental Earthquake Catalogue is the catalog to use for long-term b-value, large-event recurrence, and as the Mw-homogenization anchor in the catalog-hygiene step (see Data-Types-and-Features §3).

Field Value
What 1904–2021, M ≥ 5.5 globally (continental events down to M 5.0), Mw-homogenized, relocated.
Version / DOI v12.1 (2025-11-27). DOI 10.31905/d808b825.
Access CSV (main + supplementary) + KMZ from https://www.isc.ac.uk/iscgem/download.php (also distributed via GEM).
License CC-BY-SA 3.0 (Unported) — © International Seismological Centre & GEM Foundation.
Cadence Versioned (annual-ish), DOI'd. Stability: very high.
Size Tens of MB CSV.
Daily feasibility Periodic refresh, not daily.

Share-alike obligation. CC-BY-SA 3.0 share-alike means any redistributed derivative catalog must carry CC-BY-SA + attribution. Internal training is unaffected; if the product ships a processed ISC-GEM-derived catalog, the license and provenance are preserved. See §14 Attribution.


5. Global CMT — moment tensors and mechanism source

Centroid moment tensors for essentially all M ≳ 5 global events since 1976: focal mechanism, Mw, nodal planes, P/T axes. The source of mechanism and stress features (see Data-Types-and-Features §5), and a Mw anchor alongside ISC-GEM.

Field Value
What Moment tensors (Mw, nodal planes, P/T axes) for ~all M ≳ 5 events since 1976.
Access Download .ndk from https://www.globalcmt.org/CMTfiles.html (full historical file + monthly files since 2005 + Quick CMT). Parse natively with obspy.read_events(...) (module obspy.io.ndk).
Format NDK — ASCII, 5 lines × 80 chars per event.
License Free for research with citation (Dziewonski et al. 1981; Ekström et al. 2012).
Cadence Monthly batch + near-real-time Quick CMT. Stability: high.
Size Tens of MB.
Daily feasibility Monthly refresh suffices; Quick CMT for near-real-time mechanism on large events.
import obspy
cat = obspy.read_events("jan76_dec20.ndk")
mt = cat[0].focal_mechanisms[0].moment_tensor.tensor   # mrr, mtt, mpp, mrt, mrp, mtp

6. EMSC SeismicPortal — independent real-time cross-check

The European-Mediterranean Seismological Centre: best for low-latency real-time and an independent dedup cross-check against ComCat (a different operator seeing the same events is the cheapest guard against a single provider's bad origin swinging a public number).

Field Value
What Independent real-time feed (Euro-Med + global) plus felt reports; cross-check vs ComCat.
Access FDSN-event (https://www.seismicportal.eu/fdsnws/event/1/query?..., json/xml/text, 20k cap); WebSocket push feed; ObsPy Client("EMSC").
License Open for research with attribution.
Cadence Real-time + WebSocket. Stability: high.
Size Streaming.
Daily feasibility Excellent as a cross-check; call query?... directly (the bare /fdsnws/event/1/ index 404s).

6.1 ObsPy as the unifying access layer

obspy.clients.fdsn.Client hits every FDSN provider with one API. Built-in short names include USGS, ISC, EARTHSCOPE, GEONET, INGV, EMSC, SCEDC, NCEDC (IRIS/IRISDMC redirect to EARTHSCOPE). Operational rules:

  • get_events() has no bulk analogue → loop time windows yourself and respect each provider's 20,000-event cap. Pattern: count → if > 20k, halve the window recursively → concatenate → dedupe by event id.
  • Wrap every call in retry/backoff: HTTP 204 (no data), 400 (bad request), 413 (too large → "tile smaller"), 429/503 (slow down).
from obspy.clients.fdsn import Client
from obspy import UTCDateTime
cli = Client("USGS")          # or "ISC", "EARTHSCOPE", "GEONET", "INGV", "EMSC", "SCEDC", "NCEDC"
cat = cli.get_events(starttime=UTCDateTime("2024-01-01"), endtime=UTCDateTime("2024-12-31"),
                     minmagnitude=2.5, orderby="time-asc")

6.2 Regional networks (surfaced through the same FDSN layer)

Regional networks dramatically beat the global catalog at small magnitudes (a lower, more stable magnitude of completeness Mc). For a global product they are surfaced through the same FDSN layer and used as higher-resolution context where available; for any single-country view they sharpen Mc.

