Writings on Rosie Fisher

Prediction Infrastructure for the Earth System

Wed, 20 May 2026 00:00:00 +0000

Climate models are often discussed as scientific tools. But increasingly, they function as infrastructure: embedded systems that societies implicitly rely on when making long-horizon decisions.

This shifts the key question from “how accurate are the models?” to:

what does it mean to maintain predictive infrastructure for a complex, partially observable Earth system?

Infrastructure, not instruments

Unlike traditional scientific models, Earth system models are:

continuously evolving
distributed across institutions
dependent on shared code ecosystems (e.g. CLM, FATES, CESM)
deeply coupled to observational pipelines

They behave less like experiments and more like infrastructure stacks.

Why Earth System Models Fail in Practice

Wed, 20 May 2026 00:00:00 +0000

Earth system models (ESMs) are often evaluated in terms of their ability to reproduce historical climate statistics or large-scale mean states. But in practice, their most important role is not hindcasting — it is providing probabilistic structure for future risk.

This creates a fundamental tension: models can be “good” in a climatological sense while still being structurally weak in the variables that matter for prediction under change.

Three recurring failure modes stand out:

Why Land Surface Processes Dominate Carbon–Climate Uncertainty

Wed, 20 May 2026 00:00:00 +0000

A large fraction of uncertainty in future carbon–climate feedbacks originates not in the atmosphere or ocean, but in terrestrial ecosystem dynamics.

This is not primarily a question of missing carbon pools, but of structural uncertainty in how land processes are represented in Earth system models.

1. Nonlinear vegetation dynamics

Vegetation is not a passive tracer of climate. It exhibits:

threshold behaviour
disturbance-driven regime shifts
competition across scales of space and time

These dynamics are only partially resolved in most ESMs.