Reconciling Bottom-Up Metrics with Top-Down Reporting for Cloud Carbon Accounting

Abstract

Organizations seeking to reduce the carbon footprint of their cloud applications must rely on two largely disconnected ways of measuring it, each with important limitations. Bottom-up metrics like Software Carbon Intensity (SCI) provide signals for carbon-aware optimization, but tenants lack the information needed to account for many provider-side overheads. Top-down reports by cloud providers provide a more comprehensive view of a tenant's carbon footprint but are coarse and methodologically opaque. Because the two approaches differ in scope and reporting frequency, the current state of the art treats them as decoupled: bottom-up metrics for optimization, top-down reports for corporate disclosure. We argue that the two signals should be reconcilable. A per-workload metric whose improvements never surface in the provider's audited report will not be adopted for accountability at scale. We survey the state of the art in cloud carbon accounting and propose a vision for reconciled SCI (rSCI): a per-workload metric that re-anchors a bottom-up energy estimate to the cloud provider's top-down report through a residual. By decomposing and allocating this residual according to its physical drivers, rSCI can preserve operational incentives while also attributing idle capacity and embodied carbon to the workloads that drive them. We show that today's top-down reporting is still too coarse and methodologically inconsistent to support credible reconciliation and lay out concrete steps in provider reporting and standards to make it practical.