Region Network Access License / flag
Chile CSN (net C/C1) EarthScope/IRIS FDSN or ISC; GNSS at gps.csn.uchile.cl Public use with mandatory CSN attribution (since 2019-06)
California SCEDC (CI), NCEDC (BK/NC) Client("SCEDC")/Client("NCEDC"); AWS open-data s3://scedc-pds (--no-sign-request) Open + attribution; AWS Open Data terms
New Zealand GeoNet https://service.geonet.org.nz/fdsnws/...; Client("GEONET") CC-BY 3.0 NZ — attribute "Earth Sciences New Zealand"
Italy INGV ISIDe (IV) http://webservices.ingv.it/fdsnws/event/1/query; Client("INGV") CC-BY (verify version on the dataset page)

Networks that are registration- and agreement-gated and not freely redistributable are used for internal training quality only — never shipped in the public product or web app. The public product cites and serves only open, redistributable data.


7. Slab2 — subduction geometry (highest-value static covariate)

The first of the complementary global enrichers: geophysical-context covariates joined as static or slowly varying spatial fields onto the forecast grid. They are ranked by expected lift, and each enricher's marginal information gain over a catalog-only baseline is quantified on held-out data before it is committed. None substitutes for the catalog.

Slab2 gives depth-to-slab, dip, strike, thickness, and interface distance for every subduction zone. This is what separates interface, intraslab, and crustal seismicity — very different physics and rates — and is essential for the global product's tectonic-regime conditioning.

Field Value
What Per-zone depth/strike/dip/thickness/uncertainty grids at 0.05° × 0.05° (*_dep, *_str, *_dip, *_thk, *_unc).
Access USGS ScienceBase item 5aa1b00ee4b0b1c392e86467; code at github.com/usgs/slab2; NetCDF .grd; interactive at earthquake.usgs.gov/slab2/.
License USGS public domain.
Cadence Static (versioned). Stability: high (DOI'd, USGS).
Size ~100s MB; loaded once.
Reference Hayes et al. (2018), Science 362, 58–61. DOI 10.1126/science.aat4723.

8. GEM Global Active Faults — distance-to-fault and fault style

A homogenized global active-fault database. Yields distance-to-nearest-active-fault and fault style (the model needs to know a cell is near a mapped fault, and what kind).

Field Value
What Homogenized global active-fault geometry and attributes.
Access github.com/GEMScienceTools/gem-global-active-faults — GeoJSON / GeoPackage / KML / ESRI Shapefile.
License CC-BY-SA 4.0 (verify repo LICENSE).
Cadence Versioned. Stability: high.
Size ~100s MB; loaded once.
Reference GEM Science Tools.

9. Bird PB2002 — plate-boundary model

The plate-tectonic frame: which plate a cell sits on, distance to the nearest plate boundary, the boundary type (subduction / transform / ridge), and the plate-pair relative velocity.

Field Value
What 52 plates (14 large + 38 small); plate-boundary geometry + type.
Access peterbird.name/publications/2003_pb2002/ (ASCII digital files); also bundled in GEM.
License Open for research with citation.
Cadence Static. Stability: high (archival/DOI'd).
Size Small ASCII; loaded once.
Reference Bird (2003), G-cubed 4(3), 1027. DOI 10.1029/2001GC000252.

10. NGL GNSS / MIDAS — the strain-rate field

The Nevada Geodetic Laboratory processes more than 13,000 global GNSS stations with GipsyX. Interpolating station velocities yields a strain-rate field (dilatation, max shear, second invariant) that correlates with long-term seismicity rate — primarily a background covariate.

