Two branching event paths (t=0..4) for a climate engineering mega‑project

A worked example of Powell’s “state → decision → new information” sequence (St, xt, Wt+1) with a split caused by two different readings of global average temperature in 2028. This is a modelling illustration, not a deployment recommendation.

State (S) Decision (x) Information (W)
Setup: We treat each t as a quarter. Managers decide scope (xt), then observe new exogenous information (Wt+1)—including updated global mean temperature estimates from monitoring products—updating the next state St+1. The branching happens at W1: two different 2028 temperature readings imply different urgency and governance trajectories.

Diagram: (S0, x0, W1, S1, x1, W2, S2, x2, W3, S3, x3, W4, S4) — two sample paths

Tap a node for details. Use “Focus path” to step through a single trajectory.

Node details (click/tap a box)

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This worked example follows the sequence (S0, x0, W1, S1, x1, W2, …, ST) used to model sequential decision problems Powell: model framework and explained in Powell’s SDAM text Powell: model framework. Tap any state/decision/information node to see a plain‑English breakdown.

State (St) = “what we know now”

Use a compact state that is sufficient to decide and simulate forward. A helpful decomposition is: physical resources Rt, other deterministic info It (e.g., the current temperature), and beliefs Bt about uncertain parameters Powell: model framework Powell: model framework.

Exogenous info (Wt+1) = “what arrives after we decide”

Wt+1 is not known when xt is chosen and arrives after it; its distribution may depend on the state or chosen monitoring—for example, updated temperature estimates or field‑test observations Powell: model framework.

Path A (hot 2028 reading): (S0, x0, W1ᵃ, S1ᵃ, x1ᵃ, W2ᵃ, S2ᵃ, x2ᵃ, W3ᵃ, S3ᵃ, x3ᵃ, W4ᵃ, S4ᵃ) Path B (milder 2028 reading): (S0, x0, W1ᵇ, S1ᵇ, x1ᵇ, W2ᵇ, S2ᵇ, x2ᵇ, W3ᵇ, S3ᵇ, x3ᵇ, W4ᵇ, S4ᵇ)
Real‑world anchors used in the descriptors: monitoring products (e.g., NASA GISTEMP and HadCRUT5), plus real SRM research programmes that inform the kinds of activities you might see in “R&D / pilot” states (e.g., UW’s Marine Cloud Brightening research programme, and the now‑ended SCoPEx effort). See sources at the bottom.

Sources (framework and real-world references)

Framework (Powell / SDA):
Climate monitoring + example climate engineering projects:
  • NASA GISTEMP: global surface temperature change estimate (dataset description) data.giss.nasa.gov
  • HadCRUT5: global temperature anomaly dataset description (Met Office) Met Office
  • Copernicus climate indicators / temperature information used as an example monitoring stream climate.copernicus.eu
  • UW Marine Cloud Brightening research programme overview atmos.uw.edu
  • SCoPEx ended in March 2024 (Harvard SGRP) The Salata Institute
Note: The 2028 “temperature readings” in the two paths are hypothetical scenario inputs (W1ᵃ vs W1ᵇ) meant to illustrate how different exogenous information leads to different decisions and states, not a claim about real 2028 outcomes.