3MIP — Mobility and Migration Modeling Intercomparison Project

iEMSs 2026 · University College Dublin · July 12–16, 2026

3MIP in 90 seconds

3MIP — the Mobility and Migration Modeling Intercomparison Project — is a community of researchers who apply their climate-migration models to a shared benchmark case. The first case is coastal Bangladesh.

  • Launched October 2025, modeled on AgMIP and ISIMIP. Founded at a Princeton C-PREE workshop in 2024.
  • Led from Cornell (Bell), Ohio State (Best), and VU Amsterdam (Tierolf).
  • Registration is open and free — 16 curated datasets, your own research question, your model stays yours.

Find us at the conference

Session C7 — Mobility and Migration Modeling Intercomparison Project (3MIP) – An open, first synthesis

Workshop WSC7 — Panel Discussion – 3MIP

Day and room: to be announced when the iEMSs 2026 preliminary program is published (15 June 2026). Check the iEMSs program .

The pitch in one figure

Fig. 01

Six architectures, one dataset

The same curated dataset for coastal Bangladesh, rendered six ways

01 Agent-based

Agent-based architecture, same curated dataset. About twenty dots of varying size, denser along the southwest coast and the corridor toward Dhaka; each dot is one simulated household cluster. In motion, dots drift toward the corridor and a few relocate.

02 Gravity

Gravity architecture, same curated dataset. Flow arcs of varying thickness from five coastal origin points to three destination cities; thicker arcs are larger modeled flows. In motion, arcs draw in and pulse with flow weight.

03 Radiation

Radiation architecture, same curated dataset. Nested rings spreading from one focal point, spacing widening and color fading outward — distance-decaying catchments. In motion, rings ripple outward in sequence.

04 Integrated assessment

Integrated assessment architecture, same curated dataset. Five regional polygons, each filled with a single flat intensity value; no detail inside regions, because the model aggregates. In motion, fills jump between discrete time-step states.

05 Machine learning

Machine learning architecture, same curated dataset. Smooth nested contour bands deepening toward a coastal core — a continuous predicted surface with no hard edges. In motion, the surface crossfades between predicted states.

06 Cellular automaton

Cellular automaton architecture, same curated dataset. A coarse grid of discrete cells in stepped intensities, clipped to the country outline. In motion, cells change state in discrete generations.
Net migration intensity low high
≈ 100 km
Shared inputs
Illustrative. The same curated dataset, analysed by different model architectures — agent-based, gravity, radiation, integrated-assessment, machine-learning, and cellular-automaton approaches. 3MIP holds the data inputs constant and makes the resulting divergence legible. Archetype lineages: Bell et al. 2019; Simini et al. 2012; Stouffer 1940; Rigaud et al. 2018; ISIMIP3 protocol; Schiavina et al. 2019.

Six model architectures, the same Bangladesh outline, the same question — six different visual grammars: household dots, flow arcs, catchment rings, flat regional polygons, smooth contours, discrete cells. When animated, each panel moves in its own model's logic across a repeating 2025–2050 loop — drifting agents, drawing and pulsing flows, rippling catchments, jumping time-steps, crossfading surfaces, ticking generations. A pause control stops the loop; with reduced motion the figure is static. 3MIP exists to make that divergence legible and synthesize it.

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Webinar recordings and conference materials are on the Outputs page.