Field Value
What Daily E/N/U position time series (.tenv3) + robust MIDAS velocities (midas.IGS14.txt).
Access geodesy.unr.edu; wget/curl scriptable.
License Open with attribution (NGL; Blewitt et al. 2016, MIDAS estimator).
Cadence Daily–weekly. Stability: high (daily-maintained).
Size GBs (per-station text).
Daily feasibility Good (daily-updated, scriptable), but it feeds the slow background term, not the short-horizon term.
wget http://geodesy.unr.edu/velocities/midas.IGS14.txt
wget http://geodesy.unr.edu/gps_timeseries/tenv3/IGS14/<STATION>.tenv3

A ready-made alternative is the GEM/Kreemer GSRM global strain-rate model — a finished strain grid that is often easier than interpolating NGL stations directly.


11. World Stress Map / focal-mechanism stress

Crustal stress orientation and faulting regime. Derived from focal mechanisms (Global CMT and regional moment tensors, §5) via stress inversion, plus the World Stress Map compilation. Yields rake / faulting style, P/T-axis orientation, and Coulomb stress-transfer (ΔCFS) triggering features — physically motivated but second-tier effort.

Field Value
What Stress orientation, faulting regime, and (via inversion of §5 mechanisms) regional stress field + ΔCFS triggering.
Access World Stress Map compilation; derived from Global CMT + regional moment tensors.
License Open with attribution.
Cadence Event-driven / versioned compilation. Stability: high.
Size Small.
Daily feasibility Event-driven; second-tier priority.

12. Deferred / out of scope (v1)

Enricher Why deferred
InSAR (COMET LiCSAR) Heaviest enricher (TB rasters, atmospheric noise, frame-by-frame coverage); the deformation → short-term-probability link is weak and research-grade. Not in the daily loop; budget separate TB-scale storage out of git if added later. Products free (attribute COMET / ESA Copernicus Sentinel-1); software GPL-3.
Heat flow (World Heat Flow DB) Sparse, static; at best a slow background covariate for crustal regions. Lowest priority.

13. Tidal triggering — a physically-motivated, regularized covariate

Tides are a physically-motivated, regularized covariate with an honestly small effect — never a standalone predictor. This section states the source physics, the effect sizes by regime, and how the feature is computed. Tidal triggering is the most over-claimed phenomenon in popular discourse and the most disciplined to handle in an honest forecaster. (The encoding of the tidal feature into the model intensity is detailed in Data-Types-and-Features §5 and Models-Classical; here we document the underlying source.)

13.1 The physics — two contributions, computed separately and summed

Tidal stress on a fault has two distinct contributions that must be computed separately and summed:

  1. Solid-Earth (body) tides — the Moon and Sun deform the whole solid Earth, producing a strain/stress field throughout the lithosphere. Dominant constituents: semidiurnal M2 (12.421 h), S2 (12.000 h); diurnal O1 (25.819 h), K1 (23.934 h); and the long-period fortnightly Mf (~13.66 d) and monthly Mm.
  2. Ocean tidal loading (OTL) — the redistributed weight of ocean water flexes the seabed and adjacent crust. Near continental margins and on the ocean floor this can dominate the body tide. A 2 m tidal column imposes a vertical seafloor load of order $\rho_w g h \approx 1025 \times 9.81 \times 2 \approx 2.0\times10^{4}\ \text{Pa} \approx 20\ \text{kPa}$, attenuating inland and with depth. This is why coastal/subduction thrusts show the strongest "tidal" signal — it is really ocean-loading stress, not body tide.

Modeling consequence. A correct tidal-stress series = body tide (tidal-potential catalog + Love numbers) + ocean loading (global ocean-tide model convolved with elastic Green's functions). Doing only the body tide underestimates the signal at coastal/subduction sites by a large factor.

