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STEM foundation

STEM foundation of Systems Science and Modelling

The science, technology, engineering and mathematics Systems Science and Modelling rests on. Each method has a canonical page in the STEM Commons, hosted by GCRI, and a page here on how it is applied in this field.

Open Systems engineering for models Back to Systems Science and Modelling
Publisher
The Global Centre for Risk and Innovation
Field
Methods and modelling, Risk management and systemic risk, Research and evidence
Canvas · methods feeding this platformDesign, not a record
STEM foundation of Systems Science and Modelling: risk as hazard, exposure and vulnerabilityRisk arises from the interaction of hazard, exposure and vulnerability (sensitivity and adaptive capacity); responses act on each driver and leave a residual risk that is monitored. Design of the process, not a record of a run.

Fig.The methods this platform draws on and what each one feeds. Design, not a record.

01In brief

The short answer.

The Systems Science and Modelling STEM foundation is the set of canonical methods its findings depend on, from systems engineering to high-performance, cloud and edge computing. For the Consortium, Systems Science and Modelling stewards six of them, among them systems engineering as well as probability and statistics. Each method has a canonical STEM Commons page and a page here on its use in the methods and modelling field.

02Geography

Hazards and exposure in North America.

For STEM foundation of systems science and modelling, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery, flood water and night lights with relief in 3D, framed on North America; every other NASA layer, live feed and forecast waits in the layer list.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

Hazards and exposure, for this page

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

Loading the latest NASA imagery.

Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

For STEM foundation of systems science and modelling, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery, flood water and night lights with relief in 3D, framed on North America; every other NASA layer, live feed and forecast waits in the layer list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · Copernicus Sentinel-2 L2ASources and licences

  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). CC BY 4.0
  • GPM IMERG precipitation, NASA Precipitation Processing System; distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • Observed (EO): Copernicus Sentinel-2 L2A (contains modified Copernicus Sentinel data 2026), Microsoft Planetary Computer
  • Optional layers (35 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026

03Methods

The methods behind the field.

  1. Systems engineeringRequirements for decision models · Interface control for coupled modelsSteward · Systems Science and ModellingApplied here
    Canonical · STEM Commons
  2. Probability and statisticsBayesian calibration · Proper scoring of predictions · Ensemble statisticsSteward · Systems Science and ModellingApplied here
    Canonical · STEM Commons
  3. Uncertainty quantification and model validationUncertainty budgets · Surrogate models for expensive simulations · Credibility assessmentSteward · Systems Science and ModellingApplied here
    Canonical · STEM Commons
  4. Network science and contagionCommon network representations · Contagion model comparison · Multilayer analysisSteward · Systems Science and ModellingApplied here
    Canonical · STEM Commons
  5. Complex systems and agent-based modellingAgent-based model standards · Feedback and tipping point analysis · Early warning indicatorsSteward · Systems Science and ModellingApplied here
    Canonical · STEM Commons
  6. Optimization and operations researchProblem formulation guidance · Robust and stochastic comparisons · Solver benchmarkingSteward · Systems Science and ModellingApplied here
    Canonical · STEM Commons
  7. Decision analysis under uncertaintyFraming the decision before the model · Value of information for modelsSteward · Systemic Risk ManagementApplied here
    Canonical · STEM Commons
  8. High-performance, cloud and edge computingEnsemble design within budgets · Workflow orchestration · Reproducible environmentsSteward · Data and ComputeApplied here
    Canonical · STEM Commons
04Method mix

Why systems modelling needs this combination of methods.

Systems modelling combines systems engineering, probability, uncertainty quantification, network science, complex systems, optimisation, decision analysis and computing. The test of any combination is whether its coupled output can be validated against something observed, which is why uncertainty quantification sits at the centre.

Systems modelling combines systems engineering, probability, uncertainty quantification, network science, complex systems, optimisation, decision analysis and computing.

05Why it matters

Grounding makes claims checkable.

When a finding names the methods it depends on, a reader can see its assumptions and limits, and an expert in that method can challenge it.

06Key terms

Terms used on this page.

Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.

TermDefinition
STEM CommonsThe shared reference of science, technology, engineering and mathematics methods for the Nexus network, hosted by GCRI, with one canonical page per method and a named steward platform.
Steward platformThe platform that maintains the canonical description of a method in the STEM Commons and reviews how other platforms apply it.
Systems engineeringSystems engineering is an interdisciplinary approach to designing and managing complex systems over their life cycle.
Probability and statisticsProbability and statistics provide the mathematical framework for describing uncertainty and learning from data.
07Sources

Where this page's references lead.

The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.

08Pages

Pages in STEM foundation of Systems Science and Modelling.

Method

Systems engineering for models

Method

Statistics for modelling

Method

Uncertainty quantification

Method

Network science methods

Method

Complex systems methods

Method

Optimization methods

Method

Decision analysis for modelling

Method

Computing for modelling

09Questions

Questions and answers.

What is a steward platform?
The platform that maintains the canonical description of a method and reviews how it is applied across the Consortium.
Related

Around Systems Science and Modelling.

Systems Science and Modelling

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