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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.
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)"]
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).
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
countfirst (cheap) to decide whether to tile by time slice or magnitude band, then stitch and dedupe. -
magTypeis a first-class field — read and KEEP it. Silently mixingmb/Ms/Mwdistorts the magnitude–frequency tail; the homogenization step (see Data-Types-and-Features and Pipeline) depends on it. -
Be polite: serialize requests, prefer
updatedafterdeltas, 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, ...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. |
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.
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, mtpThe 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). |
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")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.
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. |
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. |
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. |
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>.tenv3A 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.
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. |
| 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. |
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.)
Tidal stress on a fault has two distinct contributions that must be computed separately and summed:
- 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.
-
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
with
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 |
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).
| 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 |
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 |
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.
| Tool | Component |
|---|---|
pygtide (github.com/hydrogeoscience/pygtide, wraps ETERNA PREDICT 3.4) |
Body-tide strain → stress via the crustal stiffness tensor |
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):
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.
- 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.
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.
| 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.
- 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. - Scholz, C. H., Tan, Y. J., & Albino, F. (2019). The mechanism of tidal triggering of earthquakes at mid-ocean ridges. Nat. Comms 10, 2526. DOI
10.1038/s41467-019-10605-2. - 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.
⚠️ Disclaimer — read this. CAOS_SEISMIC produces probabilistic forecasts, not predictions. It is an independent research and education tool. It is NOT an official earthquake early-warning or civil-protection system, it does NOT predict when, where, or how large an earthquake will be, and it must NOT be used for life-safety, emergency, or evacuation decisions. Every number it publishes is a bounded, calibrated probability conditioned on the present state of seismicity — never an alarm, a countdown, or a "safe" state. A single outcome neither confirms nor refutes a probabilistic forecast.It complements, and does not replace or speak for, official agencies — always follow your national seismological and civil-protection authorities (e.g. USGS, INGV, CSN (Chile, SENAPRED for civil protection), GeoNet, JMA). The software is provided "as is", without warranty of any kind (MIT License); the authors accept no liability for its use. Data are courtesy of their providers (USGS/ANSS, ISC/ISC-GEM, Global CMT, EMSC, CSN, and others) under their respective licenses and attribution terms. See Honest-Limits for the full epistemic context.
CAOS_SEISMIC · seismic.fasl-work.com · source · MIT
Conditional probabilistic seismic forecasting — forecasts, never predictions.
Overview
Methodology & History
Classical models
- Models-Classical · index
- Gutenberg-Richter-Law
- Omori-Utsu-Law
- ETAS-Model
- Reasenberg-Jones-Model
- STEP-Model
- EEPAS-Model
- Smoothed-Seismicity
- Brownian-Passage-Time
- Rate-and-State-and-Coulomb
ML & analytical methods
- Models-ML · index
- Temporal-Point-Processes
- RMTPP
- Neural-Hawkes-Process
- Transformer-Hawkes-Process
- RECAST-and-FERN
- CNN-Spatial-Models
- Graph-and-Recurrent-Networks
- Detection-vs-Forecasting
Models employed
Data
Architecture
Evaluation
Progress
Reference