Resolve to the fault — tidal Coulomb failure stress. Form the full tidal stress tensor $\sigma_{ij}(t)$ at the hypocenter (body + OTL), then resolve it onto the fault plane with unit normal $\hat{n}$ and slip direction $\hat{s}$:

$$\Delta\tau(t) = \hat{s}\cdot\big(\sigma(t),\hat{n}\big), \qquad \Delta\sigma_n(t) = \hat{n}\cdot\big(\sigma(t),\hat{n}\big)$$

$$\Delta\mathrm{CFS}(t) = \Delta\tau(t) + \mu_f,\Delta\sigma_n(t)$$

with $\mu_f \approx 0.4$ the (apparent) friction coefficient. A poroelastic variant replaces $\mu_f$ with an effective $\mu' = \mu_f(1 - B)$ (Skempton coefficient $B$) for fluid-rich subduction interfaces.

13.2 Why the effect is small — and where it is larger

The decisive numbers:

Quantity Order of magnitude
Tidal stress on faults ~0.1–10 kPa (body ~1 kPa; OTL up to ~10–20 kPa at strong-tide coast/seafloor)
Earthquake static stress drop ~0.1–10 MPa (typically 1–10 MPa)
Ratio tidal / stress-drop ~$10^{-3}$ to $10^{-4}$

A tide therefore cannot cause an earthquake; at most it can advance or retard the timing of a rupture already within ~$10^{-3}$ of failure — a small minority at any instant. The nucleation-duration argument (Beeler & Lockner 2003) is the decisive one: if nucleation takes longer than a tidal period, the oscillating stress averages out and no phase preference survives. Lab + rate-state extrapolation put crustal nucleation on a major fault at ~1 year ≫ daily tide, so daily tides should not strongly correlate — only the fortnightly Mf band, or settings with very short nucleation, should show a clean correlation. The signal is largest where (a) ocean loading is strong (margins, ridges, seafloor), (b) faults are shallow (less lithostatic clamping), and (c) the dominant tidal component aligns with the failure mode (thrust ↔ vertical ocean load; ridge normal faults ↔ ridge-axis tension).

13.3 Effect sizes by regime (canonical literature)

Study Setting Effect size
Tanaka, Ohtake & Sato (2002), JGR — DOI 10.1029/2001JB001577 9,350 global M ≥ 5.5 No correlation when lumped; reverse (thrust) faults correlate with tidal shear stress
Cochran, Vidale & Tanaka (2004), Science — DOI 10.1126/science.1103961 Shallow ocean-loaded thrusts Rate varies by factor ~3; ~75% occur during encouraging stress at tides > 2 m; best at $\mu = 0.4$; chance < 1 in 10,000. California: only ~1–2%.
Métivier et al. (2009), EPSL — DOI 10.1016/j.epsl.2008.12.024 442,412 global events ~0.5–1.0% rate excess at favorable phase, ~99% confidence; larger for smaller/shallower events
Ide, Yabe & Tanaka (2016), Nat. Geosci. — DOI 10.1038/ngeo2796 Tidal stress vs event size b-value decreases as tidal shear amplitude rises; 2004 Sumatra, 2010 Maule, 2011 Tohoku near peak. Contested (Hough 2018 found no lunar-phase effect for 204 M ≥ 8).
Scholz, Tan & Albino (2019), Nat. Comms — DOI 10.1038/s41467-019-10605-2 Mid-ocean ridges Phase inverts via axial magma-chamber response; clean rate-state $R/r=\exp(\Delta\mathrm{CFS}/A\sigma)$ with no triggering threshold

The much stronger, least-disputed channel is not regular earthquakes at all — it is nonvolcanic tremor and slow-slip events, which respond to the same ~kPa stresses far more strongly (exponential tremor rate, fortnightly Mf modulation used as an in-situ stressmeter; Rubinstein et al. 2008 DOI 10.1126/science.1150558; Houston 2015 DOI 10.1038/ngeo2419; van der Elst et al. 2016 DOI 10.1073/pnas.1524316113). Where tremor/SSE catalogs exist (Cascadia, Nankai, Mexico, parts of Chile/Hikurangi), the slow-earthquake channel is kept separate from the fast-earthquake channel in the model.

13.4 Computing the feature (the source tools)

Tool Component
pygtide (github.com/hydrogeoscience/pygtide, wraps ETERNA PREDICT 3.4) Body-tide strain → stress via the crustal stiffness tensor $\sigma_{ij}=\lambda,\epsilon_{kk}\delta_{ij}+2G,\epsilon_{ij}$
SPOTL (Agnew; nloadf/hartid) Ocean tidal loading via mass-loading Green's functions
TPXO (+ GOT/FES alternatives) Global ocean-tide model used as the OTL load

Engineered features (detailed in Data-Types-and-Features §5): $\Delta\mathrm{CFS}(t_0)$ at the forecast instant; its rate $\dot{S}(t_0)$; phase as $\sin\theta,\cos\theta$ (circular); semidiurnal envelope; and the fortnightly Mf (~14.7 d) envelope.

Validation gate (mandatory before the feature touches any public number). Reproduce a published tidal time series for a known site (e.g. Cascadia / Axial Seamount), confirm sign conventions (tension- vs compression-positive) and the Green's-function reference frame (CE vs CM) match across pygtide and SPOTL, then require positive prospective information gain (with-vs-without, declustered) — never claim improvement from in-sample Schuster p-values (a large $N$ makes a tiny effect "significant"). License: pygtide / SPOTL are open tools; TPXO has its own academic-use terms (recorded). At coastal/subduction margins, ocean loading dominates — skipping it is the single biggest tidal-modeling error.

13.5 Honest expectation

  • Most regions: the learned coupling shrinks toward ~0, negligible skill gain, possibly a tiny calibration improvement at the favorable phase — reported honestly, never buried.
  • Shallow ocean-loaded thrust / ridge regions: measurable but small (~few %) improvement, useful mostly for calibration, not sharpness.
  • Regions with tremor/SSE: the covariate can meaningfully sharpen the slow-slip forecast, which indirectly informs megathrust stress state.

14. Attribution and licensing obligations

The product credits page must display every required attribution; these are tracked here so the credits notice is never forgotten.

Source Obligation
USGS / ANSS ComCat Public domain (US Government work); credit USGS/ANSS.
ISC Bulletin / ISC-EHB Open for research with attribution.
ISC-GEM v12.1 CC-BY-SA 3.0 — share-alike: a redistributed derived catalog keeps CC-BY-SA + provenance.
Global CMT Free for research with citation (Dziewonski 1981; Ekström 2012).
EMSC SeismicPortal Open for research with attribution.
CSN (Chile) Public use with mandatory CSN attribution (since 2019-06).
GeoNet (NZ) CC-BY 3.0 NZ — attribute "Earth Sciences New Zealand."
INGV ISIDe CC-BY (verify exact version on the dataset page).
Slab2 / USGS Public domain; credit USGS.
GEM Active Faults CC-BY-SA 4.0 (verify repo LICENSE).
Bird PB2002 Open for research with citation.
NGL GNSS / MIDAS Open with attribution (NGL; Blewitt et al. 2016).
TPXO ocean-tide model Academic-use terms (recorded).

These are not redistribution blockers — but the public app must display them. Any agreement-gated raw files are used for internal training only and are never in the public repo or web app.


15. Update cadence and daily-inference feasibility (summary)

Source Cadence Daily-inference role
USGS ComCat Real-time Spine — daily updatedafter delta
EMSC SeismicPortal Real-time + WS Daily cross-check
Global CMT (Quick CMT) Monthly + near-RT Mechanism on large events
NGL GNSS / MIDAS Daily–weekly Strain-rate covariate (slow)
ISC REVIEWED / ISC-EHB ~24-month lag Training quality (not daily)
ISC-GEM v12.1 Versioned (annual-ish) Mw anchor / b-value (periodic refresh)
Slab2, GEM faults, Bird PB2002 Static Loaded once; tectonic-regime conditioning
World Stress Map / focal-mechanism stress Event-driven Stress/ΔCFS covariate (second tier)
Tidal stress (computed) On demand Regularized covariate (computed per inference)

Bottom line: ComCat + EMSC give a fully scriptable, no-auth, real-time daily spine; the homogeneous anchors and the geophysical enrichers are periodic or static and are refreshed on a slower cadence. The whole layer is reproducible from manifests (see Pipeline) and feeds the system described in Technical-Architecture.


References

  • Bird, P. (2003). An updated digital model of plate boundaries (PB2002). G-cubed 4(3), 1027. DOI 10.1029/2001GC000252.
  • Blewitt, G., Hammond, W. C., & Kreemer, C. (2016). MIDAS robust trend estimator for GPS station velocities. JGR Solid Earth 121. DOI 10.1002/2015JB012552.
  • Beeler, N. M., & Lockner, D. A. (2003). Why earthquakes correlate weakly with the solid Earth tides. JGR Solid Earth 108(B8), 2391. DOI 10.1029/2001JB001518.
  • Cochran, E. S., Vidale, J. E., & Tanaka, S. (2004). Earth tides can trigger shallow thrust fault earthquakes. Science 306(5699), 1164–1166. DOI 10.1126/science.1103961.
  • Di Giacomo, D., Engdahl, E. R., Storchak, D. A., et al. ISC-GEM Global Instrumental Earthquake Catalogue v12.1. DOI 10.31905/d808b825.
  • Dziewonski, A. M., Chou, T.-A., & Woodhouse, J. H. (1981). Determination of earthquake source parameters from waveform data. JGR 86, 2825–2852. (Global CMT founding paper.)
  • Ekström, G., Nettles, M., & Dziewoński, A. M. (2012). The global CMT project 2004–2010. PEPI 200–201, 1–9. DOI 10.1016/j.pepi.2012.04.002.
  • Hayes, G. P., et al. (2018). Slab2, a comprehensive subduction zone geometry model. Science 362, 58–61. DOI 10.1126/science.aat4723.
  • Houston, H. (2015). Low friction and fault weakening revealed by rising sensitivity of tremor to tidal stress. Nat. Geosci. 8, 409–415. DOI 10.1038/ngeo2419.
  • Ide, S., Yabe, S., & Tanaka, Y. (2016). Earthquake potential revealed by tidal influence on earthquake size–frequency statistics. Nat. Geosci. 9, 834–837. DOI 10.1038/ngeo2796.
  • Métivier, L., et al. (2009). Evidence of earthquake triggering by the solid earth tides. EPSL 278, 370–375. DOI 10.1016/j.epsl.2008.12.024.
  • Rubinstein, J. L., et al. (2008). Tidal modulation of nonvolcanic tremor. Science 319, 186–189. DOI 10.1126/science.1150558.
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  • Tanaka, S., Ohtake, M., & Sato, H. (2002). Evidence for tidal triggering of earthquakes. JGR Solid Earth 107(B10), 2211. DOI 10.1029/2001JB001577.
  • van der Elst, N. J., et al. (2016). Fortnightly modulation of San Andreas tremor and low-frequency earthquakes. PNAS 113(31), 8601–8606. DOI 10.1073/pnas.1524316113.

Service docs: USGS FDSN-event earthquake.usgs.gov/fdsnws/event/1/ · ISC web services isc.ac.uk/iscbulletin/search/webservices/catalogue/ · ObsPy FDSN docs.obspy.org/packages/obspy.clients.fdsn.html · GeoNet FDSN geonet.org.nz/data/access/FDSN · EMSC SeismicPortal seismicportal.eu/webservices.html · Slab2 earthquake.usgs.gov/slab2/ · GEM faults github.com/GEMScienceTools/gem-global-active-faults.


See also: Data-Types-and-Features — the record format and the feature set the model ingests · Pipeline — how this data is cleaned, homogenized, and turned into features · Technical-Architecture — how the global field, regime tiling, and daily job consume it.

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